diff --git a/.jupyter/jupyter_notebook_config.py b/.jupyter/jupyter_notebook_config.py
index b63ba1c19..e13a5e953 100644
--- a/.jupyter/jupyter_notebook_config.py
+++ b/.jupyter/jupyter_notebook_config.py
@@ -1 +1 @@
-c.MappingKernelManager.default_kernel_name = 'python2'
+c.MappingKernelManager.default_kernel_name = 'python3'
diff --git a/README.md b/README.md
index 70409f2db..b8c80a4b9 100644
--- a/README.md
+++ b/README.md
@@ -53,16 +53,20 @@ How to use this cookbook
 
 The easiest way is to try it out instantly online using Binder's awesome service. **[Start by clicking here](https://mybinder.org/v2/gh/jvns/pandas-cookbook/master)**, wait for it to launch, then click on "cookbook", and you'll be off to the races! It will let you run all the code interactively without having to install anything on your computer.
 
-To install it locally , you'll need an up-to-date version of IPython Notebook (>= 3.0) and
-n your computer
-pandas (>=0.13) for this to work properly. It's set up to work with Python 2.7.
+To install it locally , you'll need Python 3, an up-to-date version of IPython Notebook, and other requirements described on `requirements.txt` for this to work properly.
 
-You can get these using `pip` (you may want to do this inside a virtual environment to avoid conflicting with your other libraries).
+You can get these using `pip`:
 
 ```bash
   pip install -r requirements.txt
 ```
 
+Or, to setup inside a virtual environment to avoid conflicting with your other libraries
+```bash
+  pip install pipenv
+  pipenv install -r requirements.txt
+```
+
 This can be difficult to get set up and require you to compile
 a whole bunch of things. I instead use and recommend
 [Anaconda](https://store.continuum.io/), which is a Python distribution which
diff --git a/cookbook/A quick tour of IPython Notebook.ipynb b/cookbook/A quick tour of IPython Notebook.ipynb
index 0df81d766..9f7754a85 100644
--- a/cookbook/A quick tour of IPython Notebook.ipynb	
+++ b/cookbook/A quick tour of IPython Notebook.ipynb	
@@ -1 +1,341 @@
-{"nbformat": 4, "metadata": {"orig_nbformat": 3}, "cells": [{"source": "# A quick tour of IPython Notebook", "cell_type": "markdown", "metadata": {}}, {"source": "This tour will work a little better in interactive mode, so it'll be better if you get IPython notebook installed and running. You can start it from a terminal by running\n\n`ipython notebook`", "cell_type": "markdown", "metadata": {}}, {"source": "First, we need to explain how to run cells. Try to run the cell below!", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": null, "outputs": [], "source": "import pandas as pd\n\nprint \"Hi! This is a cell. Press the \u25b6 button above to run it\"", "metadata": {"collapsed": false, "trusted": false}}, {"source": "You can also run a cell with Ctrl+Enter or Shift+Enter. Experiment a bit with that.", "cell_type": "markdown", "metadata": {}}, {"source": "One of the most useful things about IPython notebook is its tab completion. \n\nTry this: click just after read_csv( in the cell below and press Shift+Tab (or Tab if you're using IPython 1.x) 4 times, slowly", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": null, "outputs": [], "source": "pd.read_csv(", "metadata": {"collapsed": false, "trusted": false}}, {"source": "After the first time, you should see this:\n<div align=\"center\">\n<img src=\"files/images/tab-once.png\" width=\"75%\">\n</div>\n\nAfter the second time:\n<div align=\"center\">\n<img src=\"files/images/tab-twice.png\" width=\"75%\">\n</div>\n\nAfter the fourth time, a big help box should pop up at the bottom of the screen, with the full documentation for the `read_csv` function:\n<div align=\"center\">\n<img src=\"files/images/tab-4-times.png\" width=\"90%\">\n</div>", "cell_type": "markdown", "metadata": {}}, {"source": "I find this amazingly useful. I think of this as \"the more confused I am, the more times I should press Shift+Tab\". Nothing bad will happen if you tab complete 12 times.\n\nOkay, let's try tab completion for function names!", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": null, "outputs": [], "source": "pd.r", "metadata": {"collapsed": false, "trusted": false}}, {"source": "You should see this:\n\n<div align=\"center\">\n<img src=\"files/images/function-completion.png\" width=\"30%\">\n</div>", "cell_type": "markdown", "metadata": {}}, {"source": "# Writing code", "cell_type": "markdown", "metadata": {}}, {"source": "Writing code in the notebook is pretty normal.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 1, "outputs": [], "source": "def print_10_nums():\n    for i in range(10):\n        print i,", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 2, "outputs": [{"output_type": "stream", "name": "stdout", "text": "0 1 2 3 4 5 6 7 8 9\n"}], "source": "print_10_nums()", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# Saving", "cell_type": "markdown", "metadata": {}}, {"source": "As of the latest stable version, the notebook autosaves. You should use the latest stable version. Really.", "cell_type": "markdown", "metadata": {}}, {"source": "# Magic functions", "cell_type": "markdown", "metadata": {}}, {"source": "IPython has all kinds of magic functions. Here's an example of comparing `sum()` with a list comprehension to a generator comprehension using the `%time` magic.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 3, "outputs": [{"output_type": "stream", "name": "stdout", "text": "CPU times: user 24 ms, sys: 4 ms, total: 28 ms\nWall time: 27.4 ms\n"}, {"execution_count": 3, "output_type": "execute_result", "data": {"text/plain": "4999950000"}, "metadata": {}}], "source": "%time sum([x for x in range(100000)])", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 4, "outputs": [{"output_type": "stream", "name": "stdout", "text": "CPU times: user 8 ms, sys: 0 ns, total: 8 ms\nWall time: 8.11 ms\n"}, {"execution_count": 4, "output_type": "execute_result", "data": {"text/plain": "4999950000"}, "metadata": {}}], "source": "%time sum(x for x in range(100000))", "metadata": {"collapsed": false, "trusted": false}}, {"source": "The magics I use most are `%time` and `%prun` for profiling. You can run `%magic` to get a list of all of them, and `%quickref` for a reference sheet.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 5, "outputs": [], "source": "%quickref", "metadata": {"collapsed": false, "trusted": false}}, {"source": "You can also do nutty things like run Perl code in the notebook with cell magics. This is especially cool for things like Cython code, where you can try out Cython really fast with the `%%cython` magic (you'll need to install it).", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 6, "outputs": [{"output_type": "stream", "name": "stdout", "text": "whoa, perl!"}], "source": "%%perl\n\n$_ = \"whoa, python!\";\ns/python/perl/;\nprint", "metadata": {"collapsed": false, "trusted": false}}, {"source": "That's it for now!", "cell_type": "markdown", "metadata": {}}, {"source": "<style>\n    @font-face {\n        font-family: \"Computer Modern\";\n        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n    }\n    div.cell{\n        width:800px;\n        margin-left:16% !important;\n        margin-right:auto;\n    }\n    h1 {\n        font-family: Helvetica, serif;\n    }\n    h4{\n        margin-top:12px;\n        margin-bottom: 3px;\n       }\n    div.text_cell_render{\n        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n        line-height: 145%;\n        font-size: 130%;\n        width:800px;\n        margin-left:auto;\n        margin-right:auto;\n    }\n    .CodeMirror{\n            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n    }\n    .text_cell_render h5 {\n        font-weight: 300;\n        font-size: 22pt;\n        color: #4057A1;\n        font-style: italic;\n        margin-bottom: .5em;\n        margin-top: 0.5em;\n        display: block;\n    }\n    \n    .warning{\n        color: rgb( 240, 20, 20 )\n        }  ", "cell_type": "markdown", "metadata": {}}], "nbformat_minor": 0}
\ No newline at end of file
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# A quick tour of IPython Notebook"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This tour will work a little better in interactive mode, so it'll be better if you get IPython notebook installed and running. You can start it from a terminal by running\n",
+    "\n",
+    "`ipython notebook`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, we need to explain how to run cells. Try to run the cell below!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "print(\"Hi! This is a cell. Press the ▶ button above to run it\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can also run a cell with Ctrl+Enter or Shift+Enter. Experiment a bit with that."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One of the most useful things about IPython notebook is its tab completion. \n",
+    "\n",
+    "Try this: click just after read_csv( in the cell below and press Shift+Tab (or Tab if you're using IPython 1.x) 4 times, slowly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.read_csv("
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "After the first time, you should see this:\n",
+    "<div align=\"center\">\n",
+    "<img src=\"files/images/tab-once.png\" width=\"75%\">\n",
+    "</div>\n",
+    "\n",
+    "After the second time:\n",
+    "<div align=\"center\">\n",
+    "<img src=\"files/images/tab-twice.png\" width=\"75%\">\n",
+    "</div>\n",
+    "\n",
+    "After the fourth time, a big help box should pop up at the bottom of the screen, with the full documentation for the `read_csv` function:\n",
+    "<div align=\"center\">\n",
+    "<img src=\"files/images/tab-4-times.png\" width=\"90%\">\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I find this amazingly useful. I think of this as \"the more confused I am, the more times I should press Shift+Tab\". Nothing bad will happen if you tab complete 12 times.\n",
+    "\n",
+    "Okay, let's try tab completion for function names!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.r"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You should see this:\n",
+    "\n",
+    "<div align=\"center\">\n",
+    "<img src=\"files/images/function-completion.png\" width=\"30%\">\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Writing code"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Writing code in the notebook is pretty normal."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_10_nums():\n",
+    "    for i in range(10):\n",
+    "        print(i),"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print_10_nums()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Saving"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As of the latest stable version, the notebook autosaves. You should use the latest stable version. Really."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Magic functions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "IPython has all kinds of magic functions. Here's an example of comparing `sum()` with a list comprehension to a generator comprehension using the `%time` magic."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 8 ms, sys: 4 ms, total: 12 ms\n",
+      "Wall time: 11.3 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "4999950000"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%time sum([x for x in range(100000)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 16 ms, sys: 0 ns, total: 16 ms\n",
+      "Wall time: 15.1 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "4999950000"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%time sum(x for x in range(100000))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The magics I use most are `%time` and `%prun` for profiling. You can run `%magic` to get a list of all of them, and `%quickref` for a reference sheet."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%quickref"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can also do nutty things like run Perl code in the notebook with cell magics. This is especially cool for things like Cython code, where you can try out Cython really fast with the `%%cython` magic (you'll need to install it)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%perl\n",
+    "\n",
+    "$_ = \"whoa, python!\";\n",
+    "s/python/perl/;\n",
+    "print"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That's it for now!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<style>\n",
+    "    @font-face {\n",
+    "        font-family: \"Computer Modern\";\n",
+    "        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
+    "    }\n",
+    "    div.cell{\n",
+    "        width:800px;\n",
+    "        margin-left:16% !important;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    h1 {\n",
+    "        font-family: Helvetica, serif;\n",
+    "    }\n",
+    "    h4{\n",
+    "        margin-top:12px;\n",
+    "        margin-bottom: 3px;\n",
+    "       }\n",
+    "    div.text_cell_render{\n",
+    "        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
+    "        line-height: 145%;\n",
+    "        font-size: 130%;\n",
+    "        width:800px;\n",
+    "        margin-left:auto;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    .CodeMirror{\n",
+    "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
+    "    }\n",
+    "    .text_cell_render h5 {\n",
+    "        font-weight: 300;\n",
+    "        font-size: 22pt;\n",
+    "        color: #4057A1;\n",
+    "        font-style: italic;\n",
+    "        margin-bottom: .5em;\n",
+    "        margin-top: 0.5em;\n",
+    "        display: block;\n",
+    "    }\n",
+    "    \n",
+    "    .warning{\n",
+    "        color: rgb( 240, 20, 20 )\n",
+    "        }  "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/cookbook/Chapter 1 - Reading from a CSV.ipynb b/cookbook/Chapter 1 - Reading from a CSV.ipynb
index d27f87280..8b6718eba 100644
--- a/cookbook/Chapter 1 - Reading from a CSV.ipynb	
+++ b/cookbook/Chapter 1 - Reading from a CSV.ipynb	
@@ -1 +1,541 @@
-{"nbformat": 4, "metadata": {"orig_nbformat": 3}, "cells": [{"cell_type": "code", "execution_count": 3, "outputs": [], "source": "# Render our plots inline\n%matplotlib inline\n\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\npd.set_option('display.mpl_style', 'default') # Make the graphs a bit prettier\nplt.rcParams['figure.figsize'] = (15, 5)", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 1.1 Reading data from a csv file", "cell_type": "markdown", "metadata": {}}, {"source": "You can read data from a CSV file using the `read_csv` function. By default, it assumes that the fields are comma-separated.\n\nWe're going to be looking some cyclist data from Montr\u00e9al. Here's the [original page](http://donnees.ville.montreal.qc.ca/dataset/velos-comptage) (in French), but it's already included in this repository. We're using the data from 2012.\n\nThis dataset is a list of how many people were on 7 different bike paths in Montreal, each day.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 4, "outputs": [], "source": "broken_df = pd.read_csv('../data/bikes.csv')", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 5, "outputs": [{"execution_count": 5, "output_type": "execute_result", "data": {"text/plain": "  Date;Berri 1;Br\ufffdbeuf (donn\ufffdes non disponibles);C\ufffdte-Sainte-Catherine;Maisonneuve 1;Maisonneuve 2;du Parc;Pierre-Dupuy;Rachel1;St-Urbain (donn\ufffdes non disponibles)\n0                   01/01/2012;35;;0;38;51;26;10;16;                                                                                                               \n1                   02/01/2012;83;;1;68;153;53;6;43;                                                                                                               \n2                 03/01/2012;135;;2;104;248;89;3;58;                                                                                                               \n\n[3 rows x 1 columns]", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Date;Berri 1;Br\ufffdbeuf (donn\ufffdes non disponibles);C\ufffdte-Sainte-Catherine;Maisonneuve 1;Maisonneuve 2;du Parc;Pierre-Dupuy;Rachel1;St-Urbain (donn\ufffdes non disponibles)</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>   01/01/2012;35;;0;38;51;26;10;16;</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>   02/01/2012;83;;1;68;153;53;6;43;</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td> 03/01/2012;135;;2;104;248;89;3;58;</td>\n    </tr>\n  </tbody>\n</table>\n<p>3 rows \u00d7 1 columns</p>\n</div>"}, "metadata": {}}], "source": "# Look at the first 3 rows\nbroken_df[:3]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "You'll notice that this is totally broken! `read_csv` has a bunch of options that will let us fix that, though. Here we'll\n\n* change the column separator to a `;`\n* Set the encoding to `'latin1'` (the default is `'utf8'`)\n* Parse the dates in the 'Date' column\n* Tell it that our dates have the day first instead of the month first\n* Set the index to be the 'Date' column", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 6, "outputs": [{"execution_count": 6, "output_type": "execute_result", "data": {"text/plain": "            Berri 1  Br\u00e9beuf (donn\u00e9es non disponibles)  C\u00f4te-Sainte-Catherine  \\\nDate                                                                            \n2012-01-01       35                                NaN                      0   \n2012-01-02       83                                NaN                      1   \n2012-01-03      135                                NaN                      2   \n\n            Maisonneuve 1  Maisonneuve 2  du Parc  Pierre-Dupuy  Rachel1  \\\nDate                                                                       \n2012-01-01             38             51       26            10       16   \n2012-01-02             68            153       53             6       43   \n2012-01-03            104            248       89             3       58   \n\n            St-Urbain (donn\u00e9es non disponibles)  \nDate                                             \n2012-01-01                                  NaN  \n2012-01-02                                  NaN  \n2012-01-03                                  NaN  \n\n[3 rows x 9 columns]", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Berri 1</th>\n      <th>Br\u00e9beuf (donn\u00e9es non disponibles)</th>\n      <th>C\u00f4te-Sainte-Catherine</th>\n      <th>Maisonneuve 1</th>\n      <th>Maisonneuve 2</th>\n      <th>du Parc</th>\n      <th>Pierre-Dupuy</th>\n      <th>Rachel1</th>\n      <th>St-Urbain (donn\u00e9es non disponibles)</th>\n    </tr>\n    <tr>\n      <th>Date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2012-01-01</th>\n      <td>  35</td>\n      <td>NaN</td>\n      <td> 0</td>\n      <td>  38</td>\n      <td>  51</td>\n      <td> 26</td>\n      <td> 10</td>\n      <td> 16</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2012-01-02</th>\n      <td>  83</td>\n      <td>NaN</td>\n      <td> 1</td>\n      <td>  68</td>\n      <td> 153</td>\n      <td> 53</td>\n      <td>  6</td>\n      <td> 43</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2012-01-03</th>\n      <td> 135</td>\n      <td>NaN</td>\n      <td> 2</td>\n      <td> 104</td>\n      <td> 248</td>\n      <td> 89</td>\n      <td>  3</td>\n      <td> 58</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n<p>3 rows \u00d7 9 columns</p>\n</div>"}, "metadata": {}}], "source": "fixed_df = pd.read_csv('../data/bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')\nfixed_df[:3]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 1.2 Selecting a column", "cell_type": "markdown", "metadata": {}}, {"source": "When you read a CSV, you get a kind of object called a `DataFrame`, which is made up of rows and columns. You get columns out of a DataFrame the same way you get elements out of a dictionary.\n\nHere's an example:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 7, "outputs": [{"execution_count": 7, "output_type": "execute_result", "data": {"text/plain": "Date\n2012-01-01     35\n2012-01-02     83\n2012-01-03    135\n2012-01-04    144\n2012-01-05    197\n2012-01-06    146\n2012-01-07     98\n2012-01-08     95\n2012-01-09    244\n2012-01-10    397\n2012-01-11    273\n2012-01-12    157\n2012-01-13     75\n2012-01-14     32\n2012-01-15     54\n...\n2012-10-22    3650\n2012-10-23    4177\n2012-10-24    3744\n2012-10-25    3735\n2012-10-26    4290\n2012-10-27    1857\n2012-10-28    1310\n2012-10-29    2919\n2012-10-30    2887\n2012-10-31    2634\n2012-11-01    2405\n2012-11-02    1582\n2012-11-03     844\n2012-11-04     966\n2012-11-05    2247\nName: Berri 1, Length: 310"}, "metadata": {}}], "source": "fixed_df['Berri 1']", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 1.3 Plotting a column", "cell_type": "markdown", "metadata": {}}, {"source": "Just add `.plot()` to the end! How could it be easier? =)\n\nWe can see that, unsurprisingly, not many people are biking in January, February, and March, ", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 8, "outputs": [{"execution_count": 8, "output_type": "execute_result", "data": {"text/plain": "<matplotlib.axes.AxesSubplot at 0x10a2bd1d0>"}, "metadata": {}}, {"output_type": "display_data", "metadata": {}, "data": {"image/png": 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aLlvWgjdPp20DOPP+V1x5NUInDwAAYoKehTP73wBgSULvIKlU+dDMXHDplegY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UAAAg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\nAAAaQsABAAA0hIADAABoCAEHAADQEN/0h8XWuQDOWQAAAABJRU5ErkJggg==\n", "text/plain": "<matplotlib.figure.Figure at 0x10a300090>"}}], "source": "fixed_df['Berri 1'].plot()", "metadata": {"collapsed": false, "trusted": false}}, {"source": "We can also plot all the columns just as easily. We'll make it a little bigger, too.\nYou can see that it's more squished together, but all the bike paths behave basically the same -- if it's a bad day for cyclists, it's a bad day everywhere.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 9, "outputs": [{"execution_count": 9, "output_type": "execute_result", "data": {"text/plain": "<matplotlib.axes.AxesSubplot at 0x10a34ad90>"}, "metadata": {}}, {"output_type": "display_data", "metadata": {}, "data": {"image/png": 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wwCTXTcx1a7hiDlxQUBBiY2MRGRmJDz74AGq1GlOmTEH//v1RVFSEWbNm4dat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rhGQYkkNnr6Bo3rUyCZCN3MbEsDJxGCODhKWm17GToHzoXeaYWrBo5WaeAkZ0MU6/uPOuIIUBAk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v/k3w+9vvX9F2Ejd6M7v43zZzfT59/8v76L2K2e+56HoNQ3dlnYfwCle+7Mjfe/XzidrrQe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OKRJrqRsgKQRkOYkx5Do90/cxLOJC+EA71iC8RET5lq9rHn/qB7gyTDkqDM9cGfCNuxNE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UIGTD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aP/xnPPb3/w+GvR5WeKORlZUVnrtwjTsW/Weurl4hcxaJI1xo4gSsfOmxuecvDhOsybh2/RpS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38eF4WYlBLK6R64/FvWAwdM1QhMHVsU8YH3vJvkzRvEp0+w8d1PE2yulSB6MTBovvN+zv3b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lDU0//yO1X7qb5l/+L8nXXo79/KXRac0nDdvuQ5hnT49SHPtDyc3C+fVbSLnxKuwrlhBu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\nHe7YsYOvv/6aTZs2sWPHDkaMGIFGIzOQf6igoACbzUZERAS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"text/plain": "<matplotlib.figure.Figure at 0x10a381c50>"}}], "source": "fixed_df.plot(figsize=(15, 10))", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 1.4 Putting all that together", "cell_type": "markdown", "metadata": {}}, {"source": "Here's the code we needed to write do draw that graph, all together:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 10, "outputs": [{"execution_count": 10, "output_type": "execute_result", "data": {"text/plain": "<matplotlib.axes.AxesSubplot at 0x10aef19d0>"}, "metadata": {}}, {"output_type": "display_data", "metadata": {}, "data": {"image/png": 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aLlvWgjdPp20DOPP+V1x5NUInDwAAYoKehTP73wBgSULvIKlU+dDMXHDplegY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UAAAg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\n4Hf2tuDqidmobjLhnb0tuLEiFwC8rf99Ax5BFFHX2deB0oNvx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"text/plain": "<matplotlib.figure.Figure at 0x10aef2bd0>"}}], "source": "df = pd.read_csv('../data/bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')\ndf['Berri 1'].plot()", "metadata": {"collapsed": false, "trusted": false}}, {"source": "<style>\n    @font-face {\n        font-family: \"Computer Modern\";\n        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n    }\n    div.cell{\n        width:800px;\n        margin-left:16% !important;\n        margin-right:auto;\n    }\n    h1 {\n        font-family: Helvetica, serif;\n    }\n    h4{\n        margin-top:12px;\n        margin-bottom: 3px;\n       }\n    div.text_cell_render{\n        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n        line-height: 145%;\n        font-size: 130%;\n        width:800px;\n        margin-left:auto;\n        margin-right:auto;\n    }\n    .CodeMirror{\n            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n    }\n    .text_cell_render h5 {\n        font-weight: 300;\n        font-size: 22pt;\n        color: #4057A1;\n        font-style: italic;\n        margin-bottom: .5em;\n        margin-top: 0.5em;\n        display: block;\n    }\n    \n    .warning{\n        color: rgb( 240, 20, 20 )\n        }  ", "cell_type": "markdown", "metadata": {}}], "nbformat_minor": 0}
\ No newline at end of file
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.style.use('ggplot') # Make the graphs a bit prettier\n",
+    "plt.rcParams['figure.figsize'] = (15, 5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1.1 Reading data from a csv file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can read data from a CSV file using the `read_csv` function. By default, it assumes that the fields are comma-separated.\n",
+    "\n",
+    "We're going to be looking some cyclist data from Montréal. Here's the [original page](http://donnees.ville.montreal.qc.ca/dataset/velos-comptage) (in French), but it's already included in this repository. We're using the data from 2012.\n",
+    "\n",
+    "This dataset is a list of how many people were on 7 different bike paths in Montreal, each day."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "broken_df = pd.read_csv('../data/bikes.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date;Berri 1;Br�beuf (donn�es non disponibles);C�te-Sainte-Catherine;Maisonneuve 1;Maisonneuve 2;du Parc;Pierre-Dupuy;Rachel1;St-Urbain (donn�es non disponibles)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>01/01/2012;35;;0;38;51;26;10;16;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>02/01/2012;83;;1;68;153;53;6;43;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>03/01/2012;135;;2;104;248;89;3;58;</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  Date;Berri 1;Br�beuf (donn�es non disponibles);C�te-Sainte-Catherine;Maisonneuve 1;Maisonneuve 2;du Parc;Pierre-Dupuy;Rachel1;St-Urbain (donn�es non disponibles)\n",
+       "0                   01/01/2012;35;;0;38;51;26;10;16;                                                                                                               \n",
+       "1                   02/01/2012;83;;1;68;153;53;6;43;                                                                                                               \n",
+       "2                 03/01/2012;135;;2;104;248;89;3;58;                                                                                                               "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Look at the first 3 rows\n",
+    "broken_df[:3]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You'll notice that this is totally broken! `read_csv` has a bunch of options that will let us fix that, though. Here we'll\n",
+    "\n",
+    "* change the column separator to a `;`\n",
+    "* Set the encoding to `'latin1'` (the default is `'utf8'`)\n",
+    "* Parse the dates in the 'Date' column\n",
+    "* Tell it that our dates have the day first instead of the month first\n",
+    "* Set the index to be the 'Date' column"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Berri 1</th>\n",
+       "      <th>Br�beuf (donn�es non disponibles)</th>\n",
+       "      <th>C�te-Sainte-Catherine</th>\n",
+       "      <th>Maisonneuve 1</th>\n",
+       "      <th>Maisonneuve 2</th>\n",
+       "      <th>du Parc</th>\n",
+       "      <th>Pierre-Dupuy</th>\n",
+       "      <th>Rachel1</th>\n",
+       "      <th>St-Urbain (donn�es non disponibles)</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2012-01-01</th>\n",
+       "      <td>35</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>51</td>\n",
+       "      <td>26</td>\n",
+       "      <td>10</td>\n",
+       "      <td>16</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-01-02</th>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>68</td>\n",
+       "      <td>153</td>\n",
+       "      <td>53</td>\n",
+       "      <td>6</td>\n",
+       "      <td>43</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-01-03</th>\n",
+       "      <td>135</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>104</td>\n",
+       "      <td>248</td>\n",
+       "      <td>89</td>\n",
+       "      <td>3</td>\n",
+       "      <td>58</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Berri 1  Br�beuf (donn�es non disponibles)  \\\n",
+       "Date                                                         \n",
+       "2012-01-01       35                                    NaN   \n",
+       "2012-01-02       83                                    NaN   \n",
+       "2012-01-03      135                                    NaN   \n",
+       "\n",
+       "            C�te-Sainte-Catherine  Maisonneuve 1  Maisonneuve 2  du Parc  \\\n",
+       "Date                                                                         \n",
+       "2012-01-01                        0             38             51       26   \n",
+       "2012-01-02                        1             68            153       53   \n",
+       "2012-01-03                        2            104            248       89   \n",
+       "\n",
+       "            Pierre-Dupuy  Rachel1  St-Urbain (donn�es non disponibles)  \n",
+       "Date                                                                      \n",
+       "2012-01-01            10       16                                    NaN  \n",
+       "2012-01-02             6       43                                    NaN  \n",
+       "2012-01-03             3       58                                    NaN  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fixed_df = pd.read_csv('../data/bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')\n",
+    "fixed_df[:3]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1.2 Selecting a column"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When you read a CSV, you get a kind of object called a `DataFrame`, which is made up of rows and columns. You get columns out of a DataFrame the same way you get elements out of a dictionary.\n",
+    "\n",
+    "Here's an example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date\n",
+       "2012-01-01      35\n",
+       "2012-01-02      83\n",
+       "2012-01-03     135\n",
+       "2012-01-04     144\n",
+       "2012-01-05     197\n",
+       "2012-01-06     146\n",
+       "2012-01-07      98\n",
+       "2012-01-08      95\n",
+       "2012-01-09     244\n",
+       "2012-01-10     397\n",
+       "2012-01-11     273\n",
+       "2012-01-12     157\n",
+       "2012-01-13      75\n",
+       "2012-01-14      32\n",
+       "2012-01-15      54\n",
+       "2012-01-16     168\n",
+       "2012-01-17     155\n",
+       "2012-01-18     139\n",
+       "2012-01-19     191\n",
+       "2012-01-20     161\n",
+       "2012-01-21      53\n",
+       "2012-01-22      71\n",
+       "2012-01-23     210\n",
+       "2012-01-24     299\n",
+       "2012-01-25     334\n",
+       "2012-01-26     306\n",
+       "2012-01-27      91\n",
+       "2012-01-28      80\n",
+       "2012-01-29      87\n",
+       "2012-01-30     219\n",
+       "              ... \n",
+       "2012-10-07    1580\n",
+       "2012-10-08    1854\n",
+       "2012-10-09    4787\n",
+       "2012-10-10    3115\n",
+       "2012-10-11    3746\n",
+       "2012-10-12    3169\n",
+       "2012-10-13    1783\n",
+       "2012-10-14     587\n",
+       "2012-10-15    3292\n",
+       "2012-10-16    3739\n",
+       "2012-10-17    4098\n",
+       "2012-10-18    4671\n",
+       "2012-10-19    1313\n",
+       "2012-10-20    2011\n",
+       "2012-10-21    1277\n",
+       "2012-10-22    3650\n",
+       "2012-10-23    4177\n",
+       "2012-10-24    3744\n",
+       "2012-10-25    3735\n",
+       "2012-10-26    4290\n",
+       "2012-10-27    1857\n",
+       "2012-10-28    1310\n",
+       "2012-10-29    2919\n",
+       "2012-10-30    2887\n",
+       "2012-10-31    2634\n",
+       "2012-11-01    2405\n",
+       "2012-11-02    1582\n",
+       "2012-11-03     844\n",
+       "2012-11-04     966\n",
+       "2012-11-05    2247\n",
+       "Name: Berri 1, Length: 310, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fixed_df['Berri 1']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1.3 Plotting a column"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Just add `.plot()` to the end! How could it be easier? =)\n",
+    "\n",
+    "We can see that, unsurprisingly, not many people are biking in January, February, and March, "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2ab77ff28>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fixed_df['Berri 1'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also plot all the columns just as easily. We'll make it a little bigger, too.\n",
+    "You can see that it's more squished together, but all the bike paths behave basically the same -- if it's a bad day for cyclists, it's a bad day everywhere."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2a96892b0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fixed_df.plot(figsize=(15, 10))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1.4 Putting all that together"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here's the code we needed to write do draw that graph, all together:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff2a9595cc0>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('../data/bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')\n",
+    "df['Berri 1'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<style>\n",
+    "    @font-face {\n",
+    "        font-family: \"Computer Modern\";\n",
+    "        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
+    "    }\n",
+    "    div.cell{\n",
+    "        width:800px;\n",
+    "        margin-left:16% !important;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    h1 {\n",
+    "        font-family: Helvetica, serif;\n",
+    "    }\n",
+    "    h4{\n",
+    "        margin-top:12px;\n",
+    "        margin-bottom: 3px;\n",
+    "       }\n",
+    "    div.text_cell_render{\n",
+    "        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
+    "        line-height: 145%;\n",
+    "        font-size: 130%;\n",
+    "        width:800px;\n",
+    "        margin-left:auto;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    .CodeMirror{\n",
+    "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
+    "    }\n",
+    "    .text_cell_render h5 {\n",
+    "        font-weight: 300;\n",
+    "        font-size: 22pt;\n",
+    "        color: #4057A1;\n",
+    "        font-style: italic;\n",
+    "        margin-bottom: .5em;\n",
+    "        margin-top: 0.5em;\n",
+    "        display: block;\n",
+    "    }\n",
+    "    \n",
+    "    .warning{\n",
+    "        color: rgb( 240, 20, 20 )\n",
+    "        }  "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/cookbook/Chapter 2 - Selecting data & finding the most common complaint type.ipynb b/cookbook/Chapter 2 - Selecting data & finding the most common complaint type.ipynb
index a648f32f9..d67e6612b 100644
--- a/cookbook/Chapter 2 - Selecting data & finding the most common complaint type.ipynb	
+++ b/cookbook/Chapter 2 - Selecting data & finding the most common complaint type.ipynb	
@@ -1 +1,6162 @@
-{"nbformat_minor": 0, "cells": [{"execution_count": 1, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [], "source": "# The usual preamble\n%matplotlib inline\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n# Make the graphs a bit prettier, and bigger\npd.set_option('display.mpl_style', 'default')\n\n# This is necessary to show lots of columns in pandas 0.12. \n# Not necessary in pandas 0.13.\npd.set_option('display.width', 5000) \npd.set_option('display.max_columns', 60)\n\nplt.rcParams['figure.figsize'] = (15, 5)"}, {"source": "We're going to use a new dataset here, to demonstrate how to deal with larger datasets. This is a subset of the of 311 service requests from [NYC Open Data](https://nycopendata.socrata.com/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9). ", "cell_type": "markdown", "metadata": {}}, {"execution_count": 2, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"output_type": "stream", "name": "stderr", "text": "/opt/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py:1070: DtypeWarning: Columns (8) have mixed types. Specify dtype option on import or set low_memory=False.\n  data = self._reader.read(nrows)\n"}], "source": "complaints = pd.read_csv('../data/311-service-requests.csv')"}, {"source": "Depending on your pandas version, you might see an error like \"DtypeWarning: Columns (8) have mixed types\". This means that it's encountered a problem reading in our data. In this case it almost certainly means that it has columns where some of the entries are strings and some are integers.\n\nFor now we're going to ignore it and hope we don't run into a problem, but in the long run we'd need to investigate this warning.", "cell_type": "markdown", "metadata": {}}, {"source": "# 2.1 What's even in it? (the summary)", "cell_type": "markdown", "metadata": {}}, {"source": "When you print a large dataframe, it will only show you the first few rows.\n\nIf you don't see this, don't panic! The default behavior for large dataframes changed between pandas 0.12 and 0.13. Previous to 0.13 it would show you a summary of the dataframe. This includes all the columns, and how many non-null values there are in each column.", "cell_type": "markdown", "metadata": {}}, {"execution_count": 3, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 3, "metadata": {}, "data": {"text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unique Key</th>\n      <th>Created Date</th>\n      <th>Closed Date</th>\n      <th>Agency</th>\n      <th>Agency Name</th>\n      <th>Complaint Type</th>\n      <th>Descriptor</th>\n      <th>Location Type</th>\n      <th>Incident Zip</th>\n      <th>Incident Address</th>\n      <th>Street Name</th>\n      <th>Cross Street 1</th>\n      <th>Cross Street 2</th>\n      <th>Intersection Street 1</th>\n      <th>Intersection Street 2</th>\n      <th>Address Type</th>\n      <th>City</th>\n      <th>Landmark</th>\n      <th>Facility Type</th>\n      <th>Status</th>\n      <th>Due Date</th>\n      <th>Resolution Action Updated Date</th>\n      <th>Community Board</th>\n      <th>Borough</th>\n      <th>X Coordinate (State Plane)</th>\n      <th>Y Coordinate (State Plane)</th>\n      <th>Park Facility Name</th>\n      <th>Park Borough</th>\n      <th>School Name</th>\n      <th>School Number</th>\n      <th>School Region</th>\n      <th>School Code</th>\n      <th>School Phone Number</th>\n      <th>School Address</th>\n      <th>School City</th>\n      <th>School State</th>\n      <th>School Zip</th>\n      <th>School Not Found</th>\n      <th>School or Citywide Complaint</th>\n      <th>Vehicle Type</th>\n      <th>Taxi Company Borough</th>\n      <th>Taxi Pick Up Location</th>\n      <th>Bridge Highway Name</th>\n      <th>Bridge Highway Direction</th>\n      <th>Road Ramp</th>\n      <th>Bridge Highway Segment</th>\n      <th>Garage Lot Name</th>\n      <th>Ferry Direction</th>\n      <th>Ferry Terminal Name</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Location</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0 </th>\n      <td> 26589651</td>\n      <td> 10/31/2013 02:08:41 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                     Loud Talking</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11432</td>\n      <td>          90-03 169 STREET</td>\n      <td>          169 STREET</td>\n      <td>         90 AVENUE</td>\n      <td>                        91 AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>             JAMAICA</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 10:08:41 AM</td>\n      <td> 10/31/2013 02:35:17 AM</td>\n      <td>            12 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1042027</td>\n      <td> 197389</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.708275</td>\n      <td>-73.791604</td>\n      <td>  (40.70827532593202, -73.79160395779721)</td>\n    </tr>\n    <tr>\n      <th>1 </th>\n      <td> 26593698</td>\n      <td> 10/31/2013 02:01:04 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>          Illegal Parking</td>\n      <td>     Commercial Overnight Parking</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11378</td>\n      <td>                 58 AVENUE</td>\n      <td>           58 AVENUE</td>\n      <td>          58 PLACE</td>\n      <td>                        59 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>             MASPETH</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 10:01:04 AM</td>\n      <td>                    NaN</td>\n      <td>            05 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1009349</td>\n      <td> 201984</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.721041</td>\n      <td>-73.909453</td>\n      <td> (40.721040535628305, -73.90945306791765)</td>\n    </tr>\n    <tr>\n      <th>2 </th>\n      <td> 26594139</td>\n      <td> 10/31/2013 02:00:24 AM</td>\n      <td> 10/31/2013 02:40:32 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10032</td>\n      <td>             4060 BROADWAY</td>\n      <td>            BROADWAY</td>\n      <td>   WEST 171 STREET</td>\n      <td>                  WEST 172 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 10:00:24 AM</td>\n      <td> 10/31/2013 02:39:42 AM</td>\n      <td>         12 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td> 1001088</td>\n      <td> 246531</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.843330</td>\n      <td>-73.939144</td>\n      <td>  (40.84332975466513, -73.93914371913482)</td>\n    </tr>\n    <tr>\n      <th>3 </th>\n      <td> 26595721</td>\n      <td> 10/31/2013 01:56:23 AM</td>\n      <td> 10/31/2013 02:21:48 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>          Noise - Vehicle</td>\n      <td>                   Car/Truck Horn</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10023</td>\n      <td>            WEST 72 STREET</td>\n      <td>      WEST 72 STREET</td>\n      <td>   COLUMBUS AVENUE</td>\n      <td>                 AMSTERDAM AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:56:23 AM</td>\n      <td> 10/31/2013 02:21:10 AM</td>\n      <td>         07 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  989730</td>\n      <td> 222727</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.778009</td>\n      <td>-73.980213</td>\n      <td>   (40.7780087446372, -73.98021349023975)</td>\n    </tr>\n    <tr>\n      <th>4 </th>\n      <td> 26590930</td>\n      <td> 10/31/2013 01:53:44 AM</td>\n      <td>                    NaN</td>\n      <td> DOHMH</td>\n      <td>           Department of Health and Mental Hygiene</td>\n      <td>                   Rodent</td>\n      <td>     Condition Attracting Rodents</td>\n      <td>                    Vacant Lot</td>\n      <td> 10027</td>\n      <td>           WEST 124 STREET</td>\n      <td>     WEST 124 STREET</td>\n      <td>      LENOX AVENUE</td>\n      <td> ADAM CLAYTON POWELL JR BOULEVARD</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>  Pending</td>\n      <td> 11/30/2013 01:53:44 AM</td>\n      <td> 10/31/2013 01:59:54 AM</td>\n      <td>         10 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  998815</td>\n      <td> 233545</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.807691</td>\n      <td>-73.947387</td>\n      <td>  (40.80769092704951, -73.94738703491433)</td>\n    </tr>\n    <tr>\n      <th>5 </th>\n      <td> 26592370</td>\n      <td> 10/31/2013 01:46:52 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Banging/Pounding</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11372</td>\n      <td>                 37 AVENUE</td>\n      <td>           37 AVENUE</td>\n      <td>         84 STREET</td>\n      <td>                        85 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>     JACKSON HEIGHTS</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 09:46:52 AM</td>\n      <td>                    NaN</td>\n      <td>            03 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1016948</td>\n      <td> 212540</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.749989</td>\n      <td>-73.881988</td>\n      <td>   (40.7499893014072, -73.88198770727831)</td>\n    </tr>\n    <tr>\n      <th>6 </th>\n      <td> 26595682</td>\n      <td> 10/31/2013 01:46:40 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>         Blocked Driveway</td>\n      <td>                        No Access</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11419</td>\n      <td>         107-50 109 STREET</td>\n      <td>          109 STREET</td>\n      <td>        107 AVENUE</td>\n      <td>                       109 AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td> SOUTH RICHMOND HILL</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 09:46:40 AM</td>\n      <td> 10/31/2013 01:59:51 AM</td>\n      <td>            10 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1030919</td>\n      <td> 187622</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.681533</td>\n      <td>-73.831737</td>\n      <td>  (40.68153278675525, -73.83173699701601)</td>\n    </tr>\n    <tr>\n      <th>7 </th>\n      <td> 26595195</td>\n      <td> 10/31/2013 01:44:19 AM</td>\n      <td> 10/31/2013 01:58:49 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11417</td>\n      <td> 137-09 CROSSBAY BOULEVARD</td>\n      <td>  CROSSBAY BOULEVARD</td>\n      <td>     PITKIN AVENUE</td>\n      <td>                 VAN WICKLEN ROAD</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>          OZONE PARK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:44:19 AM</td>\n      <td> 10/31/2013 01:58:49 AM</td>\n      <td>            10 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1027776</td>\n      <td> 184076</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.671816</td>\n      <td>-73.843092</td>\n      <td>  (40.67181584567338, -73.84309181950769)</td>\n    </tr>\n    <tr>\n      <th>8 </th>\n      <td> 26590540</td>\n      <td> 10/31/2013 01:44:14 AM</td>\n      <td> 10/31/2013 02:28:04 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                     Loud Talking</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10011</td>\n      <td>        258 WEST 15 STREET</td>\n      <td>      WEST 15 STREET</td>\n      <td>          7 AVENUE</td>\n      <td>                         8 AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:44:14 AM</td>\n      <td> 10/31/2013 02:00:56 AM</td>\n      <td>         04 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  984031</td>\n      <td> 208847</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.739913</td>\n      <td>-74.000790</td>\n      <td>  (40.73991339303542, -74.00079028612932)</td>\n    </tr>\n    <tr>\n      <th>9 </th>\n      <td> 26594392</td>\n      <td> 10/31/2013 01:34:41 AM</td>\n      <td> 10/31/2013 02:23:51 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11225</td>\n      <td>       835 NOSTRAND AVENUE</td>\n      <td>     NOSTRAND AVENUE</td>\n      <td>      UNION STREET</td>\n      <td>                 PRESIDENT STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:34:41 AM</td>\n      <td> 10/31/2013 01:48:26 AM</td>\n      <td>          09 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  997941</td>\n      <td> 182725</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.668204</td>\n      <td>-73.950648</td>\n      <td>  (40.66820406598287, -73.95064760056546)</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td> 26595176</td>\n      <td> 10/31/2013 01:25:12 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td> Noise - House of Worship</td>\n      <td>                 Loud Music/Party</td>\n      <td>              House of Worship</td>\n      <td> 11218</td>\n      <td>            3775 18 AVENUE</td>\n      <td>           18 AVENUE</td>\n      <td>     EAST 9 STREET</td>\n      <td>                    EAST 8 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 09:25:12 AM</td>\n      <td>                    NaN</td>\n      <td>          14 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  992726</td>\n      <td> 170399</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.634378</td>\n      <td>-73.969462</td>\n      <td>  (40.63437840816299, -73.96946177104543)</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td> 26591982</td>\n      <td> 10/31/2013 01:24:14 AM</td>\n      <td> 10/31/2013 01:54:39 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10003</td>\n      <td>              187 2 AVENUE</td>\n      <td>            2 AVENUE</td>\n      <td>    EAST 11 STREET</td>\n      <td>                   EAST 12 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:24:14 AM</td>\n      <td> 10/31/2013 01:54:39 AM</td>\n      <td>         03 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  988110</td>\n      <td> 205533</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.730816</td>\n      <td>-73.986073</td>\n      <td>  (40.73081644089586, -73.98607265739876)</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td> 26594169</td>\n      <td> 10/31/2013 01:20:57 AM</td>\n      <td> 10/31/2013 02:12:31 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>          Illegal Parking</td>\n      <td>   Double Parked Blocking Vehicle</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10029</td>\n      <td>         65 EAST 99 STREET</td>\n      <td>      EAST 99 STREET</td>\n      <td>    MADISON AVENUE</td>\n      <td>                      PARK AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:20:57 AM</td>\n      <td> 10/31/2013 01:42:05 AM</td>\n      <td>         11 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  997470</td>\n      <td> 226725</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.788974</td>\n      <td>-73.952259</td>\n      <td>  (40.78897400211689, -73.95225898702977)</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td> 26594391</td>\n      <td> 10/31/2013 01:20:13 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>          Noise - Vehicle</td>\n      <td>                    Engine Idling</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10466</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>    STRANG AVENUE</td>\n      <td>  AMUNDSON AVENUE</td>\n      <td> INTERSECTION</td>\n      <td>               BRONX</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 09:20:13 AM</td>\n      <td>                    NaN</td>\n      <td>             12 BRONX</td>\n      <td>         BRONX</td>\n      <td> 1029467</td>\n      <td> 264124</td>\n      <td> Unspecified</td>\n      <td>         BRONX</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.891517</td>\n      <td>-73.836457</td>\n      <td>  (40.89151738488846, -73.83645714593568)</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td> 26590917</td>\n      <td> 10/31/2013 01:19:54 AM</td>\n      <td>                    NaN</td>\n      <td> DOHMH</td>\n      <td>           Department of Health and Mental Hygiene</td>\n      <td>                   Rodent</td>\n      <td>                     Rat Sighting</td>\n      <td> 1-2 Family Mixed Use Building</td>\n      <td> 11219</td>\n      <td>                 63 STREET</td>\n      <td>           63 STREET</td>\n      <td>         13 AVENUE</td>\n      <td>                        14 AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>  Pending</td>\n      <td> 11/30/2013 01:19:54 AM</td>\n      <td> 10/31/2013 01:29:26 AM</td>\n      <td>          10 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  984467</td>\n      <td> 167519</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.626477</td>\n      <td>-73.999218</td>\n      <td>   (40.6264774690411, -73.99921826202639)</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td> 26591458</td>\n      <td> 10/31/2013 01:14:02 AM</td>\n      <td> 10/31/2013 01:30:34 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td> Noise - House of Worship</td>\n      <td>                 Loud Music/Party</td>\n      <td>              House of Worship</td>\n      <td> 10025</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td> WEST   99 STREET</td>\n      <td>         BROADWAY</td>\n      <td> INTERSECTION</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:14:02 AM</td>\n      <td> 10/31/2013 01:30:34 AM</td>\n      <td>         07 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  992454</td>\n      <td> 229500</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.796597</td>\n      <td>-73.970370</td>\n      <td>   (40.7965967075252, -73.97036973473399)</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td> 26594086</td>\n      <td> 10/31/2013 12:54:03 AM</td>\n      <td> 10/31/2013 02:16:39 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                 Loud Music/Party</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10310</td>\n      <td>       173 CAMPBELL AVENUE</td>\n      <td>     CAMPBELL AVENUE</td>\n      <td>  HENDERSON AVENUE</td>\n      <td>                     WINEGAR LANE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>       STATEN ISLAND</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:54:03 AM</td>\n      <td> 10/31/2013 02:07:14 AM</td>\n      <td>     01 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  952013</td>\n      <td> 171076</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.636182</td>\n      <td>-74.116150</td>\n      <td>   (40.63618202176914, -74.1161500428337)</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td> 26595117</td>\n      <td> 10/31/2013 12:52:46 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>          Illegal Parking</td>\n      <td>    Posted Parking Sign Violation</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11236</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td> ROCKAWAY PARKWAY</td>\n      <td>  SKIDMORE AVENUE</td>\n      <td> INTERSECTION</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 08:52:46 AM</td>\n      <td>                    NaN</td>\n      <td>          18 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1015289</td>\n      <td> 169710</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.632437</td>\n      <td>-73.888173</td>\n      <td>  (40.63243692394328, -73.88817263437012)</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td> 26590389</td>\n      <td> 10/31/2013 12:51:00 AM</td>\n      <td>                    NaN</td>\n      <td>   DOT</td>\n      <td>                      Department of Transportation</td>\n      <td>   Street Light Condition</td>\n      <td>                 Street Light Out</td>\n      <td>                           NaN</td>\n      <td>   NaN</td>\n      <td>               226 42 ST E</td>\n      <td>             42 ST E</td>\n      <td>        CHURCH AVE</td>\n      <td>                       SNYDER AVE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>                 NaN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td> Unspecified BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>     NaN</td>\n      <td>    NaN</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>       NaN</td>\n      <td>       NaN</td>\n      <td>                                      NaN</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td> 26594210</td>\n      <td> 10/31/2013 12:46:27 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10033</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td> WEST  184 STREET</td>\n      <td>         BROADWAY</td>\n      <td> INTERSECTION</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 08:46:27 AM</td>\n      <td> 10/31/2013 01:32:41 AM</td>\n      <td>         12 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td> 1002294</td>\n      <td> 249712</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.852058</td>\n      <td>-73.934776</td>\n      <td>  (40.85205827756883, -73.93477640780834)</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td> 26592932</td>\n      <td> 10/31/2013 12:43:47 AM</td>\n      <td> 10/31/2013 12:56:20 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td> Noise - House of Worship</td>\n      <td>                 Loud Music/Party</td>\n      <td>              House of Worship</td>\n      <td> 11216</td>\n      <td>            778 PARK PLACE</td>\n      <td>          PARK PLACE</td>\n      <td>     ROGERS AVENUE</td>\n      <td>                  NOSTRAND AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:43:47 AM</td>\n      <td> 10/31/2013 12:56:20 AM</td>\n      <td>          08 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  997608</td>\n      <td> 184656</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.673505</td>\n      <td>-73.951844</td>\n      <td>  (40.67350473678714, -73.95184414979961)</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td> 26594152</td>\n      <td> 10/31/2013 12:41:17 AM</td>\n      <td> 10/31/2013 01:04:37 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Banging/Pounding</td>\n      <td>              Store/Commercial</td>\n      <td> 10016</td>\n      <td>             155 E 34TH ST</td>\n      <td>           E 34TH ST</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      LATLONG</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:41:17 AM</td>\n      <td> 10/31/2013 01:04:38 AM</td>\n      <td>         06 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  990133</td>\n      <td> 211136</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.746194</td>\n      <td>-73.978769</td>\n      <td>  (40.74619417253121, -73.97876853124392)</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td> 26589678</td>\n      <td> 10/31/2013 12:39:55 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>          Noise - Vehicle</td>\n      <td>                  Car/Truck Music</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11419</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>       112 STREET</td>\n      <td>  ATLANTIC AVENUE</td>\n      <td> INTERSECTION</td>\n      <td> SOUTH RICHMOND HILL</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 08:39:55 AM</td>\n      <td>                    NaN</td>\n      <td>            09 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1030314</td>\n      <td> 191578</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.692394</td>\n      <td>-73.833891</td>\n      <td>   (40.69239424979043, -73.8338912453996)</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td> 26592304</td>\n      <td> 10/31/2013 12:38:00 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11216</td>\n      <td>       371 TOMPKINS AVENUE</td>\n      <td>     TOMPKINS AVENUE</td>\n      <td>    MADISON STREET</td>\n      <td>                    PUTNAM AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 08:38:00 AM</td>\n      <td> 10/31/2013 01:16:53 AM</td>\n      <td>          03 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  999720</td>\n      <td> 188825</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.684944</td>\n      <td>-73.944221</td>\n      <td>   (40.6849442562592, -73.94422078036632)</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td> 26591892</td>\n      <td> 10/31/2013 12:37:16 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>         Blocked Driveway</td>\n      <td>                   Partial Access</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10305</td>\n      <td>           1496 BAY STREET</td>\n      <td>          BAY STREET</td>\n      <td>      LYMAN AVENUE</td>\n      <td>                      SCHOOL ROAD</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>       STATEN ISLAND</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 08:37:16 AM</td>\n      <td> 10/31/2013 12:52:10 AM</td>\n      <td>     01 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  967283</td>\n      <td> 160518</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.607245</td>\n      <td>-74.061106</td>\n      <td>  (40.60724493456944, -74.06110566015863)</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td> 26591573</td>\n      <td> 10/31/2013 12:35:18 AM</td>\n      <td> 10/31/2013 02:41:35 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                     Loud Talking</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10312</td>\n      <td>         24 PRINCETON LANE</td>\n      <td>      PRINCETON LANE</td>\n      <td>     HAMPTON GREEN</td>\n      <td>                         DEAD END</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>       STATEN ISLAND</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:35:18 AM</td>\n      <td> 10/31/2013 01:45:17 AM</td>\n      <td>     03 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  929577</td>\n      <td> 140964</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.553421</td>\n      <td>-74.196743</td>\n      <td>  (40.55342078716953, -74.19674315017886)</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td> 26590509</td>\n      <td> 10/31/2013 12:33:00 AM</td>\n      <td>                    NaN</td>\n      <td>   DOT</td>\n      <td>                      Department of Transportation</td>\n      <td>   Street Light Condition</td>\n      <td>                 Street Light Out</td>\n      <td>                           NaN</td>\n      <td>   NaN</td>\n      <td>                   38 ST E</td>\n      <td>             38 ST E</td>\n      <td>        CHURCH AVE</td>\n      <td>                      LINDEN BLVD</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>                 NaN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td> Unspecified BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>     NaN</td>\n      <td>    NaN</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>       NaN</td>\n      <td>       NaN</td>\n      <td>                                      NaN</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td> 26591379</td>\n      <td> 10/31/2013 12:32:44 AM</td>\n      <td>                    NaN</td>\n      <td> DOHMH</td>\n      <td>           Department of Health and Mental Hygiene</td>\n      <td>     Harboring Bees/Wasps</td>\n      <td>      Bees/Wasps - Not a beekeper</td>\n      <td>  3+ Family Mixed Use Building</td>\n      <td> 10025</td>\n      <td>       501 WEST 110 STREET</td>\n      <td>     WEST 110 STREET</td>\n      <td>  AMSTERDAM AVENUE</td>\n      <td>                         BROADWAY</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td> 11/30/2013 12:32:44 AM</td>\n      <td>                    NaN</td>\n      <td>         09 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  994143</td>\n      <td> 231888</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.803149</td>\n      <td>-73.964266</td>\n      <td>  (40.80314938553783, -73.96426608076082)</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td> 26594085</td>\n      <td> 10/31/2013 12:32:08 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                     Loud Talking</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10026</td>\n      <td>       121 WEST 116 STREET</td>\n      <td>     WEST 116 STREET</td>\n      <td>      LENOX AVENUE</td>\n      <td>                         7 AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 08:32:08 AM</td>\n      <td> 10/31/2013 02:00:57 AM</td>\n      <td>         10 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  997947</td>\n      <td> 231613</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.802390</td>\n      <td>-73.950526</td>\n      <td>  (40.80238950799943, -73.95052644123253)</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td> 26589201</td>\n      <td> 10/31/2013 12:32:00 AM</td>\n      <td>                    NaN</td>\n      <td>   DOT</td>\n      <td>                      Department of Transportation</td>\n      <td>   Street Light Condition</td>\n      <td>                 Street Light Out</td>\n      <td>                           NaN</td>\n      <td> 10309</td>\n      <td>        295 BAYVIEW AVENUE</td>\n      <td>      BAYVIEW AVENUE</td>\n      <td>       VAIL AVENUE</td>\n      <td>                     BAYVIEW LANE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>       STATEN ISLAND</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td>     03 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  927687</td>\n      <td> 127837</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.517378</td>\n      <td>-74.203435</td>\n      <td> (40.517377871705676, -74.20343466779575)</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td> 26591641</td>\n      <td> 10/31/2013 12:31:17 AM</td>\n      <td> 10/31/2013 02:41:36 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>         Blocked Driveway</td>\n      <td>                        No Access</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10312</td>\n      <td>         24 PRINCETON LANE</td>\n      <td>      PRINCETON LANE</td>\n      <td>     HAMPTON GREEN</td>\n      <td>                         DEAD END</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>       STATEN ISLAND</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:31:17 AM</td>\n      <td> 10/31/2013 01:43:09 AM</td>\n      <td>     03 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  929577</td>\n      <td> 140964</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.553421</td>\n      <td>-74.196743</td>\n      <td>  (40.55342078716953, -74.19674315017886)</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td> 26595564</td>\n      <td> 10/31/2013 12:30:36 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                 Loud Music/Party</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11236</td>\n      <td>                  AVENUE J</td>\n      <td>            AVENUE J</td>\n      <td>    EAST 80 STREET</td>\n      <td>                   EAST 81 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 08:30:36 AM</td>\n      <td>                    NaN</td>\n      <td>          18 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1008937</td>\n      <td> 170310</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.634104</td>\n      <td>-73.911055</td>\n      <td> (40.634103775951736, -73.91105541883589)</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td> 26591378</td>\n      <td> 10/31/2013 12:30:31 AM</td>\n      <td>                    NaN</td>\n      <td>   TLC</td>\n      <td>                     Taxi and Limousine Commission</td>\n      <td>           Taxi Complaint</td>\n      <td>                 Driver Complaint</td>\n      <td>                           NaN</td>\n      <td> 10036</td>\n      <td>             645 10 AVENUE</td>\n      <td>           10 AVENUE</td>\n      <td>    WEST 45 STREET</td>\n      <td>                   WEST 46 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td>         04 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  985965</td>\n      <td> 216868</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> Other</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.761929</td>\n      <td>-73.993809</td>\n      <td> (40.761928847500016, -73.99380918401052)</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td> 26593872</td>\n      <td> 10/31/2013 12:29:47 AM</td>\n      <td> 10/31/2013 12:38:29 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td> Noise - House of Worship</td>\n      <td>                 Banging/Pounding</td>\n      <td>              House of Worship</td>\n      <td> 10025</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td> WEST   99 STREET</td>\n      <td> AMSTERDAM AVENUE</td>\n      <td> INTERSECTION</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:29:47 AM</td>\n      <td> 10/31/2013 12:38:29 AM</td>\n      <td>         07 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  992846</td>\n      <td> 229279</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.795990</td>\n      <td>-73.968954</td>\n      <td> (40.795989749917204, -73.96895423714467)</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td> 26591420</td>\n      <td> 10/31/2013 12:28:30 AM</td>\n      <td> 10/31/2013 02:06:11 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>      Homeless Encampment</td>\n      <td>                              NaN</td>\n      <td>    Residential Building/House</td>\n      <td> 10025</td>\n      <td>             2754 BROADWAY</td>\n      <td>            BROADWAY</td>\n      <td>   WEST 105 STREET</td>\n      <td>                  WEST 106 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:28:30 AM</td>\n      <td> 10/31/2013 02:06:11 AM</td>\n      <td>         07 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  993139</td>\n      <td> 231139</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.801095</td>\n      <td>-73.967894</td>\n      <td>   (40.8010946529914, -73.96789356094007)</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td> 26592976</td>\n      <td> 10/31/2013 12:23:24 AM</td>\n      <td> 10/31/2013 01:05:41 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>         Blocked Driveway</td>\n      <td>                        No Access</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11433</td>\n      <td>           173-41 103 ROAD</td>\n      <td>            103 ROAD</td>\n      <td>        173 STREET</td>\n      <td>                       177 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>             JAMAICA</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:23:24 AM</td>\n      <td> 10/31/2013 01:05:41 AM</td>\n      <td>            12 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1044124</td>\n      <td> 195866</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.704081</td>\n      <td>-73.784054</td>\n      <td>  (40.70408112125158, -73.78405385422116)</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td> 26590262</td>\n      <td> 10/31/2013 12:23:00 AM</td>\n      <td>                    NaN</td>\n      <td>   DOT</td>\n      <td>                      Department of Transportation</td>\n      <td> Traffic Signal Condition</td>\n      <td>                       Controller</td>\n      <td>                           NaN</td>\n      <td> 11235</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>  SHORE BOULEVARD</td>\n      <td>       CASS PLACE</td>\n      <td> INTERSECTION</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td>          15 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  997073</td>\n      <td> 151225</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.581744</td>\n      <td>-73.953836</td>\n      <td>   (40.5817444882428, -73.95383634845487)</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td> 26589606</td>\n      <td> 10/31/2013 12:20:44 AM</td>\n      <td> 10/31/2013 02:10:24 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11216</td>\n      <td>       826 ST JOHN'S PLACE</td>\n      <td>     ST JOHN'S PLACE</td>\n      <td>     ROGERS AVENUE</td>\n      <td>                  NOSTRAND AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:20:44 AM</td>\n      <td> 10/31/2013 02:10:24 AM</td>\n      <td>          08 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  997865</td>\n      <td> 183985</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.671663</td>\n      <td>-73.950919</td>\n      <td> (40.671662601079895, -73.95091901534035)</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td> 26592083</td>\n      <td> 10/31/2013 12:20:00 AM</td>\n      <td>                    NaN</td>\n      <td>   DOT</td>\n      <td>                      Department of Transportation</td>\n      <td> Traffic Signal Condition</td>\n      <td>                       Controller</td>\n      <td>                           NaN</td>\n      <td> 11213</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>   BUFFALO AVENUE</td>\n      <td>       PARK PLACE</td>\n      <td> INTERSECTION</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td>          08 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1004987</td>\n      <td> 184136</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.672063</td>\n      <td>-73.925244</td>\n      <td>  (40.67206324438088, -73.92524432147842)</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td> 26593840</td>\n      <td> 10/31/2013 12:19:48 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>         Blocked Driveway</td>\n      <td>                        No Access</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11379</td>\n      <td>             78-41 68 ROAD</td>\n      <td>             68 ROAD</td>\n      <td>         78 STREET</td>\n      <td>                        79 STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>      MIDDLE VILLAGE</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 08:19:48 AM</td>\n      <td>                    NaN</td>\n      <td>            05 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1019062</td>\n      <td> 198120</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.710402</td>\n      <td>-73.874433</td>\n      <td>   (40.71040190143904, -73.8744325577748)</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td> 26589646</td>\n      <td> 10/31/2013 12:18:05 AM</td>\n      <td> 10/31/2013 01:26:15 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11101</td>\n      <td>     34-19 STEINWAY STREET</td>\n      <td>     STEINWAY STREET</td>\n      <td>         34 AVENUE</td>\n      <td>                        35 AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>    LONG ISLAND CITY</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:18:05 AM</td>\n      <td> 10/31/2013 01:26:15 AM</td>\n      <td>            01 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1006080</td>\n      <td> 214807</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.756245</td>\n      <td>-73.921205</td>\n      <td>  (40.75624514774764, -73.92120466494264)</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td> 26593296</td>\n      <td> 10/31/2013 12:16:25 AM</td>\n      <td>                    NaN</td>\n      <td> DOHMH</td>\n      <td>           Department of Health and Mental Hygiene</td>\n      <td>       Food Establishment</td>\n      <td>          Rodents/Insects/Garbage</td>\n      <td>    Restaurant/Bar/Deli/Bakery</td>\n      <td> 10014</td>\n      <td>     12 CHRISTOPHER STREET</td>\n      <td>  CHRISTOPHER STREET</td>\n      <td>  GREENWICH AVENUE</td>\n      <td>                       GAY STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td> 12/07/2013 12:16:25 AM</td>\n      <td>                    NaN</td>\n      <td>         02 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  984181</td>\n      <td> 206685</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.733979</td>\n      <td>-74.000249</td>\n      <td>   (40.73397924003587, -74.0002489720853)</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td> 26590480</td>\n      <td> 10/31/2013 12:15:06 AM</td>\n      <td> 10/31/2013 03:00:20 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>              Store/Commercial</td>\n      <td> 11231</td>\n      <td>       325 COLUMBIA STREET</td>\n      <td>     COLUMBIA STREET</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      LATLONG</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:15:06 AM</td>\n      <td> 10/31/2013 02:58:55 AM</td>\n      <td>          06 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  982995</td>\n      <td> 187440</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.681156</td>\n      <td>-74.004525</td>\n      <td>  (40.68115617695543, -74.00452481832494)</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td> 26589626</td>\n      <td> 10/31/2013 12:14:42 AM</td>\n      <td> 10/31/2013 01:39:00 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 11234</td>\n      <td>      2192 FLATBUSH AVENUE</td>\n      <td>     FLATBUSH AVENUE</td>\n      <td>    EAST 46 STREET</td>\n      <td>                         AVENUE O</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:14:42 AM</td>\n      <td> 10/31/2013 01:39:00 AM</td>\n      <td>          18 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1003628</td>\n      <td> 163910</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.616550</td>\n      <td>-73.930202</td>\n      <td>  (40.61655032892211, -73.93020153359745)</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td> 26592898</td>\n      <td> 10/31/2013 12:12:08 AM</td>\n      <td> 10/31/2013 01:13:45 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>             Noise - Park</td>\n      <td>                     Loud Talking</td>\n      <td>               Park/Playground</td>\n      <td> 10457</td>\n      <td>        CROTONA PARK NORTH</td>\n      <td>  CROTONA PARK NORTH</td>\n      <td>    CLINTON AVENUE</td>\n      <td>                  PROSPECT AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>    BLOCKFACE</td>\n      <td>               BRONX</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:12:08 AM</td>\n      <td> 10/31/2013 01:13:45 AM</td>\n      <td>             06 BRONX</td>\n      <td>         BRONX</td>\n      <td> 1013947</td>\n      <td> 245819</td>\n      <td> Unspecified</td>\n      <td>         BRONX</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.841342</td>\n      <td>-73.892672</td>\n      <td> (40.841341641554614, -73.89267161957397)</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td> 26590446</td>\n      <td> 10/31/2013 12:11:58 AM</td>\n      <td> 10/31/2013 01:54:38 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                 Loud Music/Party</td>\n      <td>               Street/Sidewalk</td>\n      <td> 10459</td>\n      <td>       819 EAST 167 STREET</td>\n      <td>     EAST 167 STREET</td>\n      <td>      UNION AVENUE</td>\n      <td>                  PROSPECT AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>               BRONX</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:11:58 AM</td>\n      <td> 10/31/2013 01:54:38 AM</td>\n      <td>             03 BRONX</td>\n      <td>         BRONX</td>\n      <td> 1011935</td>\n      <td> 240454</td>\n      <td> Unspecified</td>\n      <td>         BRONX</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.826623</td>\n      <td>-73.899965</td>\n      <td>  (40.826622810177874, -73.8999653556452)</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td> 26595546</td>\n      <td> 10/31/2013 12:09:07 AM</td>\n      <td> 10/31/2013 12:53:12 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10465</td>\n      <td>  4005 EAST TREMONT AVENUE</td>\n      <td> EAST TREMONT AVENUE</td>\n      <td>    SAMPSON AVENUE</td>\n      <td>                     GERBER PLACE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>               BRONX</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:09:07 AM</td>\n      <td> 10/31/2013 12:53:12 AM</td>\n      <td>             10 BRONX</td>\n      <td>         BRONX</td>\n      <td> 1034640</td>\n      <td> 238172</td>\n      <td> Unspecified</td>\n      <td>         BRONX</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.820259</td>\n      <td>-73.817942</td>\n      <td> (40.820259030934515, -73.81794234356029)</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td> 26595944</td>\n      <td> 10/31/2013 12:08:47 AM</td>\n      <td>                    NaN</td>\n      <td>   TLC</td>\n      <td>                     Taxi and Limousine Commission</td>\n      <td>           Taxi Complaint</td>\n      <td>                 Driver Complaint</td>\n      <td>                           NaN</td>\n      <td> 10036</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td> WEST   46 STREET</td>\n      <td>        10 AVENUE</td>\n      <td> INTERSECTION</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td> 11/14/2013 12:08:47 AM</td>\n      <td>                    NaN</td>\n      <td>         04 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  986020</td>\n      <td> 216961</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> Other</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.762184</td>\n      <td>-73.993611</td>\n      <td>  (40.76218409774632, -73.99361062023596)</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td> 26595084</td>\n      <td> 10/31/2013 12:07:45 AM</td>\n      <td> 10/31/2013 01:43:11 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10014</td>\n      <td>     12 CHRISTOPHER STREET</td>\n      <td>  CHRISTOPHER STREET</td>\n      <td>  GREENWICH AVENUE</td>\n      <td>                       GAY STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:07:45 AM</td>\n      <td> 10/31/2013 01:43:11 AM</td>\n      <td>         02 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  984181</td>\n      <td> 206685</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.733979</td>\n      <td>-74.000249</td>\n      <td>   (40.73397924003587, -74.0002489720853)</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td> 26595553</td>\n      <td> 10/31/2013 12:05:10 AM</td>\n      <td> 10/31/2013 02:43:43 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>                     Loud Talking</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11225</td>\n      <td>        25 LEFFERTS AVENUE</td>\n      <td>     LEFFERTS AVENUE</td>\n      <td> WASHINGTON AVENUE</td>\n      <td>                   BEDFORD AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:05:10 AM</td>\n      <td> 10/31/2013 01:29:29 AM</td>\n      <td>          09 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  995366</td>\n      <td> 180388</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.661793</td>\n      <td>-73.959934</td>\n      <td>   (40.6617931276793, -73.95993363978067)</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td> 26594087</td>\n      <td> 10/31/2013 12:04:50 AM</td>\n      <td> 10/31/2013 01:09:38 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>              Store/Commercial</td>\n      <td> 10011</td>\n      <td>      258 WEST 15TH STREET</td>\n      <td>    WEST 15TH STREET</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      LATLONG</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:04:50 AM</td>\n      <td> 10/31/2013 01:09:38 AM</td>\n      <td>         04 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  983789</td>\n      <td> 208891</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.740034</td>\n      <td>-74.001664</td>\n      <td>  (40.74003415280169, -74.00166357336052)</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td> 26595572</td>\n      <td> 10/31/2013 12:03:27 AM</td>\n      <td>                    NaN</td>\n      <td>   DOT</td>\n      <td>                      Department of Transportation</td>\n      <td>        Broken Muni Meter</td>\n      <td>                       No Receipt</td>\n      <td>                        Street</td>\n      <td> 10003</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td> EAST   10 STREET</td>\n      <td>         2 AVENUE</td>\n      <td> INTERSECTION</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td> 11/21/2013 12:03:27 AM</td>\n      <td>                    NaN</td>\n      <td>         03 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  987906</td>\n      <td> 205154</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.729776</td>\n      <td>-73.986809</td>\n      <td>  (40.72977626532991, -73.98680891976119)</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td> 26590848</td>\n      <td> 10/31/2013 12:02:01 AM</td>\n      <td> 10/31/2013 01:02:28 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>         Blocked Driveway</td>\n      <td>                        No Access</td>\n      <td>               Street/Sidewalk</td>\n      <td> 11207</td>\n      <td>          422 WYONA STREET</td>\n      <td>        WYONA STREET</td>\n      <td>     SUTTER AVENUE</td>\n      <td>                     BLAKE AVENUE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:02:01 AM</td>\n      <td> 10/31/2013 01:02:28 AM</td>\n      <td>          05 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1014188</td>\n      <td> 182855</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.668521</td>\n      <td>-73.892081</td>\n      <td>  (40.66852085465471, -73.89208096944678)</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td> 26590413</td>\n      <td> 10/31/2013 12:01:47 AM</td>\n      <td> 10/31/2013 12:39:31 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>           Club/Bar/Restaurant</td>\n      <td> 10002</td>\n      <td>      121 RIVINGTON STREET</td>\n      <td>    RIVINGTON STREET</td>\n      <td>      ESSEX STREET</td>\n      <td>                   NORFOLK STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:01:47 AM</td>\n      <td> 10/31/2013 12:39:31 AM</td>\n      <td>         03 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td>  987766</td>\n      <td> 201503</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.719755</td>\n      <td>-73.987316</td>\n      <td>  (40.71975521311322, -73.98731595609806)</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td> 26591287</td>\n      <td> 10/31/2013 12:01:45 AM</td>\n      <td> 10/31/2013 12:02:37 AM</td>\n      <td>   HRA</td>\n      <td>                      HRA Benefit Card Replacement</td>\n      <td> Benefit Card Replacement</td>\n      <td>                         Medicaid</td>\n      <td>            NYC Street Address</td>\n      <td>   NaN</td>\n      <td>                       NaN</td>\n      <td>                 NaN</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>          NaN</td>\n      <td>                 NaN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>   Closed</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td>        0 Unspecified</td>\n      <td>   Unspecified</td>\n      <td>     NaN</td>\n      <td>    NaN</td>\n      <td> Unspecified</td>\n      <td>   Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>       NaN</td>\n      <td>       NaN</td>\n      <td>                                      NaN</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td> 26595001</td>\n      <td> 10/31/2013 12:01:34 AM</td>\n      <td> 10/31/2013 01:32:43 AM</td>\n      <td>  NYPD</td>\n      <td>                   New York City Police Department</td>\n      <td>       Noise - Commercial</td>\n      <td>                 Loud Music/Party</td>\n      <td>              Store/Commercial</td>\n      <td> 10034</td>\n      <td>     524 WEST 207TH STREET</td>\n      <td>   WEST 207TH STREET</td>\n      <td>               NaN</td>\n      <td>                              NaN</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      LATLONG</td>\n      <td>            NEW YORK</td>\n      <td> NaN</td>\n      <td>    Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:01:34 AM</td>\n      <td> 10/31/2013 01:32:43 AM</td>\n      <td>         01 MANHATTAN</td>\n      <td>     MANHATTAN</td>\n      <td> 1006481</td>\n      <td> 254514</td>\n      <td> Unspecified</td>\n      <td>     MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td>   N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.865229</td>\n      <td>-73.919626</td>\n      <td>  (40.86522877164924, -73.91962575276823)</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td> 26591162</td>\n      <td> 10/31/2013 12:01:00 AM</td>\n      <td>                    NaN</td>\n      <td>  DSNY</td>\n      <td>                              BCC - Brooklyn South</td>\n      <td>     Sanitation Condition</td>\n      <td> 15 Street Cond/Dump-Out/Drop-Off</td>\n      <td>                        Street</td>\n      <td> 11231</td>\n      <td>       135 COLUMBIA STREET</td>\n      <td>     COLUMBIA STREET</td>\n      <td>       KANE STREET</td>\n      <td>                    IRVING STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td> DSNY Garage</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td>                    NaN</td>\n      <td>          06 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td>  983797</td>\n      <td> 189648</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.687217</td>\n      <td>-74.001633</td>\n      <td>  (40.68721671044577, -74.00163340956126)</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td> 26593459</td>\n      <td> 10/31/2013 12:00:00 AM</td>\n      <td>                    NaN</td>\n      <td>   HPD</td>\n      <td> Department of Housing Preservation and Develop...</td>\n      <td>                 ELECTRIC</td>\n      <td>                  ELECTRIC-SUPPLY</td>\n      <td>          RESIDENTIAL BUILDING</td>\n      <td> 11233</td>\n      <td>         199 HOWARD AVENUE</td>\n      <td>       HOWARD AVENUE</td>\n      <td> BAINBRIDGE STREET</td>\n      <td>                  CHAUNCEY STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td> 10/31/2013 12:00:00 AM</td>\n      <td>          03 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1006513</td>\n      <td> 187623</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.681631</td>\n      <td>-73.919732</td>\n      <td>  (40.68163056217252, -73.91973166452124)</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td> 26592634</td>\n      <td> 10/31/2013 12:00:00 AM</td>\n      <td>                    NaN</td>\n      <td>   HPD</td>\n      <td> Department of Housing Preservation and Develop...</td>\n      <td>                 PLUMBING</td>\n      <td>                       BASIN/SINK</td>\n      <td>          RESIDENTIAL BUILDING</td>\n      <td> 11233</td>\n      <td>         199 HOWARD AVENUE</td>\n      <td>       HOWARD AVENUE</td>\n      <td> BAINBRIDGE STREET</td>\n      <td>                  CHAUNCEY STREET</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>            BROOKLYN</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td> 10/31/2013 12:00:00 AM</td>\n      <td>          03 BROOKLYN</td>\n      <td>      BROOKLYN</td>\n      <td> 1006513</td>\n      <td> 187623</td>\n      <td> Unspecified</td>\n      <td>      BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.681631</td>\n      <td>-73.919732</td>\n      <td>  (40.68163056217252, -73.91973166452124)</td>\n    </tr>\n    <tr>\n      <th>59</th>\n      <td> 26591688</td>\n      <td> 10/31/2013 12:00:00 AM</td>\n      <td>                    NaN</td>\n      <td>   HPD</td>\n      <td> Department of Housing Preservation and Develop...</td>\n      <td>                  HEATING</td>\n      <td>                             HEAT</td>\n      <td>          RESIDENTIAL BUILDING</td>\n      <td> 10453</td>\n      <td>       150 WEST 179 STREET</td>\n      <td>     WEST 179 STREET</td>\n      <td>    ANDREWS AVENUE</td>\n      <td>                     LORING PLACE</td>\n      <td>              NaN</td>\n      <td>              NaN</td>\n      <td>      ADDRESS</td>\n      <td>               BRONX</td>\n      <td> NaN</td>\n      <td>         NaN</td>\n      <td>     Open</td>\n      <td>                    NaN</td>\n      <td> 10/31/2013 12:00:00 AM</td>\n      <td>             05 BRONX</td>\n      <td>         BRONX</td>\n      <td> 1008161</td>\n      <td> 250940</td>\n      <td> Unspecified</td>\n      <td>         BRONX</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> NaN</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.855415</td>\n      <td>-73.913565</td>\n      <td> (40.855414830918306, -73.91356461276855)</td>\n    </tr>\n    <tr>\n      <th></th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n  </tbody>\n</table>\n<p>111069 rows \u00d7 52 columns</p>\n</div>", "text/plain": "    Unique Key            Created Date             Closed Date Agency                                        Agency Name            Complaint Type                        Descriptor                  Location Type Incident Zip           Incident Address          Street Name     Cross Street 1                    Cross Street 2 Intersection Street 1 Intersection Street 2  Address Type                 City Landmark Facility Type    Status                Due Date Resolution Action Updated Date       Community Board        Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name   Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n0     26589651  10/31/2013 02:08:41 AM                     NaN   NYPD                    New York City Police Department   Noise - Street/Sidewalk                      Loud Talking                Street/Sidewalk        11432           90-03 169 STREET           169 STREET          90 AVENUE                         91 AVENUE                   NaN                   NaN       ADDRESS              JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM             12 QUEENS         QUEENS                     1042027                      197389        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604   (40.70827532593202, -73.79160395779721)\n1     26593698  10/31/2013 02:01:04 AM                     NaN   NYPD                    New York City Police Department           Illegal Parking      Commercial Overnight Parking                Street/Sidewalk        11378                  58 AVENUE            58 AVENUE           58 PLACE                         59 STREET                   NaN                   NaN     BLOCKFACE              MASPETH      NaN      Precinct      Open  10/31/2013 10:01:04 AM                            NaN             05 QUEENS         QUEENS                     1009349                      201984        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.721041 -73.909453  (40.721040535628305, -73.90945306791765)\n2     26594139  10/31/2013 02:00:24 AM  10/31/2013 02:40:32 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        10032              4060 BROADWAY             BROADWAY    WEST 171 STREET                   WEST 172 STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 10:00:24 AM         10/31/2013 02:39:42 AM          12 MANHATTAN      MANHATTAN                     1001088                      246531        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.843330 -73.939144   (40.84332975466513, -73.93914371913482)\n3     26595721  10/31/2013 01:56:23 AM  10/31/2013 02:21:48 AM   NYPD                    New York City Police Department           Noise - Vehicle                    Car/Truck Horn                Street/Sidewalk        10023             WEST 72 STREET       WEST 72 STREET    COLUMBUS AVENUE                  AMSTERDAM AVENUE                   NaN                   NaN     BLOCKFACE             NEW YORK      NaN      Precinct    Closed  10/31/2013 09:56:23 AM         10/31/2013 02:21:10 AM          07 MANHATTAN      MANHATTAN                      989730                      222727        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.778009 -73.980213    (40.7780087446372, -73.98021349023975)\n4     26590930  10/31/2013 01:53:44 AM                     NaN  DOHMH            Department of Health and Mental Hygiene                    Rodent      Condition Attracting Rodents                     Vacant Lot        10027            WEST 124 STREET      WEST 124 STREET       LENOX AVENUE  ADAM CLAYTON POWELL JR BOULEVARD                   NaN                   NaN     BLOCKFACE             NEW YORK      NaN           NaN   Pending  11/30/2013 01:53:44 AM         10/31/2013 01:59:54 AM          10 MANHATTAN      MANHATTAN                      998815                      233545        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.807691 -73.947387   (40.80769092704951, -73.94738703491433)\n5     26592370  10/31/2013 01:46:52 AM                     NaN   NYPD                    New York City Police Department        Noise - Commercial                  Banging/Pounding            Club/Bar/Restaurant        11372                  37 AVENUE            37 AVENUE          84 STREET                         85 STREET                   NaN                   NaN     BLOCKFACE      JACKSON HEIGHTS      NaN      Precinct      Open  10/31/2013 09:46:52 AM                            NaN             03 QUEENS         QUEENS                     1016948                      212540        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.749989 -73.881988    (40.7499893014072, -73.88198770727831)\n6     26595682  10/31/2013 01:46:40 AM                     NaN   NYPD                    New York City Police Department          Blocked Driveway                         No Access                Street/Sidewalk        11419          107-50 109 STREET           109 STREET         107 AVENUE                        109 AVENUE                   NaN                   NaN       ADDRESS  SOUTH RICHMOND HILL      NaN      Precinct  Assigned  10/31/2013 09:46:40 AM         10/31/2013 01:59:51 AM             10 QUEENS         QUEENS                     1030919                      187622        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.681533 -73.831737   (40.68153278675525, -73.83173699701601)\n7     26595195  10/31/2013 01:44:19 AM  10/31/2013 01:58:49 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        11417  137-09 CROSSBAY BOULEVARD   CROSSBAY BOULEVARD      PITKIN AVENUE                  VAN WICKLEN ROAD                   NaN                   NaN       ADDRESS           OZONE PARK      NaN      Precinct    Closed  10/31/2013 09:44:19 AM         10/31/2013 01:58:49 AM             10 QUEENS         QUEENS                     1027776                      184076        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.671816 -73.843092   (40.67181584567338, -73.84309181950769)\n8     26590540  10/31/2013 01:44:14 AM  10/31/2013 02:28:04 AM   NYPD                    New York City Police Department        Noise - Commercial                      Loud Talking            Club/Bar/Restaurant        10011         258 WEST 15 STREET       WEST 15 STREET           7 AVENUE                          8 AVENUE                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 09:44:14 AM         10/31/2013 02:00:56 AM          04 MANHATTAN      MANHATTAN                      984031                      208847        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.739913 -74.000790   (40.73991339303542, -74.00079028612932)\n9     26594392  10/31/2013 01:34:41 AM  10/31/2013 02:23:51 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        11225        835 NOSTRAND AVENUE      NOSTRAND AVENUE       UNION STREET                  PRESIDENT STREET                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct    Closed  10/31/2013 09:34:41 AM         10/31/2013 01:48:26 AM           09 BROOKLYN       BROOKLYN                      997941                      182725        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.668204 -73.950648   (40.66820406598287, -73.95064760056546)\n10    26595176  10/31/2013 01:25:12 AM                     NaN   NYPD                    New York City Police Department  Noise - House of Worship                  Loud Music/Party               House of Worship        11218             3775 18 AVENUE            18 AVENUE      EAST 9 STREET                     EAST 8 STREET                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct      Open  10/31/2013 09:25:12 AM                            NaN           14 BROOKLYN       BROOKLYN                      992726                      170399        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.634378 -73.969462   (40.63437840816299, -73.96946177104543)\n11    26591982  10/31/2013 01:24:14 AM  10/31/2013 01:54:39 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        10003               187 2 AVENUE             2 AVENUE     EAST 11 STREET                    EAST 12 STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 09:24:14 AM         10/31/2013 01:54:39 AM          03 MANHATTAN      MANHATTAN                      988110                      205533        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.730816 -73.986073   (40.73081644089586, -73.98607265739876)\n12    26594169  10/31/2013 01:20:57 AM  10/31/2013 02:12:31 AM   NYPD                    New York City Police Department           Illegal Parking    Double Parked Blocking Vehicle                Street/Sidewalk        10029          65 EAST 99 STREET       EAST 99 STREET     MADISON AVENUE                       PARK AVENUE                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 09:20:57 AM         10/31/2013 01:42:05 AM          11 MANHATTAN      MANHATTAN                      997470                      226725        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.788974 -73.952259   (40.78897400211689, -73.95225898702977)\n13    26594391  10/31/2013 01:20:13 AM                     NaN   NYPD                    New York City Police Department           Noise - Vehicle                     Engine Idling                Street/Sidewalk        10466                        NaN                  NaN                NaN                               NaN         STRANG AVENUE       AMUNDSON AVENUE  INTERSECTION                BRONX      NaN      Precinct      Open  10/31/2013 09:20:13 AM                            NaN              12 BRONX          BRONX                     1029467                      264124        Unspecified          BRONX  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.891517 -73.836457   (40.89151738488846, -73.83645714593568)\n14    26590917  10/31/2013 01:19:54 AM                     NaN  DOHMH            Department of Health and Mental Hygiene                    Rodent                      Rat Sighting  1-2 Family Mixed Use Building        11219                  63 STREET            63 STREET          13 AVENUE                         14 AVENUE                   NaN                   NaN     BLOCKFACE             BROOKLYN      NaN           NaN   Pending  11/30/2013 01:19:54 AM         10/31/2013 01:29:26 AM           10 BROOKLYN       BROOKLYN                      984467                      167519        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.626477 -73.999218    (40.6264774690411, -73.99921826202639)\n15    26591458  10/31/2013 01:14:02 AM  10/31/2013 01:30:34 AM   NYPD                    New York City Police Department  Noise - House of Worship                  Loud Music/Party               House of Worship        10025                        NaN                  NaN                NaN                               NaN      WEST   99 STREET              BROADWAY  INTERSECTION             NEW YORK      NaN      Precinct    Closed  10/31/2013 09:14:02 AM         10/31/2013 01:30:34 AM          07 MANHATTAN      MANHATTAN                      992454                      229500        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.796597 -73.970370    (40.7965967075252, -73.97036973473399)\n16    26594086  10/31/2013 12:54:03 AM  10/31/2013 02:16:39 AM   NYPD                    New York City Police Department   Noise - Street/Sidewalk                  Loud Music/Party                Street/Sidewalk        10310        173 CAMPBELL AVENUE      CAMPBELL AVENUE   HENDERSON AVENUE                      WINEGAR LANE                   NaN                   NaN       ADDRESS        STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:54:03 AM         10/31/2013 02:07:14 AM      01 STATEN ISLAND  STATEN ISLAND                      952013                      171076        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.636182 -74.116150    (40.63618202176914, -74.1161500428337)\n17    26595117  10/31/2013 12:52:46 AM                     NaN   NYPD                    New York City Police Department           Illegal Parking     Posted Parking Sign Violation                Street/Sidewalk        11236                        NaN                  NaN                NaN                               NaN      ROCKAWAY PARKWAY       SKIDMORE AVENUE  INTERSECTION             BROOKLYN      NaN      Precinct      Open  10/31/2013 08:52:46 AM                            NaN           18 BROOKLYN       BROOKLYN                     1015289                      169710        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.632437 -73.888173   (40.63243692394328, -73.88817263437012)\n18    26590389  10/31/2013 12:51:00 AM                     NaN    DOT                       Department of Transportation    Street Light Condition                  Street Light Out                            NaN          NaN                226 42 ST E              42 ST E         CHURCH AVE                        SNYDER AVE                   NaN                   NaN       ADDRESS                  NaN      NaN           NaN      Open                     NaN                            NaN  Unspecified BROOKLYN       BROOKLYN                         NaN                         NaN        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN        NaN        NaN                                       NaN\n19    26594210  10/31/2013 12:46:27 AM                     NaN   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        10033                        NaN                  NaN                NaN                               NaN      WEST  184 STREET              BROADWAY  INTERSECTION             NEW YORK      NaN      Precinct  Assigned  10/31/2013 08:46:27 AM         10/31/2013 01:32:41 AM          12 MANHATTAN      MANHATTAN                     1002294                      249712        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.852058 -73.934776   (40.85205827756883, -73.93477640780834)\n20    26592932  10/31/2013 12:43:47 AM  10/31/2013 12:56:20 AM   NYPD                    New York City Police Department  Noise - House of Worship                  Loud Music/Party               House of Worship        11216             778 PARK PLACE           PARK PLACE      ROGERS AVENUE                   NOSTRAND AVENUE                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct    Closed  10/31/2013 08:43:47 AM         10/31/2013 12:56:20 AM           08 BROOKLYN       BROOKLYN                      997608                      184656        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.673505 -73.951844   (40.67350473678714, -73.95184414979961)\n21    26594152  10/31/2013 12:41:17 AM  10/31/2013 01:04:37 AM   NYPD                    New York City Police Department        Noise - Commercial                  Banging/Pounding               Store/Commercial        10016              155 E 34TH ST            E 34TH ST                NaN                               NaN                   NaN                   NaN       LATLONG             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:41:17 AM         10/31/2013 01:04:38 AM          06 MANHATTAN      MANHATTAN                      990133                      211136        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.746194 -73.978769   (40.74619417253121, -73.97876853124392)\n22    26589678  10/31/2013 12:39:55 AM                     NaN   NYPD                    New York City Police Department           Noise - Vehicle                   Car/Truck Music                Street/Sidewalk        11419                        NaN                  NaN                NaN                               NaN            112 STREET       ATLANTIC AVENUE  INTERSECTION  SOUTH RICHMOND HILL      NaN      Precinct      Open  10/31/2013 08:39:55 AM                            NaN             09 QUEENS         QUEENS                     1030314                      191578        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.692394 -73.833891    (40.69239424979043, -73.8338912453996)\n23    26592304  10/31/2013 12:38:00 AM                     NaN   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        11216        371 TOMPKINS AVENUE      TOMPKINS AVENUE     MADISON STREET                     PUTNAM AVENUE                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct  Assigned  10/31/2013 08:38:00 AM         10/31/2013 01:16:53 AM           03 BROOKLYN       BROOKLYN                      999720                      188825        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.684944 -73.944221    (40.6849442562592, -73.94422078036632)\n24    26591892  10/31/2013 12:37:16 AM                     NaN   NYPD                    New York City Police Department          Blocked Driveway                    Partial Access                Street/Sidewalk        10305            1496 BAY STREET           BAY STREET       LYMAN AVENUE                       SCHOOL ROAD                   NaN                   NaN       ADDRESS        STATEN ISLAND      NaN      Precinct  Assigned  10/31/2013 08:37:16 AM         10/31/2013 12:52:10 AM      01 STATEN ISLAND  STATEN ISLAND                      967283                      160518        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.607245 -74.061106   (40.60724493456944, -74.06110566015863)\n25    26591573  10/31/2013 12:35:18 AM  10/31/2013 02:41:35 AM   NYPD                    New York City Police Department   Noise - Street/Sidewalk                      Loud Talking                Street/Sidewalk        10312          24 PRINCETON LANE       PRINCETON LANE      HAMPTON GREEN                          DEAD END                   NaN                   NaN       ADDRESS        STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:35:18 AM         10/31/2013 01:45:17 AM      03 STATEN ISLAND  STATEN ISLAND                      929577                      140964        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.553421 -74.196743   (40.55342078716953, -74.19674315017886)\n26    26590509  10/31/2013 12:33:00 AM                     NaN    DOT                       Department of Transportation    Street Light Condition                  Street Light Out                            NaN          NaN                    38 ST E              38 ST E         CHURCH AVE                       LINDEN BLVD                   NaN                   NaN     BLOCKFACE                  NaN      NaN           NaN      Open                     NaN                            NaN  Unspecified BROOKLYN       BROOKLYN                         NaN                         NaN        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN        NaN        NaN                                       NaN\n27    26591379  10/31/2013 12:32:44 AM                     NaN  DOHMH            Department of Health and Mental Hygiene      Harboring Bees/Wasps       Bees/Wasps - Not a beekeper   3+ Family Mixed Use Building        10025        501 WEST 110 STREET      WEST 110 STREET   AMSTERDAM AVENUE                          BROADWAY                   NaN                   NaN       ADDRESS             NEW YORK      NaN           NaN      Open  11/30/2013 12:32:44 AM                            NaN          09 MANHATTAN      MANHATTAN                      994143                      231888        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.803149 -73.964266   (40.80314938553783, -73.96426608076082)\n28    26594085  10/31/2013 12:32:08 AM                     NaN   NYPD                    New York City Police Department   Noise - Street/Sidewalk                      Loud Talking                Street/Sidewalk        10026        121 WEST 116 STREET      WEST 116 STREET       LENOX AVENUE                          7 AVENUE                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct  Assigned  10/31/2013 08:32:08 AM         10/31/2013 02:00:57 AM          10 MANHATTAN      MANHATTAN                      997947                      231613        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.802390 -73.950526   (40.80238950799943, -73.95052644123253)\n29    26589201  10/31/2013 12:32:00 AM                     NaN    DOT                       Department of Transportation    Street Light Condition                  Street Light Out                            NaN        10309         295 BAYVIEW AVENUE       BAYVIEW AVENUE        VAIL AVENUE                      BAYVIEW LANE                   NaN                   NaN       ADDRESS        STATEN ISLAND      NaN           NaN      Open                     NaN                            NaN      03 STATEN ISLAND  STATEN ISLAND                      927687                      127837        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.517378 -74.203435  (40.517377871705676, -74.20343466779575)\n30    26591641  10/31/2013 12:31:17 AM  10/31/2013 02:41:36 AM   NYPD                    New York City Police Department          Blocked Driveway                         No Access                Street/Sidewalk        10312          24 PRINCETON LANE       PRINCETON LANE      HAMPTON GREEN                          DEAD END                   NaN                   NaN       ADDRESS        STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:31:17 AM         10/31/2013 01:43:09 AM      03 STATEN ISLAND  STATEN ISLAND                      929577                      140964        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.553421 -74.196743   (40.55342078716953, -74.19674315017886)\n31    26595564  10/31/2013 12:30:36 AM                     NaN   NYPD                    New York City Police Department   Noise - Street/Sidewalk                  Loud Music/Party                Street/Sidewalk        11236                   AVENUE J             AVENUE J     EAST 80 STREET                    EAST 81 STREET                   NaN                   NaN     BLOCKFACE             BROOKLYN      NaN      Precinct      Open  10/31/2013 08:30:36 AM                            NaN           18 BROOKLYN       BROOKLYN                     1008937                      170310        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.634104 -73.911055  (40.634103775951736, -73.91105541883589)\n32    26591378  10/31/2013 12:30:31 AM                     NaN    TLC                      Taxi and Limousine Commission            Taxi Complaint                  Driver Complaint                            NaN        10036              645 10 AVENUE            10 AVENUE     WEST 45 STREET                    WEST 46 STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN           NaN      Open                     NaN                            NaN          04 MANHATTAN      MANHATTAN                      985965                      216868        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                 Other                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.761929 -73.993809  (40.761928847500016, -73.99380918401052)\n33    26593872  10/31/2013 12:29:47 AM  10/31/2013 12:38:29 AM   NYPD                    New York City Police Department  Noise - House of Worship                  Banging/Pounding               House of Worship        10025                        NaN                  NaN                NaN                               NaN      WEST   99 STREET      AMSTERDAM AVENUE  INTERSECTION             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:29:47 AM         10/31/2013 12:38:29 AM          07 MANHATTAN      MANHATTAN                      992846                      229279        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.795990 -73.968954  (40.795989749917204, -73.96895423714467)\n34    26591420  10/31/2013 12:28:30 AM  10/31/2013 02:06:11 AM   NYPD                    New York City Police Department       Homeless Encampment                               NaN     Residential Building/House        10025              2754 BROADWAY             BROADWAY    WEST 105 STREET                   WEST 106 STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:28:30 AM         10/31/2013 02:06:11 AM          07 MANHATTAN      MANHATTAN                      993139                      231139        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.801095 -73.967894    (40.8010946529914, -73.96789356094007)\n35    26592976  10/31/2013 12:23:24 AM  10/31/2013 01:05:41 AM   NYPD                    New York City Police Department          Blocked Driveway                         No Access                Street/Sidewalk        11433            173-41 103 ROAD             103 ROAD         173 STREET                        177 STREET                   NaN                   NaN       ADDRESS              JAMAICA      NaN      Precinct    Closed  10/31/2013 08:23:24 AM         10/31/2013 01:05:41 AM             12 QUEENS         QUEENS                     1044124                      195866        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.704081 -73.784054   (40.70408112125158, -73.78405385422116)\n36    26590262  10/31/2013 12:23:00 AM                     NaN    DOT                       Department of Transportation  Traffic Signal Condition                        Controller                            NaN        11235                        NaN                  NaN                NaN                               NaN       SHORE BOULEVARD            CASS PLACE  INTERSECTION             BROOKLYN      NaN           NaN      Open                     NaN                            NaN           15 BROOKLYN       BROOKLYN                      997073                      151225        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.581744 -73.953836    (40.5817444882428, -73.95383634845487)\n37    26589606  10/31/2013 12:20:44 AM  10/31/2013 02:10:24 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        11216        826 ST JOHN'S PLACE      ST JOHN'S PLACE      ROGERS AVENUE                   NOSTRAND AVENUE                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct    Closed  10/31/2013 08:20:44 AM         10/31/2013 02:10:24 AM           08 BROOKLYN       BROOKLYN                      997865                      183985        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.671663 -73.950919  (40.671662601079895, -73.95091901534035)\n38    26592083  10/31/2013 12:20:00 AM                     NaN    DOT                       Department of Transportation  Traffic Signal Condition                        Controller                            NaN        11213                        NaN                  NaN                NaN                               NaN        BUFFALO AVENUE            PARK PLACE  INTERSECTION             BROOKLYN      NaN           NaN      Open                     NaN                            NaN           08 BROOKLYN       BROOKLYN                     1004987                      184136        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.672063 -73.925244   (40.67206324438088, -73.92524432147842)\n39    26593840  10/31/2013 12:19:48 AM                     NaN   NYPD                    New York City Police Department          Blocked Driveway                         No Access                Street/Sidewalk        11379              78-41 68 ROAD              68 ROAD          78 STREET                         79 STREET                   NaN                   NaN       ADDRESS       MIDDLE VILLAGE      NaN      Precinct      Open  10/31/2013 08:19:48 AM                            NaN             05 QUEENS         QUEENS                     1019062                      198120        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.710402 -73.874433    (40.71040190143904, -73.8744325577748)\n40    26589646  10/31/2013 12:18:05 AM  10/31/2013 01:26:15 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        11101      34-19 STEINWAY STREET      STEINWAY STREET          34 AVENUE                         35 AVENUE                   NaN                   NaN       ADDRESS     LONG ISLAND CITY      NaN      Precinct    Closed  10/31/2013 08:18:05 AM         10/31/2013 01:26:15 AM             01 QUEENS         QUEENS                     1006080                      214807        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.756245 -73.921205   (40.75624514774764, -73.92120466494264)\n41    26593296  10/31/2013 12:16:25 AM                     NaN  DOHMH            Department of Health and Mental Hygiene        Food Establishment           Rodents/Insects/Garbage     Restaurant/Bar/Deli/Bakery        10014      12 CHRISTOPHER STREET   CHRISTOPHER STREET   GREENWICH AVENUE                        GAY STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN           NaN      Open  12/07/2013 12:16:25 AM                            NaN          02 MANHATTAN      MANHATTAN                      984181                      206685        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.733979 -74.000249    (40.73397924003587, -74.0002489720853)\n42    26590480  10/31/2013 12:15:06 AM  10/31/2013 03:00:20 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party               Store/Commercial        11231        325 COLUMBIA STREET      COLUMBIA STREET                NaN                               NaN                   NaN                   NaN       LATLONG             BROOKLYN      NaN      Precinct    Closed  10/31/2013 08:15:06 AM         10/31/2013 02:58:55 AM           06 BROOKLYN       BROOKLYN                      982995                      187440        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.681156 -74.004525   (40.68115617695543, -74.00452481832494)\n43    26589626  10/31/2013 12:14:42 AM  10/31/2013 01:39:00 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        11234       2192 FLATBUSH AVENUE      FLATBUSH AVENUE     EAST 46 STREET                          AVENUE O                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct    Closed  10/31/2013 08:14:42 AM         10/31/2013 01:39:00 AM           18 BROOKLYN       BROOKLYN                     1003628                      163910        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.616550 -73.930202   (40.61655032892211, -73.93020153359745)\n44    26592898  10/31/2013 12:12:08 AM  10/31/2013 01:13:45 AM   NYPD                    New York City Police Department              Noise - Park                      Loud Talking                Park/Playground        10457         CROTONA PARK NORTH   CROTONA PARK NORTH     CLINTON AVENUE                   PROSPECT AVENUE                   NaN                   NaN     BLOCKFACE                BRONX      NaN      Precinct    Closed  10/31/2013 08:12:08 AM         10/31/2013 01:13:45 AM              06 BRONX          BRONX                     1013947                      245819        Unspecified          BRONX  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.841342 -73.892672  (40.841341641554614, -73.89267161957397)\n45    26590446  10/31/2013 12:11:58 AM  10/31/2013 01:54:38 AM   NYPD                    New York City Police Department   Noise - Street/Sidewalk                  Loud Music/Party                Street/Sidewalk        10459        819 EAST 167 STREET      EAST 167 STREET       UNION AVENUE                   PROSPECT AVENUE                   NaN                   NaN       ADDRESS                BRONX      NaN      Precinct    Closed  10/31/2013 08:11:58 AM         10/31/2013 01:54:38 AM              03 BRONX          BRONX                     1011935                      240454        Unspecified          BRONX  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.826623 -73.899965   (40.826622810177874, -73.8999653556452)\n46    26595546  10/31/2013 12:09:07 AM  10/31/2013 12:53:12 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        10465   4005 EAST TREMONT AVENUE  EAST TREMONT AVENUE     SAMPSON AVENUE                      GERBER PLACE                   NaN                   NaN       ADDRESS                BRONX      NaN      Precinct    Closed  10/31/2013 08:09:07 AM         10/31/2013 12:53:12 AM              10 BRONX          BRONX                     1034640                      238172        Unspecified          BRONX  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.820259 -73.817942  (40.820259030934515, -73.81794234356029)\n47    26595944  10/31/2013 12:08:47 AM                     NaN    TLC                      Taxi and Limousine Commission            Taxi Complaint                  Driver Complaint                            NaN        10036                        NaN                  NaN                NaN                               NaN      WEST   46 STREET             10 AVENUE  INTERSECTION             NEW YORK      NaN           NaN      Open  11/14/2013 12:08:47 AM                            NaN          04 MANHATTAN      MANHATTAN                      986020                      216961        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                 Other                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.762184 -73.993611   (40.76218409774632, -73.99361062023596)\n48    26595084  10/31/2013 12:07:45 AM  10/31/2013 01:43:11 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        10014      12 CHRISTOPHER STREET   CHRISTOPHER STREET   GREENWICH AVENUE                        GAY STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:07:45 AM         10/31/2013 01:43:11 AM          02 MANHATTAN      MANHATTAN                      984181                      206685        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.733979 -74.000249    (40.73397924003587, -74.0002489720853)\n49    26595553  10/31/2013 12:05:10 AM  10/31/2013 02:43:43 AM   NYPD                    New York City Police Department   Noise - Street/Sidewalk                      Loud Talking                Street/Sidewalk        11225         25 LEFFERTS AVENUE      LEFFERTS AVENUE  WASHINGTON AVENUE                    BEDFORD AVENUE                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct    Closed  10/31/2013 08:05:10 AM         10/31/2013 01:29:29 AM           09 BROOKLYN       BROOKLYN                      995366                      180388        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.661793 -73.959934    (40.6617931276793, -73.95993363978067)\n50    26594087  10/31/2013 12:04:50 AM  10/31/2013 01:09:38 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party               Store/Commercial        10011       258 WEST 15TH STREET     WEST 15TH STREET                NaN                               NaN                   NaN                   NaN       LATLONG             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:04:50 AM         10/31/2013 01:09:38 AM          04 MANHATTAN      MANHATTAN                      983789                      208891        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.740034 -74.001664   (40.74003415280169, -74.00166357336052)\n51    26595572  10/31/2013 12:03:27 AM                     NaN    DOT                       Department of Transportation         Broken Muni Meter                        No Receipt                         Street        10003                        NaN                  NaN                NaN                               NaN      EAST   10 STREET              2 AVENUE  INTERSECTION             NEW YORK      NaN           NaN      Open  11/21/2013 12:03:27 AM                            NaN          03 MANHATTAN      MANHATTAN                      987906                      205154        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.729776 -73.986809   (40.72977626532991, -73.98680891976119)\n52    26590848  10/31/2013 12:02:01 AM  10/31/2013 01:02:28 AM   NYPD                    New York City Police Department          Blocked Driveway                         No Access                Street/Sidewalk        11207           422 WYONA STREET         WYONA STREET      SUTTER AVENUE                      BLAKE AVENUE                   NaN                   NaN       ADDRESS             BROOKLYN      NaN      Precinct    Closed  10/31/2013 08:02:01 AM         10/31/2013 01:02:28 AM           05 BROOKLYN       BROOKLYN                     1014188                      182855        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.668521 -73.892081   (40.66852085465471, -73.89208096944678)\n53    26590413  10/31/2013 12:01:47 AM  10/31/2013 12:39:31 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party            Club/Bar/Restaurant        10002       121 RIVINGTON STREET     RIVINGTON STREET       ESSEX STREET                    NORFOLK STREET                   NaN                   NaN       ADDRESS             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:01:47 AM         10/31/2013 12:39:31 AM          03 MANHATTAN      MANHATTAN                      987766                      201503        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.719755 -73.987316   (40.71975521311322, -73.98731595609806)\n54    26591287  10/31/2013 12:01:45 AM  10/31/2013 12:02:37 AM    HRA                       HRA Benefit Card Replacement  Benefit Card Replacement                          Medicaid             NYC Street Address          NaN                        NaN                  NaN                NaN                               NaN                   NaN                   NaN           NaN                  NaN      NaN           NaN    Closed                     NaN                            NaN         0 Unspecified    Unspecified                         NaN                         NaN        Unspecified    Unspecified  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN        NaN        NaN                                       NaN\n55    26595001  10/31/2013 12:01:34 AM  10/31/2013 01:32:43 AM   NYPD                    New York City Police Department        Noise - Commercial                  Loud Music/Party               Store/Commercial        10034      524 WEST 207TH STREET    WEST 207TH STREET                NaN                               NaN                   NaN                   NaN       LATLONG             NEW YORK      NaN      Precinct    Closed  10/31/2013 08:01:34 AM         10/31/2013 01:32:43 AM          01 MANHATTAN      MANHATTAN                     1006481                      254514        Unspecified      MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.865229 -73.919626   (40.86522877164924, -73.91962575276823)\n56    26591162  10/31/2013 12:01:00 AM                     NaN   DSNY                               BCC - Brooklyn South      Sanitation Condition  15 Street Cond/Dump-Out/Drop-Off                         Street        11231        135 COLUMBIA STREET      COLUMBIA STREET        KANE STREET                     IRVING STREET                   NaN                   NaN       ADDRESS             BROOKLYN      NaN   DSNY Garage      Open                     NaN                            NaN           06 BROOKLYN       BROOKLYN                      983797                      189648        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.687217 -74.001633   (40.68721671044577, -74.00163340956126)\n57    26593459  10/31/2013 12:00:00 AM                     NaN    HPD  Department of Housing Preservation and Develop...                  ELECTRIC                   ELECTRIC-SUPPLY           RESIDENTIAL BUILDING        11233          199 HOWARD AVENUE        HOWARD AVENUE  BAINBRIDGE STREET                   CHAUNCEY STREET                   NaN                   NaN       ADDRESS             BROOKLYN      NaN           NaN      Open                     NaN         10/31/2013 12:00:00 AM           03 BROOKLYN       BROOKLYN                     1006513                      187623        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.681631 -73.919732   (40.68163056217252, -73.91973166452124)\n58    26592634  10/31/2013 12:00:00 AM                     NaN    HPD  Department of Housing Preservation and Develop...                  PLUMBING                        BASIN/SINK           RESIDENTIAL BUILDING        11233          199 HOWARD AVENUE        HOWARD AVENUE  BAINBRIDGE STREET                   CHAUNCEY STREET                   NaN                   NaN       ADDRESS             BROOKLYN      NaN           NaN      Open                     NaN         10/31/2013 12:00:00 AM           03 BROOKLYN       BROOKLYN                     1006513                      187623        Unspecified       BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.681631 -73.919732   (40.68163056217252, -73.91973166452124)\n59    26591688  10/31/2013 12:00:00 AM                     NaN    HPD  Department of Housing Preservation and Develop...                   HEATING                              HEAT           RESIDENTIAL BUILDING        10453        150 WEST 179 STREET      WEST 179 STREET     ANDREWS AVENUE                      LORING PLACE                   NaN                   NaN       ADDRESS                BRONX      NaN           NaN      Open                     NaN         10/31/2013 12:00:00 AM              05 BRONX          BRONX                     1008161                      250940        Unspecified          BRONX  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified              NaN                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.855415 -73.913565  (40.855414830918306, -73.91356461276855)\n           ...                     ...                     ...    ...                                                ...                       ...                               ...                            ...          ...                        ...                  ...                ...                               ...                   ...                   ...           ...                  ...      ...           ...       ...                     ...                            ...                   ...            ...                         ...                         ...                ...            ...          ...           ...           ...          ...                 ...            ...          ...          ...          ...              ...                           ...          ...                  ...                   ...                 ...                      ...       ...                    ...             ...             ...                 ...        ...        ...                                       ...\n\n[111069 rows x 52 columns]"}, "output_type": "execute_result"}], "source": "complaints"}, {"source": "# 2.2 Selecting columns and rows", "cell_type": "markdown", "metadata": {}}, {"source": "To select a column, we index with the name of the column, like this:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 4, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 4, "metadata": {}, "data": {"text/plain": "0      Noise - Street/Sidewalk\n1              Illegal Parking\n2           Noise - Commercial\n3              Noise - Vehicle\n4                       Rodent\n5           Noise - Commercial\n6             Blocked Driveway\n7           Noise - Commercial\n8           Noise - Commercial\n9           Noise - Commercial\n10    Noise - House of Worship\n11          Noise - Commercial\n12             Illegal Parking\n13             Noise - Vehicle\n14                      Rodent\n...\n111054    Noise - Street/Sidewalk\n111055         Noise - Commercial\n111056      Street Sign - Missing\n111057                      Noise\n111058         Noise - Commercial\n111059    Noise - Street/Sidewalk\n111060                      Noise\n111061         Noise - Commercial\n111062               Water System\n111063               Water System\n111064    Maintenance or Facility\n111065            Illegal Parking\n111066    Noise - Street/Sidewalk\n111067         Noise - Commercial\n111068           Blocked Driveway\nName: Complaint Type, Length: 111069, dtype: object"}, "output_type": "execute_result"}], "source": "complaints['Complaint Type']"}, {"source": "To get the first 5 rows of a dataframe, we can use a slice: `df[:5]`.\n\nThis is a great way to get a sense for what kind of information is in the dataframe -- take a minute to look at the contents and get a feel for this dataset.", "cell_type": "markdown", "metadata": {}}, {"execution_count": 5, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 5, "metadata": {}, "data": {"text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unique Key</th>\n      <th>Created Date</th>\n      <th>Closed Date</th>\n      <th>Agency</th>\n      <th>Agency Name</th>\n      <th>Complaint Type</th>\n      <th>Descriptor</th>\n      <th>Location Type</th>\n      <th>Incident Zip</th>\n      <th>Incident Address</th>\n      <th>Street Name</th>\n      <th>Cross Street 1</th>\n      <th>Cross Street 2</th>\n      <th>Intersection Street 1</th>\n      <th>Intersection Street 2</th>\n      <th>Address Type</th>\n      <th>City</th>\n      <th>Landmark</th>\n      <th>Facility Type</th>\n      <th>Status</th>\n      <th>Due Date</th>\n      <th>Resolution Action Updated Date</th>\n      <th>Community Board</th>\n      <th>Borough</th>\n      <th>X Coordinate (State Plane)</th>\n      <th>Y Coordinate (State Plane)</th>\n      <th>Park Facility Name</th>\n      <th>Park Borough</th>\n      <th>School Name</th>\n      <th>School Number</th>\n      <th>School Region</th>\n      <th>School Code</th>\n      <th>School Phone Number</th>\n      <th>School Address</th>\n      <th>School City</th>\n      <th>School State</th>\n      <th>School Zip</th>\n      <th>School Not Found</th>\n      <th>School or Citywide Complaint</th>\n      <th>Vehicle Type</th>\n      <th>Taxi Company Borough</th>\n      <th>Taxi Pick Up Location</th>\n      <th>Bridge Highway Name</th>\n      <th>Bridge Highway Direction</th>\n      <th>Road Ramp</th>\n      <th>Bridge Highway Segment</th>\n      <th>Garage Lot Name</th>\n      <th>Ferry Direction</th>\n      <th>Ferry Terminal Name</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Location</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td> 26589651</td>\n      <td> 10/31/2013 02:08:41 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td>                 Loud Talking</td>\n      <td>     Street/Sidewalk</td>\n      <td> 11432</td>\n      <td> 90-03 169 STREET</td>\n      <td>      169 STREET</td>\n      <td>       90 AVENUE</td>\n      <td>                        91 AVENUE</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   ADDRESS</td>\n      <td>  JAMAICA</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 10:08:41 AM</td>\n      <td> 10/31/2013 02:35:17 AM</td>\n      <td>    12 QUEENS</td>\n      <td>    QUEENS</td>\n      <td> 1042027</td>\n      <td> 197389</td>\n      <td> Unspecified</td>\n      <td>    QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.708275</td>\n      <td>-73.791604</td>\n      <td>  (40.70827532593202, -73.79160395779721)</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td> 26593698</td>\n      <td> 10/31/2013 02:01:04 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td>         Illegal Parking</td>\n      <td> Commercial Overnight Parking</td>\n      <td>     Street/Sidewalk</td>\n      <td> 11378</td>\n      <td>        58 AVENUE</td>\n      <td>       58 AVENUE</td>\n      <td>        58 PLACE</td>\n      <td>                        59 STREET</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> BLOCKFACE</td>\n      <td>  MASPETH</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 10:01:04 AM</td>\n      <td>                    NaN</td>\n      <td>    05 QUEENS</td>\n      <td>    QUEENS</td>\n      <td> 1009349</td>\n      <td> 201984</td>\n      <td> Unspecified</td>\n      <td>    QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.721041</td>\n      <td>-73.909453</td>\n      <td> (40.721040535628305, -73.90945306791765)</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td> 26594139</td>\n      <td> 10/31/2013 02:00:24 AM</td>\n      <td> 10/31/2013 02:40:32 AM</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td>      Noise - Commercial</td>\n      <td>             Loud Music/Party</td>\n      <td> Club/Bar/Restaurant</td>\n      <td> 10032</td>\n      <td>    4060 BROADWAY</td>\n      <td>        BROADWAY</td>\n      <td> WEST 171 STREET</td>\n      <td>                  WEST 172 STREET</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   ADDRESS</td>\n      <td> NEW YORK</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 10:00:24 AM</td>\n      <td> 10/31/2013 02:39:42 AM</td>\n      <td> 12 MANHATTAN</td>\n      <td> MANHATTAN</td>\n      <td> 1001088</td>\n      <td> 246531</td>\n      <td> Unspecified</td>\n      <td> MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.843330</td>\n      <td>-73.939144</td>\n      <td>  (40.84332975466513, -73.93914371913482)</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td> 26595721</td>\n      <td> 10/31/2013 01:56:23 AM</td>\n      <td> 10/31/2013 02:21:48 AM</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td>         Noise - Vehicle</td>\n      <td>               Car/Truck Horn</td>\n      <td>     Street/Sidewalk</td>\n      <td> 10023</td>\n      <td>   WEST 72 STREET</td>\n      <td>  WEST 72 STREET</td>\n      <td> COLUMBUS AVENUE</td>\n      <td>                 AMSTERDAM AVENUE</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> BLOCKFACE</td>\n      <td> NEW YORK</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:56:23 AM</td>\n      <td> 10/31/2013 02:21:10 AM</td>\n      <td> 07 MANHATTAN</td>\n      <td> MANHATTAN</td>\n      <td>  989730</td>\n      <td> 222727</td>\n      <td> Unspecified</td>\n      <td> MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.778009</td>\n      <td>-73.980213</td>\n      <td>   (40.7780087446372, -73.98021349023975)</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td> 26590930</td>\n      <td> 10/31/2013 01:53:44 AM</td>\n      <td>                    NaN</td>\n      <td> DOHMH</td>\n      <td> Department of Health and Mental Hygiene</td>\n      <td>                  Rodent</td>\n      <td> Condition Attracting Rodents</td>\n      <td>          Vacant Lot</td>\n      <td> 10027</td>\n      <td>  WEST 124 STREET</td>\n      <td> WEST 124 STREET</td>\n      <td>    LENOX AVENUE</td>\n      <td> ADAM CLAYTON POWELL JR BOULEVARD</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> BLOCKFACE</td>\n      <td> NEW YORK</td>\n      <td> NaN</td>\n      <td>      NaN</td>\n      <td>  Pending</td>\n      <td> 11/30/2013 01:53:44 AM</td>\n      <td> 10/31/2013 01:59:54 AM</td>\n      <td> 10 MANHATTAN</td>\n      <td> MANHATTAN</td>\n      <td>  998815</td>\n      <td> 233545</td>\n      <td> Unspecified</td>\n      <td> MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.807691</td>\n      <td>-73.947387</td>\n      <td>  (40.80769092704951, -73.94738703491433)</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows \u00d7 52 columns</p>\n</div>", "text/plain": "   Unique Key            Created Date             Closed Date Agency                              Agency Name           Complaint Type                    Descriptor        Location Type Incident Zip  Incident Address      Street Name   Cross Street 1                    Cross Street 2 Intersection Street 1 Intersection Street 2 Address Type      City Landmark Facility Type    Status                Due Date Resolution Action Updated Date Community Board    Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n0    26589651  10/31/2013 02:08:41 AM                     NaN   NYPD          New York City Police Department  Noise - Street/Sidewalk                  Loud Talking      Street/Sidewalk        11432  90-03 169 STREET       169 STREET        90 AVENUE                         91 AVENUE                   NaN                   NaN      ADDRESS   JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM       12 QUEENS     QUEENS                     1042027                      197389        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604   (40.70827532593202, -73.79160395779721)\n1    26593698  10/31/2013 02:01:04 AM                     NaN   NYPD          New York City Police Department          Illegal Parking  Commercial Overnight Parking      Street/Sidewalk        11378         58 AVENUE        58 AVENUE         58 PLACE                         59 STREET                   NaN                   NaN    BLOCKFACE   MASPETH      NaN      Precinct      Open  10/31/2013 10:01:04 AM                            NaN       05 QUEENS     QUEENS                     1009349                      201984        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.721041 -73.909453  (40.721040535628305, -73.90945306791765)\n2    26594139  10/31/2013 02:00:24 AM  10/31/2013 02:40:32 AM   NYPD          New York City Police Department       Noise - Commercial              Loud Music/Party  Club/Bar/Restaurant        10032     4060 BROADWAY         BROADWAY  WEST 171 STREET                   WEST 172 STREET                   NaN                   NaN      ADDRESS  NEW YORK      NaN      Precinct    Closed  10/31/2013 10:00:24 AM         10/31/2013 02:39:42 AM    12 MANHATTAN  MANHATTAN                     1001088                      246531        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.843330 -73.939144   (40.84332975466513, -73.93914371913482)\n3    26595721  10/31/2013 01:56:23 AM  10/31/2013 02:21:48 AM   NYPD          New York City Police Department          Noise - Vehicle                Car/Truck Horn      Street/Sidewalk        10023    WEST 72 STREET   WEST 72 STREET  COLUMBUS AVENUE                  AMSTERDAM AVENUE                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN      Precinct    Closed  10/31/2013 09:56:23 AM         10/31/2013 02:21:10 AM    07 MANHATTAN  MANHATTAN                      989730                      222727        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.778009 -73.980213    (40.7780087446372, -73.98021349023975)\n4    26590930  10/31/2013 01:53:44 AM                     NaN  DOHMH  Department of Health and Mental Hygiene                   Rodent  Condition Attracting Rodents           Vacant Lot        10027   WEST 124 STREET  WEST 124 STREET     LENOX AVENUE  ADAM CLAYTON POWELL JR BOULEVARD                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN           NaN   Pending  11/30/2013 01:53:44 AM         10/31/2013 01:59:54 AM    10 MANHATTAN  MANHATTAN                      998815                      233545        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.807691 -73.947387   (40.80769092704951, -73.94738703491433)\n\n[5 rows x 52 columns]"}, "output_type": "execute_result"}], "source": "complaints[:5]"}, {"source": "We can combine these to get the first 5 rows of a column:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 6, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 6, "metadata": {}, "data": {"text/plain": "0    Noise - Street/Sidewalk\n1            Illegal Parking\n2         Noise - Commercial\n3            Noise - Vehicle\n4                     Rodent\nName: Complaint Type, dtype: object"}, "output_type": "execute_result"}], "source": "complaints['Complaint Type'][:5]"}, {"source": "and it doesn't matter which direction we do it in:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 7, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 7, "metadata": {}, "data": {"text/plain": "0    Noise - Street/Sidewalk\n1            Illegal Parking\n2         Noise - Commercial\n3            Noise - Vehicle\n4                     Rodent\nName: Complaint Type, dtype: object"}, "output_type": "execute_result"}], "source": "complaints[:5]['Complaint Type']"}, {"source": "# 2.3 Selecting multiple columns", "cell_type": "markdown", "metadata": {}}, {"source": "What if we just want to know the complaint type and the borough, but not the rest of the information? Pandas makes it really easy to select a subset of the columns: just index with list of columns you want.", "cell_type": "markdown", "metadata": {}}, {"execution_count": 8, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 8, "metadata": {}, "data": {"text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Complaint Type</th>\n      <th>Borough</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0 </th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>1 </th>\n      <td>          Illegal Parking</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>2 </th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>3 </th>\n      <td>          Noise - Vehicle</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>4 </th>\n      <td>                   Rodent</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>5 </th>\n      <td>       Noise - Commercial</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>6 </th>\n      <td>         Blocked Driveway</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>7 </th>\n      <td>       Noise - Commercial</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>8 </th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>9 </th>\n      <td>       Noise - Commercial</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td> Noise - House of Worship</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>          Illegal Parking</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>          Noise - Vehicle</td>\n      <td>         BRONX</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>                   Rodent</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td> Noise - House of Worship</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td> STATEN ISLAND</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>          Illegal Parking</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>   Street Light Condition</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td> Noise - House of Worship</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>          Noise - Vehicle</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>       Noise - Commercial</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>         Blocked Driveway</td>\n      <td> STATEN ISLAND</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td> STATEN ISLAND</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>   Street Light Condition</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>     Harboring Bees/Wasps</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>   Street Light Condition</td>\n      <td> STATEN ISLAND</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>         Blocked Driveway</td>\n      <td> STATEN ISLAND</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>           Taxi Complaint</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td> Noise - House of Worship</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>      Homeless Encampment</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>         Blocked Driveway</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td> Traffic Signal Condition</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>       Noise - Commercial</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td> Traffic Signal Condition</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>         Blocked Driveway</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>       Noise - Commercial</td>\n      <td>        QUEENS</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>       Food Establishment</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>       Noise - Commercial</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>       Noise - Commercial</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>             Noise - Park</td>\n      <td>         BRONX</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>         BRONX</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>       Noise - Commercial</td>\n      <td>         BRONX</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>           Taxi Complaint</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>  Noise - Street/Sidewalk</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>        Broken Muni Meter</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>         Blocked Driveway</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td> Benefit Card Replacement</td>\n      <td>   Unspecified</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>       Noise - Commercial</td>\n      <td>     MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>     Sanitation Condition</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>                 ELECTRIC</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>                 PLUMBING</td>\n      <td>      BROOKLYN</td>\n    </tr>\n    <tr>\n      <th>59</th>\n      <td>                  HEATING</td>\n      <td>         BRONX</td>\n    </tr>\n    <tr>\n      <th></th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n  </tbody>\n</table>\n<p>111069 rows \u00d7 2 columns</p>\n</div>", "text/plain": "              Complaint Type        Borough\n0    Noise - Street/Sidewalk         QUEENS\n1            Illegal Parking         QUEENS\n2         Noise - Commercial      MANHATTAN\n3            Noise - Vehicle      MANHATTAN\n4                     Rodent      MANHATTAN\n5         Noise - Commercial         QUEENS\n6           Blocked Driveway         QUEENS\n7         Noise - Commercial         QUEENS\n8         Noise - Commercial      MANHATTAN\n9         Noise - Commercial       BROOKLYN\n10  Noise - House of Worship       BROOKLYN\n11        Noise - Commercial      MANHATTAN\n12           Illegal Parking      MANHATTAN\n13           Noise - Vehicle          BRONX\n14                    Rodent       BROOKLYN\n15  Noise - House of Worship      MANHATTAN\n16   Noise - Street/Sidewalk  STATEN ISLAND\n17           Illegal Parking       BROOKLYN\n18    Street Light Condition       BROOKLYN\n19        Noise - Commercial      MANHATTAN\n20  Noise - House of Worship       BROOKLYN\n21        Noise - Commercial      MANHATTAN\n22           Noise - Vehicle         QUEENS\n23        Noise - Commercial       BROOKLYN\n24          Blocked Driveway  STATEN ISLAND\n25   Noise - Street/Sidewalk  STATEN ISLAND\n26    Street Light Condition       BROOKLYN\n27      Harboring Bees/Wasps      MANHATTAN\n28   Noise - Street/Sidewalk      MANHATTAN\n29    Street Light Condition  STATEN ISLAND\n30          Blocked Driveway  STATEN ISLAND\n31   Noise - Street/Sidewalk       BROOKLYN\n32            Taxi Complaint      MANHATTAN\n33  Noise - House of Worship      MANHATTAN\n34       Homeless Encampment      MANHATTAN\n35          Blocked Driveway         QUEENS\n36  Traffic Signal Condition       BROOKLYN\n37        Noise - Commercial       BROOKLYN\n38  Traffic Signal Condition       BROOKLYN\n39          Blocked Driveway         QUEENS\n40        Noise - Commercial         QUEENS\n41        Food Establishment      MANHATTAN\n42        Noise - Commercial       BROOKLYN\n43        Noise - Commercial       BROOKLYN\n44              Noise - Park          BRONX\n45   Noise - Street/Sidewalk          BRONX\n46        Noise - Commercial          BRONX\n47            Taxi Complaint      MANHATTAN\n48        Noise - Commercial      MANHATTAN\n49   Noise - Street/Sidewalk       BROOKLYN\n50        Noise - Commercial      MANHATTAN\n51         Broken Muni Meter      MANHATTAN\n52          Blocked Driveway       BROOKLYN\n53        Noise - Commercial      MANHATTAN\n54  Benefit Card Replacement    Unspecified\n55        Noise - Commercial      MANHATTAN\n56      Sanitation Condition       BROOKLYN\n57                  ELECTRIC       BROOKLYN\n58                  PLUMBING       BROOKLYN\n59                   HEATING          BRONX\n                         ...            ...\n\n[111069 rows x 2 columns]"}, "output_type": "execute_result"}], "source": "complaints[['Complaint Type', 'Borough']]"}, {"source": "That showed us a summary, and then we can look at the first 10 rows:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 9, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 9, "metadata": {}, "data": {"text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Complaint Type</th>\n      <th>Borough</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td> Noise - Street/Sidewalk</td>\n      <td>    QUEENS</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>         Illegal Parking</td>\n      <td>    QUEENS</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>      Noise - Commercial</td>\n      <td> MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>         Noise - Vehicle</td>\n      <td> MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>                  Rodent</td>\n      <td> MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>      Noise - Commercial</td>\n      <td>    QUEENS</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>        Blocked Driveway</td>\n      <td>    QUEENS</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>      Noise - Commercial</td>\n      <td>    QUEENS</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>      Noise - Commercial</td>\n      <td> MANHATTAN</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>      Noise - Commercial</td>\n      <td>  BROOKLYN</td>\n    </tr>\n  </tbody>\n</table>\n<p>10 rows \u00d7 2 columns</p>\n</div>", "text/plain": "            Complaint Type    Borough\n0  Noise - Street/Sidewalk     QUEENS\n1          Illegal Parking     QUEENS\n2       Noise - Commercial  MANHATTAN\n3          Noise - Vehicle  MANHATTAN\n4                   Rodent  MANHATTAN\n5       Noise - Commercial     QUEENS\n6         Blocked Driveway     QUEENS\n7       Noise - Commercial     QUEENS\n8       Noise - Commercial  MANHATTAN\n9       Noise - Commercial   BROOKLYN\n\n[10 rows x 2 columns]"}, "output_type": "execute_result"}], "source": "complaints[['Complaint Type', 'Borough']][:10]"}, {"source": "# 2.4 What's the most common complaint type?", "cell_type": "markdown", "metadata": {}}, {"source": "This is a really easy question to answer! There's a `.value_counts()` method that we can use:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 10, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 10, "metadata": {}, "data": {"text/plain": "HEATING                     14200\nGENERAL CONSTRUCTION         7471\nStreet Light Condition       7117\nDOF Literature Request       5797\nPLUMBING                     5373\nPAINT - PLASTER              5149\nBlocked Driveway             4590\nNONCONST                     3998\nStreet Condition             3473\nIllegal Parking              3343\nNoise                        3321\nTraffic Signal Condition     3145\nDirty Conditions             2653\nWater System                 2636\nNoise - Commercial           2578\n...\nOpinion for the Mayor                2\nWindow Guard                         2\nDFTA Literature Request              2\nLegal Services Provider Complaint    2\nOpen Flame Permit                    1\nSnow                                 1\nMunicipal Parking Facility           1\nX-Ray Machine/Equipment              1\nStalled Sites                        1\nDHS Income Savings Requirement       1\nTunnel Condition                     1\nHighway Sign - Damaged               1\nFerry Permit                         1\nTrans Fat                            1\nDWD                                  1\nLength: 165, dtype: int64"}, "output_type": "execute_result"}], "source": "complaints['Complaint Type'].value_counts()"}, {"source": "If we just wanted the top 10 most common complaints, we can do this:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 11, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 11, "metadata": {}, "data": {"text/plain": "HEATING                   14200\nGENERAL CONSTRUCTION       7471\nStreet Light Condition     7117\nDOF Literature Request     5797\nPLUMBING                   5373\nPAINT - PLASTER            5149\nBlocked Driveway           4590\nNONCONST                   3998\nStreet Condition           3473\nIllegal Parking            3343\ndtype: int64"}, "output_type": "execute_result"}], "source": "complaint_counts = complaints['Complaint Type'].value_counts()\ncomplaint_counts[:10]"}, {"source": "But it gets better! We can plot them!", "cell_type": "markdown", "metadata": {}}, {"execution_count": 12, "cell_type": "code", "metadata": {"collapsed": false, "trusted": false}, "outputs": [{"execution_count": 12, "metadata": {}, "data": {"text/plain": "<matplotlib.axes.AxesSubplot at 0x38f88d0>"}, "output_type": "execute_result"}, {"output_type": "display_data", "data": {"image/png": 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Szvu1EoLBYDCSIvfu3auPPvpIc+fOVU1NjTZv3qxbb71VwWBQTz/9tObNmyfL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\nl30gEAho//79evPNN7Vv3z5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\ No newline at end of file
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Make the graphs a bit prettier, and bigger\n",
+    "plt.style.use('ggplot')\n",
+    "\n",
+    "# This is necessary to show lots of columns in pandas 0.12. \n",
+    "# Not necessary in pandas 0.13.\n",
+    "pd.set_option('display.max_colwidth', 5000) \n",
+    "pd.set_option('display.max_columns', 60)\n",
+    "\n",
+    "plt.rcParams['figure.figsize'] = (15, 5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We're going to use a new dataset here, to demonstrate how to deal with larger datasets. This is a subset of the of 311 service requests from [NYC Open Data](https://nycopendata.socrata.com/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/gabriela/.local/share/virtualenvs/pandas-cookbook-M4OY_8hn/lib/python3.5/site-packages/IPython/core/interactiveshell.py:3018: DtypeWarning: Columns (8) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  interactivity=interactivity, compiler=compiler, result=result)\n"
+     ]
+    }
+   ],
+   "source": [
+    "complaints = pd.read_csv('../data/311-service-requests.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Depending on your pandas version, you might see an error like \"DtypeWarning: Columns (8) have mixed types\". This means that it's encountered a problem reading in our data. In this case it almost certainly means that it has columns where some of the entries are strings and some are integers.\n",
+    "\n",
+    "For now we're going to ignore it and hope we don't run into a problem, but in the long run we'd need to investigate this warning."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2.1 What's even in it? (the summary)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When you print a large dataframe, it will only show you the first few rows.\n",
+    "\n",
+    "If you don't see this, don't panic! The default behavior for large dataframes changed between pandas 0.12 and 0.13. Previous to 0.13 it would show you a summary of the dataframe. This includes all the columns, and how many non-null values there are in each column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unique Key</th>\n",
+       "      <th>Created Date</th>\n",
+       "      <th>Closed Date</th>\n",
+       "      <th>Agency</th>\n",
+       "      <th>Agency Name</th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Descriptor</th>\n",
+       "      <th>Location Type</th>\n",
+       "      <th>Incident Zip</th>\n",
+       "      <th>Incident Address</th>\n",
+       "      <th>Street Name</th>\n",
+       "      <th>Cross Street 1</th>\n",
+       "      <th>Cross Street 2</th>\n",
+       "      <th>Intersection Street 1</th>\n",
+       "      <th>Intersection Street 2</th>\n",
+       "      <th>Address Type</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Landmark</th>\n",
+       "      <th>Facility Type</th>\n",
+       "      <th>Status</th>\n",
+       "      <th>Due Date</th>\n",
+       "      <th>Resolution Action Updated Date</th>\n",
+       "      <th>Community Board</th>\n",
+       "      <th>Borough</th>\n",
+       "      <th>X Coordinate (State Plane)</th>\n",
+       "      <th>Y Coordinate (State Plane)</th>\n",
+       "      <th>Park Facility Name</th>\n",
+       "      <th>Park Borough</th>\n",
+       "      <th>School Name</th>\n",
+       "      <th>School Number</th>\n",
+       "      <th>School Region</th>\n",
+       "      <th>School Code</th>\n",
+       "      <th>School Phone Number</th>\n",
+       "      <th>School Address</th>\n",
+       "      <th>School City</th>\n",
+       "      <th>School State</th>\n",
+       "      <th>School Zip</th>\n",
+       "      <th>School Not Found</th>\n",
+       "      <th>School or Citywide Complaint</th>\n",
+       "      <th>Vehicle Type</th>\n",
+       "      <th>Taxi Company Borough</th>\n",
+       "      <th>Taxi Pick Up Location</th>\n",
+       "      <th>Bridge Highway Name</th>\n",
+       "      <th>Bridge Highway Direction</th>\n",
+       "      <th>Road Ramp</th>\n",
+       "      <th>Bridge Highway Segment</th>\n",
+       "      <th>Garage Lot Name</th>\n",
+       "      <th>Ferry Direction</th>\n",
+       "      <th>Ferry Terminal Name</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Location</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>26589651</td>\n",
+       "      <td>10/31/2013 02:08:41 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11432</td>\n",
+       "      <td>90-03 169 STREET</td>\n",
+       "      <td>169 STREET</td>\n",
+       "      <td>90 AVENUE</td>\n",
+       "      <td>91 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>JAMAICA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 10:08:41 AM</td>\n",
+       "      <td>10/31/2013 02:35:17 AM</td>\n",
+       "      <td>12 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1042027.0</td>\n",
+       "      <td>197389.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.708275</td>\n",
+       "      <td>-73.791604</td>\n",
+       "      <td>(40.70827532593202, -73.79160395779721)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>26593698</td>\n",
+       "      <td>10/31/2013 02:01:04 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Commercial Overnight Parking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11378</td>\n",
+       "      <td>58 AVENUE</td>\n",
+       "      <td>58 AVENUE</td>\n",
+       "      <td>58 PLACE</td>\n",
+       "      <td>59 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>MASPETH</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 10:01:04 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>05 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1009349.0</td>\n",
+       "      <td>201984.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.721041</td>\n",
+       "      <td>-73.909453</td>\n",
+       "      <td>(40.721040535628305, -73.90945306791765)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>26594139</td>\n",
+       "      <td>10/31/2013 02:00:24 AM</td>\n",
+       "      <td>10/31/2013 02:40:32 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10032</td>\n",
+       "      <td>4060 BROADWAY</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>WEST 171 STREET</td>\n",
+       "      <td>WEST 172 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 10:00:24 AM</td>\n",
+       "      <td>10/31/2013 02:39:42 AM</td>\n",
+       "      <td>12 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>1001088.0</td>\n",
+       "      <td>246531.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.843330</td>\n",
+       "      <td>-73.939144</td>\n",
+       "      <td>(40.84332975466513, -73.93914371913482)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>26595721</td>\n",
+       "      <td>10/31/2013 01:56:23 AM</td>\n",
+       "      <td>10/31/2013 02:21:48 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>Car/Truck Horn</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10023</td>\n",
+       "      <td>WEST 72 STREET</td>\n",
+       "      <td>WEST 72 STREET</td>\n",
+       "      <td>COLUMBUS AVENUE</td>\n",
+       "      <td>AMSTERDAM AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:56:23 AM</td>\n",
+       "      <td>10/31/2013 02:21:10 AM</td>\n",
+       "      <td>07 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>989730.0</td>\n",
+       "      <td>222727.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.778009</td>\n",
+       "      <td>-73.980213</td>\n",
+       "      <td>(40.7780087446372, -73.98021349023975)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>26590930</td>\n",
+       "      <td>10/31/2013 01:53:44 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOHMH</td>\n",
+       "      <td>Department of Health and Mental Hygiene</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Condition Attracting Rodents</td>\n",
+       "      <td>Vacant Lot</td>\n",
+       "      <td>10027</td>\n",
+       "      <td>WEST 124 STREET</td>\n",
+       "      <td>WEST 124 STREET</td>\n",
+       "      <td>LENOX AVENUE</td>\n",
+       "      <td>ADAM CLAYTON POWELL JR BOULEVARD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Pending</td>\n",
+       "      <td>11/30/2013 01:53:44 AM</td>\n",
+       "      <td>10/31/2013 01:59:54 AM</td>\n",
+       "      <td>10 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>998815.0</td>\n",
+       "      <td>233545.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.807691</td>\n",
+       "      <td>-73.947387</td>\n",
+       "      <td>(40.80769092704951, -73.94738703491433)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>26592370</td>\n",
+       "      <td>10/31/2013 01:46:52 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Banging/Pounding</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11372</td>\n",
+       "      <td>37 AVENUE</td>\n",
+       "      <td>37 AVENUE</td>\n",
+       "      <td>84 STREET</td>\n",
+       "      <td>85 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>JACKSON HEIGHTS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 09:46:52 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>03 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1016948.0</td>\n",
+       "      <td>212540.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.749989</td>\n",
+       "      <td>-73.881988</td>\n",
+       "      <td>(40.7499893014072, -73.88198770727831)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>26595682</td>\n",
+       "      <td>10/31/2013 01:46:40 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>No Access</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>107-50 109 STREET</td>\n",
+       "      <td>109 STREET</td>\n",
+       "      <td>107 AVENUE</td>\n",
+       "      <td>109 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>SOUTH RICHMOND HILL</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 09:46:40 AM</td>\n",
+       "      <td>10/31/2013 01:59:51 AM</td>\n",
+       "      <td>10 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1030919.0</td>\n",
+       "      <td>187622.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.681533</td>\n",
+       "      <td>-73.831737</td>\n",
+       "      <td>(40.68153278675525, -73.83173699701601)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26595195</td>\n",
+       "      <td>10/31/2013 01:44:19 AM</td>\n",
+       "      <td>10/31/2013 01:58:49 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11417</td>\n",
+       "      <td>137-09 CROSSBAY BOULEVARD</td>\n",
+       "      <td>CROSSBAY BOULEVARD</td>\n",
+       "      <td>PITKIN AVENUE</td>\n",
+       "      <td>VAN WICKLEN ROAD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>OZONE PARK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:44:19 AM</td>\n",
+       "      <td>10/31/2013 01:58:49 AM</td>\n",
+       "      <td>10 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1027776.0</td>\n",
+       "      <td>184076.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.671816</td>\n",
+       "      <td>-73.843092</td>\n",
+       "      <td>(40.67181584567338, -73.84309181950769)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>26590540</td>\n",
+       "      <td>10/31/2013 01:44:14 AM</td>\n",
+       "      <td>10/31/2013 02:28:04 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10011</td>\n",
+       "      <td>258 WEST 15 STREET</td>\n",
+       "      <td>WEST 15 STREET</td>\n",
+       "      <td>7 AVENUE</td>\n",
+       "      <td>8 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:44:14 AM</td>\n",
+       "      <td>10/31/2013 02:00:56 AM</td>\n",
+       "      <td>04 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>984031.0</td>\n",
+       "      <td>208847.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.739913</td>\n",
+       "      <td>-74.000790</td>\n",
+       "      <td>(40.73991339303542, -74.00079028612932)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>26594392</td>\n",
+       "      <td>10/31/2013 01:34:41 AM</td>\n",
+       "      <td>10/31/2013 02:23:51 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11225</td>\n",
+       "      <td>835 NOSTRAND AVENUE</td>\n",
+       "      <td>NOSTRAND AVENUE</td>\n",
+       "      <td>UNION STREET</td>\n",
+       "      <td>PRESIDENT STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:34:41 AM</td>\n",
+       "      <td>10/31/2013 01:48:26 AM</td>\n",
+       "      <td>09 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>997941.0</td>\n",
+       "      <td>182725.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.668204</td>\n",
+       "      <td>-73.950648</td>\n",
+       "      <td>(40.66820406598287, -73.95064760056546)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>26595176</td>\n",
+       "      <td>10/31/2013 01:25:12 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - House of Worship</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>House of Worship</td>\n",
+       "      <td>11218</td>\n",
+       "      <td>3775 18 AVENUE</td>\n",
+       "      <td>18 AVENUE</td>\n",
+       "      <td>EAST 9 STREET</td>\n",
+       "      <td>EAST 8 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 09:25:12 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>992726.0</td>\n",
+       "      <td>170399.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.634378</td>\n",
+       "      <td>-73.969462</td>\n",
+       "      <td>(40.63437840816299, -73.96946177104543)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>26591982</td>\n",
+       "      <td>10/31/2013 01:24:14 AM</td>\n",
+       "      <td>10/31/2013 01:54:39 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10003</td>\n",
+       "      <td>187 2 AVENUE</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>EAST 11 STREET</td>\n",
+       "      <td>EAST 12 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:24:14 AM</td>\n",
+       "      <td>10/31/2013 01:54:39 AM</td>\n",
+       "      <td>03 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>988110.0</td>\n",
+       "      <td>205533.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.730816</td>\n",
+       "      <td>-73.986073</td>\n",
+       "      <td>(40.73081644089586, -73.98607265739876)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>26594169</td>\n",
+       "      <td>10/31/2013 01:20:57 AM</td>\n",
+       "      <td>10/31/2013 02:12:31 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Double Parked Blocking Vehicle</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10029</td>\n",
+       "      <td>65 EAST 99 STREET</td>\n",
+       "      <td>EAST 99 STREET</td>\n",
+       "      <td>MADISON AVENUE</td>\n",
+       "      <td>PARK AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:20:57 AM</td>\n",
+       "      <td>10/31/2013 01:42:05 AM</td>\n",
+       "      <td>11 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>997470.0</td>\n",
+       "      <td>226725.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.788974</td>\n",
+       "      <td>-73.952259</td>\n",
+       "      <td>(40.78897400211689, -73.95225898702977)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>26594391</td>\n",
+       "      <td>10/31/2013 01:20:13 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>Engine Idling</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10466</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>STRANG AVENUE</td>\n",
+       "      <td>AMUNDSON AVENUE</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>BRONX</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 09:20:13 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12 BRONX</td>\n",
+       "      <td>BRONX</td>\n",
+       "      <td>1029467.0</td>\n",
+       "      <td>264124.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BRONX</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.891517</td>\n",
+       "      <td>-73.836457</td>\n",
+       "      <td>(40.89151738488846, -73.83645714593568)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>26590917</td>\n",
+       "      <td>10/31/2013 01:19:54 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOHMH</td>\n",
+       "      <td>Department of Health and Mental Hygiene</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Rat Sighting</td>\n",
+       "      <td>1-2 Family Mixed Use Building</td>\n",
+       "      <td>11219</td>\n",
+       "      <td>63 STREET</td>\n",
+       "      <td>63 STREET</td>\n",
+       "      <td>13 AVENUE</td>\n",
+       "      <td>14 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Pending</td>\n",
+       "      <td>11/30/2013 01:19:54 AM</td>\n",
+       "      <td>10/31/2013 01:29:26 AM</td>\n",
+       "      <td>10 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>984467.0</td>\n",
+       "      <td>167519.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.626477</td>\n",
+       "      <td>-73.999218</td>\n",
+       "      <td>(40.6264774690411, -73.99921826202639)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>26591458</td>\n",
+       "      <td>10/31/2013 01:14:02 AM</td>\n",
+       "      <td>10/31/2013 01:30:34 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - House of Worship</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>House of Worship</td>\n",
+       "      <td>10025</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>WEST   99 STREET</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:14:02 AM</td>\n",
+       "      <td>10/31/2013 01:30:34 AM</td>\n",
+       "      <td>07 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>992454.0</td>\n",
+       "      <td>229500.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.796597</td>\n",
+       "      <td>-73.970370</td>\n",
+       "      <td>(40.7965967075252, -73.97036973473399)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>26594086</td>\n",
+       "      <td>10/31/2013 12:54:03 AM</td>\n",
+       "      <td>10/31/2013 02:16:39 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10310</td>\n",
+       "      <td>173 CAMPBELL AVENUE</td>\n",
+       "      <td>CAMPBELL AVENUE</td>\n",
+       "      <td>HENDERSON AVENUE</td>\n",
+       "      <td>WINEGAR LANE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:54:03 AM</td>\n",
+       "      <td>10/31/2013 02:07:14 AM</td>\n",
+       "      <td>01 STATEN ISLAND</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>952013.0</td>\n",
+       "      <td>171076.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.636182</td>\n",
+       "      <td>-74.116150</td>\n",
+       "      <td>(40.63618202176914, -74.1161500428337)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>26595117</td>\n",
+       "      <td>10/31/2013 12:52:46 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Posted Parking Sign Violation</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11236</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ROCKAWAY PARKWAY</td>\n",
+       "      <td>SKIDMORE AVENUE</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 08:52:46 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>1015289.0</td>\n",
+       "      <td>169710.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.632437</td>\n",
+       "      <td>-73.888173</td>\n",
+       "      <td>(40.63243692394328, -73.88817263437012)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>26590389</td>\n",
+       "      <td>10/31/2013 12:51:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOT</td>\n",
+       "      <td>Department of Transportation</td>\n",
+       "      <td>Street Light Condition</td>\n",
+       "      <td>Street Light Out</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>226 42 ST E</td>\n",
+       "      <td>42 ST E</td>\n",
+       "      <td>CHURCH AVE</td>\n",
+       "      <td>SNYDER AVE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>26594210</td>\n",
+       "      <td>10/31/2013 12:46:27 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10033</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>WEST  184 STREET</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 08:46:27 AM</td>\n",
+       "      <td>10/31/2013 01:32:41 AM</td>\n",
+       "      <td>12 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>1002294.0</td>\n",
+       "      <td>249712.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.852058</td>\n",
+       "      <td>-73.934776</td>\n",
+       "      <td>(40.85205827756883, -73.93477640780834)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>26592932</td>\n",
+       "      <td>10/31/2013 12:43:47 AM</td>\n",
+       "      <td>10/31/2013 12:56:20 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - House of Worship</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>House of Worship</td>\n",
+       "      <td>11216</td>\n",
+       "      <td>778 PARK PLACE</td>\n",
+       "      <td>PARK PLACE</td>\n",
+       "      <td>ROGERS AVENUE</td>\n",
+       "      <td>NOSTRAND AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:43:47 AM</td>\n",
+       "      <td>10/31/2013 12:56:20 AM</td>\n",
+       "      <td>08 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>997608.0</td>\n",
+       "      <td>184656.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.673505</td>\n",
+       "      <td>-73.951844</td>\n",
+       "      <td>(40.67350473678714, -73.95184414979961)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>26594152</td>\n",
+       "      <td>10/31/2013 12:41:17 AM</td>\n",
+       "      <td>10/31/2013 01:04:37 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Banging/Pounding</td>\n",
+       "      <td>Store/Commercial</td>\n",
+       "      <td>10016</td>\n",
+       "      <td>155 E 34TH ST</td>\n",
+       "      <td>E 34TH ST</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>LATLONG</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:41:17 AM</td>\n",
+       "      <td>10/31/2013 01:04:38 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>990133.0</td>\n",
+       "      <td>211136.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.746194</td>\n",
+       "      <td>-73.978769</td>\n",
+       "      <td>(40.74619417253121, -73.97876853124392)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>26589678</td>\n",
+       "      <td>10/31/2013 12:39:55 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>Car/Truck Music</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11419</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>112 STREET</td>\n",
+       "      <td>ATLANTIC AVENUE</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>SOUTH RICHMOND HILL</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 08:39:55 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>09 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1030314.0</td>\n",
+       "      <td>191578.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.692394</td>\n",
+       "      <td>-73.833891</td>\n",
+       "      <td>(40.69239424979043, -73.8338912453996)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>26592304</td>\n",
+       "      <td>10/31/2013 12:38:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11216</td>\n",
+       "      <td>371 TOMPKINS AVENUE</td>\n",
+       "      <td>TOMPKINS AVENUE</td>\n",
+       "      <td>MADISON STREET</td>\n",
+       "      <td>PUTNAM AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 08:38:00 AM</td>\n",
+       "      <td>10/31/2013 01:16:53 AM</td>\n",
+       "      <td>03 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>999720.0</td>\n",
+       "      <td>188825.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.684944</td>\n",
+       "      <td>-73.944221</td>\n",
+       "      <td>(40.6849442562592, -73.94422078036632)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>26591892</td>\n",
+       "      <td>10/31/2013 12:37:16 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>Partial Access</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10305</td>\n",
+       "      <td>1496 BAY STREET</td>\n",
+       "      <td>BAY STREET</td>\n",
+       "      <td>LYMAN AVENUE</td>\n",
+       "      <td>SCHOOL ROAD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 08:37:16 AM</td>\n",
+       "      <td>10/31/2013 12:52:10 AM</td>\n",
+       "      <td>01 STATEN ISLAND</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>967283.0</td>\n",
+       "      <td>160518.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.607245</td>\n",
+       "      <td>-74.061106</td>\n",
+       "      <td>(40.60724493456944, -74.06110566015863)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>26591573</td>\n",
+       "      <td>10/31/2013 12:35:18 AM</td>\n",
+       "      <td>10/31/2013 02:41:35 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10312</td>\n",
+       "      <td>24 PRINCETON LANE</td>\n",
+       "      <td>PRINCETON LANE</td>\n",
+       "      <td>HAMPTON GREEN</td>\n",
+       "      <td>DEAD END</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:35:18 AM</td>\n",
+       "      <td>10/31/2013 01:45:17 AM</td>\n",
+       "      <td>03 STATEN ISLAND</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>929577.0</td>\n",
+       "      <td>140964.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.553421</td>\n",
+       "      <td>-74.196743</td>\n",
+       "      <td>(40.55342078716953, -74.19674315017886)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>26590509</td>\n",
+       "      <td>10/31/2013 12:33:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOT</td>\n",
+       "      <td>Department of Transportation</td>\n",
+       "      <td>Street Light Condition</td>\n",
+       "      <td>Street Light Out</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>38 ST E</td>\n",
+       "      <td>38 ST E</td>\n",
+       "      <td>CHURCH AVE</td>\n",
+       "      <td>LINDEN BLVD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>26591379</td>\n",
+       "      <td>10/31/2013 12:32:44 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOHMH</td>\n",
+       "      <td>Department of Health and Mental Hygiene</td>\n",
+       "      <td>Harboring Bees/Wasps</td>\n",
+       "      <td>Bees/Wasps - Not a beekeper</td>\n",
+       "      <td>3+ Family Mixed Use Building</td>\n",
+       "      <td>10025</td>\n",
+       "      <td>501 WEST 110 STREET</td>\n",
+       "      <td>WEST 110 STREET</td>\n",
+       "      <td>AMSTERDAM AVENUE</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>11/30/2013 12:32:44 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>09 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>994143.0</td>\n",
+       "      <td>231888.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.803149</td>\n",
+       "      <td>-73.964266</td>\n",
+       "      <td>(40.80314938553783, -73.96426608076082)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>26594085</td>\n",
+       "      <td>10/31/2013 12:32:08 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10026</td>\n",
+       "      <td>121 WEST 116 STREET</td>\n",
+       "      <td>WEST 116 STREET</td>\n",
+       "      <td>LENOX AVENUE</td>\n",
+       "      <td>7 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 08:32:08 AM</td>\n",
+       "      <td>10/31/2013 02:00:57 AM</td>\n",
+       "      <td>10 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>997947.0</td>\n",
+       "      <td>231613.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.802390</td>\n",
+       "      <td>-73.950526</td>\n",
+       "      <td>(40.80238950799943, -73.95052644123253)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>26589201</td>\n",
+       "      <td>10/31/2013 12:32:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOT</td>\n",
+       "      <td>Department of Transportation</td>\n",
+       "      <td>Street Light Condition</td>\n",
+       "      <td>Street Light Out</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10309</td>\n",
+       "      <td>295 BAYVIEW AVENUE</td>\n",
+       "      <td>BAYVIEW AVENUE</td>\n",
+       "      <td>VAIL AVENUE</td>\n",
+       "      <td>BAYVIEW LANE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>03 STATEN ISLAND</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>927687.0</td>\n",
+       "      <td>127837.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.517378</td>\n",
+       "      <td>-74.203435</td>\n",
+       "      <td>(40.517377871705676, -74.20343466779575)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111039</th>\n",
+       "      <td>26428764</td>\n",
+       "      <td>10/04/2013 12:17:03 AM</td>\n",
+       "      <td>10/04/2013 12:38:37 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10022</td>\n",
+       "      <td>249 EAST 53 STREET</td>\n",
+       "      <td>EAST 53 STREET</td>\n",
+       "      <td>3 AVENUE</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:17:03 AM</td>\n",
+       "      <td>10/04/2013 12:38:37 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>993036.0</td>\n",
+       "      <td>215164.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.757248</td>\n",
+       "      <td>-73.968286</td>\n",
+       "      <td>(40.757247604963055, -73.96828647941395)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111040</th>\n",
+       "      <td>26426166</td>\n",
+       "      <td>10/04/2013 12:16:22 AM</td>\n",
+       "      <td>10/04/2013 05:50:49 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Store/Commercial</td>\n",
+       "      <td>10029</td>\n",
+       "      <td>252 EAST 110 STREET</td>\n",
+       "      <td>EAST 110 STREET</td>\n",
+       "      <td>3 AVENUE</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:16:22 AM</td>\n",
+       "      <td>10/04/2013 05:50:49 AM</td>\n",
+       "      <td>11 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>1000407.0</td>\n",
+       "      <td>228425.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.793635</td>\n",
+       "      <td>-73.941649</td>\n",
+       "      <td>(40.79363516179995, -73.94164859515777)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111041</th>\n",
+       "      <td>26438565</td>\n",
+       "      <td>10/04/2013 12:16:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Noise</td>\n",
+       "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11231</td>\n",
+       "      <td>480 VAN BRUNT STREET</td>\n",
+       "      <td>VAN BRUNT STREET</td>\n",
+       "      <td>REED STREET</td>\n",
+       "      <td>DEAD END</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>06 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>979657.0</td>\n",
+       "      <td>184924.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.674249</td>\n",
+       "      <td>-74.016558</td>\n",
+       "      <td>(40.6742492231181, -74.01655803856313)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111042</th>\n",
+       "      <td>26428990</td>\n",
+       "      <td>10/04/2013 12:15:52 AM</td>\n",
+       "      <td>10/04/2013 12:44:52 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10014</td>\n",
+       "      <td>733 WASHINGTON STREET</td>\n",
+       "      <td>WASHINGTON STREET</td>\n",
+       "      <td>BANK STREET</td>\n",
+       "      <td>BETHUNE STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:15:52 AM</td>\n",
+       "      <td>10/04/2013 12:44:52 AM</td>\n",
+       "      <td>02 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>981950.0</td>\n",
+       "      <td>207532.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.736304</td>\n",
+       "      <td>-74.008299</td>\n",
+       "      <td>(40.736303747410034, -74.00829935904578)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111043</th>\n",
+       "      <td>26432659</td>\n",
+       "      <td>10/04/2013 12:15:46 AM</td>\n",
+       "      <td>10/04/2013 04:18:45 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11218</td>\n",
+       "      <td>1213 CORTELYOU ROAD</td>\n",
+       "      <td>CORTELYOU ROAD</td>\n",
+       "      <td>EAST 12 STREET</td>\n",
+       "      <td>EAST 13 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:15:46 AM</td>\n",
+       "      <td>10/04/2013 04:18:45 AM</td>\n",
+       "      <td>14 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>993451.0</td>\n",
+       "      <td>172498.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.640139</td>\n",
+       "      <td>-73.966847</td>\n",
+       "      <td>(40.64013899178716, -73.96684680242933)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111044</th>\n",
+       "      <td>26426096</td>\n",
+       "      <td>10/04/2013 12:14:09 AM</td>\n",
+       "      <td>10/04/2013 01:03:46 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10032</td>\n",
+       "      <td>539 WEST 162 STREET</td>\n",
+       "      <td>WEST 162 STREET</td>\n",
+       "      <td>ST NICHOLAS AVENUE</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:14:09 AM</td>\n",
+       "      <td>10/04/2013 01:03:46 AM</td>\n",
+       "      <td>12 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>1000571.0</td>\n",
+       "      <td>244054.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.836532</td>\n",
+       "      <td>-73.941018</td>\n",
+       "      <td>(40.836532082987944, -73.9410182995914)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111045</th>\n",
+       "      <td>26437764</td>\n",
+       "      <td>10/04/2013 12:14:00 AM</td>\n",
+       "      <td>10/04/2013 12:14:00 AM</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Water System</td>\n",
+       "      <td>Dirty Water (WE)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10022</td>\n",
+       "      <td>251 EAST 51 STREET</td>\n",
+       "      <td>EAST 51 STREET</td>\n",
+       "      <td>3 AVENUE</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/04/2013 12:14:00 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>992791.0</td>\n",
+       "      <td>214702.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.755980</td>\n",
+       "      <td>-73.969171</td>\n",
+       "      <td>(40.75597977288785, -73.96917140638074)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111046</th>\n",
+       "      <td>26436286</td>\n",
+       "      <td>10/04/2013 12:14:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Noise</td>\n",
+       "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11231</td>\n",
+       "      <td>480 VAN BRUNT STREET</td>\n",
+       "      <td>VAN BRUNT STREET</td>\n",
+       "      <td>REED STREET</td>\n",
+       "      <td>DEAD END</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>06 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>979657.0</td>\n",
+       "      <td>184924.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.674249</td>\n",
+       "      <td>-74.016558</td>\n",
+       "      <td>(40.6742492231181, -74.01655803856313)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111047</th>\n",
+       "      <td>26428989</td>\n",
+       "      <td>10/04/2013 12:13:08 AM</td>\n",
+       "      <td>10/04/2013 02:12:47 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Posted Parking Sign Violation</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11434</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>GUY R BREWER BOULEVARD</td>\n",
+       "      <td>ROCKAWAY BOULEVARD</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>JAMAICA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:13:08 AM</td>\n",
+       "      <td>10/04/2013 02:12:47 AM</td>\n",
+       "      <td>13 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1048801.0</td>\n",
+       "      <td>178419.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.656160</td>\n",
+       "      <td>-73.767353</td>\n",
+       "      <td>(40.656160351546845, -73.76735262738222)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111048</th>\n",
+       "      <td>26430030</td>\n",
+       "      <td>10/04/2013 12:12:07 AM</td>\n",
+       "      <td>10/04/2013 02:45:24 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10027</td>\n",
+       "      <td>215 WEST 131ST STREET</td>\n",
+       "      <td>WEST 131ST STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>LATLONG</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:12:07 AM</td>\n",
+       "      <td>10/04/2013 02:45:24 AM</td>\n",
+       "      <td>01 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>999107.0</td>\n",
+       "      <td>235603.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.813339</td>\n",
+       "      <td>-73.946328</td>\n",
+       "      <td>(40.81333907832113, -73.94632769228208)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111049</th>\n",
+       "      <td>26429663</td>\n",
+       "      <td>10/04/2013 12:12:07 AM</td>\n",
+       "      <td>10/04/2013 01:03:44 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11209</td>\n",
+       "      <td>8915 5 AVENUE</td>\n",
+       "      <td>5 AVENUE</td>\n",
+       "      <td>89 STREET</td>\n",
+       "      <td>90 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:12:07 AM</td>\n",
+       "      <td>10/04/2013 01:03:44 AM</td>\n",
+       "      <td>10 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>976525.0</td>\n",
+       "      <td>165015.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.619601</td>\n",
+       "      <td>-74.027826</td>\n",
+       "      <td>(40.619601147364584, -74.02782628492785)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111050</th>\n",
+       "      <td>26437763</td>\n",
+       "      <td>10/04/2013 12:11:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Noise</td>\n",
+       "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10028</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>EAST 84 STREET</td>\n",
+       "      <td>YORK AVENUE</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>08 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>998629.0</td>\n",
+       "      <td>221493.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.774612</td>\n",
+       "      <td>-73.948085</td>\n",
+       "      <td>(40.77461174278734, -73.94808472177321)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111051</th>\n",
+       "      <td>26432955</td>\n",
+       "      <td>10/04/2013 12:08:15 AM</td>\n",
+       "      <td>10/04/2013 12:48:02 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10009</td>\n",
+       "      <td>506 EAST 13 STREET</td>\n",
+       "      <td>EAST 13 STREET</td>\n",
+       "      <td>AVENUE A</td>\n",
+       "      <td>AVENUE B</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:08:15 AM</td>\n",
+       "      <td>10/04/2013 12:48:03 AM</td>\n",
+       "      <td>03 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>989678.0</td>\n",
+       "      <td>205065.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.729531</td>\n",
+       "      <td>-73.980416</td>\n",
+       "      <td>(40.72953107218499, -73.98041550317102)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111052</th>\n",
+       "      <td>26437035</td>\n",
+       "      <td>10/04/2013 12:08:00 AM</td>\n",
+       "      <td>10/04/2013 12:13:00 AM</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Water System</td>\n",
+       "      <td>Dirty Water (WE)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10022</td>\n",
+       "      <td>325 EAST 54 STREET</td>\n",
+       "      <td>EAST 54 STREET</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>1 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/04/2013 12:13:00 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>993688.0</td>\n",
+       "      <td>215099.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.757069</td>\n",
+       "      <td>-73.965933</td>\n",
+       "      <td>(40.75706852462872, -73.96593314322774)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111053</th>\n",
+       "      <td>26433197</td>\n",
+       "      <td>10/04/2013 12:08:00 AM</td>\n",
+       "      <td>10/04/2013 12:00:00 PM</td>\n",
+       "      <td>DSNY</td>\n",
+       "      <td>BCC - Queens East</td>\n",
+       "      <td>Derelict Vehicles</td>\n",
+       "      <td>14 Derelict Vehicles</td>\n",
+       "      <td>Street</td>\n",
+       "      <td>11413</td>\n",
+       "      <td>220-11 145 AVENUE</td>\n",
+       "      <td>145 AVENUE</td>\n",
+       "      <td>221 STREET</td>\n",
+       "      <td>221 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>Springfield Gardens</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DSNY Garage</td>\n",
+       "      <td>Pending</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/04/2013 12:08:00 AM</td>\n",
+       "      <td>13 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1051511.0</td>\n",
+       "      <td>181411.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.664353</td>\n",
+       "      <td>-73.757556</td>\n",
+       "      <td>(40.6643525308449, -73.75755575708348)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111054</th>\n",
+       "      <td>26426060</td>\n",
+       "      <td>10/04/2013 12:06:39 AM</td>\n",
+       "      <td>10/04/2013 12:31:16 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11224</td>\n",
+       "      <td>4823 BEACH 48 STREET</td>\n",
+       "      <td>BEACH 48 STREET</td>\n",
+       "      <td>BODY OF WATER</td>\n",
+       "      <td>SURF AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:06:39 AM</td>\n",
+       "      <td>10/04/2013 12:31:16 AM</td>\n",
+       "      <td>13 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>980859.0</td>\n",
+       "      <td>149681.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.577515</td>\n",
+       "      <td>-74.012207</td>\n",
+       "      <td>(40.57751513866536, -74.01220705163807)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111055</th>\n",
+       "      <td>26430628</td>\n",
+       "      <td>10/04/2013 12:06:28 AM</td>\n",
+       "      <td>10/04/2013 12:21:39 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11209</td>\n",
+       "      <td>7915 3 AVENUE</td>\n",
+       "      <td>3 AVENUE</td>\n",
+       "      <td>79 STREET</td>\n",
+       "      <td>80 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:06:28 AM</td>\n",
+       "      <td>10/04/2013 12:21:39 AM</td>\n",
+       "      <td>10 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>976189.0</td>\n",
+       "      <td>168214.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.628381</td>\n",
+       "      <td>-74.029040</td>\n",
+       "      <td>(40.62838143294541, -74.02904041333245)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111056</th>\n",
+       "      <td>26431648</td>\n",
+       "      <td>10/04/2013 12:06:26 AM</td>\n",
+       "      <td>10/23/2013 08:14:52 AM</td>\n",
+       "      <td>DOT</td>\n",
+       "      <td>Department of Transportation</td>\n",
+       "      <td>Street Sign - Missing</td>\n",
+       "      <td>Bus Stop</td>\n",
+       "      <td>Street</td>\n",
+       "      <td>11378</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>54 AVENUE</td>\n",
+       "      <td>43 STREET</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>MASPETH</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/14/2013 09:38:47 AM</td>\n",
+       "      <td>10/23/2013 08:14:52 AM</td>\n",
+       "      <td>02 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1005171.0</td>\n",
+       "      <td>206064.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.732250</td>\n",
+       "      <td>-73.924513</td>\n",
+       "      <td>(40.73225000573841, -73.92451289173367)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111057</th>\n",
+       "      <td>26437034</td>\n",
+       "      <td>10/04/2013 12:06:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Noise</td>\n",
+       "      <td>Noise: Jack Hammering (NC2)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>WEST 48 STREET</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>05 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>988451.0</td>\n",
+       "      <td>216208.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.760116</td>\n",
+       "      <td>-73.984836</td>\n",
+       "      <td>(40.76011648520396, -73.98483562074706)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111058</th>\n",
+       "      <td>26426094</td>\n",
+       "      <td>10/04/2013 12:05:12 AM</td>\n",
+       "      <td>10/04/2013 01:08:29 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11237</td>\n",
+       "      <td>211 KNICKERBOCKER AVENUE</td>\n",
+       "      <td>KNICKERBOCKER AVENUE</td>\n",
+       "      <td>JEFFERSON STREET</td>\n",
+       "      <td>TROUTMAN STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:05:12 AM</td>\n",
+       "      <td>10/04/2013 01:08:29 AM</td>\n",
+       "      <td>04 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>1004672.0</td>\n",
+       "      <td>195540.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.703365</td>\n",
+       "      <td>-73.926345</td>\n",
+       "      <td>(40.703365329011284, -73.92634531031759)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111059</th>\n",
+       "      <td>26429040</td>\n",
+       "      <td>10/04/2013 12:04:52 AM</td>\n",
+       "      <td>10/04/2013 03:01:04 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10003</td>\n",
+       "      <td>99 2 AVENUE</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>EAST 5 STREET</td>\n",
+       "      <td>EAST 6 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:04:52 AM</td>\n",
+       "      <td>10/04/2013 03:01:04 AM</td>\n",
+       "      <td>03 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>987393.0</td>\n",
+       "      <td>204234.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.727251</td>\n",
+       "      <td>-73.988660</td>\n",
+       "      <td>(40.727251287038676, -73.98866028603422)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111060</th>\n",
+       "      <td>26434084</td>\n",
+       "      <td>10/04/2013 12:04:00 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Noise</td>\n",
+       "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10036</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8 AVENUE</td>\n",
+       "      <td>WEST 47 STREET</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>04 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>987720.0</td>\n",
+       "      <td>216313.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.760405</td>\n",
+       "      <td>-73.987474</td>\n",
+       "      <td>(40.76040500039782, -73.98747426235285)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111061</th>\n",
+       "      <td>26426164</td>\n",
+       "      <td>10/04/2013 12:03:00 AM</td>\n",
+       "      <td>10/04/2013 02:14:57 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11106</td>\n",
+       "      <td>30-09 BROADWAY</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>30 STREET</td>\n",
+       "      <td>31 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>ASTORIA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:03:00 AM</td>\n",
+       "      <td>10/04/2013 02:14:57 AM</td>\n",
+       "      <td>01 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1004746.0</td>\n",
+       "      <td>217004.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.762279</td>\n",
+       "      <td>-73.926013</td>\n",
+       "      <td>(40.762278541098084, -73.92601303458156)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111062</th>\n",
+       "      <td>26439710</td>\n",
+       "      <td>10/04/2013 12:03:00 AM</td>\n",
+       "      <td>10/04/2013 12:03:00 AM</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Water System</td>\n",
+       "      <td>Dirty Water (WE)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10022</td>\n",
+       "      <td>325 EAST 54 STREET</td>\n",
+       "      <td>EAST 54 STREET</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>1 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/04/2013 12:03:00 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>993688.0</td>\n",
+       "      <td>215099.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.757069</td>\n",
+       "      <td>-73.965933</td>\n",
+       "      <td>(40.75706852462872, -73.96593314322774)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111063</th>\n",
+       "      <td>26435569</td>\n",
+       "      <td>10/04/2013 12:02:00 AM</td>\n",
+       "      <td>10/04/2013 01:10:00 AM</td>\n",
+       "      <td>DEP</td>\n",
+       "      <td>Department of Environmental Protection</td>\n",
+       "      <td>Water System</td>\n",
+       "      <td>Dirty Water (WE)</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10022</td>\n",
+       "      <td>311 EAST 50 STREET</td>\n",
+       "      <td>EAST 50 STREET</td>\n",
+       "      <td>2 AVENUE</td>\n",
+       "      <td>1 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/04/2013 01:10:00 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>993118.0</td>\n",
+       "      <td>214222.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.754662</td>\n",
+       "      <td>-73.967992</td>\n",
+       "      <td>(40.75466197318078, -73.96799173864807)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111064</th>\n",
+       "      <td>26426013</td>\n",
+       "      <td>10/04/2013 12:01:13 AM</td>\n",
+       "      <td>10/07/2013 04:07:16 PM</td>\n",
+       "      <td>DPR</td>\n",
+       "      <td>Department of Parks and Recreation</td>\n",
+       "      <td>Maintenance or Facility</td>\n",
+       "      <td>Structure - Outdoors</td>\n",
+       "      <td>Park</td>\n",
+       "      <td>11213</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/18/2013 12:01:13 AM</td>\n",
+       "      <td>10/07/2013 04:07:16 PM</td>\n",
+       "      <td>08 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Brower Park</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Brower Park</td>\n",
+       "      <td>B012</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7189658900</td>\n",
+       "      <td>Brooklyn, St. Marks, Kingston Avenues, Park Place</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NY</td>\n",
+       "      <td>11213</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111065</th>\n",
+       "      <td>26428083</td>\n",
+       "      <td>10/04/2013 12:01:05 AM</td>\n",
+       "      <td>10/04/2013 02:13:50 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Posted Parking Sign Violation</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11434</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>GUY R BREWER BOULEVARD</td>\n",
+       "      <td>ROCKAWAY BOULEVARD</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>JAMAICA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:01:05 AM</td>\n",
+       "      <td>10/04/2013 02:13:50 AM</td>\n",
+       "      <td>13 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1048801.0</td>\n",
+       "      <td>178419.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.656160</td>\n",
+       "      <td>-73.767353</td>\n",
+       "      <td>(40.656160351546845, -73.76735262738222)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111066</th>\n",
+       "      <td>26428987</td>\n",
+       "      <td>10/04/2013 12:00:45 AM</td>\n",
+       "      <td>10/04/2013 01:25:01 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10016</td>\n",
+       "      <td>344 EAST 28 STREET</td>\n",
+       "      <td>EAST 28 STREET</td>\n",
+       "      <td>MOUNT CARMEL PLACE</td>\n",
+       "      <td>1 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:00:45 AM</td>\n",
+       "      <td>10/04/2013 01:25:01 AM</td>\n",
+       "      <td>06 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>990637.0</td>\n",
+       "      <td>208987.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.740295</td>\n",
+       "      <td>-73.976952</td>\n",
+       "      <td>(40.740295354643706, -73.97695165980414)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111067</th>\n",
+       "      <td>26426115</td>\n",
+       "      <td>10/04/2013 12:00:28 AM</td>\n",
+       "      <td>10/04/2013 04:17:32 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>11226</td>\n",
+       "      <td>1233 FLATBUSH AVENUE</td>\n",
+       "      <td>FLATBUSH AVENUE</td>\n",
+       "      <td>AVENUE D</td>\n",
+       "      <td>NEWKIRK AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:00:28 AM</td>\n",
+       "      <td>10/04/2013 04:17:32 AM</td>\n",
+       "      <td>14 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>996654.0</td>\n",
+       "      <td>172515.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.640182</td>\n",
+       "      <td>-73.955306</td>\n",
+       "      <td>(40.64018174662485, -73.95530566958138)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111068</th>\n",
+       "      <td>26428033</td>\n",
+       "      <td>10/04/2013 12:00:10 AM</td>\n",
+       "      <td>10/04/2013 01:20:52 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>Partial Access</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11236</td>\n",
+       "      <td>1259 EAST 94 STREET</td>\n",
+       "      <td>EAST 94 STREET</td>\n",
+       "      <td>AVENUE J</td>\n",
+       "      <td>AVENUE K</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/04/2013 08:00:10 AM</td>\n",
+       "      <td>10/04/2013 01:20:52 AM</td>\n",
+       "      <td>18 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>1011804.0</td>\n",
+       "      <td>172470.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.640024</td>\n",
+       "      <td>-73.900717</td>\n",
+       "      <td>(40.640024057399216, -73.90071711703163)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>111069 rows × 52 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Unique Key            Created Date             Closed Date Agency  \\\n",
+       "0         26589651  10/31/2013 02:08:41 AM                     NaN   NYPD   \n",
+       "1         26593698  10/31/2013 02:01:04 AM                     NaN   NYPD   \n",
+       "2         26594139  10/31/2013 02:00:24 AM  10/31/2013 02:40:32 AM   NYPD   \n",
+       "3         26595721  10/31/2013 01:56:23 AM  10/31/2013 02:21:48 AM   NYPD   \n",
+       "4         26590930  10/31/2013 01:53:44 AM                     NaN  DOHMH   \n",
+       "5         26592370  10/31/2013 01:46:52 AM                     NaN   NYPD   \n",
+       "6         26595682  10/31/2013 01:46:40 AM                     NaN   NYPD   \n",
+       "7         26595195  10/31/2013 01:44:19 AM  10/31/2013 01:58:49 AM   NYPD   \n",
+       "8         26590540  10/31/2013 01:44:14 AM  10/31/2013 02:28:04 AM   NYPD   \n",
+       "9         26594392  10/31/2013 01:34:41 AM  10/31/2013 02:23:51 AM   NYPD   \n",
+       "10        26595176  10/31/2013 01:25:12 AM                     NaN   NYPD   \n",
+       "11        26591982  10/31/2013 01:24:14 AM  10/31/2013 01:54:39 AM   NYPD   \n",
+       "12        26594169  10/31/2013 01:20:57 AM  10/31/2013 02:12:31 AM   NYPD   \n",
+       "13        26594391  10/31/2013 01:20:13 AM                     NaN   NYPD   \n",
+       "14        26590917  10/31/2013 01:19:54 AM                     NaN  DOHMH   \n",
+       "15        26591458  10/31/2013 01:14:02 AM  10/31/2013 01:30:34 AM   NYPD   \n",
+       "16        26594086  10/31/2013 12:54:03 AM  10/31/2013 02:16:39 AM   NYPD   \n",
+       "17        26595117  10/31/2013 12:52:46 AM                     NaN   NYPD   \n",
+       "18        26590389  10/31/2013 12:51:00 AM                     NaN    DOT   \n",
+       "19        26594210  10/31/2013 12:46:27 AM                     NaN   NYPD   \n",
+       "20        26592932  10/31/2013 12:43:47 AM  10/31/2013 12:56:20 AM   NYPD   \n",
+       "21        26594152  10/31/2013 12:41:17 AM  10/31/2013 01:04:37 AM   NYPD   \n",
+       "22        26589678  10/31/2013 12:39:55 AM                     NaN   NYPD   \n",
+       "23        26592304  10/31/2013 12:38:00 AM                     NaN   NYPD   \n",
+       "24        26591892  10/31/2013 12:37:16 AM                     NaN   NYPD   \n",
+       "25        26591573  10/31/2013 12:35:18 AM  10/31/2013 02:41:35 AM   NYPD   \n",
+       "26        26590509  10/31/2013 12:33:00 AM                     NaN    DOT   \n",
+       "27        26591379  10/31/2013 12:32:44 AM                     NaN  DOHMH   \n",
+       "28        26594085  10/31/2013 12:32:08 AM                     NaN   NYPD   \n",
+       "29        26589201  10/31/2013 12:32:00 AM                     NaN    DOT   \n",
+       "...            ...                     ...                     ...    ...   \n",
+       "111039    26428764  10/04/2013 12:17:03 AM  10/04/2013 12:38:37 AM   NYPD   \n",
+       "111040    26426166  10/04/2013 12:16:22 AM  10/04/2013 05:50:49 AM   NYPD   \n",
+       "111041    26438565  10/04/2013 12:16:00 AM                     NaN    DEP   \n",
+       "111042    26428990  10/04/2013 12:15:52 AM  10/04/2013 12:44:52 AM   NYPD   \n",
+       "111043    26432659  10/04/2013 12:15:46 AM  10/04/2013 04:18:45 AM   NYPD   \n",
+       "111044    26426096  10/04/2013 12:14:09 AM  10/04/2013 01:03:46 AM   NYPD   \n",
+       "111045    26437764  10/04/2013 12:14:00 AM  10/04/2013 12:14:00 AM    DEP   \n",
+       "111046    26436286  10/04/2013 12:14:00 AM                     NaN    DEP   \n",
+       "111047    26428989  10/04/2013 12:13:08 AM  10/04/2013 02:12:47 AM   NYPD   \n",
+       "111048    26430030  10/04/2013 12:12:07 AM  10/04/2013 02:45:24 AM   NYPD   \n",
+       "111049    26429663  10/04/2013 12:12:07 AM  10/04/2013 01:03:44 AM   NYPD   \n",
+       "111050    26437763  10/04/2013 12:11:00 AM                     NaN    DEP   \n",
+       "111051    26432955  10/04/2013 12:08:15 AM  10/04/2013 12:48:02 AM   NYPD   \n",
+       "111052    26437035  10/04/2013 12:08:00 AM  10/04/2013 12:13:00 AM    DEP   \n",
+       "111053    26433197  10/04/2013 12:08:00 AM  10/04/2013 12:00:00 PM   DSNY   \n",
+       "111054    26426060  10/04/2013 12:06:39 AM  10/04/2013 12:31:16 AM   NYPD   \n",
+       "111055    26430628  10/04/2013 12:06:28 AM  10/04/2013 12:21:39 AM   NYPD   \n",
+       "111056    26431648  10/04/2013 12:06:26 AM  10/23/2013 08:14:52 AM    DOT   \n",
+       "111057    26437034  10/04/2013 12:06:00 AM                     NaN    DEP   \n",
+       "111058    26426094  10/04/2013 12:05:12 AM  10/04/2013 01:08:29 AM   NYPD   \n",
+       "111059    26429040  10/04/2013 12:04:52 AM  10/04/2013 03:01:04 AM   NYPD   \n",
+       "111060    26434084  10/04/2013 12:04:00 AM                     NaN    DEP   \n",
+       "111061    26426164  10/04/2013 12:03:00 AM  10/04/2013 02:14:57 AM   NYPD   \n",
+       "111062    26439710  10/04/2013 12:03:00 AM  10/04/2013 12:03:00 AM    DEP   \n",
+       "111063    26435569  10/04/2013 12:02:00 AM  10/04/2013 01:10:00 AM    DEP   \n",
+       "111064    26426013  10/04/2013 12:01:13 AM  10/07/2013 04:07:16 PM    DPR   \n",
+       "111065    26428083  10/04/2013 12:01:05 AM  10/04/2013 02:13:50 AM   NYPD   \n",
+       "111066    26428987  10/04/2013 12:00:45 AM  10/04/2013 01:25:01 AM   NYPD   \n",
+       "111067    26426115  10/04/2013 12:00:28 AM  10/04/2013 04:17:32 AM   NYPD   \n",
+       "111068    26428033  10/04/2013 12:00:10 AM  10/04/2013 01:20:52 AM   NYPD   \n",
+       "\n",
+       "                                    Agency Name            Complaint Type  \\\n",
+       "0               New York City Police Department   Noise - Street/Sidewalk   \n",
+       "1               New York City Police Department           Illegal Parking   \n",
+       "2               New York City Police Department        Noise - Commercial   \n",
+       "3               New York City Police Department           Noise - Vehicle   \n",
+       "4       Department of Health and Mental Hygiene                    Rodent   \n",
+       "5               New York City Police Department        Noise - Commercial   \n",
+       "6               New York City Police Department          Blocked Driveway   \n",
+       "7               New York City Police Department        Noise - Commercial   \n",
+       "8               New York City Police Department        Noise - Commercial   \n",
+       "9               New York City Police Department        Noise - Commercial   \n",
+       "10              New York City Police Department  Noise - House of Worship   \n",
+       "11              New York City Police Department        Noise - Commercial   \n",
+       "12              New York City Police Department           Illegal Parking   \n",
+       "13              New York City Police Department           Noise - Vehicle   \n",
+       "14      Department of Health and Mental Hygiene                    Rodent   \n",
+       "15              New York City Police Department  Noise - House of Worship   \n",
+       "16              New York City Police Department   Noise - Street/Sidewalk   \n",
+       "17              New York City Police Department           Illegal Parking   \n",
+       "18                 Department of Transportation    Street Light Condition   \n",
+       "19              New York City Police Department        Noise - Commercial   \n",
+       "20              New York City Police Department  Noise - House of Worship   \n",
+       "21              New York City Police Department        Noise - Commercial   \n",
+       "22              New York City Police Department           Noise - Vehicle   \n",
+       "23              New York City Police Department        Noise - Commercial   \n",
+       "24              New York City Police Department          Blocked Driveway   \n",
+       "25              New York City Police Department   Noise - Street/Sidewalk   \n",
+       "26                 Department of Transportation    Street Light Condition   \n",
+       "27      Department of Health and Mental Hygiene      Harboring Bees/Wasps   \n",
+       "28              New York City Police Department   Noise - Street/Sidewalk   \n",
+       "29                 Department of Transportation    Street Light Condition   \n",
+       "...                                         ...                       ...   \n",
+       "111039          New York City Police Department        Noise - Commercial   \n",
+       "111040          New York City Police Department        Noise - Commercial   \n",
+       "111041   Department of Environmental Protection                     Noise   \n",
+       "111042          New York City Police Department   Noise - Street/Sidewalk   \n",
+       "111043          New York City Police Department        Noise - Commercial   \n",
+       "111044          New York City Police Department   Noise - Street/Sidewalk   \n",
+       "111045   Department of Environmental Protection              Water System   \n",
+       "111046   Department of Environmental Protection                     Noise   \n",
+       "111047          New York City Police Department           Illegal Parking   \n",
+       "111048          New York City Police Department   Noise - Street/Sidewalk   \n",
+       "111049          New York City Police Department        Noise - Commercial   \n",
+       "111050   Department of Environmental Protection                     Noise   \n",
+       "111051          New York City Police Department        Noise - Commercial   \n",
+       "111052   Department of Environmental Protection              Water System   \n",
+       "111053                        BCC - Queens East         Derelict Vehicles   \n",
+       "111054          New York City Police Department   Noise - Street/Sidewalk   \n",
+       "111055          New York City Police Department        Noise - Commercial   \n",
+       "111056             Department of Transportation     Street Sign - Missing   \n",
+       "111057   Department of Environmental Protection                     Noise   \n",
+       "111058          New York City Police Department        Noise - Commercial   \n",
+       "111059          New York City Police Department   Noise - Street/Sidewalk   \n",
+       "111060   Department of Environmental Protection                     Noise   \n",
+       "111061          New York City Police Department        Noise - Commercial   \n",
+       "111062   Department of Environmental Protection              Water System   \n",
+       "111063   Department of Environmental Protection              Water System   \n",
+       "111064       Department of Parks and Recreation   Maintenance or Facility   \n",
+       "111065          New York City Police Department           Illegal Parking   \n",
+       "111066          New York City Police Department   Noise - Street/Sidewalk   \n",
+       "111067          New York City Police Department        Noise - Commercial   \n",
+       "111068          New York City Police Department          Blocked Driveway   \n",
+       "\n",
+       "                                          Descriptor  \\\n",
+       "0                                       Loud Talking   \n",
+       "1                       Commercial Overnight Parking   \n",
+       "2                                   Loud Music/Party   \n",
+       "3                                     Car/Truck Horn   \n",
+       "4                       Condition Attracting Rodents   \n",
+       "5                                   Banging/Pounding   \n",
+       "6                                          No Access   \n",
+       "7                                   Loud Music/Party   \n",
+       "8                                       Loud Talking   \n",
+       "9                                   Loud Music/Party   \n",
+       "10                                  Loud Music/Party   \n",
+       "11                                  Loud Music/Party   \n",
+       "12                    Double Parked Blocking Vehicle   \n",
+       "13                                     Engine Idling   \n",
+       "14                                      Rat Sighting   \n",
+       "15                                  Loud Music/Party   \n",
+       "16                                  Loud Music/Party   \n",
+       "17                     Posted Parking Sign Violation   \n",
+       "18                                  Street Light Out   \n",
+       "19                                  Loud Music/Party   \n",
+       "20                                  Loud Music/Party   \n",
+       "21                                  Banging/Pounding   \n",
+       "22                                   Car/Truck Music   \n",
+       "23                                  Loud Music/Party   \n",
+       "24                                    Partial Access   \n",
+       "25                                      Loud Talking   \n",
+       "26                                  Street Light Out   \n",
+       "27                       Bees/Wasps - Not a beekeper   \n",
+       "28                                      Loud Talking   \n",
+       "29                                  Street Light Out   \n",
+       "...                                              ...   \n",
+       "111039                              Loud Music/Party   \n",
+       "111040                              Loud Music/Party   \n",
+       "111041  Noise: Construction Before/After Hours (NM1)   \n",
+       "111042                                  Loud Talking   \n",
+       "111043                              Loud Music/Party   \n",
+       "111044                                  Loud Talking   \n",
+       "111045                              Dirty Water (WE)   \n",
+       "111046  Noise: Construction Before/After Hours (NM1)   \n",
+       "111047                 Posted Parking Sign Violation   \n",
+       "111048                                  Loud Talking   \n",
+       "111049                              Loud Music/Party   \n",
+       "111050  Noise: Construction Before/After Hours (NM1)   \n",
+       "111051                              Loud Music/Party   \n",
+       "111052                              Dirty Water (WE)   \n",
+       "111053                          14 Derelict Vehicles   \n",
+       "111054                                  Loud Talking   \n",
+       "111055                                  Loud Talking   \n",
+       "111056                                      Bus Stop   \n",
+       "111057                   Noise: Jack Hammering (NC2)   \n",
+       "111058                              Loud Music/Party   \n",
+       "111059                                  Loud Talking   \n",
+       "111060  Noise: Construction Before/After Hours (NM1)   \n",
+       "111061                              Loud Music/Party   \n",
+       "111062                              Dirty Water (WE)   \n",
+       "111063                              Dirty Water (WE)   \n",
+       "111064                          Structure - Outdoors   \n",
+       "111065                 Posted Parking Sign Violation   \n",
+       "111066                                  Loud Talking   \n",
+       "111067                                  Loud Talking   \n",
+       "111068                                Partial Access   \n",
+       "\n",
+       "                        Location Type Incident Zip           Incident Address  \\\n",
+       "0                     Street/Sidewalk        11432           90-03 169 STREET   \n",
+       "1                     Street/Sidewalk        11378                  58 AVENUE   \n",
+       "2                 Club/Bar/Restaurant        10032              4060 BROADWAY   \n",
+       "3                     Street/Sidewalk        10023             WEST 72 STREET   \n",
+       "4                          Vacant Lot        10027            WEST 124 STREET   \n",
+       "5                 Club/Bar/Restaurant        11372                  37 AVENUE   \n",
+       "6                     Street/Sidewalk        11419          107-50 109 STREET   \n",
+       "7                 Club/Bar/Restaurant        11417  137-09 CROSSBAY BOULEVARD   \n",
+       "8                 Club/Bar/Restaurant        10011         258 WEST 15 STREET   \n",
+       "9                 Club/Bar/Restaurant        11225        835 NOSTRAND AVENUE   \n",
+       "10                   House of Worship        11218             3775 18 AVENUE   \n",
+       "11                Club/Bar/Restaurant        10003               187 2 AVENUE   \n",
+       "12                    Street/Sidewalk        10029          65 EAST 99 STREET   \n",
+       "13                    Street/Sidewalk        10466                        NaN   \n",
+       "14      1-2 Family Mixed Use Building        11219                  63 STREET   \n",
+       "15                   House of Worship        10025                        NaN   \n",
+       "16                    Street/Sidewalk        10310        173 CAMPBELL AVENUE   \n",
+       "17                    Street/Sidewalk        11236                        NaN   \n",
+       "18                                NaN          NaN                226 42 ST E   \n",
+       "19                Club/Bar/Restaurant        10033                        NaN   \n",
+       "20                   House of Worship        11216             778 PARK PLACE   \n",
+       "21                   Store/Commercial        10016              155 E 34TH ST   \n",
+       "22                    Street/Sidewalk        11419                        NaN   \n",
+       "23                Club/Bar/Restaurant        11216        371 TOMPKINS AVENUE   \n",
+       "24                    Street/Sidewalk        10305            1496 BAY STREET   \n",
+       "25                    Street/Sidewalk        10312          24 PRINCETON LANE   \n",
+       "26                                NaN          NaN                    38 ST E   \n",
+       "27       3+ Family Mixed Use Building        10025        501 WEST 110 STREET   \n",
+       "28                    Street/Sidewalk        10026        121 WEST 116 STREET   \n",
+       "29                                NaN        10309         295 BAYVIEW AVENUE   \n",
+       "...                               ...          ...                        ...   \n",
+       "111039            Club/Bar/Restaurant        10022         249 EAST 53 STREET   \n",
+       "111040               Store/Commercial        10029        252 EAST 110 STREET   \n",
+       "111041                            NaN        11231       480 VAN BRUNT STREET   \n",
+       "111042                Street/Sidewalk        10014      733 WASHINGTON STREET   \n",
+       "111043            Club/Bar/Restaurant        11218        1213 CORTELYOU ROAD   \n",
+       "111044                Street/Sidewalk        10032        539 WEST 162 STREET   \n",
+       "111045                            NaN        10022         251 EAST 51 STREET   \n",
+       "111046                            NaN        11231       480 VAN BRUNT STREET   \n",
+       "111047                Street/Sidewalk        11434                        NaN   \n",
+       "111048                Street/Sidewalk        10027      215 WEST 131ST STREET   \n",
+       "111049            Club/Bar/Restaurant        11209              8915 5 AVENUE   \n",
+       "111050                            NaN        10028                        NaN   \n",
+       "111051            Club/Bar/Restaurant        10009         506 EAST 13 STREET   \n",
+       "111052                            NaN        10022         325 EAST 54 STREET   \n",
+       "111053                         Street        11413          220-11 145 AVENUE   \n",
+       "111054                Street/Sidewalk        11224       4823 BEACH 48 STREET   \n",
+       "111055            Club/Bar/Restaurant        11209              7915 3 AVENUE   \n",
+       "111056                         Street        11378                        NaN   \n",
+       "111057                            NaN        10036                        NaN   \n",
+       "111058            Club/Bar/Restaurant        11237   211 KNICKERBOCKER AVENUE   \n",
+       "111059                Street/Sidewalk        10003                99 2 AVENUE   \n",
+       "111060                            NaN        10036                        NaN   \n",
+       "111061            Club/Bar/Restaurant        11106             30-09 BROADWAY   \n",
+       "111062                            NaN        10022         325 EAST 54 STREET   \n",
+       "111063                            NaN        10022         311 EAST 50 STREET   \n",
+       "111064                           Park        11213                        NaN   \n",
+       "111065                Street/Sidewalk        11434                        NaN   \n",
+       "111066                Street/Sidewalk        10016         344 EAST 28 STREET   \n",
+       "111067            Club/Bar/Restaurant        11226       1233 FLATBUSH AVENUE   \n",
+       "111068                Street/Sidewalk        11236        1259 EAST 94 STREET   \n",
+       "\n",
+       "                 Street Name      Cross Street 1  \\\n",
+       "0                 169 STREET           90 AVENUE   \n",
+       "1                  58 AVENUE            58 PLACE   \n",
+       "2                   BROADWAY     WEST 171 STREET   \n",
+       "3             WEST 72 STREET     COLUMBUS AVENUE   \n",
+       "4            WEST 124 STREET        LENOX AVENUE   \n",
+       "5                  37 AVENUE           84 STREET   \n",
+       "6                 109 STREET          107 AVENUE   \n",
+       "7         CROSSBAY BOULEVARD       PITKIN AVENUE   \n",
+       "8             WEST 15 STREET            7 AVENUE   \n",
+       "9            NOSTRAND AVENUE        UNION STREET   \n",
+       "10                 18 AVENUE       EAST 9 STREET   \n",
+       "11                  2 AVENUE      EAST 11 STREET   \n",
+       "12            EAST 99 STREET      MADISON AVENUE   \n",
+       "13                       NaN                 NaN   \n",
+       "14                 63 STREET           13 AVENUE   \n",
+       "15                       NaN                 NaN   \n",
+       "16           CAMPBELL AVENUE    HENDERSON AVENUE   \n",
+       "17                       NaN                 NaN   \n",
+       "18                   42 ST E          CHURCH AVE   \n",
+       "19                       NaN                 NaN   \n",
+       "20                PARK PLACE       ROGERS AVENUE   \n",
+       "21                 E 34TH ST                 NaN   \n",
+       "22                       NaN                 NaN   \n",
+       "23           TOMPKINS AVENUE      MADISON STREET   \n",
+       "24                BAY STREET        LYMAN AVENUE   \n",
+       "25            PRINCETON LANE       HAMPTON GREEN   \n",
+       "26                   38 ST E          CHURCH AVE   \n",
+       "27           WEST 110 STREET    AMSTERDAM AVENUE   \n",
+       "28           WEST 116 STREET        LENOX AVENUE   \n",
+       "29            BAYVIEW AVENUE         VAIL AVENUE   \n",
+       "...                      ...                 ...   \n",
+       "111039        EAST 53 STREET            3 AVENUE   \n",
+       "111040       EAST 110 STREET            3 AVENUE   \n",
+       "111041      VAN BRUNT STREET         REED STREET   \n",
+       "111042     WASHINGTON STREET         BANK STREET   \n",
+       "111043        CORTELYOU ROAD      EAST 12 STREET   \n",
+       "111044       WEST 162 STREET  ST NICHOLAS AVENUE   \n",
+       "111045        EAST 51 STREET            3 AVENUE   \n",
+       "111046      VAN BRUNT STREET         REED STREET   \n",
+       "111047                   NaN                 NaN   \n",
+       "111048     WEST 131ST STREET                 NaN   \n",
+       "111049              5 AVENUE           89 STREET   \n",
+       "111050                   NaN                 NaN   \n",
+       "111051        EAST 13 STREET            AVENUE A   \n",
+       "111052        EAST 54 STREET            2 AVENUE   \n",
+       "111053            145 AVENUE          221 STREET   \n",
+       "111054       BEACH 48 STREET       BODY OF WATER   \n",
+       "111055              3 AVENUE           79 STREET   \n",
+       "111056                   NaN                 NaN   \n",
+       "111057                   NaN                 NaN   \n",
+       "111058  KNICKERBOCKER AVENUE    JEFFERSON STREET   \n",
+       "111059              2 AVENUE       EAST 5 STREET   \n",
+       "111060                   NaN                 NaN   \n",
+       "111061              BROADWAY           30 STREET   \n",
+       "111062        EAST 54 STREET            2 AVENUE   \n",
+       "111063        EAST 50 STREET            2 AVENUE   \n",
+       "111064                   NaN                 NaN   \n",
+       "111065                   NaN                 NaN   \n",
+       "111066        EAST 28 STREET  MOUNT CARMEL PLACE   \n",
+       "111067       FLATBUSH AVENUE            AVENUE D   \n",
+       "111068        EAST 94 STREET            AVENUE J   \n",
+       "\n",
+       "                          Cross Street 2   Intersection Street 1  \\\n",
+       "0                              91 AVENUE                     NaN   \n",
+       "1                              59 STREET                     NaN   \n",
+       "2                        WEST 172 STREET                     NaN   \n",
+       "3                       AMSTERDAM AVENUE                     NaN   \n",
+       "4       ADAM CLAYTON POWELL JR BOULEVARD                     NaN   \n",
+       "5                              85 STREET                     NaN   \n",
+       "6                             109 AVENUE                     NaN   \n",
+       "7                       VAN WICKLEN ROAD                     NaN   \n",
+       "8                               8 AVENUE                     NaN   \n",
+       "9                       PRESIDENT STREET                     NaN   \n",
+       "10                         EAST 8 STREET                     NaN   \n",
+       "11                        EAST 12 STREET                     NaN   \n",
+       "12                           PARK AVENUE                     NaN   \n",
+       "13                                   NaN           STRANG AVENUE   \n",
+       "14                             14 AVENUE                     NaN   \n",
+       "15                                   NaN        WEST   99 STREET   \n",
+       "16                          WINEGAR LANE                     NaN   \n",
+       "17                                   NaN        ROCKAWAY PARKWAY   \n",
+       "18                            SNYDER AVE                     NaN   \n",
+       "19                                   NaN        WEST  184 STREET   \n",
+       "20                       NOSTRAND AVENUE                     NaN   \n",
+       "21                                   NaN                     NaN   \n",
+       "22                                   NaN              112 STREET   \n",
+       "23                         PUTNAM AVENUE                     NaN   \n",
+       "24                           SCHOOL ROAD                     NaN   \n",
+       "25                              DEAD END                     NaN   \n",
+       "26                           LINDEN BLVD                     NaN   \n",
+       "27                              BROADWAY                     NaN   \n",
+       "28                              7 AVENUE                     NaN   \n",
+       "29                          BAYVIEW LANE                     NaN   \n",
+       "...                                  ...                     ...   \n",
+       "111039                          2 AVENUE                     NaN   \n",
+       "111040                          2 AVENUE                     NaN   \n",
+       "111041                          DEAD END                     NaN   \n",
+       "111042                    BETHUNE STREET                     NaN   \n",
+       "111043                    EAST 13 STREET                     NaN   \n",
+       "111044                          BROADWAY                     NaN   \n",
+       "111045                          2 AVENUE                     NaN   \n",
+       "111046                          DEAD END                     NaN   \n",
+       "111047                               NaN  GUY R BREWER BOULEVARD   \n",
+       "111048                               NaN                     NaN   \n",
+       "111049                         90 STREET                     NaN   \n",
+       "111050                               NaN          EAST 84 STREET   \n",
+       "111051                          AVENUE B                     NaN   \n",
+       "111052                          1 AVENUE                     NaN   \n",
+       "111053                        221 STREET                     NaN   \n",
+       "111054                       SURF AVENUE                     NaN   \n",
+       "111055                         80 STREET                     NaN   \n",
+       "111056                               NaN               54 AVENUE   \n",
+       "111057                               NaN          WEST 48 STREET   \n",
+       "111058                   TROUTMAN STREET                     NaN   \n",
+       "111059                     EAST 6 STREET                     NaN   \n",
+       "111060                               NaN                8 AVENUE   \n",
+       "111061                         31 STREET                     NaN   \n",
+       "111062                          1 AVENUE                     NaN   \n",
+       "111063                          1 AVENUE                     NaN   \n",
+       "111064                               NaN                     NaN   \n",
+       "111065                               NaN  GUY R BREWER BOULEVARD   \n",
+       "111066                          1 AVENUE                     NaN   \n",
+       "111067                    NEWKIRK AVENUE                     NaN   \n",
+       "111068                          AVENUE K                     NaN   \n",
+       "\n",
+       "       Intersection Street 2  Address Type                 City Landmark  \\\n",
+       "0                        NaN       ADDRESS              JAMAICA      NaN   \n",
+       "1                        NaN     BLOCKFACE              MASPETH      NaN   \n",
+       "2                        NaN       ADDRESS             NEW YORK      NaN   \n",
+       "3                        NaN     BLOCKFACE             NEW YORK      NaN   \n",
+       "4                        NaN     BLOCKFACE             NEW YORK      NaN   \n",
+       "5                        NaN     BLOCKFACE      JACKSON HEIGHTS      NaN   \n",
+       "6                        NaN       ADDRESS  SOUTH RICHMOND HILL      NaN   \n",
+       "7                        NaN       ADDRESS           OZONE PARK      NaN   \n",
+       "8                        NaN       ADDRESS             NEW YORK      NaN   \n",
+       "9                        NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "10                       NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "11                       NaN       ADDRESS             NEW YORK      NaN   \n",
+       "12                       NaN       ADDRESS             NEW YORK      NaN   \n",
+       "13           AMUNDSON AVENUE  INTERSECTION                BRONX      NaN   \n",
+       "14                       NaN     BLOCKFACE             BROOKLYN      NaN   \n",
+       "15                  BROADWAY  INTERSECTION             NEW YORK      NaN   \n",
+       "16                       NaN       ADDRESS        STATEN ISLAND      NaN   \n",
+       "17           SKIDMORE AVENUE  INTERSECTION             BROOKLYN      NaN   \n",
+       "18                       NaN       ADDRESS                  NaN      NaN   \n",
+       "19                  BROADWAY  INTERSECTION             NEW YORK      NaN   \n",
+       "20                       NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "21                       NaN       LATLONG             NEW YORK      NaN   \n",
+       "22           ATLANTIC AVENUE  INTERSECTION  SOUTH RICHMOND HILL      NaN   \n",
+       "23                       NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "24                       NaN       ADDRESS        STATEN ISLAND      NaN   \n",
+       "25                       NaN       ADDRESS        STATEN ISLAND      NaN   \n",
+       "26                       NaN     BLOCKFACE                  NaN      NaN   \n",
+       "27                       NaN       ADDRESS             NEW YORK      NaN   \n",
+       "28                       NaN       ADDRESS             NEW YORK      NaN   \n",
+       "29                       NaN       ADDRESS        STATEN ISLAND      NaN   \n",
+       "...                      ...           ...                  ...      ...   \n",
+       "111039                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111040                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111041                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111042                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111043                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111044                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111045                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111046                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111047    ROCKAWAY BOULEVARD  INTERSECTION              JAMAICA      NaN   \n",
+       "111048                   NaN       LATLONG             NEW YORK      NaN   \n",
+       "111049                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111050           YORK AVENUE  INTERSECTION             NEW YORK      NaN   \n",
+       "111051                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111052                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111053                   NaN       ADDRESS  Springfield Gardens      NaN   \n",
+       "111054                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111055                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111056             43 STREET  INTERSECTION              MASPETH      NaN   \n",
+       "111057              BROADWAY  INTERSECTION             NEW YORK      NaN   \n",
+       "111058                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111059                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111060        WEST 47 STREET  INTERSECTION             NEW YORK      NaN   \n",
+       "111061                   NaN       ADDRESS              ASTORIA      NaN   \n",
+       "111062                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111063                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111064                   NaN           NaN             BROOKLYN      NaN   \n",
+       "111065    ROCKAWAY BOULEVARD  INTERSECTION              JAMAICA      NaN   \n",
+       "111066                   NaN       ADDRESS             NEW YORK      NaN   \n",
+       "111067                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "111068                   NaN       ADDRESS             BROOKLYN      NaN   \n",
+       "\n",
+       "       Facility Type    Status                Due Date  \\\n",
+       "0           Precinct  Assigned  10/31/2013 10:08:41 AM   \n",
+       "1           Precinct      Open  10/31/2013 10:01:04 AM   \n",
+       "2           Precinct    Closed  10/31/2013 10:00:24 AM   \n",
+       "3           Precinct    Closed  10/31/2013 09:56:23 AM   \n",
+       "4                NaN   Pending  11/30/2013 01:53:44 AM   \n",
+       "5           Precinct      Open  10/31/2013 09:46:52 AM   \n",
+       "6           Precinct  Assigned  10/31/2013 09:46:40 AM   \n",
+       "7           Precinct    Closed  10/31/2013 09:44:19 AM   \n",
+       "8           Precinct    Closed  10/31/2013 09:44:14 AM   \n",
+       "9           Precinct    Closed  10/31/2013 09:34:41 AM   \n",
+       "10          Precinct      Open  10/31/2013 09:25:12 AM   \n",
+       "11          Precinct    Closed  10/31/2013 09:24:14 AM   \n",
+       "12          Precinct    Closed  10/31/2013 09:20:57 AM   \n",
+       "13          Precinct      Open  10/31/2013 09:20:13 AM   \n",
+       "14               NaN   Pending  11/30/2013 01:19:54 AM   \n",
+       "15          Precinct    Closed  10/31/2013 09:14:02 AM   \n",
+       "16          Precinct    Closed  10/31/2013 08:54:03 AM   \n",
+       "17          Precinct      Open  10/31/2013 08:52:46 AM   \n",
+       "18               NaN      Open                     NaN   \n",
+       "19          Precinct  Assigned  10/31/2013 08:46:27 AM   \n",
+       "20          Precinct    Closed  10/31/2013 08:43:47 AM   \n",
+       "21          Precinct    Closed  10/31/2013 08:41:17 AM   \n",
+       "22          Precinct      Open  10/31/2013 08:39:55 AM   \n",
+       "23          Precinct  Assigned  10/31/2013 08:38:00 AM   \n",
+       "24          Precinct  Assigned  10/31/2013 08:37:16 AM   \n",
+       "25          Precinct    Closed  10/31/2013 08:35:18 AM   \n",
+       "26               NaN      Open                     NaN   \n",
+       "27               NaN      Open  11/30/2013 12:32:44 AM   \n",
+       "28          Precinct  Assigned  10/31/2013 08:32:08 AM   \n",
+       "29               NaN      Open                     NaN   \n",
+       "...              ...       ...                     ...   \n",
+       "111039      Precinct    Closed  10/04/2013 08:17:03 AM   \n",
+       "111040      Precinct    Closed  10/04/2013 08:16:22 AM   \n",
+       "111041           NaN      Open                     NaN   \n",
+       "111042      Precinct    Closed  10/04/2013 08:15:52 AM   \n",
+       "111043      Precinct    Closed  10/04/2013 08:15:46 AM   \n",
+       "111044      Precinct    Closed  10/04/2013 08:14:09 AM   \n",
+       "111045           NaN    Closed                     NaN   \n",
+       "111046           NaN      Open                     NaN   \n",
+       "111047      Precinct    Closed  10/04/2013 08:13:08 AM   \n",
+       "111048      Precinct    Closed  10/04/2013 08:12:07 AM   \n",
+       "111049      Precinct    Closed  10/04/2013 08:12:07 AM   \n",
+       "111050           NaN      Open                     NaN   \n",
+       "111051      Precinct    Closed  10/04/2013 08:08:15 AM   \n",
+       "111052           NaN    Closed                     NaN   \n",
+       "111053   DSNY Garage   Pending                     NaN   \n",
+       "111054      Precinct    Closed  10/04/2013 08:06:39 AM   \n",
+       "111055      Precinct    Closed  10/04/2013 08:06:28 AM   \n",
+       "111056           NaN    Closed  10/14/2013 09:38:47 AM   \n",
+       "111057           NaN      Open                     NaN   \n",
+       "111058      Precinct    Closed  10/04/2013 08:05:12 AM   \n",
+       "111059      Precinct    Closed  10/04/2013 08:04:52 AM   \n",
+       "111060           NaN      Open                     NaN   \n",
+       "111061      Precinct    Closed  10/04/2013 08:03:00 AM   \n",
+       "111062           NaN    Closed                     NaN   \n",
+       "111063           NaN    Closed                     NaN   \n",
+       "111064           NaN    Closed  10/18/2013 12:01:13 AM   \n",
+       "111065      Precinct    Closed  10/04/2013 08:01:05 AM   \n",
+       "111066      Precinct    Closed  10/04/2013 08:00:45 AM   \n",
+       "111067      Precinct    Closed  10/04/2013 08:00:28 AM   \n",
+       "111068      Precinct    Closed  10/04/2013 08:00:10 AM   \n",
+       "\n",
+       "       Resolution Action Updated Date       Community Board        Borough  \\\n",
+       "0              10/31/2013 02:35:17 AM             12 QUEENS         QUEENS   \n",
+       "1                                 NaN             05 QUEENS         QUEENS   \n",
+       "2              10/31/2013 02:39:42 AM          12 MANHATTAN      MANHATTAN   \n",
+       "3              10/31/2013 02:21:10 AM          07 MANHATTAN      MANHATTAN   \n",
+       "4              10/31/2013 01:59:54 AM          10 MANHATTAN      MANHATTAN   \n",
+       "5                                 NaN             03 QUEENS         QUEENS   \n",
+       "6              10/31/2013 01:59:51 AM             10 QUEENS         QUEENS   \n",
+       "7              10/31/2013 01:58:49 AM             10 QUEENS         QUEENS   \n",
+       "8              10/31/2013 02:00:56 AM          04 MANHATTAN      MANHATTAN   \n",
+       "9              10/31/2013 01:48:26 AM           09 BROOKLYN       BROOKLYN   \n",
+       "10                                NaN           14 BROOKLYN       BROOKLYN   \n",
+       "11             10/31/2013 01:54:39 AM          03 MANHATTAN      MANHATTAN   \n",
+       "12             10/31/2013 01:42:05 AM          11 MANHATTAN      MANHATTAN   \n",
+       "13                                NaN              12 BRONX          BRONX   \n",
+       "14             10/31/2013 01:29:26 AM           10 BROOKLYN       BROOKLYN   \n",
+       "15             10/31/2013 01:30:34 AM          07 MANHATTAN      MANHATTAN   \n",
+       "16             10/31/2013 02:07:14 AM      01 STATEN ISLAND  STATEN ISLAND   \n",
+       "17                                NaN           18 BROOKLYN       BROOKLYN   \n",
+       "18                                NaN  Unspecified BROOKLYN       BROOKLYN   \n",
+       "19             10/31/2013 01:32:41 AM          12 MANHATTAN      MANHATTAN   \n",
+       "20             10/31/2013 12:56:20 AM           08 BROOKLYN       BROOKLYN   \n",
+       "21             10/31/2013 01:04:38 AM          06 MANHATTAN      MANHATTAN   \n",
+       "22                                NaN             09 QUEENS         QUEENS   \n",
+       "23             10/31/2013 01:16:53 AM           03 BROOKLYN       BROOKLYN   \n",
+       "24             10/31/2013 12:52:10 AM      01 STATEN ISLAND  STATEN ISLAND   \n",
+       "25             10/31/2013 01:45:17 AM      03 STATEN ISLAND  STATEN ISLAND   \n",
+       "26                                NaN  Unspecified BROOKLYN       BROOKLYN   \n",
+       "27                                NaN          09 MANHATTAN      MANHATTAN   \n",
+       "28             10/31/2013 02:00:57 AM          10 MANHATTAN      MANHATTAN   \n",
+       "29                                NaN      03 STATEN ISLAND  STATEN ISLAND   \n",
+       "...                               ...                   ...            ...   \n",
+       "111039         10/04/2013 12:38:37 AM          06 MANHATTAN      MANHATTAN   \n",
+       "111040         10/04/2013 05:50:49 AM          11 MANHATTAN      MANHATTAN   \n",
+       "111041                            NaN           06 BROOKLYN       BROOKLYN   \n",
+       "111042         10/04/2013 12:44:52 AM          02 MANHATTAN      MANHATTAN   \n",
+       "111043         10/04/2013 04:18:45 AM           14 BROOKLYN       BROOKLYN   \n",
+       "111044         10/04/2013 01:03:46 AM          12 MANHATTAN      MANHATTAN   \n",
+       "111045         10/04/2013 12:14:00 AM          06 MANHATTAN      MANHATTAN   \n",
+       "111046                            NaN           06 BROOKLYN       BROOKLYN   \n",
+       "111047         10/04/2013 02:12:47 AM             13 QUEENS         QUEENS   \n",
+       "111048         10/04/2013 02:45:24 AM          01 MANHATTAN      MANHATTAN   \n",
+       "111049         10/04/2013 01:03:44 AM           10 BROOKLYN       BROOKLYN   \n",
+       "111050                            NaN          08 MANHATTAN      MANHATTAN   \n",
+       "111051         10/04/2013 12:48:03 AM          03 MANHATTAN      MANHATTAN   \n",
+       "111052         10/04/2013 12:13:00 AM          06 MANHATTAN      MANHATTAN   \n",
+       "111053         10/04/2013 12:08:00 AM             13 QUEENS         QUEENS   \n",
+       "111054         10/04/2013 12:31:16 AM           13 BROOKLYN       BROOKLYN   \n",
+       "111055         10/04/2013 12:21:39 AM           10 BROOKLYN       BROOKLYN   \n",
+       "111056         10/23/2013 08:14:52 AM             02 QUEENS         QUEENS   \n",
+       "111057                            NaN          05 MANHATTAN      MANHATTAN   \n",
+       "111058         10/04/2013 01:08:29 AM           04 BROOKLYN       BROOKLYN   \n",
+       "111059         10/04/2013 03:01:04 AM          03 MANHATTAN      MANHATTAN   \n",
+       "111060                            NaN          04 MANHATTAN      MANHATTAN   \n",
+       "111061         10/04/2013 02:14:57 AM             01 QUEENS         QUEENS   \n",
+       "111062         10/04/2013 12:03:00 AM          06 MANHATTAN      MANHATTAN   \n",
+       "111063         10/04/2013 01:10:00 AM          06 MANHATTAN      MANHATTAN   \n",
+       "111064         10/07/2013 04:07:16 PM           08 BROOKLYN       BROOKLYN   \n",
+       "111065         10/04/2013 02:13:50 AM             13 QUEENS         QUEENS   \n",
+       "111066         10/04/2013 01:25:01 AM          06 MANHATTAN      MANHATTAN   \n",
+       "111067         10/04/2013 04:17:32 AM           14 BROOKLYN       BROOKLYN   \n",
+       "111068         10/04/2013 01:20:52 AM           18 BROOKLYN       BROOKLYN   \n",
+       "\n",
+       "        X Coordinate (State Plane)  Y Coordinate (State Plane)  \\\n",
+       "0                        1042027.0                    197389.0   \n",
+       "1                        1009349.0                    201984.0   \n",
+       "2                        1001088.0                    246531.0   \n",
+       "3                         989730.0                    222727.0   \n",
+       "4                         998815.0                    233545.0   \n",
+       "5                        1016948.0                    212540.0   \n",
+       "6                        1030919.0                    187622.0   \n",
+       "7                        1027776.0                    184076.0   \n",
+       "8                         984031.0                    208847.0   \n",
+       "9                         997941.0                    182725.0   \n",
+       "10                        992726.0                    170399.0   \n",
+       "11                        988110.0                    205533.0   \n",
+       "12                        997470.0                    226725.0   \n",
+       "13                       1029467.0                    264124.0   \n",
+       "14                        984467.0                    167519.0   \n",
+       "15                        992454.0                    229500.0   \n",
+       "16                        952013.0                    171076.0   \n",
+       "17                       1015289.0                    169710.0   \n",
+       "18                             NaN                         NaN   \n",
+       "19                       1002294.0                    249712.0   \n",
+       "20                        997608.0                    184656.0   \n",
+       "21                        990133.0                    211136.0   \n",
+       "22                       1030314.0                    191578.0   \n",
+       "23                        999720.0                    188825.0   \n",
+       "24                        967283.0                    160518.0   \n",
+       "25                        929577.0                    140964.0   \n",
+       "26                             NaN                         NaN   \n",
+       "27                        994143.0                    231888.0   \n",
+       "28                        997947.0                    231613.0   \n",
+       "29                        927687.0                    127837.0   \n",
+       "...                            ...                         ...   \n",
+       "111039                    993036.0                    215164.0   \n",
+       "111040                   1000407.0                    228425.0   \n",
+       "111041                    979657.0                    184924.0   \n",
+       "111042                    981950.0                    207532.0   \n",
+       "111043                    993451.0                    172498.0   \n",
+       "111044                   1000571.0                    244054.0   \n",
+       "111045                    992791.0                    214702.0   \n",
+       "111046                    979657.0                    184924.0   \n",
+       "111047                   1048801.0                    178419.0   \n",
+       "111048                    999107.0                    235603.0   \n",
+       "111049                    976525.0                    165015.0   \n",
+       "111050                    998629.0                    221493.0   \n",
+       "111051                    989678.0                    205065.0   \n",
+       "111052                    993688.0                    215099.0   \n",
+       "111053                   1051511.0                    181411.0   \n",
+       "111054                    980859.0                    149681.0   \n",
+       "111055                    976189.0                    168214.0   \n",
+       "111056                   1005171.0                    206064.0   \n",
+       "111057                    988451.0                    216208.0   \n",
+       "111058                   1004672.0                    195540.0   \n",
+       "111059                    987393.0                    204234.0   \n",
+       "111060                    987720.0                    216313.0   \n",
+       "111061                   1004746.0                    217004.0   \n",
+       "111062                    993688.0                    215099.0   \n",
+       "111063                    993118.0                    214222.0   \n",
+       "111064                         NaN                         NaN   \n",
+       "111065                   1048801.0                    178419.0   \n",
+       "111066                    990637.0                    208987.0   \n",
+       "111067                    996654.0                    172515.0   \n",
+       "111068                   1011804.0                    172470.0   \n",
+       "\n",
+       "       Park Facility Name   Park Borough  School Name School Number  \\\n",
+       "0             Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "1             Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "2             Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "3             Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "4             Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "5             Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "6             Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "7             Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "8             Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "9             Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "10            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "11            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "12            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "13            Unspecified          BRONX  Unspecified   Unspecified   \n",
+       "14            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "15            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "16            Unspecified  STATEN ISLAND  Unspecified   Unspecified   \n",
+       "17            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "18            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "19            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "20            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "21            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "22            Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "23            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "24            Unspecified  STATEN ISLAND  Unspecified   Unspecified   \n",
+       "25            Unspecified  STATEN ISLAND  Unspecified   Unspecified   \n",
+       "26            Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "27            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "28            Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "29            Unspecified  STATEN ISLAND  Unspecified   Unspecified   \n",
+       "...                   ...            ...          ...           ...   \n",
+       "111039        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111040        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111041        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111042        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111043        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111044        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111045        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111046        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111047        Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "111048        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111049        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111050        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111051        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111052        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111053        Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "111054        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111055        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111056        Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "111057        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111058        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111059        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111060        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111061        Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "111062        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111063        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111064        Brower Park       BROOKLYN  Brower Park          B012   \n",
+       "111065        Unspecified         QUEENS  Unspecified   Unspecified   \n",
+       "111066        Unspecified      MANHATTAN  Unspecified   Unspecified   \n",
+       "111067        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "111068        Unspecified       BROOKLYN  Unspecified   Unspecified   \n",
+       "\n",
+       "       School Region  School Code School Phone Number  \\\n",
+       "0        Unspecified  Unspecified         Unspecified   \n",
+       "1        Unspecified  Unspecified         Unspecified   \n",
+       "2        Unspecified  Unspecified         Unspecified   \n",
+       "3        Unspecified  Unspecified         Unspecified   \n",
+       "4        Unspecified  Unspecified         Unspecified   \n",
+       "5        Unspecified  Unspecified         Unspecified   \n",
+       "6        Unspecified  Unspecified         Unspecified   \n",
+       "7        Unspecified  Unspecified         Unspecified   \n",
+       "8        Unspecified  Unspecified         Unspecified   \n",
+       "9        Unspecified  Unspecified         Unspecified   \n",
+       "10       Unspecified  Unspecified         Unspecified   \n",
+       "11       Unspecified  Unspecified         Unspecified   \n",
+       "12       Unspecified  Unspecified         Unspecified   \n",
+       "13       Unspecified  Unspecified         Unspecified   \n",
+       "14       Unspecified  Unspecified         Unspecified   \n",
+       "15       Unspecified  Unspecified         Unspecified   \n",
+       "16       Unspecified  Unspecified         Unspecified   \n",
+       "17       Unspecified  Unspecified         Unspecified   \n",
+       "18       Unspecified  Unspecified         Unspecified   \n",
+       "19       Unspecified  Unspecified         Unspecified   \n",
+       "20       Unspecified  Unspecified         Unspecified   \n",
+       "21       Unspecified  Unspecified         Unspecified   \n",
+       "22       Unspecified  Unspecified         Unspecified   \n",
+       "23       Unspecified  Unspecified         Unspecified   \n",
+       "24       Unspecified  Unspecified         Unspecified   \n",
+       "25       Unspecified  Unspecified         Unspecified   \n",
+       "26       Unspecified  Unspecified         Unspecified   \n",
+       "27       Unspecified  Unspecified         Unspecified   \n",
+       "28       Unspecified  Unspecified         Unspecified   \n",
+       "29       Unspecified  Unspecified         Unspecified   \n",
+       "...              ...          ...                 ...   \n",
+       "111039   Unspecified  Unspecified         Unspecified   \n",
+       "111040   Unspecified  Unspecified         Unspecified   \n",
+       "111041   Unspecified  Unspecified         Unspecified   \n",
+       "111042   Unspecified  Unspecified         Unspecified   \n",
+       "111043   Unspecified  Unspecified         Unspecified   \n",
+       "111044   Unspecified  Unspecified         Unspecified   \n",
+       "111045   Unspecified  Unspecified         Unspecified   \n",
+       "111046   Unspecified  Unspecified         Unspecified   \n",
+       "111047   Unspecified  Unspecified         Unspecified   \n",
+       "111048   Unspecified  Unspecified         Unspecified   \n",
+       "111049   Unspecified  Unspecified         Unspecified   \n",
+       "111050   Unspecified  Unspecified         Unspecified   \n",
+       "111051   Unspecified  Unspecified         Unspecified   \n",
+       "111052   Unspecified  Unspecified         Unspecified   \n",
+       "111053   Unspecified  Unspecified         Unspecified   \n",
+       "111054   Unspecified  Unspecified         Unspecified   \n",
+       "111055   Unspecified  Unspecified         Unspecified   \n",
+       "111056   Unspecified  Unspecified         Unspecified   \n",
+       "111057   Unspecified  Unspecified         Unspecified   \n",
+       "111058   Unspecified  Unspecified         Unspecified   \n",
+       "111059   Unspecified  Unspecified         Unspecified   \n",
+       "111060   Unspecified  Unspecified         Unspecified   \n",
+       "111061   Unspecified  Unspecified         Unspecified   \n",
+       "111062   Unspecified  Unspecified         Unspecified   \n",
+       "111063   Unspecified  Unspecified         Unspecified   \n",
+       "111064           NaN          NaN          7189658900   \n",
+       "111065   Unspecified  Unspecified         Unspecified   \n",
+       "111066   Unspecified  Unspecified         Unspecified   \n",
+       "111067   Unspecified  Unspecified         Unspecified   \n",
+       "111068   Unspecified  Unspecified         Unspecified   \n",
+       "\n",
+       "                                           School Address  School City  \\\n",
+       "0                                             Unspecified  Unspecified   \n",
+       "1                                             Unspecified  Unspecified   \n",
+       "2                                             Unspecified  Unspecified   \n",
+       "3                                             Unspecified  Unspecified   \n",
+       "4                                             Unspecified  Unspecified   \n",
+       "5                                             Unspecified  Unspecified   \n",
+       "6                                             Unspecified  Unspecified   \n",
+       "7                                             Unspecified  Unspecified   \n",
+       "8                                             Unspecified  Unspecified   \n",
+       "9                                             Unspecified  Unspecified   \n",
+       "10                                            Unspecified  Unspecified   \n",
+       "11                                            Unspecified  Unspecified   \n",
+       "12                                            Unspecified  Unspecified   \n",
+       "13                                            Unspecified  Unspecified   \n",
+       "14                                            Unspecified  Unspecified   \n",
+       "15                                            Unspecified  Unspecified   \n",
+       "16                                            Unspecified  Unspecified   \n",
+       "17                                            Unspecified  Unspecified   \n",
+       "18                                            Unspecified  Unspecified   \n",
+       "19                                            Unspecified  Unspecified   \n",
+       "20                                            Unspecified  Unspecified   \n",
+       "21                                            Unspecified  Unspecified   \n",
+       "22                                            Unspecified  Unspecified   \n",
+       "23                                            Unspecified  Unspecified   \n",
+       "24                                            Unspecified  Unspecified   \n",
+       "25                                            Unspecified  Unspecified   \n",
+       "26                                            Unspecified  Unspecified   \n",
+       "27                                            Unspecified  Unspecified   \n",
+       "28                                            Unspecified  Unspecified   \n",
+       "29                                            Unspecified  Unspecified   \n",
+       "...                                                   ...          ...   \n",
+       "111039                                        Unspecified  Unspecified   \n",
+       "111040                                        Unspecified  Unspecified   \n",
+       "111041                                        Unspecified  Unspecified   \n",
+       "111042                                        Unspecified  Unspecified   \n",
+       "111043                                        Unspecified  Unspecified   \n",
+       "111044                                        Unspecified  Unspecified   \n",
+       "111045                                        Unspecified  Unspecified   \n",
+       "111046                                        Unspecified  Unspecified   \n",
+       "111047                                        Unspecified  Unspecified   \n",
+       "111048                                        Unspecified  Unspecified   \n",
+       "111049                                        Unspecified  Unspecified   \n",
+       "111050                                        Unspecified  Unspecified   \n",
+       "111051                                        Unspecified  Unspecified   \n",
+       "111052                                        Unspecified  Unspecified   \n",
+       "111053                                        Unspecified  Unspecified   \n",
+       "111054                                        Unspecified  Unspecified   \n",
+       "111055                                        Unspecified  Unspecified   \n",
+       "111056                                        Unspecified  Unspecified   \n",
+       "111057                                        Unspecified  Unspecified   \n",
+       "111058                                        Unspecified  Unspecified   \n",
+       "111059                                        Unspecified  Unspecified   \n",
+       "111060                                        Unspecified  Unspecified   \n",
+       "111061                                        Unspecified  Unspecified   \n",
+       "111062                                        Unspecified  Unspecified   \n",
+       "111063                                        Unspecified  Unspecified   \n",
+       "111064  Brooklyn, St. Marks, Kingston Avenues, Park Place     BROOKLYN   \n",
+       "111065                                        Unspecified  Unspecified   \n",
+       "111066                                        Unspecified  Unspecified   \n",
+       "111067                                        Unspecified  Unspecified   \n",
+       "111068                                        Unspecified  Unspecified   \n",
+       "\n",
+       "       School State   School Zip School Not Found  \\\n",
+       "0       Unspecified  Unspecified                N   \n",
+       "1       Unspecified  Unspecified                N   \n",
+       "2       Unspecified  Unspecified                N   \n",
+       "3       Unspecified  Unspecified                N   \n",
+       "4       Unspecified  Unspecified                N   \n",
+       "5       Unspecified  Unspecified                N   \n",
+       "6       Unspecified  Unspecified                N   \n",
+       "7       Unspecified  Unspecified                N   \n",
+       "8       Unspecified  Unspecified                N   \n",
+       "9       Unspecified  Unspecified                N   \n",
+       "10      Unspecified  Unspecified                N   \n",
+       "11      Unspecified  Unspecified                N   \n",
+       "12      Unspecified  Unspecified                N   \n",
+       "13      Unspecified  Unspecified                N   \n",
+       "14      Unspecified  Unspecified                N   \n",
+       "15      Unspecified  Unspecified                N   \n",
+       "16      Unspecified  Unspecified                N   \n",
+       "17      Unspecified  Unspecified                N   \n",
+       "18      Unspecified  Unspecified              NaN   \n",
+       "19      Unspecified  Unspecified                N   \n",
+       "20      Unspecified  Unspecified                N   \n",
+       "21      Unspecified  Unspecified                N   \n",
+       "22      Unspecified  Unspecified                N   \n",
+       "23      Unspecified  Unspecified                N   \n",
+       "24      Unspecified  Unspecified                N   \n",
+       "25      Unspecified  Unspecified                N   \n",
+       "26      Unspecified  Unspecified              NaN   \n",
+       "27      Unspecified  Unspecified                N   \n",
+       "28      Unspecified  Unspecified                N   \n",
+       "29      Unspecified  Unspecified              NaN   \n",
+       "...             ...          ...              ...   \n",
+       "111039  Unspecified  Unspecified                N   \n",
+       "111040  Unspecified  Unspecified                N   \n",
+       "111041  Unspecified  Unspecified              NaN   \n",
+       "111042  Unspecified  Unspecified                N   \n",
+       "111043  Unspecified  Unspecified                N   \n",
+       "111044  Unspecified  Unspecified                N   \n",
+       "111045  Unspecified  Unspecified              NaN   \n",
+       "111046  Unspecified  Unspecified              NaN   \n",
+       "111047  Unspecified  Unspecified                N   \n",
+       "111048  Unspecified  Unspecified                N   \n",
+       "111049  Unspecified  Unspecified                N   \n",
+       "111050  Unspecified  Unspecified              NaN   \n",
+       "111051  Unspecified  Unspecified                N   \n",
+       "111052  Unspecified  Unspecified              NaN   \n",
+       "111053  Unspecified  Unspecified              NaN   \n",
+       "111054  Unspecified  Unspecified                N   \n",
+       "111055  Unspecified  Unspecified                N   \n",
+       "111056  Unspecified  Unspecified                N   \n",
+       "111057  Unspecified  Unspecified              NaN   \n",
+       "111058  Unspecified  Unspecified                N   \n",
+       "111059  Unspecified  Unspecified                N   \n",
+       "111060  Unspecified  Unspecified              NaN   \n",
+       "111061  Unspecified  Unspecified                N   \n",
+       "111062  Unspecified  Unspecified              NaN   \n",
+       "111063  Unspecified  Unspecified              NaN   \n",
+       "111064           NY        11213                N   \n",
+       "111065  Unspecified  Unspecified                N   \n",
+       "111066  Unspecified  Unspecified                N   \n",
+       "111067  Unspecified  Unspecified                N   \n",
+       "111068  Unspecified  Unspecified                N   \n",
+       "\n",
+       "        School or Citywide Complaint Vehicle Type Taxi Company Borough  \\\n",
+       "0                                NaN          NaN                  NaN   \n",
+       "1                                NaN          NaN                  NaN   \n",
+       "2                                NaN          NaN                  NaN   \n",
+       "3                                NaN          NaN                  NaN   \n",
+       "4                                NaN          NaN                  NaN   \n",
+       "5                                NaN          NaN                  NaN   \n",
+       "6                                NaN          NaN                  NaN   \n",
+       "7                                NaN          NaN                  NaN   \n",
+       "8                                NaN          NaN                  NaN   \n",
+       "9                                NaN          NaN                  NaN   \n",
+       "10                               NaN          NaN                  NaN   \n",
+       "11                               NaN          NaN                  NaN   \n",
+       "12                               NaN          NaN                  NaN   \n",
+       "13                               NaN          NaN                  NaN   \n",
+       "14                               NaN          NaN                  NaN   \n",
+       "15                               NaN          NaN                  NaN   \n",
+       "16                               NaN          NaN                  NaN   \n",
+       "17                               NaN          NaN                  NaN   \n",
+       "18                               NaN          NaN                  NaN   \n",
+       "19                               NaN          NaN                  NaN   \n",
+       "20                               NaN          NaN                  NaN   \n",
+       "21                               NaN          NaN                  NaN   \n",
+       "22                               NaN          NaN                  NaN   \n",
+       "23                               NaN          NaN                  NaN   \n",
+       "24                               NaN          NaN                  NaN   \n",
+       "25                               NaN          NaN                  NaN   \n",
+       "26                               NaN          NaN                  NaN   \n",
+       "27                               NaN          NaN                  NaN   \n",
+       "28                               NaN          NaN                  NaN   \n",
+       "29                               NaN          NaN                  NaN   \n",
+       "...                              ...          ...                  ...   \n",
+       "111039                           NaN          NaN                  NaN   \n",
+       "111040                           NaN          NaN                  NaN   \n",
+       "111041                           NaN          NaN                  NaN   \n",
+       "111042                           NaN          NaN                  NaN   \n",
+       "111043                           NaN          NaN                  NaN   \n",
+       "111044                           NaN          NaN                  NaN   \n",
+       "111045                           NaN          NaN                  NaN   \n",
+       "111046                           NaN          NaN                  NaN   \n",
+       "111047                           NaN          NaN                  NaN   \n",
+       "111048                           NaN          NaN                  NaN   \n",
+       "111049                           NaN          NaN                  NaN   \n",
+       "111050                           NaN          NaN                  NaN   \n",
+       "111051                           NaN          NaN                  NaN   \n",
+       "111052                           NaN          NaN                  NaN   \n",
+       "111053                           NaN          NaN                  NaN   \n",
+       "111054                           NaN          NaN                  NaN   \n",
+       "111055                           NaN          NaN                  NaN   \n",
+       "111056                           NaN          NaN                  NaN   \n",
+       "111057                           NaN          NaN                  NaN   \n",
+       "111058                           NaN          NaN                  NaN   \n",
+       "111059                           NaN          NaN                  NaN   \n",
+       "111060                           NaN          NaN                  NaN   \n",
+       "111061                           NaN          NaN                  NaN   \n",
+       "111062                           NaN          NaN                  NaN   \n",
+       "111063                           NaN          NaN                  NaN   \n",
+       "111064                           NaN          NaN                  NaN   \n",
+       "111065                           NaN          NaN                  NaN   \n",
+       "111066                           NaN          NaN                  NaN   \n",
+       "111067                           NaN          NaN                  NaN   \n",
+       "111068                           NaN          NaN                  NaN   \n",
+       "\n",
+       "       Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction  \\\n",
+       "0                        NaN                 NaN                      NaN   \n",
+       "1                        NaN                 NaN                      NaN   \n",
+       "2                        NaN                 NaN                      NaN   \n",
+       "3                        NaN                 NaN                      NaN   \n",
+       "4                        NaN                 NaN                      NaN   \n",
+       "5                        NaN                 NaN                      NaN   \n",
+       "6                        NaN                 NaN                      NaN   \n",
+       "7                        NaN                 NaN                      NaN   \n",
+       "8                        NaN                 NaN                      NaN   \n",
+       "9                        NaN                 NaN                      NaN   \n",
+       "10                       NaN                 NaN                      NaN   \n",
+       "11                       NaN                 NaN                      NaN   \n",
+       "12                       NaN                 NaN                      NaN   \n",
+       "13                       NaN                 NaN                      NaN   \n",
+       "14                       NaN                 NaN                      NaN   \n",
+       "15                       NaN                 NaN                      NaN   \n",
+       "16                       NaN                 NaN                      NaN   \n",
+       "17                       NaN                 NaN                      NaN   \n",
+       "18                       NaN                 NaN                      NaN   \n",
+       "19                       NaN                 NaN                      NaN   \n",
+       "20                       NaN                 NaN                      NaN   \n",
+       "21                       NaN                 NaN                      NaN   \n",
+       "22                       NaN                 NaN                      NaN   \n",
+       "23                       NaN                 NaN                      NaN   \n",
+       "24                       NaN                 NaN                      NaN   \n",
+       "25                       NaN                 NaN                      NaN   \n",
+       "26                       NaN                 NaN                      NaN   \n",
+       "27                       NaN                 NaN                      NaN   \n",
+       "28                       NaN                 NaN                      NaN   \n",
+       "29                       NaN                 NaN                      NaN   \n",
+       "...                      ...                 ...                      ...   \n",
+       "111039                   NaN                 NaN                      NaN   \n",
+       "111040                   NaN                 NaN                      NaN   \n",
+       "111041                   NaN                 NaN                      NaN   \n",
+       "111042                   NaN                 NaN                      NaN   \n",
+       "111043                   NaN                 NaN                      NaN   \n",
+       "111044                   NaN                 NaN                      NaN   \n",
+       "111045                   NaN                 NaN                      NaN   \n",
+       "111046                   NaN                 NaN                      NaN   \n",
+       "111047                   NaN                 NaN                      NaN   \n",
+       "111048                   NaN                 NaN                      NaN   \n",
+       "111049                   NaN                 NaN                      NaN   \n",
+       "111050                   NaN                 NaN                      NaN   \n",
+       "111051                   NaN                 NaN                      NaN   \n",
+       "111052                   NaN                 NaN                      NaN   \n",
+       "111053                   NaN                 NaN                      NaN   \n",
+       "111054                   NaN                 NaN                      NaN   \n",
+       "111055                   NaN                 NaN                      NaN   \n",
+       "111056                   NaN                 NaN                      NaN   \n",
+       "111057                   NaN                 NaN                      NaN   \n",
+       "111058                   NaN                 NaN                      NaN   \n",
+       "111059                   NaN                 NaN                      NaN   \n",
+       "111060                   NaN                 NaN                      NaN   \n",
+       "111061                   NaN                 NaN                      NaN   \n",
+       "111062                   NaN                 NaN                      NaN   \n",
+       "111063                   NaN                 NaN                      NaN   \n",
+       "111064                   NaN                 NaN                      NaN   \n",
+       "111065                   NaN                 NaN                      NaN   \n",
+       "111066                   NaN                 NaN                      NaN   \n",
+       "111067                   NaN                 NaN                      NaN   \n",
+       "111068                   NaN                 NaN                      NaN   \n",
+       "\n",
+       "       Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction  \\\n",
+       "0            NaN                    NaN             NaN             NaN   \n",
+       "1            NaN                    NaN             NaN             NaN   \n",
+       "2            NaN                    NaN             NaN             NaN   \n",
+       "3            NaN                    NaN             NaN             NaN   \n",
+       "4            NaN                    NaN             NaN             NaN   \n",
+       "5            NaN                    NaN             NaN             NaN   \n",
+       "6            NaN                    NaN             NaN             NaN   \n",
+       "7            NaN                    NaN             NaN             NaN   \n",
+       "8            NaN                    NaN             NaN             NaN   \n",
+       "9            NaN                    NaN             NaN             NaN   \n",
+       "10           NaN                    NaN             NaN             NaN   \n",
+       "11           NaN                    NaN             NaN             NaN   \n",
+       "12           NaN                    NaN             NaN             NaN   \n",
+       "13           NaN                    NaN             NaN             NaN   \n",
+       "14           NaN                    NaN             NaN             NaN   \n",
+       "15           NaN                    NaN             NaN             NaN   \n",
+       "16           NaN                    NaN             NaN             NaN   \n",
+       "17           NaN                    NaN             NaN             NaN   \n",
+       "18           NaN                    NaN             NaN             NaN   \n",
+       "19           NaN                    NaN             NaN             NaN   \n",
+       "20           NaN                    NaN             NaN             NaN   \n",
+       "21           NaN                    NaN             NaN             NaN   \n",
+       "22           NaN                    NaN             NaN             NaN   \n",
+       "23           NaN                    NaN             NaN             NaN   \n",
+       "24           NaN                    NaN             NaN             NaN   \n",
+       "25           NaN                    NaN             NaN             NaN   \n",
+       "26           NaN                    NaN             NaN             NaN   \n",
+       "27           NaN                    NaN             NaN             NaN   \n",
+       "28           NaN                    NaN             NaN             NaN   \n",
+       "29           NaN                    NaN             NaN             NaN   \n",
+       "...          ...                    ...             ...             ...   \n",
+       "111039       NaN                    NaN             NaN             NaN   \n",
+       "111040       NaN                    NaN             NaN             NaN   \n",
+       "111041       NaN                    NaN             NaN             NaN   \n",
+       "111042       NaN                    NaN             NaN             NaN   \n",
+       "111043       NaN                    NaN             NaN             NaN   \n",
+       "111044       NaN                    NaN             NaN             NaN   \n",
+       "111045       NaN                    NaN             NaN             NaN   \n",
+       "111046       NaN                    NaN             NaN             NaN   \n",
+       "111047       NaN                    NaN             NaN             NaN   \n",
+       "111048       NaN                    NaN             NaN             NaN   \n",
+       "111049       NaN                    NaN             NaN             NaN   \n",
+       "111050       NaN                    NaN             NaN             NaN   \n",
+       "111051       NaN                    NaN             NaN             NaN   \n",
+       "111052       NaN                    NaN             NaN             NaN   \n",
+       "111053       NaN                    NaN             NaN             NaN   \n",
+       "111054       NaN                    NaN             NaN             NaN   \n",
+       "111055       NaN                    NaN             NaN             NaN   \n",
+       "111056       NaN                    NaN             NaN             NaN   \n",
+       "111057       NaN                    NaN             NaN             NaN   \n",
+       "111058       NaN                    NaN             NaN             NaN   \n",
+       "111059       NaN                    NaN             NaN             NaN   \n",
+       "111060       NaN                    NaN             NaN             NaN   \n",
+       "111061       NaN                    NaN             NaN             NaN   \n",
+       "111062       NaN                    NaN             NaN             NaN   \n",
+       "111063       NaN                    NaN             NaN             NaN   \n",
+       "111064       NaN                    NaN             NaN             NaN   \n",
+       "111065       NaN                    NaN             NaN             NaN   \n",
+       "111066       NaN                    NaN             NaN             NaN   \n",
+       "111067       NaN                    NaN             NaN             NaN   \n",
+       "111068       NaN                    NaN             NaN             NaN   \n",
+       "\n",
+       "       Ferry Terminal Name   Latitude  Longitude  \\\n",
+       "0                      NaN  40.708275 -73.791604   \n",
+       "1                      NaN  40.721041 -73.909453   \n",
+       "2                      NaN  40.843330 -73.939144   \n",
+       "3                      NaN  40.778009 -73.980213   \n",
+       "4                      NaN  40.807691 -73.947387   \n",
+       "5                      NaN  40.749989 -73.881988   \n",
+       "6                      NaN  40.681533 -73.831737   \n",
+       "7                      NaN  40.671816 -73.843092   \n",
+       "8                      NaN  40.739913 -74.000790   \n",
+       "9                      NaN  40.668204 -73.950648   \n",
+       "10                     NaN  40.634378 -73.969462   \n",
+       "11                     NaN  40.730816 -73.986073   \n",
+       "12                     NaN  40.788974 -73.952259   \n",
+       "13                     NaN  40.891517 -73.836457   \n",
+       "14                     NaN  40.626477 -73.999218   \n",
+       "15                     NaN  40.796597 -73.970370   \n",
+       "16                     NaN  40.636182 -74.116150   \n",
+       "17                     NaN  40.632437 -73.888173   \n",
+       "18                     NaN        NaN        NaN   \n",
+       "19                     NaN  40.852058 -73.934776   \n",
+       "20                     NaN  40.673505 -73.951844   \n",
+       "21                     NaN  40.746194 -73.978769   \n",
+       "22                     NaN  40.692394 -73.833891   \n",
+       "23                     NaN  40.684944 -73.944221   \n",
+       "24                     NaN  40.607245 -74.061106   \n",
+       "25                     NaN  40.553421 -74.196743   \n",
+       "26                     NaN        NaN        NaN   \n",
+       "27                     NaN  40.803149 -73.964266   \n",
+       "28                     NaN  40.802390 -73.950526   \n",
+       "29                     NaN  40.517378 -74.203435   \n",
+       "...                    ...        ...        ...   \n",
+       "111039                 NaN  40.757248 -73.968286   \n",
+       "111040                 NaN  40.793635 -73.941649   \n",
+       "111041                 NaN  40.674249 -74.016558   \n",
+       "111042                 NaN  40.736304 -74.008299   \n",
+       "111043                 NaN  40.640139 -73.966847   \n",
+       "111044                 NaN  40.836532 -73.941018   \n",
+       "111045                 NaN  40.755980 -73.969171   \n",
+       "111046                 NaN  40.674249 -74.016558   \n",
+       "111047                 NaN  40.656160 -73.767353   \n",
+       "111048                 NaN  40.813339 -73.946328   \n",
+       "111049                 NaN  40.619601 -74.027826   \n",
+       "111050                 NaN  40.774612 -73.948085   \n",
+       "111051                 NaN  40.729531 -73.980416   \n",
+       "111052                 NaN  40.757069 -73.965933   \n",
+       "111053                 NaN  40.664353 -73.757556   \n",
+       "111054                 NaN  40.577515 -74.012207   \n",
+       "111055                 NaN  40.628381 -74.029040   \n",
+       "111056                 NaN  40.732250 -73.924513   \n",
+       "111057                 NaN  40.760116 -73.984836   \n",
+       "111058                 NaN  40.703365 -73.926345   \n",
+       "111059                 NaN  40.727251 -73.988660   \n",
+       "111060                 NaN  40.760405 -73.987474   \n",
+       "111061                 NaN  40.762279 -73.926013   \n",
+       "111062                 NaN  40.757069 -73.965933   \n",
+       "111063                 NaN  40.754662 -73.967992   \n",
+       "111064                 NaN        NaN        NaN   \n",
+       "111065                 NaN  40.656160 -73.767353   \n",
+       "111066                 NaN  40.740295 -73.976952   \n",
+       "111067                 NaN  40.640182 -73.955306   \n",
+       "111068                 NaN  40.640024 -73.900717   \n",
+       "\n",
+       "                                        Location  \n",
+       "0        (40.70827532593202, -73.79160395779721)  \n",
+       "1       (40.721040535628305, -73.90945306791765)  \n",
+       "2        (40.84332975466513, -73.93914371913482)  \n",
+       "3         (40.7780087446372, -73.98021349023975)  \n",
+       "4        (40.80769092704951, -73.94738703491433)  \n",
+       "5         (40.7499893014072, -73.88198770727831)  \n",
+       "6        (40.68153278675525, -73.83173699701601)  \n",
+       "7        (40.67181584567338, -73.84309181950769)  \n",
+       "8        (40.73991339303542, -74.00079028612932)  \n",
+       "9        (40.66820406598287, -73.95064760056546)  \n",
+       "10       (40.63437840816299, -73.96946177104543)  \n",
+       "11       (40.73081644089586, -73.98607265739876)  \n",
+       "12       (40.78897400211689, -73.95225898702977)  \n",
+       "13       (40.89151738488846, -73.83645714593568)  \n",
+       "14        (40.6264774690411, -73.99921826202639)  \n",
+       "15        (40.7965967075252, -73.97036973473399)  \n",
+       "16        (40.63618202176914, -74.1161500428337)  \n",
+       "17       (40.63243692394328, -73.88817263437012)  \n",
+       "18                                           NaN  \n",
+       "19       (40.85205827756883, -73.93477640780834)  \n",
+       "20       (40.67350473678714, -73.95184414979961)  \n",
+       "21       (40.74619417253121, -73.97876853124392)  \n",
+       "22        (40.69239424979043, -73.8338912453996)  \n",
+       "23        (40.6849442562592, -73.94422078036632)  \n",
+       "24       (40.60724493456944, -74.06110566015863)  \n",
+       "25       (40.55342078716953, -74.19674315017886)  \n",
+       "26                                           NaN  \n",
+       "27       (40.80314938553783, -73.96426608076082)  \n",
+       "28       (40.80238950799943, -73.95052644123253)  \n",
+       "29      (40.517377871705676, -74.20343466779575)  \n",
+       "...                                          ...  \n",
+       "111039  (40.757247604963055, -73.96828647941395)  \n",
+       "111040   (40.79363516179995, -73.94164859515777)  \n",
+       "111041    (40.6742492231181, -74.01655803856313)  \n",
+       "111042  (40.736303747410034, -74.00829935904578)  \n",
+       "111043   (40.64013899178716, -73.96684680242933)  \n",
+       "111044   (40.836532082987944, -73.9410182995914)  \n",
+       "111045   (40.75597977288785, -73.96917140638074)  \n",
+       "111046    (40.6742492231181, -74.01655803856313)  \n",
+       "111047  (40.656160351546845, -73.76735262738222)  \n",
+       "111048   (40.81333907832113, -73.94632769228208)  \n",
+       "111049  (40.619601147364584, -74.02782628492785)  \n",
+       "111050   (40.77461174278734, -73.94808472177321)  \n",
+       "111051   (40.72953107218499, -73.98041550317102)  \n",
+       "111052   (40.75706852462872, -73.96593314322774)  \n",
+       "111053    (40.6643525308449, -73.75755575708348)  \n",
+       "111054   (40.57751513866536, -74.01220705163807)  \n",
+       "111055   (40.62838143294541, -74.02904041333245)  \n",
+       "111056   (40.73225000573841, -73.92451289173367)  \n",
+       "111057   (40.76011648520396, -73.98483562074706)  \n",
+       "111058  (40.703365329011284, -73.92634531031759)  \n",
+       "111059  (40.727251287038676, -73.98866028603422)  \n",
+       "111060   (40.76040500039782, -73.98747426235285)  \n",
+       "111061  (40.762278541098084, -73.92601303458156)  \n",
+       "111062   (40.75706852462872, -73.96593314322774)  \n",
+       "111063   (40.75466197318078, -73.96799173864807)  \n",
+       "111064                                       NaN  \n",
+       "111065  (40.656160351546845, -73.76735262738222)  \n",
+       "111066  (40.740295354643706, -73.97695165980414)  \n",
+       "111067   (40.64018174662485, -73.95530566958138)  \n",
+       "111068  (40.640024057399216, -73.90071711703163)  \n",
+       "\n",
+       "[111069 rows x 52 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2.2 Selecting columns and rows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To select a column, we index with the name of the column, like this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0          Noise - Street/Sidewalk\n",
+       "1                  Illegal Parking\n",
+       "2               Noise - Commercial\n",
+       "3                  Noise - Vehicle\n",
+       "4                           Rodent\n",
+       "5               Noise - Commercial\n",
+       "6                 Blocked Driveway\n",
+       "7               Noise - Commercial\n",
+       "8               Noise - Commercial\n",
+       "9               Noise - Commercial\n",
+       "10        Noise - House of Worship\n",
+       "11              Noise - Commercial\n",
+       "12                 Illegal Parking\n",
+       "13                 Noise - Vehicle\n",
+       "14                          Rodent\n",
+       "15        Noise - House of Worship\n",
+       "16         Noise - Street/Sidewalk\n",
+       "17                 Illegal Parking\n",
+       "18          Street Light Condition\n",
+       "19              Noise - Commercial\n",
+       "20        Noise - House of Worship\n",
+       "21              Noise - Commercial\n",
+       "22                 Noise - Vehicle\n",
+       "23              Noise - Commercial\n",
+       "24                Blocked Driveway\n",
+       "25         Noise - Street/Sidewalk\n",
+       "26          Street Light Condition\n",
+       "27            Harboring Bees/Wasps\n",
+       "28         Noise - Street/Sidewalk\n",
+       "29          Street Light Condition\n",
+       "                    ...           \n",
+       "111039          Noise - Commercial\n",
+       "111040          Noise - Commercial\n",
+       "111041                       Noise\n",
+       "111042     Noise - Street/Sidewalk\n",
+       "111043          Noise - Commercial\n",
+       "111044     Noise - Street/Sidewalk\n",
+       "111045                Water System\n",
+       "111046                       Noise\n",
+       "111047             Illegal Parking\n",
+       "111048     Noise - Street/Sidewalk\n",
+       "111049          Noise - Commercial\n",
+       "111050                       Noise\n",
+       "111051          Noise - Commercial\n",
+       "111052                Water System\n",
+       "111053           Derelict Vehicles\n",
+       "111054     Noise - Street/Sidewalk\n",
+       "111055          Noise - Commercial\n",
+       "111056       Street Sign - Missing\n",
+       "111057                       Noise\n",
+       "111058          Noise - Commercial\n",
+       "111059     Noise - Street/Sidewalk\n",
+       "111060                       Noise\n",
+       "111061          Noise - Commercial\n",
+       "111062                Water System\n",
+       "111063                Water System\n",
+       "111064     Maintenance or Facility\n",
+       "111065             Illegal Parking\n",
+       "111066     Noise - Street/Sidewalk\n",
+       "111067          Noise - Commercial\n",
+       "111068            Blocked Driveway\n",
+       "Name: Complaint Type, Length: 111069, dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints['Complaint Type']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To get the first 5 rows of a dataframe, we can use a slice: `df[:5]`.\n",
+    "\n",
+    "This is a great way to get a sense for what kind of information is in the dataframe -- take a minute to look at the contents and get a feel for this dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unique Key</th>\n",
+       "      <th>Created Date</th>\n",
+       "      <th>Closed Date</th>\n",
+       "      <th>Agency</th>\n",
+       "      <th>Agency Name</th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Descriptor</th>\n",
+       "      <th>Location Type</th>\n",
+       "      <th>Incident Zip</th>\n",
+       "      <th>Incident Address</th>\n",
+       "      <th>Street Name</th>\n",
+       "      <th>Cross Street 1</th>\n",
+       "      <th>Cross Street 2</th>\n",
+       "      <th>Intersection Street 1</th>\n",
+       "      <th>Intersection Street 2</th>\n",
+       "      <th>Address Type</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Landmark</th>\n",
+       "      <th>Facility Type</th>\n",
+       "      <th>Status</th>\n",
+       "      <th>Due Date</th>\n",
+       "      <th>Resolution Action Updated Date</th>\n",
+       "      <th>Community Board</th>\n",
+       "      <th>Borough</th>\n",
+       "      <th>X Coordinate (State Plane)</th>\n",
+       "      <th>Y Coordinate (State Plane)</th>\n",
+       "      <th>Park Facility Name</th>\n",
+       "      <th>Park Borough</th>\n",
+       "      <th>School Name</th>\n",
+       "      <th>School Number</th>\n",
+       "      <th>School Region</th>\n",
+       "      <th>School Code</th>\n",
+       "      <th>School Phone Number</th>\n",
+       "      <th>School Address</th>\n",
+       "      <th>School City</th>\n",
+       "      <th>School State</th>\n",
+       "      <th>School Zip</th>\n",
+       "      <th>School Not Found</th>\n",
+       "      <th>School or Citywide Complaint</th>\n",
+       "      <th>Vehicle Type</th>\n",
+       "      <th>Taxi Company Borough</th>\n",
+       "      <th>Taxi Pick Up Location</th>\n",
+       "      <th>Bridge Highway Name</th>\n",
+       "      <th>Bridge Highway Direction</th>\n",
+       "      <th>Road Ramp</th>\n",
+       "      <th>Bridge Highway Segment</th>\n",
+       "      <th>Garage Lot Name</th>\n",
+       "      <th>Ferry Direction</th>\n",
+       "      <th>Ferry Terminal Name</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Location</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>26589651</td>\n",
+       "      <td>10/31/2013 02:08:41 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11432</td>\n",
+       "      <td>90-03 169 STREET</td>\n",
+       "      <td>169 STREET</td>\n",
+       "      <td>90 AVENUE</td>\n",
+       "      <td>91 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>JAMAICA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 10:08:41 AM</td>\n",
+       "      <td>10/31/2013 02:35:17 AM</td>\n",
+       "      <td>12 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1042027.0</td>\n",
+       "      <td>197389.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.708275</td>\n",
+       "      <td>-73.791604</td>\n",
+       "      <td>(40.70827532593202, -73.79160395779721)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>26593698</td>\n",
+       "      <td>10/31/2013 02:01:04 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Commercial Overnight Parking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11378</td>\n",
+       "      <td>58 AVENUE</td>\n",
+       "      <td>58 AVENUE</td>\n",
+       "      <td>58 PLACE</td>\n",
+       "      <td>59 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>MASPETH</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 10:01:04 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>05 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1009349.0</td>\n",
+       "      <td>201984.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.721041</td>\n",
+       "      <td>-73.909453</td>\n",
+       "      <td>(40.721040535628305, -73.90945306791765)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>26594139</td>\n",
+       "      <td>10/31/2013 02:00:24 AM</td>\n",
+       "      <td>10/31/2013 02:40:32 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10032</td>\n",
+       "      <td>4060 BROADWAY</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>WEST 171 STREET</td>\n",
+       "      <td>WEST 172 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 10:00:24 AM</td>\n",
+       "      <td>10/31/2013 02:39:42 AM</td>\n",
+       "      <td>12 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>1001088.0</td>\n",
+       "      <td>246531.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.843330</td>\n",
+       "      <td>-73.939144</td>\n",
+       "      <td>(40.84332975466513, -73.93914371913482)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>26595721</td>\n",
+       "      <td>10/31/2013 01:56:23 AM</td>\n",
+       "      <td>10/31/2013 02:21:48 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>Car/Truck Horn</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10023</td>\n",
+       "      <td>WEST 72 STREET</td>\n",
+       "      <td>WEST 72 STREET</td>\n",
+       "      <td>COLUMBUS AVENUE</td>\n",
+       "      <td>AMSTERDAM AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:56:23 AM</td>\n",
+       "      <td>10/31/2013 02:21:10 AM</td>\n",
+       "      <td>07 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>989730.0</td>\n",
+       "      <td>222727.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.778009</td>\n",
+       "      <td>-73.980213</td>\n",
+       "      <td>(40.7780087446372, -73.98021349023975)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>26590930</td>\n",
+       "      <td>10/31/2013 01:53:44 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOHMH</td>\n",
+       "      <td>Department of Health and Mental Hygiene</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Condition Attracting Rodents</td>\n",
+       "      <td>Vacant Lot</td>\n",
+       "      <td>10027</td>\n",
+       "      <td>WEST 124 STREET</td>\n",
+       "      <td>WEST 124 STREET</td>\n",
+       "      <td>LENOX AVENUE</td>\n",
+       "      <td>ADAM CLAYTON POWELL JR BOULEVARD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Pending</td>\n",
+       "      <td>11/30/2013 01:53:44 AM</td>\n",
+       "      <td>10/31/2013 01:59:54 AM</td>\n",
+       "      <td>10 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>998815.0</td>\n",
+       "      <td>233545.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.807691</td>\n",
+       "      <td>-73.947387</td>\n",
+       "      <td>(40.80769092704951, -73.94738703491433)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unique Key            Created Date             Closed Date Agency  \\\n",
+       "0    26589651  10/31/2013 02:08:41 AM                     NaN   NYPD   \n",
+       "1    26593698  10/31/2013 02:01:04 AM                     NaN   NYPD   \n",
+       "2    26594139  10/31/2013 02:00:24 AM  10/31/2013 02:40:32 AM   NYPD   \n",
+       "3    26595721  10/31/2013 01:56:23 AM  10/31/2013 02:21:48 AM   NYPD   \n",
+       "4    26590930  10/31/2013 01:53:44 AM                     NaN  DOHMH   \n",
+       "\n",
+       "                               Agency Name           Complaint Type  \\\n",
+       "0          New York City Police Department  Noise - Street/Sidewalk   \n",
+       "1          New York City Police Department          Illegal Parking   \n",
+       "2          New York City Police Department       Noise - Commercial   \n",
+       "3          New York City Police Department          Noise - Vehicle   \n",
+       "4  Department of Health and Mental Hygiene                   Rodent   \n",
+       "\n",
+       "                     Descriptor        Location Type Incident Zip  \\\n",
+       "0                  Loud Talking      Street/Sidewalk        11432   \n",
+       "1  Commercial Overnight Parking      Street/Sidewalk        11378   \n",
+       "2              Loud Music/Party  Club/Bar/Restaurant        10032   \n",
+       "3                Car/Truck Horn      Street/Sidewalk        10023   \n",
+       "4  Condition Attracting Rodents           Vacant Lot        10027   \n",
+       "\n",
+       "   Incident Address      Street Name   Cross Street 1  \\\n",
+       "0  90-03 169 STREET       169 STREET        90 AVENUE   \n",
+       "1         58 AVENUE        58 AVENUE         58 PLACE   \n",
+       "2     4060 BROADWAY         BROADWAY  WEST 171 STREET   \n",
+       "3    WEST 72 STREET   WEST 72 STREET  COLUMBUS AVENUE   \n",
+       "4   WEST 124 STREET  WEST 124 STREET     LENOX AVENUE   \n",
+       "\n",
+       "                     Cross Street 2 Intersection Street 1  \\\n",
+       "0                         91 AVENUE                   NaN   \n",
+       "1                         59 STREET                   NaN   \n",
+       "2                   WEST 172 STREET                   NaN   \n",
+       "3                  AMSTERDAM AVENUE                   NaN   \n",
+       "4  ADAM CLAYTON POWELL JR BOULEVARD                   NaN   \n",
+       "\n",
+       "  Intersection Street 2 Address Type      City Landmark Facility Type  \\\n",
+       "0                   NaN      ADDRESS   JAMAICA      NaN      Precinct   \n",
+       "1                   NaN    BLOCKFACE   MASPETH      NaN      Precinct   \n",
+       "2                   NaN      ADDRESS  NEW YORK      NaN      Precinct   \n",
+       "3                   NaN    BLOCKFACE  NEW YORK      NaN      Precinct   \n",
+       "4                   NaN    BLOCKFACE  NEW YORK      NaN           NaN   \n",
+       "\n",
+       "     Status                Due Date Resolution Action Updated Date  \\\n",
+       "0  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM   \n",
+       "1      Open  10/31/2013 10:01:04 AM                            NaN   \n",
+       "2    Closed  10/31/2013 10:00:24 AM         10/31/2013 02:39:42 AM   \n",
+       "3    Closed  10/31/2013 09:56:23 AM         10/31/2013 02:21:10 AM   \n",
+       "4   Pending  11/30/2013 01:53:44 AM         10/31/2013 01:59:54 AM   \n",
+       "\n",
+       "  Community Board    Borough  X Coordinate (State Plane)  \\\n",
+       "0       12 QUEENS     QUEENS                   1042027.0   \n",
+       "1       05 QUEENS     QUEENS                   1009349.0   \n",
+       "2    12 MANHATTAN  MANHATTAN                   1001088.0   \n",
+       "3    07 MANHATTAN  MANHATTAN                    989730.0   \n",
+       "4    10 MANHATTAN  MANHATTAN                    998815.0   \n",
+       "\n",
+       "   Y Coordinate (State Plane) Park Facility Name Park Borough  School Name  \\\n",
+       "0                    197389.0        Unspecified       QUEENS  Unspecified   \n",
+       "1                    201984.0        Unspecified       QUEENS  Unspecified   \n",
+       "2                    246531.0        Unspecified    MANHATTAN  Unspecified   \n",
+       "3                    222727.0        Unspecified    MANHATTAN  Unspecified   \n",
+       "4                    233545.0        Unspecified    MANHATTAN  Unspecified   \n",
+       "\n",
+       "  School Number School Region  School Code School Phone Number School Address  \\\n",
+       "0   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified   \n",
+       "1   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified   \n",
+       "2   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified   \n",
+       "3   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified   \n",
+       "4   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified   \n",
+       "\n",
+       "   School City School State   School Zip School Not Found  \\\n",
+       "0  Unspecified  Unspecified  Unspecified                N   \n",
+       "1  Unspecified  Unspecified  Unspecified                N   \n",
+       "2  Unspecified  Unspecified  Unspecified                N   \n",
+       "3  Unspecified  Unspecified  Unspecified                N   \n",
+       "4  Unspecified  Unspecified  Unspecified                N   \n",
+       "\n",
+       "   School or Citywide Complaint Vehicle Type Taxi Company Borough  \\\n",
+       "0                           NaN          NaN                  NaN   \n",
+       "1                           NaN          NaN                  NaN   \n",
+       "2                           NaN          NaN                  NaN   \n",
+       "3                           NaN          NaN                  NaN   \n",
+       "4                           NaN          NaN                  NaN   \n",
+       "\n",
+       "  Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction  \\\n",
+       "0                   NaN                 NaN                      NaN   \n",
+       "1                   NaN                 NaN                      NaN   \n",
+       "2                   NaN                 NaN                      NaN   \n",
+       "3                   NaN                 NaN                      NaN   \n",
+       "4                   NaN                 NaN                      NaN   \n",
+       "\n",
+       "  Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction  \\\n",
+       "0       NaN                    NaN             NaN             NaN   \n",
+       "1       NaN                    NaN             NaN             NaN   \n",
+       "2       NaN                    NaN             NaN             NaN   \n",
+       "3       NaN                    NaN             NaN             NaN   \n",
+       "4       NaN                    NaN             NaN             NaN   \n",
+       "\n",
+       "  Ferry Terminal Name   Latitude  Longitude  \\\n",
+       "0                 NaN  40.708275 -73.791604   \n",
+       "1                 NaN  40.721041 -73.909453   \n",
+       "2                 NaN  40.843330 -73.939144   \n",
+       "3                 NaN  40.778009 -73.980213   \n",
+       "4                 NaN  40.807691 -73.947387   \n",
+       "\n",
+       "                                   Location  \n",
+       "0   (40.70827532593202, -73.79160395779721)  \n",
+       "1  (40.721040535628305, -73.90945306791765)  \n",
+       "2   (40.84332975466513, -73.93914371913482)  \n",
+       "3    (40.7780087446372, -73.98021349023975)  \n",
+       "4   (40.80769092704951, -73.94738703491433)  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can combine these to get the first 5 rows of a column:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    Noise - Street/Sidewalk\n",
+       "1            Illegal Parking\n",
+       "2         Noise - Commercial\n",
+       "3            Noise - Vehicle\n",
+       "4                     Rodent\n",
+       "Name: Complaint Type, dtype: object"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints['Complaint Type'][:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "and it doesn't matter which direction we do it in:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    Noise - Street/Sidewalk\n",
+       "1            Illegal Parking\n",
+       "2         Noise - Commercial\n",
+       "3            Noise - Vehicle\n",
+       "4                     Rodent\n",
+       "Name: Complaint Type, dtype: object"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[:5]['Complaint Type']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2.3 Selecting multiple columns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What if we just want to know the complaint type and the borough, but not the rest of the information? Pandas makes it really easy to select a subset of the columns: just index with list of columns you want."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Borough</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Noise - House of Worship</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>BRONX</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Noise - House of Worship</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Street Light Condition</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>Noise - House of Worship</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>Street Light Condition</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>Harboring Bees/Wasps</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Street Light Condition</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111039</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111040</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111041</th>\n",
+       "      <td>Noise</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111042</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111043</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111044</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111045</th>\n",
+       "      <td>Water System</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111046</th>\n",
+       "      <td>Noise</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111047</th>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111048</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111049</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111050</th>\n",
+       "      <td>Noise</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111051</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111052</th>\n",
+       "      <td>Water System</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111053</th>\n",
+       "      <td>Derelict Vehicles</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111054</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111055</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111056</th>\n",
+       "      <td>Street Sign - Missing</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111057</th>\n",
+       "      <td>Noise</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111058</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111059</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111060</th>\n",
+       "      <td>Noise</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111061</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111062</th>\n",
+       "      <td>Water System</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111063</th>\n",
+       "      <td>Water System</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111064</th>\n",
+       "      <td>Maintenance or Facility</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111065</th>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111066</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111067</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111068</th>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>111069 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Complaint Type        Borough\n",
+       "0        Noise - Street/Sidewalk         QUEENS\n",
+       "1                Illegal Parking         QUEENS\n",
+       "2             Noise - Commercial      MANHATTAN\n",
+       "3                Noise - Vehicle      MANHATTAN\n",
+       "4                         Rodent      MANHATTAN\n",
+       "5             Noise - Commercial         QUEENS\n",
+       "6               Blocked Driveway         QUEENS\n",
+       "7             Noise - Commercial         QUEENS\n",
+       "8             Noise - Commercial      MANHATTAN\n",
+       "9             Noise - Commercial       BROOKLYN\n",
+       "10      Noise - House of Worship       BROOKLYN\n",
+       "11            Noise - Commercial      MANHATTAN\n",
+       "12               Illegal Parking      MANHATTAN\n",
+       "13               Noise - Vehicle          BRONX\n",
+       "14                        Rodent       BROOKLYN\n",
+       "15      Noise - House of Worship      MANHATTAN\n",
+       "16       Noise - Street/Sidewalk  STATEN ISLAND\n",
+       "17               Illegal Parking       BROOKLYN\n",
+       "18        Street Light Condition       BROOKLYN\n",
+       "19            Noise - Commercial      MANHATTAN\n",
+       "20      Noise - House of Worship       BROOKLYN\n",
+       "21            Noise - Commercial      MANHATTAN\n",
+       "22               Noise - Vehicle         QUEENS\n",
+       "23            Noise - Commercial       BROOKLYN\n",
+       "24              Blocked Driveway  STATEN ISLAND\n",
+       "25       Noise - Street/Sidewalk  STATEN ISLAND\n",
+       "26        Street Light Condition       BROOKLYN\n",
+       "27          Harboring Bees/Wasps      MANHATTAN\n",
+       "28       Noise - Street/Sidewalk      MANHATTAN\n",
+       "29        Street Light Condition  STATEN ISLAND\n",
+       "...                          ...            ...\n",
+       "111039        Noise - Commercial      MANHATTAN\n",
+       "111040        Noise - Commercial      MANHATTAN\n",
+       "111041                     Noise       BROOKLYN\n",
+       "111042   Noise - Street/Sidewalk      MANHATTAN\n",
+       "111043        Noise - Commercial       BROOKLYN\n",
+       "111044   Noise - Street/Sidewalk      MANHATTAN\n",
+       "111045              Water System      MANHATTAN\n",
+       "111046                     Noise       BROOKLYN\n",
+       "111047           Illegal Parking         QUEENS\n",
+       "111048   Noise - Street/Sidewalk      MANHATTAN\n",
+       "111049        Noise - Commercial       BROOKLYN\n",
+       "111050                     Noise      MANHATTAN\n",
+       "111051        Noise - Commercial      MANHATTAN\n",
+       "111052              Water System      MANHATTAN\n",
+       "111053         Derelict Vehicles         QUEENS\n",
+       "111054   Noise - Street/Sidewalk       BROOKLYN\n",
+       "111055        Noise - Commercial       BROOKLYN\n",
+       "111056     Street Sign - Missing         QUEENS\n",
+       "111057                     Noise      MANHATTAN\n",
+       "111058        Noise - Commercial       BROOKLYN\n",
+       "111059   Noise - Street/Sidewalk      MANHATTAN\n",
+       "111060                     Noise      MANHATTAN\n",
+       "111061        Noise - Commercial         QUEENS\n",
+       "111062              Water System      MANHATTAN\n",
+       "111063              Water System      MANHATTAN\n",
+       "111064   Maintenance or Facility       BROOKLYN\n",
+       "111065           Illegal Parking         QUEENS\n",
+       "111066   Noise - Street/Sidewalk      MANHATTAN\n",
+       "111067        Noise - Commercial       BROOKLYN\n",
+       "111068          Blocked Driveway       BROOKLYN\n",
+       "\n",
+       "[111069 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[['Complaint Type', 'Borough']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That showed us a summary, and then we can look at the first 10 rows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Borough</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Blocked Driveway</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>QUEENS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Complaint Type    Borough\n",
+       "0  Noise - Street/Sidewalk     QUEENS\n",
+       "1          Illegal Parking     QUEENS\n",
+       "2       Noise - Commercial  MANHATTAN\n",
+       "3          Noise - Vehicle  MANHATTAN\n",
+       "4                   Rodent  MANHATTAN\n",
+       "5       Noise - Commercial     QUEENS\n",
+       "6         Blocked Driveway     QUEENS\n",
+       "7       Noise - Commercial     QUEENS\n",
+       "8       Noise - Commercial  MANHATTAN\n",
+       "9       Noise - Commercial   BROOKLYN"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[['Complaint Type', 'Borough']][:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2.4 What's the most common complaint type?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a really easy question to answer! There's a `.value_counts()` method that we can use:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "HEATING                                 14200\n",
+       "GENERAL CONSTRUCTION                     7471\n",
+       "Street Light Condition                   7117\n",
+       "DOF Literature Request                   5797\n",
+       "PLUMBING                                 5373\n",
+       "PAINT - PLASTER                          5149\n",
+       "Blocked Driveway                         4590\n",
+       "NONCONST                                 3998\n",
+       "Street Condition                         3473\n",
+       "Illegal Parking                          3343\n",
+       "Noise                                    3321\n",
+       "Traffic Signal Condition                 3145\n",
+       "Dirty Conditions                         2653\n",
+       "Water System                             2636\n",
+       "Noise - Commercial                       2578\n",
+       "ELECTRIC                                 2350\n",
+       "Broken Muni Meter                        2070\n",
+       "Noise - Street/Sidewalk                  1928\n",
+       "Sanitation Condition                     1824\n",
+       "Rodent                                   1632\n",
+       "Sewer                                    1627\n",
+       "Taxi Complaint                           1227\n",
+       "Consumer Complaint                       1227\n",
+       "Damaged Tree                             1180\n",
+       "Overgrown Tree/Branches                  1083\n",
+       "Graffiti                                  973\n",
+       "Missed Collection (All Materials)         973\n",
+       "Building/Use                              942\n",
+       "Root/Sewer/Sidewalk Condition             836\n",
+       "Derelict Vehicle                          803\n",
+       "                                        ...  \n",
+       "Posting Advertisement                       5\n",
+       "Internal Code                               5\n",
+       "Miscellaneous Categories                    5\n",
+       "Fire Alarm - Modification                   5\n",
+       "Poison Ivy                                  5\n",
+       "Special Natural Area District (SNAD)        4\n",
+       "Transportation Provider Complaint           4\n",
+       "Illegal Animal Sold                         4\n",
+       "Ferry Complaint                             4\n",
+       "Adopt-A-Basket                              3\n",
+       "Illegal Fireworks                           3\n",
+       "Fire Alarm - Replacement                    3\n",
+       "Invitation                                  3\n",
+       "Window Guard                                2\n",
+       "Misc. Comments                              2\n",
+       "DFTA Literature Request                     2\n",
+       "Legal Services Provider Complaint           2\n",
+       "Opinion for the Mayor                       2\n",
+       "Public Assembly                             2\n",
+       "Snow                                        1\n",
+       "DWD                                         1\n",
+       "Municipal Parking Facility                  1\n",
+       "Open Flame Permit                           1\n",
+       "Highway Sign - Damaged                      1\n",
+       "Stalled Sites                               1\n",
+       "Trans Fat                                   1\n",
+       "DHS Income Savings Requirement              1\n",
+       "X-Ray Machine/Equipment                     1\n",
+       "Ferry Permit                                1\n",
+       "Tunnel Condition                            1\n",
+       "Name: Complaint Type, Length: 165, dtype: int64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints['Complaint Type'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we just wanted the top 10 most common complaints, we can do this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "HEATING                   14200\n",
+       "GENERAL CONSTRUCTION       7471\n",
+       "Street Light Condition     7117\n",
+       "DOF Literature Request     5797\n",
+       "PLUMBING                   5373\n",
+       "PAINT - PLASTER            5149\n",
+       "Blocked Driveway           4590\n",
+       "NONCONST                   3998\n",
+       "Street Condition           3473\n",
+       "Illegal Parking            3343\n",
+       "Name: Complaint Type, dtype: int64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaint_counts = complaints['Complaint Type'].value_counts()\n",
+    "complaint_counts[:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "But it gets better! We can plot them!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f56f7b48160>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "complaint_counts[:10].plot(kind='bar')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<style>\n",
+    "    @font-face {\n",
+    "        font-family: \"Computer Modern\";\n",
+    "        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
+    "    }\n",
+    "    div.cell{\n",
+    "        width:800px;\n",
+    "        margin-left:16% !important;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    h1 {\n",
+    "        font-family: Helvetica, serif;\n",
+    "    }\n",
+    "    h4{\n",
+    "        margin-top:12px;\n",
+    "        margin-bottom: 3px;\n",
+    "       }\n",
+    "    div.text_cell_render{\n",
+    "        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
+    "        line-height: 145%;\n",
+    "        font-size: 130%;\n",
+    "        width:800px;\n",
+    "        margin-left:auto;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    .CodeMirror{\n",
+    "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
+    "    }\n",
+    "    .text_cell_render h5 {\n",
+    "        font-weight: 300;\n",
+    "        font-size: 22pt;\n",
+    "        color: #4057A1;\n",
+    "        font-style: italic;\n",
+    "        margin-bottom: .5em;\n",
+    "        margin-top: 0.5em;\n",
+    "        display: block;\n",
+    "    }\n",
+    "    \n",
+    "    .warning{\n",
+    "        color: rgb( 240, 20, 20 )\n",
+    "        }  "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/cookbook/Chapter 3 - Which borough has the most noise complaints (or, more selecting data).ipynb b/cookbook/Chapter 3 - Which borough has the most noise complaints (or, more selecting data).ipynb
index ed1738a66..289b20c8a 100644
--- a/cookbook/Chapter 3 - Which borough has the most noise complaints (or, more selecting data).ipynb	
+++ b/cookbook/Chapter 3 - Which borough has the most noise complaints (or, more selecting data).ipynb	
@@ -1 +1,1654 @@
-{"nbformat": 4, "metadata": {"orig_nbformat": 3}, "cells": [{"cell_type": "code", "execution_count": 11, "outputs": [], "source": "# The usual preamble\n%matplotlib inline\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# Make the graphs a bit prettier, and bigger\npd.set_option('display.mpl_style', 'default')\nplt.rcParams['figure.figsize'] = (15, 5)\n\n\n# This is necessary to show lots of columns in pandas 0.12. \n# Not necessary in pandas 0.13.\npd.set_option('display.width', 5000) \npd.set_option('display.max_columns', 60)", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Let's continue with our NYC 311 service requests example.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 12, "outputs": [], "source": "complaints = pd.read_csv('../data/311-service-requests.csv')", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 3.1 Selecting only noise complaints", "cell_type": "markdown", "metadata": {}}, {"source": "I'd like to know which borough has the most noise complaints. First, we'll take a look at the data to see what it looks like:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 13, "outputs": [{"execution_count": 13, "output_type": "execute_result", "data": {"text/plain": "   Unique Key            Created Date             Closed Date Agency                              Agency Name           Complaint Type                    Descriptor        Location Type Incident Zip  Incident Address      Street Name   Cross Street 1                    Cross Street 2 Intersection Street 1 Intersection Street 2 Address Type      City Landmark Facility Type    Status                Due Date Resolution Action Updated Date Community Board    Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n0    26589651  10/31/2013 02:08:41 AM                     NaN   NYPD          New York City Police Department  Noise - Street/Sidewalk                  Loud Talking      Street/Sidewalk        11432  90-03 169 STREET       169 STREET        90 AVENUE                         91 AVENUE                   NaN                   NaN      ADDRESS   JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM       12 QUEENS     QUEENS                     1042027                      197389        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604   (40.70827532593202, -73.79160395779721)\n1    26593698  10/31/2013 02:01:04 AM                     NaN   NYPD          New York City Police Department          Illegal Parking  Commercial Overnight Parking      Street/Sidewalk        11378         58 AVENUE        58 AVENUE         58 PLACE                         59 STREET                   NaN                   NaN    BLOCKFACE   MASPETH      NaN      Precinct      Open  10/31/2013 10:01:04 AM                            NaN       05 QUEENS     QUEENS                     1009349                      201984        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.721041 -73.909453  (40.721040535628305, -73.90945306791765)\n2    26594139  10/31/2013 02:00:24 AM  10/31/2013 02:40:32 AM   NYPD          New York City Police Department       Noise - Commercial              Loud Music/Party  Club/Bar/Restaurant        10032     4060 BROADWAY         BROADWAY  WEST 171 STREET                   WEST 172 STREET                   NaN                   NaN      ADDRESS  NEW YORK      NaN      Precinct    Closed  10/31/2013 10:00:24 AM         10/31/2013 02:39:42 AM    12 MANHATTAN  MANHATTAN                     1001088                      246531        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.843330 -73.939144   (40.84332975466513, -73.93914371913482)\n3    26595721  10/31/2013 01:56:23 AM  10/31/2013 02:21:48 AM   NYPD          New York City Police Department          Noise - Vehicle                Car/Truck Horn      Street/Sidewalk        10023    WEST 72 STREET   WEST 72 STREET  COLUMBUS AVENUE                  AMSTERDAM AVENUE                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN      Precinct    Closed  10/31/2013 09:56:23 AM         10/31/2013 02:21:10 AM    07 MANHATTAN  MANHATTAN                      989730                      222727        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.778009 -73.980213    (40.7780087446372, -73.98021349023975)\n4    26590930  10/31/2013 01:53:44 AM                     NaN  DOHMH  Department of Health and Mental Hygiene                   Rodent  Condition Attracting Rodents           Vacant Lot        10027   WEST 124 STREET  WEST 124 STREET     LENOX AVENUE  ADAM CLAYTON POWELL JR BOULEVARD                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN           NaN   Pending  11/30/2013 01:53:44 AM         10/31/2013 01:59:54 AM    10 MANHATTAN  MANHATTAN                      998815                      233545        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.807691 -73.947387   (40.80769092704951, -73.94738703491433)\n\n[5 rows x 52 columns]", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unique Key</th>\n      <th>Created Date</th>\n      <th>Closed Date</th>\n      <th>Agency</th>\n      <th>Agency Name</th>\n      <th>Complaint Type</th>\n      <th>Descriptor</th>\n      <th>Location Type</th>\n      <th>Incident Zip</th>\n      <th>Incident Address</th>\n      <th>Street Name</th>\n      <th>Cross Street 1</th>\n      <th>Cross Street 2</th>\n      <th>Intersection Street 1</th>\n      <th>Intersection Street 2</th>\n      <th>Address Type</th>\n      <th>City</th>\n      <th>Landmark</th>\n      <th>Facility Type</th>\n      <th>Status</th>\n      <th>Due Date</th>\n      <th>Resolution Action Updated Date</th>\n      <th>Community Board</th>\n      <th>Borough</th>\n      <th>X Coordinate (State Plane)</th>\n      <th>Y Coordinate (State Plane)</th>\n      <th>Park Facility Name</th>\n      <th>Park Borough</th>\n      <th>School Name</th>\n      <th>School Number</th>\n      <th>School Region</th>\n      <th>School Code</th>\n      <th>School Phone Number</th>\n      <th>School Address</th>\n      <th>School City</th>\n      <th>School State</th>\n      <th>School Zip</th>\n      <th>School Not Found</th>\n      <th>School or Citywide Complaint</th>\n      <th>Vehicle Type</th>\n      <th>Taxi Company Borough</th>\n      <th>Taxi Pick Up Location</th>\n      <th>Bridge Highway Name</th>\n      <th>Bridge Highway Direction</th>\n      <th>Road Ramp</th>\n      <th>Bridge Highway Segment</th>\n      <th>Garage Lot Name</th>\n      <th>Ferry Direction</th>\n      <th>Ferry Terminal Name</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Location</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td> 26589651</td>\n      <td> 10/31/2013 02:08:41 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td>                 Loud Talking</td>\n      <td>     Street/Sidewalk</td>\n      <td> 11432</td>\n      <td> 90-03 169 STREET</td>\n      <td>      169 STREET</td>\n      <td>       90 AVENUE</td>\n      <td>                        91 AVENUE</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   ADDRESS</td>\n      <td>  JAMAICA</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 10:08:41 AM</td>\n      <td> 10/31/2013 02:35:17 AM</td>\n      <td>    12 QUEENS</td>\n      <td>    QUEENS</td>\n      <td> 1042027</td>\n      <td> 197389</td>\n      <td> Unspecified</td>\n      <td>    QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.708275</td>\n      <td>-73.791604</td>\n      <td>  (40.70827532593202, -73.79160395779721)</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td> 26593698</td>\n      <td> 10/31/2013 02:01:04 AM</td>\n      <td>                    NaN</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td>         Illegal Parking</td>\n      <td> Commercial Overnight Parking</td>\n      <td>     Street/Sidewalk</td>\n      <td> 11378</td>\n      <td>        58 AVENUE</td>\n      <td>       58 AVENUE</td>\n      <td>        58 PLACE</td>\n      <td>                        59 STREET</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> BLOCKFACE</td>\n      <td>  MASPETH</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>     Open</td>\n      <td> 10/31/2013 10:01:04 AM</td>\n      <td>                    NaN</td>\n      <td>    05 QUEENS</td>\n      <td>    QUEENS</td>\n      <td> 1009349</td>\n      <td> 201984</td>\n      <td> Unspecified</td>\n      <td>    QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.721041</td>\n      <td>-73.909453</td>\n      <td> (40.721040535628305, -73.90945306791765)</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td> 26594139</td>\n      <td> 10/31/2013 02:00:24 AM</td>\n      <td> 10/31/2013 02:40:32 AM</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td>      Noise - Commercial</td>\n      <td>             Loud Music/Party</td>\n      <td> Club/Bar/Restaurant</td>\n      <td> 10032</td>\n      <td>    4060 BROADWAY</td>\n      <td>        BROADWAY</td>\n      <td> WEST 171 STREET</td>\n      <td>                  WEST 172 STREET</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td>   ADDRESS</td>\n      <td> NEW YORK</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 10:00:24 AM</td>\n      <td> 10/31/2013 02:39:42 AM</td>\n      <td> 12 MANHATTAN</td>\n      <td> MANHATTAN</td>\n      <td> 1001088</td>\n      <td> 246531</td>\n      <td> Unspecified</td>\n      <td> MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.843330</td>\n      <td>-73.939144</td>\n      <td>  (40.84332975466513, -73.93914371913482)</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td> 26595721</td>\n      <td> 10/31/2013 01:56:23 AM</td>\n      <td> 10/31/2013 02:21:48 AM</td>\n      <td>  NYPD</td>\n      <td>         New York City Police Department</td>\n      <td>         Noise - Vehicle</td>\n      <td>               Car/Truck Horn</td>\n      <td>     Street/Sidewalk</td>\n      <td> 10023</td>\n      <td>   WEST 72 STREET</td>\n      <td>  WEST 72 STREET</td>\n      <td> COLUMBUS AVENUE</td>\n      <td>                 AMSTERDAM AVENUE</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> BLOCKFACE</td>\n      <td> NEW YORK</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 09:56:23 AM</td>\n      <td> 10/31/2013 02:21:10 AM</td>\n      <td> 07 MANHATTAN</td>\n      <td> MANHATTAN</td>\n      <td>  989730</td>\n      <td> 222727</td>\n      <td> Unspecified</td>\n      <td> MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.778009</td>\n      <td>-73.980213</td>\n      <td>   (40.7780087446372, -73.98021349023975)</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td> 26590930</td>\n      <td> 10/31/2013 01:53:44 AM</td>\n      <td>                    NaN</td>\n      <td> DOHMH</td>\n      <td> Department of Health and Mental Hygiene</td>\n      <td>                  Rodent</td>\n      <td> Condition Attracting Rodents</td>\n      <td>          Vacant Lot</td>\n      <td> 10027</td>\n      <td>  WEST 124 STREET</td>\n      <td> WEST 124 STREET</td>\n      <td>    LENOX AVENUE</td>\n      <td> ADAM CLAYTON POWELL JR BOULEVARD</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> BLOCKFACE</td>\n      <td> NEW YORK</td>\n      <td> NaN</td>\n      <td>      NaN</td>\n      <td>  Pending</td>\n      <td> 11/30/2013 01:53:44 AM</td>\n      <td> 10/31/2013 01:59:54 AM</td>\n      <td> 10 MANHATTAN</td>\n      <td> MANHATTAN</td>\n      <td>  998815</td>\n      <td> 233545</td>\n      <td> Unspecified</td>\n      <td> MANHATTAN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.807691</td>\n      <td>-73.947387</td>\n      <td>  (40.80769092704951, -73.94738703491433)</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows \u00d7 52 columns</p>\n</div>"}, "metadata": {}}], "source": "complaints[:5]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "To get the noise complaints, we need to find the rows where the \"Complaint Type\" column is \"Noise - Street/Sidewalk\". I'll show you how to do that, and then explain what's going on.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 14, "outputs": [{"execution_count": 14, "output_type": "execute_result", "data": {"text/plain": "    Unique Key            Created Date             Closed Date Agency                      Agency Name           Complaint Type        Descriptor    Location Type Incident Zip     Incident Address      Street Name    Cross Street 1 Cross Street 2 Intersection Street 1 Intersection Street 2 Address Type           City Landmark Facility Type    Status                Due Date Resolution Action Updated Date   Community Board        Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name   Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                 Location\n0     26589651  10/31/2013 02:08:41 AM                     NaN   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        11432     90-03 169 STREET       169 STREET         90 AVENUE      91 AVENUE                   NaN                   NaN      ADDRESS        JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM         12 QUEENS         QUEENS                     1042027                      197389        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604  (40.70827532593202, -73.79160395779721)\n16    26594086  10/31/2013 12:54:03 AM  10/31/2013 02:16:39 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        10310  173 CAMPBELL AVENUE  CAMPBELL AVENUE  HENDERSON AVENUE   WINEGAR LANE                   NaN                   NaN      ADDRESS  STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:54:03 AM         10/31/2013 02:07:14 AM  01 STATEN ISLAND  STATEN ISLAND                      952013                      171076        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.636182 -74.116150   (40.63618202176914, -74.1161500428337)\n25    26591573  10/31/2013 12:35:18 AM  10/31/2013 02:41:35 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        10312    24 PRINCETON LANE   PRINCETON LANE     HAMPTON GREEN       DEAD END                   NaN                   NaN      ADDRESS  STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:35:18 AM         10/31/2013 01:45:17 AM  03 STATEN ISLAND  STATEN ISLAND                      929577                      140964        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.553421 -74.196743  (40.55342078716953, -74.19674315017886)\n\n[3 rows x 52 columns]", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unique Key</th>\n      <th>Created Date</th>\n      <th>Closed Date</th>\n      <th>Agency</th>\n      <th>Agency Name</th>\n      <th>Complaint Type</th>\n      <th>Descriptor</th>\n      <th>Location Type</th>\n      <th>Incident Zip</th>\n      <th>Incident Address</th>\n      <th>Street Name</th>\n      <th>Cross Street 1</th>\n      <th>Cross Street 2</th>\n      <th>Intersection Street 1</th>\n      <th>Intersection Street 2</th>\n      <th>Address Type</th>\n      <th>City</th>\n      <th>Landmark</th>\n      <th>Facility Type</th>\n      <th>Status</th>\n      <th>Due Date</th>\n      <th>Resolution Action Updated Date</th>\n      <th>Community Board</th>\n      <th>Borough</th>\n      <th>X Coordinate (State Plane)</th>\n      <th>Y Coordinate (State Plane)</th>\n      <th>Park Facility Name</th>\n      <th>Park Borough</th>\n      <th>School Name</th>\n      <th>School Number</th>\n      <th>School Region</th>\n      <th>School Code</th>\n      <th>School Phone Number</th>\n      <th>School Address</th>\n      <th>School City</th>\n      <th>School State</th>\n      <th>School Zip</th>\n      <th>School Not Found</th>\n      <th>School or Citywide Complaint</th>\n      <th>Vehicle Type</th>\n      <th>Taxi Company Borough</th>\n      <th>Taxi Pick Up Location</th>\n      <th>Bridge Highway Name</th>\n      <th>Bridge Highway Direction</th>\n      <th>Road Ramp</th>\n      <th>Bridge Highway Segment</th>\n      <th>Garage Lot Name</th>\n      <th>Ferry Direction</th>\n      <th>Ferry Terminal Name</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Location</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0 </th>\n      <td> 26589651</td>\n      <td> 10/31/2013 02:08:41 AM</td>\n      <td>                    NaN</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td>     Loud Talking</td>\n      <td> Street/Sidewalk</td>\n      <td> 11432</td>\n      <td>    90-03 169 STREET</td>\n      <td>      169 STREET</td>\n      <td>        90 AVENUE</td>\n      <td>    91 AVENUE</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> ADDRESS</td>\n      <td>       JAMAICA</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Assigned</td>\n      <td> 10/31/2013 10:08:41 AM</td>\n      <td> 10/31/2013 02:35:17 AM</td>\n      <td>        12 QUEENS</td>\n      <td>        QUEENS</td>\n      <td> 1042027</td>\n      <td> 197389</td>\n      <td> Unspecified</td>\n      <td>        QUEENS</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.708275</td>\n      <td>-73.791604</td>\n      <td> (40.70827532593202, -73.79160395779721)</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td> 26594086</td>\n      <td> 10/31/2013 12:54:03 AM</td>\n      <td> 10/31/2013 02:16:39 AM</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td> Loud Music/Party</td>\n      <td> Street/Sidewalk</td>\n      <td> 10310</td>\n      <td> 173 CAMPBELL AVENUE</td>\n      <td> CAMPBELL AVENUE</td>\n      <td> HENDERSON AVENUE</td>\n      <td> WINEGAR LANE</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> ADDRESS</td>\n      <td> STATEN ISLAND</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:54:03 AM</td>\n      <td> 10/31/2013 02:07:14 AM</td>\n      <td> 01 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  952013</td>\n      <td> 171076</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.636182</td>\n      <td>-74.116150</td>\n      <td>  (40.63618202176914, -74.1161500428337)</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td> 26591573</td>\n      <td> 10/31/2013 12:35:18 AM</td>\n      <td> 10/31/2013 02:41:35 AM</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td>     Loud Talking</td>\n      <td> Street/Sidewalk</td>\n      <td> 10312</td>\n      <td>   24 PRINCETON LANE</td>\n      <td>  PRINCETON LANE</td>\n      <td>    HAMPTON GREEN</td>\n      <td>     DEAD END</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> ADDRESS</td>\n      <td> STATEN ISLAND</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Closed</td>\n      <td> 10/31/2013 08:35:18 AM</td>\n      <td> 10/31/2013 01:45:17 AM</td>\n      <td> 03 STATEN ISLAND</td>\n      <td> STATEN ISLAND</td>\n      <td>  929577</td>\n      <td> 140964</td>\n      <td> Unspecified</td>\n      <td> STATEN ISLAND</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.553421</td>\n      <td>-74.196743</td>\n      <td> (40.55342078716953, -74.19674315017886)</td>\n    </tr>\n  </tbody>\n</table>\n<p>3 rows \u00d7 52 columns</p>\n</div>"}, "metadata": {}}], "source": "noise_complaints = complaints[complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"]\nnoise_complaints[:3]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "If you look at `noise_complaints`, you'll see that this worked, and it only contains complaints with the right complaint type. But how does this work? Let's deconstruct it into two pieces", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 15, "outputs": [{"execution_count": 15, "output_type": "execute_result", "data": {"text/plain": "0      True\n1     False\n2     False\n3     False\n4     False\n5     False\n6     False\n7     False\n8     False\n9     False\n10    False\n11    False\n12    False\n13    False\n14    False\n...\n111054     True\n111055    False\n111056    False\n111057    False\n111058    False\n111059     True\n111060    False\n111061    False\n111062    False\n111063    False\n111064    False\n111065    False\n111066     True\n111067    False\n111068    False\nName: Complaint Type, Length: 111069, dtype: bool"}, "metadata": {}}], "source": "complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"", "metadata": {"collapsed": false, "trusted": false}}, {"source": "This is a big array of `True`s and `False`s, one for each row in our dataframe. When we index our dataframe with this array, we get just the rows where our boolean array evaluated to `True`.  It's important to note that for row filtering by a boolean array the length of our dataframe's index must be the same length as the boolean array used for filtering.\n\nYou can also combine more than one condition with the `&` operator like this:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 16, "outputs": [{"execution_count": 16, "output_type": "execute_result", "data": {"text/plain": "     Unique Key            Created Date             Closed Date Agency                      Agency Name           Complaint Type        Descriptor    Location Type Incident Zip    Incident Address      Street Name     Cross Street 1  Cross Street 2 Intersection Street 1 Intersection Street 2  Address Type      City Landmark Facility Type  Status                Due Date Resolution Action Updated Date Community Board   Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n31     26595564  10/31/2013 12:30:36 AM                     NaN   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        11236            AVENUE J         AVENUE J     EAST 80 STREET  EAST 81 STREET                   NaN                   NaN     BLOCKFACE  BROOKLYN      NaN      Precinct    Open  10/31/2013 08:30:36 AM                            NaN     18 BROOKLYN  BROOKLYN                     1008937                      170310        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.634104 -73.911055  (40.634103775951736, -73.91105541883589)\n49     26595553  10/31/2013 12:05:10 AM  10/31/2013 02:43:43 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        11225  25 LEFFERTS AVENUE  LEFFERTS AVENUE  WASHINGTON AVENUE  BEDFORD AVENUE                   NaN                   NaN       ADDRESS  BROOKLYN      NaN      Precinct  Closed  10/31/2013 08:05:10 AM         10/31/2013 01:29:29 AM     09 BROOKLYN  BROOKLYN                      995366                      180388        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.661793 -73.959934    (40.6617931276793, -73.95993363978067)\n109    26594653  10/30/2013 11:26:32 PM  10/31/2013 12:18:54 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        11222                 NaN              NaN                NaN             NaN         DOBBIN STREET         NORMAN STREET  INTERSECTION  BROOKLYN      NaN      Precinct  Closed  10/31/2013 07:26:32 AM         10/31/2013 12:18:54 AM     01 BROOKLYN  BROOKLYN                      996925                      203271        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.724600 -73.954271  (40.724599563793525, -73.95427134534344)\n236    26591992  10/30/2013 10:02:58 PM  10/30/2013 10:23:20 PM   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        11218       DITMAS AVENUE    DITMAS AVENUE                NaN             NaN                   NaN                   NaN       LATLONG  BROOKLYN      NaN      Precinct  Closed  10/31/2013 06:02:58 AM         10/30/2013 10:23:20 PM     01 BROOKLYN  BROOKLYN                      991895                      171051        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.636169 -73.972455   (40.63616876563881, -73.97245504682485)\n370    26594167  10/30/2013 08:38:25 PM  10/30/2013 10:26:28 PM   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        11218    126 BEVERLY ROAD     BEVERLY ROAD      CHURCH AVENUE   EAST 2 STREET                   NaN                   NaN       ADDRESS  BROOKLYN      NaN      Precinct  Closed  10/31/2013 04:38:25 AM         10/30/2013 10:26:28 PM     12 BROOKLYN  BROOKLYN                      990144                      173511        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.642922 -73.978762    (40.6429222774404, -73.97876175474585)\n\n[5 rows x 52 columns]", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unique Key</th>\n      <th>Created Date</th>\n      <th>Closed Date</th>\n      <th>Agency</th>\n      <th>Agency Name</th>\n      <th>Complaint Type</th>\n      <th>Descriptor</th>\n      <th>Location Type</th>\n      <th>Incident Zip</th>\n      <th>Incident Address</th>\n      <th>Street Name</th>\n      <th>Cross Street 1</th>\n      <th>Cross Street 2</th>\n      <th>Intersection Street 1</th>\n      <th>Intersection Street 2</th>\n      <th>Address Type</th>\n      <th>City</th>\n      <th>Landmark</th>\n      <th>Facility Type</th>\n      <th>Status</th>\n      <th>Due Date</th>\n      <th>Resolution Action Updated Date</th>\n      <th>Community Board</th>\n      <th>Borough</th>\n      <th>X Coordinate (State Plane)</th>\n      <th>Y Coordinate (State Plane)</th>\n      <th>Park Facility Name</th>\n      <th>Park Borough</th>\n      <th>School Name</th>\n      <th>School Number</th>\n      <th>School Region</th>\n      <th>School Code</th>\n      <th>School Phone Number</th>\n      <th>School Address</th>\n      <th>School City</th>\n      <th>School State</th>\n      <th>School Zip</th>\n      <th>School Not Found</th>\n      <th>School or Citywide Complaint</th>\n      <th>Vehicle Type</th>\n      <th>Taxi Company Borough</th>\n      <th>Taxi Pick Up Location</th>\n      <th>Bridge Highway Name</th>\n      <th>Bridge Highway Direction</th>\n      <th>Road Ramp</th>\n      <th>Bridge Highway Segment</th>\n      <th>Garage Lot Name</th>\n      <th>Ferry Direction</th>\n      <th>Ferry Terminal Name</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Location</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>31 </th>\n      <td> 26595564</td>\n      <td> 10/31/2013 12:30:36 AM</td>\n      <td>                    NaN</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td> Loud Music/Party</td>\n      <td> Street/Sidewalk</td>\n      <td> 11236</td>\n      <td>           AVENUE J</td>\n      <td>        AVENUE J</td>\n      <td>    EAST 80 STREET</td>\n      <td> EAST 81 STREET</td>\n      <td>           NaN</td>\n      <td>           NaN</td>\n      <td>    BLOCKFACE</td>\n      <td> BROOKLYN</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td>   Open</td>\n      <td> 10/31/2013 08:30:36 AM</td>\n      <td>                    NaN</td>\n      <td> 18 BROOKLYN</td>\n      <td> BROOKLYN</td>\n      <td> 1008937</td>\n      <td> 170310</td>\n      <td> Unspecified</td>\n      <td> BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.634104</td>\n      <td>-73.911055</td>\n      <td> (40.634103775951736, -73.91105541883589)</td>\n    </tr>\n    <tr>\n      <th>49 </th>\n      <td> 26595553</td>\n      <td> 10/31/2013 12:05:10 AM</td>\n      <td> 10/31/2013 02:43:43 AM</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td>     Loud Talking</td>\n      <td> Street/Sidewalk</td>\n      <td> 11225</td>\n      <td> 25 LEFFERTS AVENUE</td>\n      <td> LEFFERTS AVENUE</td>\n      <td> WASHINGTON AVENUE</td>\n      <td> BEDFORD AVENUE</td>\n      <td>           NaN</td>\n      <td>           NaN</td>\n      <td>      ADDRESS</td>\n      <td> BROOKLYN</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Closed</td>\n      <td> 10/31/2013 08:05:10 AM</td>\n      <td> 10/31/2013 01:29:29 AM</td>\n      <td> 09 BROOKLYN</td>\n      <td> BROOKLYN</td>\n      <td>  995366</td>\n      <td> 180388</td>\n      <td> Unspecified</td>\n      <td> BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.661793</td>\n      <td>-73.959934</td>\n      <td>   (40.6617931276793, -73.95993363978067)</td>\n    </tr>\n    <tr>\n      <th>109</th>\n      <td> 26594653</td>\n      <td> 10/30/2013 11:26:32 PM</td>\n      <td> 10/31/2013 12:18:54 AM</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td> Loud Music/Party</td>\n      <td> Street/Sidewalk</td>\n      <td> 11222</td>\n      <td>                NaN</td>\n      <td>             NaN</td>\n      <td>               NaN</td>\n      <td>            NaN</td>\n      <td> DOBBIN STREET</td>\n      <td> NORMAN STREET</td>\n      <td> INTERSECTION</td>\n      <td> BROOKLYN</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Closed</td>\n      <td> 10/31/2013 07:26:32 AM</td>\n      <td> 10/31/2013 12:18:54 AM</td>\n      <td> 01 BROOKLYN</td>\n      <td> BROOKLYN</td>\n      <td>  996925</td>\n      <td> 203271</td>\n      <td> Unspecified</td>\n      <td> BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.724600</td>\n      <td>-73.954271</td>\n      <td> (40.724599563793525, -73.95427134534344)</td>\n    </tr>\n    <tr>\n      <th>236</th>\n      <td> 26591992</td>\n      <td> 10/30/2013 10:02:58 PM</td>\n      <td> 10/30/2013 10:23:20 PM</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td>     Loud Talking</td>\n      <td> Street/Sidewalk</td>\n      <td> 11218</td>\n      <td>      DITMAS AVENUE</td>\n      <td>   DITMAS AVENUE</td>\n      <td>               NaN</td>\n      <td>            NaN</td>\n      <td>           NaN</td>\n      <td>           NaN</td>\n      <td>      LATLONG</td>\n      <td> BROOKLYN</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Closed</td>\n      <td> 10/31/2013 06:02:58 AM</td>\n      <td> 10/30/2013 10:23:20 PM</td>\n      <td> 01 BROOKLYN</td>\n      <td> BROOKLYN</td>\n      <td>  991895</td>\n      <td> 171051</td>\n      <td> Unspecified</td>\n      <td> BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.636169</td>\n      <td>-73.972455</td>\n      <td>  (40.63616876563881, -73.97245504682485)</td>\n    </tr>\n    <tr>\n      <th>370</th>\n      <td> 26594167</td>\n      <td> 10/30/2013 08:38:25 PM</td>\n      <td> 10/30/2013 10:26:28 PM</td>\n      <td> NYPD</td>\n      <td> New York City Police Department</td>\n      <td> Noise - Street/Sidewalk</td>\n      <td> Loud Music/Party</td>\n      <td> Street/Sidewalk</td>\n      <td> 11218</td>\n      <td>   126 BEVERLY ROAD</td>\n      <td>    BEVERLY ROAD</td>\n      <td>     CHURCH AVENUE</td>\n      <td>  EAST 2 STREET</td>\n      <td>           NaN</td>\n      <td>           NaN</td>\n      <td>      ADDRESS</td>\n      <td> BROOKLYN</td>\n      <td> NaN</td>\n      <td> Precinct</td>\n      <td> Closed</td>\n      <td> 10/31/2013 04:38:25 AM</td>\n      <td> 10/30/2013 10:26:28 PM</td>\n      <td> 12 BROOKLYN</td>\n      <td> BROOKLYN</td>\n      <td>  990144</td>\n      <td> 173511</td>\n      <td> Unspecified</td>\n      <td> BROOKLYN</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> Unspecified</td>\n      <td> N</td>\n      <td>NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> NaN</td>\n      <td> 40.642922</td>\n      <td>-73.978762</td>\n      <td>   (40.6429222774404, -73.97876175474585)</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows \u00d7 52 columns</p>\n</div>"}, "metadata": {}}], "source": "is_noise = complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"\nin_brooklyn = complaints['Borough'] == \"BROOKLYN\"\ncomplaints[is_noise & in_brooklyn][:5]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Or if we just wanted a few columns:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 17, "outputs": [{"execution_count": 17, "output_type": "execute_result", "data": {"text/plain": "               Complaint Type   Borough            Created Date        Descriptor\n31    Noise - Street/Sidewalk  BROOKLYN  10/31/2013 12:30:36 AM  Loud Music/Party\n49    Noise - Street/Sidewalk  BROOKLYN  10/31/2013 12:05:10 AM      Loud Talking\n109   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 11:26:32 PM  Loud Music/Party\n236   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 10:02:58 PM      Loud Talking\n370   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 08:38:25 PM  Loud Music/Party\n378   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 08:32:13 PM      Loud Talking\n656   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 06:07:39 PM  Loud Music/Party\n1251  Noise - Street/Sidewalk  BROOKLYN  10/30/2013 03:04:51 PM      Loud Talking\n5416  Noise - Street/Sidewalk  BROOKLYN  10/29/2013 10:07:02 PM      Loud Talking\n5584  Noise - Street/Sidewalk  BROOKLYN  10/29/2013 08:15:59 PM  Loud Music/Party\n\n[10 rows x 4 columns]", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Complaint Type</th>\n      <th>Borough</th>\n      <th>Created Date</th>\n      <th>Descriptor</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>31  </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/31/2013 12:30:36 AM</td>\n      <td> Loud Music/Party</td>\n    </tr>\n    <tr>\n      <th>49  </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/31/2013 12:05:10 AM</td>\n      <td>     Loud Talking</td>\n    </tr>\n    <tr>\n      <th>109 </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/30/2013 11:26:32 PM</td>\n      <td> Loud Music/Party</td>\n    </tr>\n    <tr>\n      <th>236 </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/30/2013 10:02:58 PM</td>\n      <td>     Loud Talking</td>\n    </tr>\n    <tr>\n      <th>370 </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/30/2013 08:38:25 PM</td>\n      <td> Loud Music/Party</td>\n    </tr>\n    <tr>\n      <th>378 </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/30/2013 08:32:13 PM</td>\n      <td>     Loud Talking</td>\n    </tr>\n    <tr>\n      <th>656 </th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/30/2013 06:07:39 PM</td>\n      <td> Loud Music/Party</td>\n    </tr>\n    <tr>\n      <th>1251</th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/30/2013 03:04:51 PM</td>\n      <td>     Loud Talking</td>\n    </tr>\n    <tr>\n      <th>5416</th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/29/2013 10:07:02 PM</td>\n      <td>     Loud Talking</td>\n    </tr>\n    <tr>\n      <th>5584</th>\n      <td> Noise - Street/Sidewalk</td>\n      <td> BROOKLYN</td>\n      <td> 10/29/2013 08:15:59 PM</td>\n      <td> Loud Music/Party</td>\n    </tr>\n  </tbody>\n</table>\n<p>10 rows \u00d7 4 columns</p>\n</div>"}, "metadata": {}}], "source": "complaints[is_noise & in_brooklyn][['Complaint Type', 'Borough', 'Created Date', 'Descriptor']][:10]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 3.2 A digression about numpy arrays", "cell_type": "markdown", "metadata": {}}, {"source": "On the inside, the type of a column is `pd.Series`", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 18, "outputs": [{"execution_count": 18, "output_type": "execute_result", "data": {"text/plain": "0    1\n1    2\n2    3\ndtype: int64"}, "metadata": {}}], "source": "pd.Series([1,2,3])", "metadata": {"collapsed": false, "trusted": false}}, {"source": "and pandas Series are internally numpy arrays. If you add `.values` to the end of any `Series`, you'll get its internal numpy array", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 19, "outputs": [{"execution_count": 19, "output_type": "execute_result", "data": {"text/plain": "array([1, 2, 3])"}, "metadata": {}}], "source": "np.array([1,2,3])", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 20, "outputs": [{"execution_count": 20, "output_type": "execute_result", "data": {"text/plain": "array([1, 2, 3])"}, "metadata": {}}], "source": "pd.Series([1,2,3]).values", "metadata": {"collapsed": false, "trusted": false}}, {"source": "So this binary-array-selection business is actually something that works with any numpy array:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 21, "outputs": [], "source": "arr = np.array([1,2,3])", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 22, "outputs": [{"execution_count": 22, "output_type": "execute_result", "data": {"text/plain": "array([ True, False,  True], dtype=bool)"}, "metadata": {}}], "source": "arr != 2", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 23, "outputs": [{"execution_count": 23, "output_type": "execute_result", "data": {"text/plain": "array([1, 3])"}, "metadata": {}}], "source": "arr[arr != 2]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 3.3 So, which borough has the most noise complaints?", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 24, "outputs": [{"execution_count": 24, "output_type": "execute_result", "data": {"text/plain": "MANHATTAN        917\nBROOKLYN         456\nBRONX            292\nQUEENS           226\nSTATEN ISLAND     36\nUnspecified        1\ndtype: int64"}, "metadata": {}}], "source": "is_noise = complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"\nnoise_complaints = complaints[is_noise]\nnoise_complaints['Borough'].value_counts()", "metadata": {"collapsed": false, "trusted": false}}, {"source": "It's Manhattan! But what if we wanted to divide by the total number of complaints, to make it make a bit more sense? That would be easy too:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 25, "outputs": [], "source": "noise_complaint_counts = noise_complaints['Borough'].value_counts()\ncomplaint_counts = complaints['Borough'].value_counts()", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 26, "outputs": [{"execution_count": 26, "output_type": "execute_result", "data": {"text/plain": "BRONX            0.014833\nBROOKLYN         0.013864\nMANHATTAN        0.037755\nQUEENS           0.010143\nSTATEN ISLAND    0.007474\nUnspecified      0.000141\ndtype: float64"}, "metadata": {}}], "source": "noise_complaint_counts / complaint_counts", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Oops, why was that zero? That's no good. This is because of integer division in Python 2. Let's fix it, by converting `complaint_counts` into an array of floats.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 27, "outputs": [{"execution_count": 27, "output_type": "execute_result", "data": {"text/plain": "BRONX            0.014833\nBROOKLYN         0.013864\nMANHATTAN        0.037755\nQUEENS           0.010143\nSTATEN ISLAND    0.007474\nUnspecified      0.000141\ndtype: float64"}, "metadata": {}}], "source": "noise_complaint_counts / complaint_counts.astype(float)", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 28, "outputs": [{"execution_count": 28, "output_type": "execute_result", "data": {"text/plain": "<matplotlib.axes.AxesSubplot at 0x113a628d0>"}, "metadata": {}}, {"output_type": "display_data", "metadata": {}, "data": {"image/png": 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gnjp70NQBAAAAgIvR1AEAAAAYENxTZw+aOgAAAABwMZo6AAAAAAOCe+rsQVMH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\n6uLFi3ruueeUSCT0ve99j13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"text/plain": "<matplotlib.figure.Figure at 0x113a62e50>"}}], "source": "(noise_complaint_counts / complaint_counts.astype(float)).plot(kind='bar')", "metadata": {"collapsed": false, "trusted": false}}, {"source": "So Manhattan really does complain more about noise than the other boroughs! Neat.", "cell_type": "markdown", "metadata": {}}, {"source": "<style>\n    @font-face {\n        font-family: \"Computer Modern\";\n        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n    }\n    div.cell{\n        width:800px;\n        margin-left:16% !important;\n        margin-right:auto;\n    }\n    h1 {\n        font-family: Helvetica, serif;\n    }\n    h4{\n        margin-top:12px;\n        margin-bottom: 3px;\n       }\n    div.text_cell_render{\n        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n        line-height: 145%;\n        font-size: 130%;\n        width:800px;\n        margin-left:auto;\n        margin-right:auto;\n    }\n    .CodeMirror{\n            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n    }\n    .text_cell_render h5 {\n        font-weight: 300;\n        font-size: 22pt;\n        color: #4057A1;\n        font-style: italic;\n        margin-bottom: .5em;\n        margin-top: 0.5em;\n        display: block;\n    }\n    \n    .warning{\n        color: rgb( 240, 20, 20 )\n        }  ", "cell_type": "markdown", "metadata": {}}], "nbformat_minor": 0}
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "# Make the graphs a bit prettier, and bigger\n",
+    "plt.style.use('ggplot')\n",
+    "plt.rcParams['figure.figsize'] = (15, 5)\n",
+    "\n",
+    "# This is necessary to show lots of columns in pandas 0.12. \n",
+    "# Not necessary in pandas 0.13.\n",
+    "pd.set_option('display.max_colwidth', 5000) \n",
+    "pd.set_option('display.max_columns', 60)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's continue with our NYC 311 service requests example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/gabriela/.local/share/virtualenvs/pandas-cookbook-M4OY_8hn/lib/python3.5/site-packages/IPython/core/interactiveshell.py:3018: DtypeWarning: Columns (8) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  interactivity=interactivity, compiler=compiler, result=result)\n"
+     ]
+    }
+   ],
+   "source": [
+    "complaints = pd.read_csv('../data/311-service-requests.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 3.1 Selecting only noise complaints"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I'd like to know which borough has the most noise complaints. First, we'll take a look at the data to see what it looks like:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unique Key</th>\n",
+       "      <th>Created Date</th>\n",
+       "      <th>Closed Date</th>\n",
+       "      <th>Agency</th>\n",
+       "      <th>Agency Name</th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Descriptor</th>\n",
+       "      <th>Location Type</th>\n",
+       "      <th>Incident Zip</th>\n",
+       "      <th>Incident Address</th>\n",
+       "      <th>Street Name</th>\n",
+       "      <th>Cross Street 1</th>\n",
+       "      <th>Cross Street 2</th>\n",
+       "      <th>Intersection Street 1</th>\n",
+       "      <th>Intersection Street 2</th>\n",
+       "      <th>Address Type</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Landmark</th>\n",
+       "      <th>Facility Type</th>\n",
+       "      <th>Status</th>\n",
+       "      <th>Due Date</th>\n",
+       "      <th>Resolution Action Updated Date</th>\n",
+       "      <th>Community Board</th>\n",
+       "      <th>Borough</th>\n",
+       "      <th>X Coordinate (State Plane)</th>\n",
+       "      <th>Y Coordinate (State Plane)</th>\n",
+       "      <th>Park Facility Name</th>\n",
+       "      <th>Park Borough</th>\n",
+       "      <th>School Name</th>\n",
+       "      <th>School Number</th>\n",
+       "      <th>School Region</th>\n",
+       "      <th>School Code</th>\n",
+       "      <th>School Phone Number</th>\n",
+       "      <th>School Address</th>\n",
+       "      <th>School City</th>\n",
+       "      <th>School State</th>\n",
+       "      <th>School Zip</th>\n",
+       "      <th>School Not Found</th>\n",
+       "      <th>School or Citywide Complaint</th>\n",
+       "      <th>Vehicle Type</th>\n",
+       "      <th>Taxi Company Borough</th>\n",
+       "      <th>Taxi Pick Up Location</th>\n",
+       "      <th>Bridge Highway Name</th>\n",
+       "      <th>Bridge Highway Direction</th>\n",
+       "      <th>Road Ramp</th>\n",
+       "      <th>Bridge Highway Segment</th>\n",
+       "      <th>Garage Lot Name</th>\n",
+       "      <th>Ferry Direction</th>\n",
+       "      <th>Ferry Terminal Name</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Location</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>26589651</td>\n",
+       "      <td>10/31/2013 02:08:41 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11432</td>\n",
+       "      <td>90-03 169 STREET</td>\n",
+       "      <td>169 STREET</td>\n",
+       "      <td>90 AVENUE</td>\n",
+       "      <td>91 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>JAMAICA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 10:08:41 AM</td>\n",
+       "      <td>10/31/2013 02:35:17 AM</td>\n",
+       "      <td>12 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1042027.0</td>\n",
+       "      <td>197389.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.708275</td>\n",
+       "      <td>-73.791604</td>\n",
+       "      <td>(40.70827532593202, -73.79160395779721)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>26593698</td>\n",
+       "      <td>10/31/2013 02:01:04 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Illegal Parking</td>\n",
+       "      <td>Commercial Overnight Parking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11378</td>\n",
+       "      <td>58 AVENUE</td>\n",
+       "      <td>58 AVENUE</td>\n",
+       "      <td>58 PLACE</td>\n",
+       "      <td>59 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>MASPETH</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 10:01:04 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>05 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1009349.0</td>\n",
+       "      <td>201984.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.721041</td>\n",
+       "      <td>-73.909453</td>\n",
+       "      <td>(40.721040535628305, -73.90945306791765)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>26594139</td>\n",
+       "      <td>10/31/2013 02:00:24 AM</td>\n",
+       "      <td>10/31/2013 02:40:32 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Commercial</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Club/Bar/Restaurant</td>\n",
+       "      <td>10032</td>\n",
+       "      <td>4060 BROADWAY</td>\n",
+       "      <td>BROADWAY</td>\n",
+       "      <td>WEST 171 STREET</td>\n",
+       "      <td>WEST 172 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 10:00:24 AM</td>\n",
+       "      <td>10/31/2013 02:39:42 AM</td>\n",
+       "      <td>12 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>1001088.0</td>\n",
+       "      <td>246531.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.843330</td>\n",
+       "      <td>-73.939144</td>\n",
+       "      <td>(40.84332975466513, -73.93914371913482)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>26595721</td>\n",
+       "      <td>10/31/2013 01:56:23 AM</td>\n",
+       "      <td>10/31/2013 02:21:48 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Vehicle</td>\n",
+       "      <td>Car/Truck Horn</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10023</td>\n",
+       "      <td>WEST 72 STREET</td>\n",
+       "      <td>WEST 72 STREET</td>\n",
+       "      <td>COLUMBUS AVENUE</td>\n",
+       "      <td>AMSTERDAM AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 09:56:23 AM</td>\n",
+       "      <td>10/31/2013 02:21:10 AM</td>\n",
+       "      <td>07 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>989730.0</td>\n",
+       "      <td>222727.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.778009</td>\n",
+       "      <td>-73.980213</td>\n",
+       "      <td>(40.7780087446372, -73.98021349023975)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>26590930</td>\n",
+       "      <td>10/31/2013 01:53:44 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOHMH</td>\n",
+       "      <td>Department of Health and Mental Hygiene</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Condition Attracting Rodents</td>\n",
+       "      <td>Vacant Lot</td>\n",
+       "      <td>10027</td>\n",
+       "      <td>WEST 124 STREET</td>\n",
+       "      <td>WEST 124 STREET</td>\n",
+       "      <td>LENOX AVENUE</td>\n",
+       "      <td>ADAM CLAYTON POWELL JR BOULEVARD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>NEW YORK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Pending</td>\n",
+       "      <td>11/30/2013 01:53:44 AM</td>\n",
+       "      <td>10/31/2013 01:59:54 AM</td>\n",
+       "      <td>10 MANHATTAN</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>998815.0</td>\n",
+       "      <td>233545.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>MANHATTAN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.807691</td>\n",
+       "      <td>-73.947387</td>\n",
+       "      <td>(40.80769092704951, -73.94738703491433)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unique Key            Created Date             Closed Date Agency                              Agency Name           Complaint Type                    Descriptor        Location Type Incident Zip  Incident Address      Street Name   Cross Street 1                    Cross Street 2 Intersection Street 1 Intersection Street 2 Address Type      City Landmark Facility Type    Status                Due Date Resolution Action Updated Date Community Board    Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n",
+       "0    26589651  10/31/2013 02:08:41 AM                     NaN   NYPD          New York City Police Department  Noise - Street/Sidewalk                  Loud Talking      Street/Sidewalk        11432  90-03 169 STREET       169 STREET        90 AVENUE                         91 AVENUE                   NaN                   NaN      ADDRESS   JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM       12 QUEENS     QUEENS                   1042027.0                    197389.0        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604   (40.70827532593202, -73.79160395779721)\n",
+       "1    26593698  10/31/2013 02:01:04 AM                     NaN   NYPD          New York City Police Department          Illegal Parking  Commercial Overnight Parking      Street/Sidewalk        11378         58 AVENUE        58 AVENUE         58 PLACE                         59 STREET                   NaN                   NaN    BLOCKFACE   MASPETH      NaN      Precinct      Open  10/31/2013 10:01:04 AM                            NaN       05 QUEENS     QUEENS                   1009349.0                    201984.0        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.721041 -73.909453  (40.721040535628305, -73.90945306791765)\n",
+       "2    26594139  10/31/2013 02:00:24 AM  10/31/2013 02:40:32 AM   NYPD          New York City Police Department       Noise - Commercial              Loud Music/Party  Club/Bar/Restaurant        10032     4060 BROADWAY         BROADWAY  WEST 171 STREET                   WEST 172 STREET                   NaN                   NaN      ADDRESS  NEW YORK      NaN      Precinct    Closed  10/31/2013 10:00:24 AM         10/31/2013 02:39:42 AM    12 MANHATTAN  MANHATTAN                   1001088.0                    246531.0        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.843330 -73.939144   (40.84332975466513, -73.93914371913482)\n",
+       "3    26595721  10/31/2013 01:56:23 AM  10/31/2013 02:21:48 AM   NYPD          New York City Police Department          Noise - Vehicle                Car/Truck Horn      Street/Sidewalk        10023    WEST 72 STREET   WEST 72 STREET  COLUMBUS AVENUE                  AMSTERDAM AVENUE                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN      Precinct    Closed  10/31/2013 09:56:23 AM         10/31/2013 02:21:10 AM    07 MANHATTAN  MANHATTAN                    989730.0                    222727.0        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.778009 -73.980213    (40.7780087446372, -73.98021349023975)\n",
+       "4    26590930  10/31/2013 01:53:44 AM                     NaN  DOHMH  Department of Health and Mental Hygiene                   Rodent  Condition Attracting Rodents           Vacant Lot        10027   WEST 124 STREET  WEST 124 STREET     LENOX AVENUE  ADAM CLAYTON POWELL JR BOULEVARD                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN           NaN   Pending  11/30/2013 01:53:44 AM         10/31/2013 01:59:54 AM    10 MANHATTAN  MANHATTAN                    998815.0                    233545.0        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.807691 -73.947387   (40.80769092704951, -73.94738703491433)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To get the noise complaints, we need to find the rows where the \"Complaint Type\" column is \"Noise - Street/Sidewalk\". I'll show you how to do that, and then explain what's going on."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unique Key</th>\n",
+       "      <th>Created Date</th>\n",
+       "      <th>Closed Date</th>\n",
+       "      <th>Agency</th>\n",
+       "      <th>Agency Name</th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Descriptor</th>\n",
+       "      <th>Location Type</th>\n",
+       "      <th>Incident Zip</th>\n",
+       "      <th>Incident Address</th>\n",
+       "      <th>Street Name</th>\n",
+       "      <th>Cross Street 1</th>\n",
+       "      <th>Cross Street 2</th>\n",
+       "      <th>Intersection Street 1</th>\n",
+       "      <th>Intersection Street 2</th>\n",
+       "      <th>Address Type</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Landmark</th>\n",
+       "      <th>Facility Type</th>\n",
+       "      <th>Status</th>\n",
+       "      <th>Due Date</th>\n",
+       "      <th>Resolution Action Updated Date</th>\n",
+       "      <th>Community Board</th>\n",
+       "      <th>Borough</th>\n",
+       "      <th>X Coordinate (State Plane)</th>\n",
+       "      <th>Y Coordinate (State Plane)</th>\n",
+       "      <th>Park Facility Name</th>\n",
+       "      <th>Park Borough</th>\n",
+       "      <th>School Name</th>\n",
+       "      <th>School Number</th>\n",
+       "      <th>School Region</th>\n",
+       "      <th>School Code</th>\n",
+       "      <th>School Phone Number</th>\n",
+       "      <th>School Address</th>\n",
+       "      <th>School City</th>\n",
+       "      <th>School State</th>\n",
+       "      <th>School Zip</th>\n",
+       "      <th>School Not Found</th>\n",
+       "      <th>School or Citywide Complaint</th>\n",
+       "      <th>Vehicle Type</th>\n",
+       "      <th>Taxi Company Borough</th>\n",
+       "      <th>Taxi Pick Up Location</th>\n",
+       "      <th>Bridge Highway Name</th>\n",
+       "      <th>Bridge Highway Direction</th>\n",
+       "      <th>Road Ramp</th>\n",
+       "      <th>Bridge Highway Segment</th>\n",
+       "      <th>Garage Lot Name</th>\n",
+       "      <th>Ferry Direction</th>\n",
+       "      <th>Ferry Terminal Name</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Location</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>26589651</td>\n",
+       "      <td>10/31/2013 02:08:41 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11432</td>\n",
+       "      <td>90-03 169 STREET</td>\n",
+       "      <td>169 STREET</td>\n",
+       "      <td>90 AVENUE</td>\n",
+       "      <td>91 AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>JAMAICA</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>10/31/2013 10:08:41 AM</td>\n",
+       "      <td>10/31/2013 02:35:17 AM</td>\n",
+       "      <td>12 QUEENS</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>1042027.0</td>\n",
+       "      <td>197389.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>QUEENS</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.708275</td>\n",
+       "      <td>-73.791604</td>\n",
+       "      <td>(40.70827532593202, -73.79160395779721)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>26594086</td>\n",
+       "      <td>10/31/2013 12:54:03 AM</td>\n",
+       "      <td>10/31/2013 02:16:39 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10310</td>\n",
+       "      <td>173 CAMPBELL AVENUE</td>\n",
+       "      <td>CAMPBELL AVENUE</td>\n",
+       "      <td>HENDERSON AVENUE</td>\n",
+       "      <td>WINEGAR LANE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:54:03 AM</td>\n",
+       "      <td>10/31/2013 02:07:14 AM</td>\n",
+       "      <td>01 STATEN ISLAND</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>952013.0</td>\n",
+       "      <td>171076.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.636182</td>\n",
+       "      <td>-74.116150</td>\n",
+       "      <td>(40.63618202176914, -74.1161500428337)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>26591573</td>\n",
+       "      <td>10/31/2013 12:35:18 AM</td>\n",
+       "      <td>10/31/2013 02:41:35 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>10312</td>\n",
+       "      <td>24 PRINCETON LANE</td>\n",
+       "      <td>PRINCETON LANE</td>\n",
+       "      <td>HAMPTON GREEN</td>\n",
+       "      <td>DEAD END</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:35:18 AM</td>\n",
+       "      <td>10/31/2013 01:45:17 AM</td>\n",
+       "      <td>03 STATEN ISLAND</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>929577.0</td>\n",
+       "      <td>140964.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>STATEN ISLAND</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.553421</td>\n",
+       "      <td>-74.196743</td>\n",
+       "      <td>(40.55342078716953, -74.19674315017886)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Unique Key            Created Date             Closed Date Agency                      Agency Name           Complaint Type        Descriptor    Location Type Incident Zip     Incident Address      Street Name    Cross Street 1 Cross Street 2 Intersection Street 1 Intersection Street 2 Address Type           City Landmark Facility Type    Status                Due Date Resolution Action Updated Date   Community Board        Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name   Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                 Location\n",
+       "0     26589651  10/31/2013 02:08:41 AM                     NaN   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        11432     90-03 169 STREET       169 STREET         90 AVENUE      91 AVENUE                   NaN                   NaN      ADDRESS        JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM         12 QUEENS         QUEENS                   1042027.0                    197389.0        Unspecified         QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604  (40.70827532593202, -73.79160395779721)\n",
+       "16    26594086  10/31/2013 12:54:03 AM  10/31/2013 02:16:39 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        10310  173 CAMPBELL AVENUE  CAMPBELL AVENUE  HENDERSON AVENUE   WINEGAR LANE                   NaN                   NaN      ADDRESS  STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:54:03 AM         10/31/2013 02:07:14 AM  01 STATEN ISLAND  STATEN ISLAND                    952013.0                    171076.0        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.636182 -74.116150   (40.63618202176914, -74.1161500428337)\n",
+       "25    26591573  10/31/2013 12:35:18 AM  10/31/2013 02:41:35 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        10312    24 PRINCETON LANE   PRINCETON LANE     HAMPTON GREEN       DEAD END                   NaN                   NaN      ADDRESS  STATEN ISLAND      NaN      Precinct    Closed  10/31/2013 08:35:18 AM         10/31/2013 01:45:17 AM  03 STATEN ISLAND  STATEN ISLAND                    929577.0                    140964.0        Unspecified  STATEN ISLAND  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.553421 -74.196743  (40.55342078716953, -74.19674315017886)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "noise_complaints = complaints[complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"]\n",
+    "noise_complaints[:3]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If you look at `noise_complaints`, you'll see that this worked, and it only contains complaints with the right complaint type. But how does this work? Let's deconstruct it into two pieces"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0          True\n",
+       "1         False\n",
+       "2         False\n",
+       "3         False\n",
+       "4         False\n",
+       "5         False\n",
+       "6         False\n",
+       "7         False\n",
+       "8         False\n",
+       "9         False\n",
+       "10        False\n",
+       "11        False\n",
+       "12        False\n",
+       "13        False\n",
+       "14        False\n",
+       "15        False\n",
+       "16         True\n",
+       "17        False\n",
+       "18        False\n",
+       "19        False\n",
+       "20        False\n",
+       "21        False\n",
+       "22        False\n",
+       "23        False\n",
+       "24        False\n",
+       "25         True\n",
+       "26        False\n",
+       "27        False\n",
+       "28         True\n",
+       "29        False\n",
+       "          ...  \n",
+       "111039    False\n",
+       "111040    False\n",
+       "111041    False\n",
+       "111042     True\n",
+       "111043    False\n",
+       "111044     True\n",
+       "111045    False\n",
+       "111046    False\n",
+       "111047    False\n",
+       "111048     True\n",
+       "111049    False\n",
+       "111050    False\n",
+       "111051    False\n",
+       "111052    False\n",
+       "111053    False\n",
+       "111054     True\n",
+       "111055    False\n",
+       "111056    False\n",
+       "111057    False\n",
+       "111058    False\n",
+       "111059     True\n",
+       "111060    False\n",
+       "111061    False\n",
+       "111062    False\n",
+       "111063    False\n",
+       "111064    False\n",
+       "111065    False\n",
+       "111066     True\n",
+       "111067    False\n",
+       "111068    False\n",
+       "Name: Complaint Type, Length: 111069, dtype: bool"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints['Complaint Type'] == \"Noise - Street/Sidewalk\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a big array of `True`s and `False`s, one for each row in our dataframe. When we index our dataframe with this array, we get just the rows where our boolean array evaluated to `True`.  It's important to note that for row filtering by a boolean array the length of our dataframe's index must be the same length as the boolean array used for filtering.\n",
+    "\n",
+    "You can also combine more than one condition with the `&` operator like this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unique Key</th>\n",
+       "      <th>Created Date</th>\n",
+       "      <th>Closed Date</th>\n",
+       "      <th>Agency</th>\n",
+       "      <th>Agency Name</th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Descriptor</th>\n",
+       "      <th>Location Type</th>\n",
+       "      <th>Incident Zip</th>\n",
+       "      <th>Incident Address</th>\n",
+       "      <th>Street Name</th>\n",
+       "      <th>Cross Street 1</th>\n",
+       "      <th>Cross Street 2</th>\n",
+       "      <th>Intersection Street 1</th>\n",
+       "      <th>Intersection Street 2</th>\n",
+       "      <th>Address Type</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Landmark</th>\n",
+       "      <th>Facility Type</th>\n",
+       "      <th>Status</th>\n",
+       "      <th>Due Date</th>\n",
+       "      <th>Resolution Action Updated Date</th>\n",
+       "      <th>Community Board</th>\n",
+       "      <th>Borough</th>\n",
+       "      <th>X Coordinate (State Plane)</th>\n",
+       "      <th>Y Coordinate (State Plane)</th>\n",
+       "      <th>Park Facility Name</th>\n",
+       "      <th>Park Borough</th>\n",
+       "      <th>School Name</th>\n",
+       "      <th>School Number</th>\n",
+       "      <th>School Region</th>\n",
+       "      <th>School Code</th>\n",
+       "      <th>School Phone Number</th>\n",
+       "      <th>School Address</th>\n",
+       "      <th>School City</th>\n",
+       "      <th>School State</th>\n",
+       "      <th>School Zip</th>\n",
+       "      <th>School Not Found</th>\n",
+       "      <th>School or Citywide Complaint</th>\n",
+       "      <th>Vehicle Type</th>\n",
+       "      <th>Taxi Company Borough</th>\n",
+       "      <th>Taxi Pick Up Location</th>\n",
+       "      <th>Bridge Highway Name</th>\n",
+       "      <th>Bridge Highway Direction</th>\n",
+       "      <th>Road Ramp</th>\n",
+       "      <th>Bridge Highway Segment</th>\n",
+       "      <th>Garage Lot Name</th>\n",
+       "      <th>Ferry Direction</th>\n",
+       "      <th>Ferry Terminal Name</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Location</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>26595564</td>\n",
+       "      <td>10/31/2013 12:30:36 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11236</td>\n",
+       "      <td>AVENUE J</td>\n",
+       "      <td>AVENUE J</td>\n",
+       "      <td>EAST 80 STREET</td>\n",
+       "      <td>EAST 81 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BLOCKFACE</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Open</td>\n",
+       "      <td>10/31/2013 08:30:36 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>18 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>1008937.0</td>\n",
+       "      <td>170310.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.634104</td>\n",
+       "      <td>-73.911055</td>\n",
+       "      <td>(40.634103775951736, -73.91105541883589)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>26595553</td>\n",
+       "      <td>10/31/2013 12:05:10 AM</td>\n",
+       "      <td>10/31/2013 02:43:43 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11225</td>\n",
+       "      <td>25 LEFFERTS AVENUE</td>\n",
+       "      <td>LEFFERTS AVENUE</td>\n",
+       "      <td>WASHINGTON AVENUE</td>\n",
+       "      <td>BEDFORD AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 08:05:10 AM</td>\n",
+       "      <td>10/31/2013 01:29:29 AM</td>\n",
+       "      <td>09 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>995366.0</td>\n",
+       "      <td>180388.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.661793</td>\n",
+       "      <td>-73.959934</td>\n",
+       "      <td>(40.6617931276793, -73.95993363978067)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>109</th>\n",
+       "      <td>26594653</td>\n",
+       "      <td>10/30/2013 11:26:32 PM</td>\n",
+       "      <td>10/31/2013 12:18:54 AM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11222</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DOBBIN STREET</td>\n",
+       "      <td>NORMAN STREET</td>\n",
+       "      <td>INTERSECTION</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 07:26:32 AM</td>\n",
+       "      <td>10/31/2013 12:18:54 AM</td>\n",
+       "      <td>01 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>996925.0</td>\n",
+       "      <td>203271.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.724600</td>\n",
+       "      <td>-73.954271</td>\n",
+       "      <td>(40.724599563793525, -73.95427134534344)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>236</th>\n",
+       "      <td>26591992</td>\n",
+       "      <td>10/30/2013 10:02:58 PM</td>\n",
+       "      <td>10/30/2013 10:23:20 PM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11218</td>\n",
+       "      <td>DITMAS AVENUE</td>\n",
+       "      <td>DITMAS AVENUE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>LATLONG</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 06:02:58 AM</td>\n",
+       "      <td>10/30/2013 10:23:20 PM</td>\n",
+       "      <td>01 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>991895.0</td>\n",
+       "      <td>171051.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.636169</td>\n",
+       "      <td>-73.972455</td>\n",
+       "      <td>(40.63616876563881, -73.97245504682485)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>370</th>\n",
+       "      <td>26594167</td>\n",
+       "      <td>10/30/2013 08:38:25 PM</td>\n",
+       "      <td>10/30/2013 10:26:28 PM</td>\n",
+       "      <td>NYPD</td>\n",
+       "      <td>New York City Police Department</td>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "      <td>Street/Sidewalk</td>\n",
+       "      <td>11218</td>\n",
+       "      <td>126 BEVERLY ROAD</td>\n",
+       "      <td>BEVERLY ROAD</td>\n",
+       "      <td>CHURCH AVENUE</td>\n",
+       "      <td>EAST 2 STREET</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ADDRESS</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Precinct</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/31/2013 04:38:25 AM</td>\n",
+       "      <td>10/30/2013 10:26:28 PM</td>\n",
+       "      <td>12 BROOKLYN</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>990144.0</td>\n",
+       "      <td>173511.0</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>40.642922</td>\n",
+       "      <td>-73.978762</td>\n",
+       "      <td>(40.6429222774404, -73.97876175474585)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     Unique Key            Created Date             Closed Date Agency                      Agency Name           Complaint Type        Descriptor    Location Type Incident Zip    Incident Address      Street Name     Cross Street 1  Cross Street 2 Intersection Street 1 Intersection Street 2  Address Type      City Landmark Facility Type  Status                Due Date Resolution Action Updated Date Community Board   Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n",
+       "31     26595564  10/31/2013 12:30:36 AM                     NaN   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        11236            AVENUE J         AVENUE J     EAST 80 STREET  EAST 81 STREET                   NaN                   NaN     BLOCKFACE  BROOKLYN      NaN      Precinct    Open  10/31/2013 08:30:36 AM                            NaN     18 BROOKLYN  BROOKLYN                   1008937.0                    170310.0        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.634104 -73.911055  (40.634103775951736, -73.91105541883589)\n",
+       "49     26595553  10/31/2013 12:05:10 AM  10/31/2013 02:43:43 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        11225  25 LEFFERTS AVENUE  LEFFERTS AVENUE  WASHINGTON AVENUE  BEDFORD AVENUE                   NaN                   NaN       ADDRESS  BROOKLYN      NaN      Precinct  Closed  10/31/2013 08:05:10 AM         10/31/2013 01:29:29 AM     09 BROOKLYN  BROOKLYN                    995366.0                    180388.0        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.661793 -73.959934    (40.6617931276793, -73.95993363978067)\n",
+       "109    26594653  10/30/2013 11:26:32 PM  10/31/2013 12:18:54 AM   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        11222                 NaN              NaN                NaN             NaN         DOBBIN STREET         NORMAN STREET  INTERSECTION  BROOKLYN      NaN      Precinct  Closed  10/31/2013 07:26:32 AM         10/31/2013 12:18:54 AM     01 BROOKLYN  BROOKLYN                    996925.0                    203271.0        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.724600 -73.954271  (40.724599563793525, -73.95427134534344)\n",
+       "236    26591992  10/30/2013 10:02:58 PM  10/30/2013 10:23:20 PM   NYPD  New York City Police Department  Noise - Street/Sidewalk      Loud Talking  Street/Sidewalk        11218       DITMAS AVENUE    DITMAS AVENUE                NaN             NaN                   NaN                   NaN       LATLONG  BROOKLYN      NaN      Precinct  Closed  10/31/2013 06:02:58 AM         10/30/2013 10:23:20 PM     01 BROOKLYN  BROOKLYN                    991895.0                    171051.0        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.636169 -73.972455   (40.63616876563881, -73.97245504682485)\n",
+       "370    26594167  10/30/2013 08:38:25 PM  10/30/2013 10:26:28 PM   NYPD  New York City Police Department  Noise - Street/Sidewalk  Loud Music/Party  Street/Sidewalk        11218    126 BEVERLY ROAD     BEVERLY ROAD      CHURCH AVENUE   EAST 2 STREET                   NaN                   NaN       ADDRESS  BROOKLYN      NaN      Precinct  Closed  10/31/2013 04:38:25 AM         10/30/2013 10:26:28 PM     12 BROOKLYN  BROOKLYN                    990144.0                    173511.0        Unspecified     BROOKLYN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.642922 -73.978762    (40.6429222774404, -73.97876175474585)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "is_noise = complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"\n",
+    "in_brooklyn = complaints['Borough'] == \"BROOKLYN\"\n",
+    "complaints[is_noise & in_brooklyn][:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Or if we just wanted a few columns:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Complaint Type</th>\n",
+       "      <th>Borough</th>\n",
+       "      <th>Created Date</th>\n",
+       "      <th>Descriptor</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/31/2013 12:30:36 AM</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/31/2013 12:05:10 AM</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>109</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/30/2013 11:26:32 PM</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>236</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/30/2013 10:02:58 PM</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>370</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/30/2013 08:38:25 PM</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>378</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/30/2013 08:32:13 PM</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>656</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/30/2013 06:07:39 PM</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1251</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/30/2013 03:04:51 PM</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5416</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/29/2013 10:07:02 PM</td>\n",
+       "      <td>Loud Talking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5584</th>\n",
+       "      <td>Noise - Street/Sidewalk</td>\n",
+       "      <td>BROOKLYN</td>\n",
+       "      <td>10/29/2013 08:15:59 PM</td>\n",
+       "      <td>Loud Music/Party</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               Complaint Type   Borough            Created Date        Descriptor\n",
+       "31    Noise - Street/Sidewalk  BROOKLYN  10/31/2013 12:30:36 AM  Loud Music/Party\n",
+       "49    Noise - Street/Sidewalk  BROOKLYN  10/31/2013 12:05:10 AM      Loud Talking\n",
+       "109   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 11:26:32 PM  Loud Music/Party\n",
+       "236   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 10:02:58 PM      Loud Talking\n",
+       "370   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 08:38:25 PM  Loud Music/Party\n",
+       "378   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 08:32:13 PM      Loud Talking\n",
+       "656   Noise - Street/Sidewalk  BROOKLYN  10/30/2013 06:07:39 PM  Loud Music/Party\n",
+       "1251  Noise - Street/Sidewalk  BROOKLYN  10/30/2013 03:04:51 PM      Loud Talking\n",
+       "5416  Noise - Street/Sidewalk  BROOKLYN  10/29/2013 10:07:02 PM      Loud Talking\n",
+       "5584  Noise - Street/Sidewalk  BROOKLYN  10/29/2013 08:15:59 PM  Loud Music/Party"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "complaints[is_noise & in_brooklyn][['Complaint Type', 'Borough', 'Created Date', 'Descriptor']][:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 3.2 A digression about numpy arrays"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On the inside, the type of a column is `pd.Series`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    1\n",
+       "1    2\n",
+       "2    3\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.Series([1,2,3])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "and pandas Series are internally numpy arrays. If you add `.values` to the end of any `Series`, you'll get its internal numpy array"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 2, 3])"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array([1,2,3])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 2, 3])"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.Series([1,2,3]).values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So this binary-array-selection business is actually something that works with any numpy array:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "arr = np.array([1,2,3])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ True, False,  True])"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arr != 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 3])"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "arr[arr != 2]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 3.3 So, which borough has the most noise complaints?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "MANHATTAN        917\n",
+       "BROOKLYN         456\n",
+       "BRONX            292\n",
+       "QUEENS           226\n",
+       "STATEN ISLAND     36\n",
+       "Unspecified        1\n",
+       "Name: Borough, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "is_noise = complaints['Complaint Type'] == \"Noise - Street/Sidewalk\"\n",
+    "noise_complaints = complaints[is_noise]\n",
+    "noise_complaints['Borough'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It's Manhattan! But what if we wanted to divide by the total number of complaints, to make it make a bit more sense? That would be easy too:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "noise_complaint_counts = noise_complaints['Borough'].value_counts()\n",
+    "complaint_counts = complaints['Borough'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "BRONX            0.014833\n",
+       "BROOKLYN         0.013864\n",
+       "MANHATTAN        0.037755\n",
+       "QUEENS           0.010143\n",
+       "STATEN ISLAND    0.007474\n",
+       "Unspecified      0.000141\n",
+       "Name: Borough, dtype: float64"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "noise_complaint_counts / complaint_counts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fae0b60d748>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(noise_complaint_counts / complaint_counts.astype(float)).plot(kind='bar')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So Manhattan really does complain more about noise than the other boroughs! Neat."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<style>\n",
+    "    @font-face {\n",
+    "        font-family: \"Computer Modern\";\n",
+    "        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
+    "    }\n",
+    "    div.cell{\n",
+    "        width:800px;\n",
+    "        margin-left:16% !important;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    h1 {\n",
+    "        font-family: Helvetica, serif;\n",
+    "    }\n",
+    "    h4{\n",
+    "        margin-top:12px;\n",
+    "        margin-bottom: 3px;\n",
+    "       }\n",
+    "    div.text_cell_render{\n",
+    "        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
+    "        line-height: 145%;\n",
+    "        font-size: 130%;\n",
+    "        width:800px;\n",
+    "        margin-left:auto;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    .CodeMirror{\n",
+    "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
+    "    }\n",
+    "    .text_cell_render h5 {\n",
+    "        font-weight: 300;\n",
+    "        font-size: 22pt;\n",
+    "        color: #4057A1;\n",
+    "        font-style: italic;\n",
+    "        margin-bottom: .5em;\n",
+    "        margin-top: 0.5em;\n",
+    "        display: block;\n",
+    "    }\n",
+    "    \n",
+    "    .warning{\n",
+    "        color: rgb( 240, 20, 20 )\n",
+    "        }  "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/cookbook/Chapter 4 - Find out on which weekday people bike the most with groupby and aggregate.ipynb b/cookbook/Chapter 4 - Find out on which weekday people bike the most with groupby and aggregate.ipynb
index 6792fe714..7f72eb7dd 100644
--- a/cookbook/Chapter 4 - Find out on which weekday people bike the most with groupby and aggregate.ipynb	
+++ b/cookbook/Chapter 4 - Find out on which weekday people bike the most with groupby and aggregate.ipynb	
@@ -3,23 +3,19 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "%matplotlib inline\n",
-    "\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "pd.set_option('display.mpl_style', 'default') # Make the graphs a bit prettier\n",
+    "plt.style.use('ggplot') # Make the graphs a bit prettier\n",
     "plt.rcParams['figure.figsize'] = (15, 5)\n",
     "plt.rcParams['font.family'] = 'sans-serif'\n",
     "\n",
     "# This is necessary to show lots of columns in pandas 0.12. \n",
     "# Not necessary in pandas 0.13.\n",
-    "pd.set_option('display.width', 5000) \n",
+    "pd.set_option('display.max_colwidth', 5000) \n",
     "pd.set_option('display.max_columns', 60)"
    ]
   },
@@ -47,14 +43,12 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f082e34dad0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f67efed4b38>"
       ]
      },
      "execution_count": 2,
@@ -63,1107 +57,14 @@
     },
     {
      "data": {
-      "image/png": [
-       "iVBORw0KGgoAAAANSUhEUgAAA3EAAAFXCAYAAAAMHsdOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
-       "AAALEgAACxIB0t1+/AAAIABJREFUeJzsvXmcHPV55/+pqq6+Z6bn1H0gBoMNSAgLCEYBYpzEduw1\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f084c534910>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1184,9 +85,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "berri_bikes = bikes[['Berri 1']].copy()"
@@ -1195,14 +94,25 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1217,23 +127,23 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-01-01</th>\n",
-       "      <td>  35</td>\n",
+       "      <td>35</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02</th>\n",
-       "      <td>  83</td>\n",
+       "      <td>83</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03</th>\n",
-       "      <td> 135</td>\n",
+       "      <td>135</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-04</th>\n",
-       "      <td> 144</td>\n",
+       "      <td>144</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-05</th>\n",
-       "      <td> 197</td>\n",
+       "      <td>197</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1268,16 +178,19 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<class 'pandas.tseries.index.DatetimeIndex'>\n",
-       "[2012-01-01, ..., 2012-11-05]\n",
-       "Length: 310, Freq: None, Timezone: None"
+       "DatetimeIndex(['2012-01-01', '2012-01-02', '2012-01-03', '2012-01-04',\n",
+       "               '2012-01-05', '2012-01-06', '2012-01-07', '2012-01-08',\n",
+       "               '2012-01-09', '2012-01-10',\n",
+       "               ...\n",
+       "               '2012-10-27', '2012-10-28', '2012-10-29', '2012-10-30',\n",
+       "               '2012-10-31', '2012-11-01', '2012-11-02', '2012-11-03',\n",
+       "               '2012-11-04', '2012-11-05'],\n",
+       "              dtype='datetime64[ns]', name='Date', length=310, freq=None)"
       ]
      },
      "execution_count": 5,
@@ -1301,32 +214,15 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
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-       "        2,  3,  4,  5], dtype=int32)"
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      "execution_count": 6,
@@ -1348,27 +244,15 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
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    "outputs": [
     {
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      "execution_count": 7,
@@ -1392,14 +276,25 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
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+       "        vertical-align: middle;\n",
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+       "    .dataframe thead th {\n",
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+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1416,28 +311,28 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-01-01</th>\n",
-       "      <td>  35</td>\n",
-       "      <td> 6</td>\n",
+       "      <td>35</td>\n",
+       "      <td>6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02</th>\n",
-       "      <td>  83</td>\n",
-       "      <td> 0</td>\n",
+       "      <td>83</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03</th>\n",
-       "      <td> 135</td>\n",
-       "      <td> 1</td>\n",
+       "      <td>135</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-04</th>\n",
-       "      <td> 144</td>\n",
-       "      <td> 2</td>\n",
+       "      <td>144</td>\n",
+       "      <td>2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-05</th>\n",
-       "      <td> 197</td>\n",
-       "      <td> 3</td>\n",
+       "      <td>197</td>\n",
+       "      <td>3</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1484,14 +379,25 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
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@@ -1506,31 +412,31 @@
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        "      <th>0</th>\n",
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        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td> 135305</td>\n",
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        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td> 152972</td>\n",
+       "      <td>152972</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td> 160131</td>\n",
+       "      <td>160131</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td> 141771</td>\n",
+       "      <td>141771</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td> 101578</td>\n",
+       "      <td>101578</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>  99310</td>\n",
+       "      <td>99310</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1568,14 +474,25 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1586,31 +503,31 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Monday</th>\n",
-       "      <td> 134298</td>\n",
+       "      <td>134298</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Tuesday</th>\n",
-       "      <td> 135305</td>\n",
+       "      <td>135305</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Wednesday</th>\n",
-       "      <td> 152972</td>\n",
+       "      <td>152972</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Thursday</th>\n",
-       "      <td> 160131</td>\n",
+       "      <td>160131</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Friday</th>\n",
-       "      <td> 141771</td>\n",
+       "      <td>141771</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Saturday</th>\n",
-       "      <td> 101578</td>\n",
+       "      <td>101578</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Sunday</th>\n",
-       "      <td>  99310</td>\n",
+       "      <td>99310</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1640,14 +557,12 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f082df35490>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f67edaf7b00>"
       ]
      },
      "execution_count": 11,
@@ -1656,326 +571,14 @@
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f084c53eb50>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2009,14 +612,12 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f082dd7f790>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f67edada668>"
       ]
      },
      "execution_count": 12,
@@ -2025,326 +626,14 @@
     },
     {
      "data": {
-      "image/png": [
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-       "+frGN74hr9ermpoaxcXFyWaz6eKLL9aBAwcUFxen7du3a8aMGf513nzzTV111VV66623dN1110mS\n",
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-       "888/V3R0tGbPnq3LL79czz//vNrb2zVkyBDNmzdPV1xxhSTptddeU2lpqex2u+69914lJiZK+vst\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f082dd74150>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2366,23 +655,23 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
-   "name": "python2"
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.8"
-  },
-  "signature": "sha256:fc65c5245eb0b7b16ea28251f067cbbe64e7da1b9340f0f03fc786c53807a96c"
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
  },
  "nbformat": 4,
- "nbformat_minor": 0
-}
\ No newline at end of file
+ "nbformat_minor": 1
+}
diff --git a/cookbook/Chapter 5 - Combining dataframes and scraping Canadian weather data.ipynb b/cookbook/Chapter 5 - Combining dataframes and scraping Canadian weather data.ipynb
index 277658ff3..5c4a4f02c 100644
--- a/cookbook/Chapter 5 - Combining dataframes and scraping Canadian weather data.ipynb	
+++ b/cookbook/Chapter 5 - Combining dataframes and scraping Canadian weather data.ipynb	
@@ -3,17 +3,14 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "%matplotlib inline\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "\n",
-    "pd.set_option('display.mpl_style', 'default')\n",
+    "plt.style.use('ggplot')\n",
     "plt.rcParams['figure.figsize'] = (15, 3)\n",
     "plt.rcParams['font.family'] = 'sans-serif'"
    ]
@@ -39,14 +36,12 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fbac6cffb90>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f414f716a58>"
       ]
      },
      "execution_count": 2,
@@ -55,1377 +50,14 @@
     },
     {
      "data": {
-      "image/png": [
-       "iVBORw0KGgoAAAANSUhEUgAAA4gAAAGECAYAAAB07Q6cAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
-       "AAALEgAACxIB0t1+/AAAIABJREFUeJzsnXmcXFWZ93/33tp6SboTkkAgEMImBAybIioDjDhx1BnJ\n",
-       "jDqo4Pa6zTgL4+74DjpuM+Mow6jjvL7z4oKiiCMaEEFQRCCIrCEhZCP7vnTSe9dyl/P+ce5zzrm3\n",
-       "blVXd1f6dnU/388nn05V3XvrnOfeqjq/+2yWEEKAYRiGYRiGYRiGmfHYaQ+AYRiGYRiGYRiGmRqw\n",
-       "QGQYhmEYhmEYhmEAsEBkGIZhGIZhGIZhQlggMgzDMAzDMAzDMABYIDIMwzAMwzAMwzAhLBAZhmEY\n",
-       "hmEYhmEYAEAm7QGMlSAI8MlPfhJz587FJz/5SQwNDeGmm25CT08P5s+fjw996EPo6OhIe5gMwzAM\n",
-       "wzAMwzAtR8t5EO+55x4sWrQIlmUBAFauXIlly5bhq1/9Ks477zysXLky5REyDMMwDMMwDMO0Ji0l\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbac6cff790>"
+       "<Figure size 1080x432 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1455,12 +87,10 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "url_template = \"http://climate.weather.gc.ca/climateData/bulkdata_e.html?format=csv&stationID=5415&Year={year}&Month={month}&timeframe=1&submit=Download+Data\""
+    "url_template = \"http://climate.weather.gc.ca/climate_data/bulk_data_e.html?format=csv&stationID=5415&Year={year}&Month={month}&timeframe=1&submit=Download+Data\""
    ]
   },
   {
@@ -1473,13 +103,20 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "http://climate.weather.gc.ca/climate_data/bulk_data_e.html?format=csv&stationID=5415&Year=2012&Month=3&timeframe=1&submit=Download+Data\n"
+     ]
+    }
+   ],
    "source": [
     "url = url_template.format(month=3, year=2012)\n",
-    "weather_mar2012 = pd.read_csv(url, skiprows=15, index_col='Date/Time', parse_dates=True, encoding='latin1', header=True)"
+    "print(url)\n",
+    "weather_mar2012 = pd.read_csv(url, skiprows=15, index_col='Date/Time', parse_dates=True, encoding='latin1')"
    ]
   },
   {
@@ -1494,14 +131,25 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1510,12 +158,12 @@
        "      <th>Month</th>\n",
        "      <th>Day</th>\n",
        "      <th>Time</th>\n",
-       "      <th>Data Quality</th>\n",
        "      <th>Temp (°C)</th>\n",
        "      <th>Temp Flag</th>\n",
        "      <th>Dew Point Temp (°C)</th>\n",
        "      <th>Dew Point Temp Flag</th>\n",
        "      <th>Rel Hum (%)</th>\n",
+       "      <th>Rel Hum Flag</th>\n",
        "      <th>...</th>\n",
        "      <th>Wind Spd Flag</th>\n",
        "      <th>Visibility (km)</th>\n",
@@ -1556,723 +204,723 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-03-01 00:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 00:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>00:00</td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 72</td>\n",
+       "      <td>72</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.97</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.97</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 01:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 01:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>01:00</td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 79</td>\n",
+       "      <td>79</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.87</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.87</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 02:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 02:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>02:00</td>\n",
        "      <td>-5.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 80</td>\n",
+       "      <td>80</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.80</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 03:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 03:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>03:00</td>\n",
        "      <td>-4.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 79</td>\n",
+       "      <td>79</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.69</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.69</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-12.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 04:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 04:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>04:00</td>\n",
        "      <td>-5.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.62</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.62</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-14</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-14.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 05:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 05:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>05:00</td>\n",
        "      <td>-5.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.58</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.58</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-14</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-14.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 06:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 06:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>06:00</td>\n",
        "      <td>-5.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.57</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.57</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-14</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-14.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 07:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 07:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>07:00</td>\n",
        "      <td>-4.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.59</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.59</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 08:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 08:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>08:00</td>\n",
        "      <td>-5.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.5</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.59</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.59</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-13.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 09:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 09:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>09:00</td>\n",
        "      <td>-4.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.5</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.60</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.60</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 10:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 10:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>10:00</td>\n",
        "      <td>-4.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.62</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.62</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 11:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 11:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11:00</td>\n",
        "      <td>-4.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.66</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.66</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 12:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 12:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12:00</td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.66</td>\n",
+       "      <td>1.2</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.66</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 13:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 13:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>13:00</td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.65</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.65</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 14:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 14:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>14:00</td>\n",
        "      <td>-3.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 81</td>\n",
+       "      <td>81</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.67</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.67</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-11.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-11</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 15:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 15:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>15:00</td>\n",
        "      <td>-3.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 80</td>\n",
+       "      <td>80</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.71</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.71</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-10.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-10</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 16:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 16:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>16:00</td>\n",
        "      <td>-2.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 80</td>\n",
+       "      <td>80</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.74</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.74</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -8</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-8.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 17:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 17:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>17:00</td>\n",
        "      <td>-2.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 80</td>\n",
+       "      <td>80</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.80</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -9</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-9.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 18:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 18:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>18:00</td>\n",
        "      <td>-3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 80</td>\n",
+       "      <td>80</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.87</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -9</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-9.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 19:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 19:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>19:00</td>\n",
        "      <td>-3.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 81</td>\n",
+       "      <td>81</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  3.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.93</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.93</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -9</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-9.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 20:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 20:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>20:00</td>\n",
        "      <td>-3.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 81</td>\n",
+       "      <td>81</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.95</td>\n",
+       "      <td>4.8</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.95</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-10</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-10.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 21:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 21:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21:00</td>\n",
        "      <td>-3.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 81</td>\n",
+       "      <td>81</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  6.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.98</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.98</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-10.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-10</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 22:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 22:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>22:00</td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.00</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.00</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-11</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-11.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 23:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  1</td>\n",
-       "      <td> 23:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23:00</td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.1</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 81</td>\n",
+       "      <td>81</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.04</td>\n",
+       "      <td>4.8</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>101.04</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-11</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-11.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 00:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  2</td>\n",
-       "      <td> 00:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>00:00</td>\n",
        "      <td>-4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  3.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.04</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.04</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-12.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 01:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  2</td>\n",
-       "      <td> 01:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>01:00</td>\n",
        "      <td>-5.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.09</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.09</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 02:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  2</td>\n",
-       "      <td> 02:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>02:00</td>\n",
        "      <td>-5.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  6.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.11</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.11</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 03:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  2</td>\n",
-       "      <td> 03:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>03:00</td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 83</td>\n",
+       "      <td>83</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.15</td>\n",
+       "      <td>4.8</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>101.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 04:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  2</td>\n",
-       "      <td> 04:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>04:00</td>\n",
        "      <td>-5.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  6.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.15</td>\n",
+       "      <td>6.4</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>101.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-13</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-13.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 05:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td>  2</td>\n",
-       "      <td> 05:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>05:00</td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 81</td>\n",
+       "      <td>81</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 12.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.15</td>\n",
+       "      <td>12.9</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>-12</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -2300,1049 +948,1049 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-30 18:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 18:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 3.9</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30</td>\n",
+       "      <td>18:00</td>\n",
+       "      <td>3.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 42</td>\n",
+       "      <td>42</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.26</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.26</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-30 19:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 19:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 3.1</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30</td>\n",
+       "      <td>19:00</td>\n",
+       "      <td>3.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 49</td>\n",
+       "      <td>49</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.29</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.29</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-30 20:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 20:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 3.0</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30</td>\n",
+       "      <td>20:00</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.4</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 43</td>\n",
+       "      <td>43</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.30</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-30 21:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 21:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.7</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30</td>\n",
+       "      <td>21:00</td>\n",
+       "      <td>1.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 45</td>\n",
+       "      <td>45</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.32</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.32</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-30 22:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 22:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 0.4</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30</td>\n",
+       "      <td>22:00</td>\n",
+       "      <td>0.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.1</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 53</td>\n",
+       "      <td>53</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.30</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-30 23:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 23:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.4</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30</td>\n",
+       "      <td>23:00</td>\n",
+       "      <td>1.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 51</td>\n",
+       "      <td>51</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.34</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.34</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 00:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 00:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.5</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>00:00</td>\n",
+       "      <td>1.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 47</td>\n",
+       "      <td>47</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.33</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.33</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 01:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 01:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.3</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>01:00</td>\n",
+       "      <td>1.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 44</td>\n",
+       "      <td>44</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.31</td>\n",
+       "      <td>25.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>101.31</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 02:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 02:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.3</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>02:00</td>\n",
+       "      <td>1.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 44</td>\n",
+       "      <td>44</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.29</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.29</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 03:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 03:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 0.7</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>03:00</td>\n",
+       "      <td>0.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 49</td>\n",
+       "      <td>49</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.30</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 04:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 04:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>04:00</td>\n",
        "      <td>-0.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.5</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 56</td>\n",
+       "      <td>56</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.32</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.32</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -5</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>-5.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 05:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 05:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>05:00</td>\n",
        "      <td>-0.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 52</td>\n",
+       "      <td>52</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.30</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>-5.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -5</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 06:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 06:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>06:00</td>\n",
        "      <td>-0.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 52</td>\n",
+       "      <td>52</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.32</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.32</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -5</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>-5.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 07:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 07:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>07:00</td>\n",
        "      <td>-0.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 51</td>\n",
+       "      <td>51</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.32</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.32</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> -5</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>-5.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 08:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 08:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 0.7</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>08:00</td>\n",
+       "      <td>0.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.5</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 50</td>\n",
+       "      <td>50</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.33</td>\n",
+       "      <td>48.3</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>101.33</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 09:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 09:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.5</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>09:00</td>\n",
+       "      <td>1.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 50</td>\n",
+       "      <td>50</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.34</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.34</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 10:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 10:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 2.9</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>10:00</td>\n",
+       "      <td>2.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.1</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 44</td>\n",
+       "      <td>44</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.30</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.30</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 11:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 11:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 4.6</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>11:00</td>\n",
+       "      <td>4.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 35</td>\n",
+       "      <td>35</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.24</td>\n",
+       "      <td>48.3</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>101.24</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 12:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 12:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 6.4</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>12:00</td>\n",
+       "      <td>6.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.1</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 37</td>\n",
+       "      <td>37</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.16</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.16</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 13:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 13:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 6.5</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>13:00</td>\n",
+       "      <td>6.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.08</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.08</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 14:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 14:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 7.7</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>14:00</td>\n",
+       "      <td>7.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.5</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 31</td>\n",
+       "      <td>31</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 101.01</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>101.01</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 15:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 15:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 7.7</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>15:00</td>\n",
+       "      <td>7.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.6</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.94</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.94</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 16:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 16:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 8.4</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>16:00</td>\n",
+       "      <td>8.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 31</td>\n",
+       "      <td>31</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.89</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.89</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 17:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 17:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 7.9</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>17:00</td>\n",
+       "      <td>7.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.1</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 31</td>\n",
+       "      <td>31</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.88</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.88</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 18:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 18:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 7.0</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>18:00</td>\n",
+       "      <td>7.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 33</td>\n",
+       "      <td>33</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 48.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.87</td>\n",
+       "      <td>48.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.87</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 19:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 19:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 5.9</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>19:00</td>\n",
+       "      <td>5.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 36</td>\n",
+       "      <td>36</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.88</td>\n",
+       "      <td>25.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.88</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 20:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 20:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 4.4</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>20:00</td>\n",
+       "      <td>4.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.2</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 43</td>\n",
+       "      <td>43</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.85</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.85</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 21:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 21:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 2.6</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>21:00</td>\n",
+       "      <td>2.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.3</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 52</td>\n",
+       "      <td>52</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.86</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.86</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 22:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 22:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 2.7</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>22:00</td>\n",
+       "      <td>2.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.7</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 50</td>\n",
+       "      <td>50</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.82</td>\n",
+       "      <td>25.0</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>100.82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31 23:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 31</td>\n",
-       "      <td> 23:00</td>\n",
-       "      <td>  </td>\n",
-       "      <td> 1.5</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>31</td>\n",
+       "      <td>23:00</td>\n",
+       "      <td>1.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.9</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 54</td>\n",
+       "      <td>54</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> 100.79</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>100.79</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>744 rows × 24 columns</p>\n",
+       "<p>744 rows × 23 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "                     Year  Month  Day   Time Data Quality  Temp (°C)  \\\n",
-       "Date/Time                                                               \n",
-       "2012-03-01 00:00:00  2012      3    1  00:00                     -5.5   \n",
-       "2012-03-01 01:00:00  2012      3    1  01:00                     -5.7   \n",
-       "2012-03-01 02:00:00  2012      3    1  02:00                     -5.4   \n",
-       "2012-03-01 03:00:00  2012      3    1  03:00                     -4.7   \n",
-       "2012-03-01 04:00:00  2012      3    1  04:00                     -5.4   \n",
-       "2012-03-01 05:00:00  2012      3    1  05:00                     -5.3   \n",
-       "2012-03-01 06:00:00  2012      3    1  06:00                     -5.2   \n",
-       "2012-03-01 07:00:00  2012      3    1  07:00                     -4.9   \n",
-       "2012-03-01 08:00:00  2012      3    1  08:00                     -5.0   \n",
-       "2012-03-01 09:00:00  2012      3    1  09:00                     -4.9   \n",
-       "2012-03-01 10:00:00  2012      3    1  10:00                     -4.7   \n",
-       "2012-03-01 11:00:00  2012      3    1  11:00                     -4.4   \n",
-       "2012-03-01 12:00:00  2012      3    1  12:00                     -4.3   \n",
-       "2012-03-01 13:00:00  2012      3    1  13:00                     -4.3   \n",
-       "2012-03-01 14:00:00  2012      3    1  14:00                     -3.9   \n",
-       "2012-03-01 15:00:00  2012      3    1  15:00                     -3.3   \n",
-       "2012-03-01 16:00:00  2012      3    1  16:00                     -2.7   \n",
-       "2012-03-01 17:00:00  2012      3    1  17:00                     -2.9   \n",
-       "2012-03-01 18:00:00  2012      3    1  18:00                     -3.0   \n",
-       "2012-03-01 19:00:00  2012      3    1  19:00                     -3.6   \n",
-       "2012-03-01 20:00:00  2012      3    1  20:00                     -3.7   \n",
-       "2012-03-01 21:00:00  2012      3    1  21:00                     -3.9   \n",
-       "2012-03-01 22:00:00  2012      3    1  22:00                     -4.3   \n",
-       "2012-03-01 23:00:00  2012      3    1  23:00                     -4.3   \n",
-       "2012-03-02 00:00:00  2012      3    2  00:00                     -4.8   \n",
-       "2012-03-02 01:00:00  2012      3    2  01:00                     -5.3   \n",
-       "2012-03-02 02:00:00  2012      3    2  02:00                     -5.2   \n",
-       "2012-03-02 03:00:00  2012      3    2  03:00                     -5.5   \n",
-       "2012-03-02 04:00:00  2012      3    2  04:00                     -5.6   \n",
-       "2012-03-02 05:00:00  2012      3    2  05:00                     -5.5   \n",
-       "...                   ...    ...  ...    ...          ...         ...   \n",
-       "2012-03-30 18:00:00  2012      3   30  18:00                      3.9   \n",
-       "2012-03-30 19:00:00  2012      3   30  19:00                      3.1   \n",
-       "2012-03-30 20:00:00  2012      3   30  20:00                      3.0   \n",
-       "2012-03-30 21:00:00  2012      3   30  21:00                      1.7   \n",
-       "2012-03-30 22:00:00  2012      3   30  22:00                      0.4   \n",
-       "2012-03-30 23:00:00  2012      3   30  23:00                      1.4   \n",
-       "2012-03-31 00:00:00  2012      3   31  00:00                      1.5   \n",
-       "2012-03-31 01:00:00  2012      3   31  01:00                      1.3   \n",
-       "2012-03-31 02:00:00  2012      3   31  02:00                      1.3   \n",
-       "2012-03-31 03:00:00  2012      3   31  03:00                      0.7   \n",
-       "2012-03-31 04:00:00  2012      3   31  04:00                     -0.9   \n",
-       "2012-03-31 05:00:00  2012      3   31  05:00                     -0.6   \n",
-       "2012-03-31 06:00:00  2012      3   31  06:00                     -0.5   \n",
-       "2012-03-31 07:00:00  2012      3   31  07:00                     -0.3   \n",
-       "2012-03-31 08:00:00  2012      3   31  08:00                      0.7   \n",
-       "2012-03-31 09:00:00  2012      3   31  09:00                      1.5   \n",
-       "2012-03-31 10:00:00  2012      3   31  10:00                      2.9   \n",
-       "2012-03-31 11:00:00  2012      3   31  11:00                      4.6   \n",
-       "2012-03-31 12:00:00  2012      3   31  12:00                      6.4   \n",
-       "2012-03-31 13:00:00  2012      3   31  13:00                      6.5   \n",
-       "2012-03-31 14:00:00  2012      3   31  14:00                      7.7   \n",
-       "2012-03-31 15:00:00  2012      3   31  15:00                      7.7   \n",
-       "2012-03-31 16:00:00  2012      3   31  16:00                      8.4   \n",
-       "2012-03-31 17:00:00  2012      3   31  17:00                      7.9   \n",
-       "2012-03-31 18:00:00  2012      3   31  18:00                      7.0   \n",
-       "2012-03-31 19:00:00  2012      3   31  19:00                      5.9   \n",
-       "2012-03-31 20:00:00  2012      3   31  20:00                      4.4   \n",
-       "2012-03-31 21:00:00  2012      3   31  21:00                      2.6   \n",
-       "2012-03-31 22:00:00  2012      3   31  22:00                      2.7   \n",
-       "2012-03-31 23:00:00  2012      3   31  23:00                      1.5   \n",
+       "                     Year  Month  Day   Time  Temp (°C)  Temp Flag  \\\n",
+       "Date/Time                                                             \n",
+       "2012-03-01 00:00:00  2012      3    1  00:00        -5.5        NaN   \n",
+       "2012-03-01 01:00:00  2012      3    1  01:00        -5.7        NaN   \n",
+       "2012-03-01 02:00:00  2012      3    1  02:00        -5.4        NaN   \n",
+       "2012-03-01 03:00:00  2012      3    1  03:00        -4.7        NaN   \n",
+       "2012-03-01 04:00:00  2012      3    1  04:00        -5.4        NaN   \n",
+       "2012-03-01 05:00:00  2012      3    1  05:00        -5.3        NaN   \n",
+       "2012-03-01 06:00:00  2012      3    1  06:00        -5.2        NaN   \n",
+       "2012-03-01 07:00:00  2012      3    1  07:00        -4.9        NaN   \n",
+       "2012-03-01 08:00:00  2012      3    1  08:00        -5.0        NaN   \n",
+       "2012-03-01 09:00:00  2012      3    1  09:00        -4.9        NaN   \n",
+       "2012-03-01 10:00:00  2012      3    1  10:00        -4.7        NaN   \n",
+       "2012-03-01 11:00:00  2012      3    1  11:00        -4.4        NaN   \n",
+       "2012-03-01 12:00:00  2012      3    1  12:00        -4.3        NaN   \n",
+       "2012-03-01 13:00:00  2012      3    1  13:00        -4.3        NaN   \n",
+       "2012-03-01 14:00:00  2012      3    1  14:00        -3.9        NaN   \n",
+       "2012-03-01 15:00:00  2012      3    1  15:00        -3.3        NaN   \n",
+       "2012-03-01 16:00:00  2012      3    1  16:00        -2.7        NaN   \n",
+       "2012-03-01 17:00:00  2012      3    1  17:00        -2.9        NaN   \n",
+       "2012-03-01 18:00:00  2012      3    1  18:00        -3.0        NaN   \n",
+       "2012-03-01 19:00:00  2012      3    1  19:00        -3.6        NaN   \n",
+       "2012-03-01 20:00:00  2012      3    1  20:00        -3.7        NaN   \n",
+       "2012-03-01 21:00:00  2012      3    1  21:00        -3.9        NaN   \n",
+       "2012-03-01 22:00:00  2012      3    1  22:00        -4.3        NaN   \n",
+       "2012-03-01 23:00:00  2012      3    1  23:00        -4.3        NaN   \n",
+       "2012-03-02 00:00:00  2012      3    2  00:00        -4.8        NaN   \n",
+       "2012-03-02 01:00:00  2012      3    2  01:00        -5.3        NaN   \n",
+       "2012-03-02 02:00:00  2012      3    2  02:00        -5.2        NaN   \n",
+       "2012-03-02 03:00:00  2012      3    2  03:00        -5.5        NaN   \n",
+       "2012-03-02 04:00:00  2012      3    2  04:00        -5.6        NaN   \n",
+       "2012-03-02 05:00:00  2012      3    2  05:00        -5.5        NaN   \n",
+       "...                   ...    ...  ...    ...         ...        ...   \n",
+       "2012-03-30 18:00:00  2012      3   30  18:00         3.9        NaN   \n",
+       "2012-03-30 19:00:00  2012      3   30  19:00         3.1        NaN   \n",
+       "2012-03-30 20:00:00  2012      3   30  20:00         3.0        NaN   \n",
+       "2012-03-30 21:00:00  2012      3   30  21:00         1.7        NaN   \n",
+       "2012-03-30 22:00:00  2012      3   30  22:00         0.4        NaN   \n",
+       "2012-03-30 23:00:00  2012      3   30  23:00         1.4        NaN   \n",
+       "2012-03-31 00:00:00  2012      3   31  00:00         1.5        NaN   \n",
+       "2012-03-31 01:00:00  2012      3   31  01:00         1.3        NaN   \n",
+       "2012-03-31 02:00:00  2012      3   31  02:00         1.3        NaN   \n",
+       "2012-03-31 03:00:00  2012      3   31  03:00         0.7        NaN   \n",
+       "2012-03-31 04:00:00  2012      3   31  04:00        -0.9        NaN   \n",
+       "2012-03-31 05:00:00  2012      3   31  05:00        -0.6        NaN   \n",
+       "2012-03-31 06:00:00  2012      3   31  06:00        -0.5        NaN   \n",
+       "2012-03-31 07:00:00  2012      3   31  07:00        -0.3        NaN   \n",
+       "2012-03-31 08:00:00  2012      3   31  08:00         0.7        NaN   \n",
+       "2012-03-31 09:00:00  2012      3   31  09:00         1.5        NaN   \n",
+       "2012-03-31 10:00:00  2012      3   31  10:00         2.9        NaN   \n",
+       "2012-03-31 11:00:00  2012      3   31  11:00         4.6        NaN   \n",
+       "2012-03-31 12:00:00  2012      3   31  12:00         6.4        NaN   \n",
+       "2012-03-31 13:00:00  2012      3   31  13:00         6.5        NaN   \n",
+       "2012-03-31 14:00:00  2012      3   31  14:00         7.7        NaN   \n",
+       "2012-03-31 15:00:00  2012      3   31  15:00         7.7        NaN   \n",
+       "2012-03-31 16:00:00  2012      3   31  16:00         8.4        NaN   \n",
+       "2012-03-31 17:00:00  2012      3   31  17:00         7.9        NaN   \n",
+       "2012-03-31 18:00:00  2012      3   31  18:00         7.0        NaN   \n",
+       "2012-03-31 19:00:00  2012      3   31  19:00         5.9        NaN   \n",
+       "2012-03-31 20:00:00  2012      3   31  20:00         4.4        NaN   \n",
+       "2012-03-31 21:00:00  2012      3   31  21:00         2.6        NaN   \n",
+       "2012-03-31 22:00:00  2012      3   31  22:00         2.7        NaN   \n",
+       "2012-03-31 23:00:00  2012      3   31  23:00         1.5        NaN   \n",
        "\n",
-       "                     Temp Flag  Dew Point Temp (°C)  Dew Point Temp Flag  \\\n",
-       "Date/Time                                                                   \n",
-       "2012-03-01 00:00:00        NaN                  -9.7                  NaN   \n",
-       "2012-03-01 01:00:00        NaN                  -8.7                  NaN   \n",
-       "2012-03-01 02:00:00        NaN                  -8.3                  NaN   \n",
-       "2012-03-01 03:00:00        NaN                  -7.7                  NaN   \n",
-       "2012-03-01 04:00:00        NaN                  -7.8                  NaN   \n",
-       "2012-03-01 05:00:00        NaN                  -7.9                  NaN   \n",
-       "2012-03-01 06:00:00        NaN                  -7.8                  NaN   \n",
-       "2012-03-01 07:00:00        NaN                  -7.4                  NaN   \n",
-       "2012-03-01 08:00:00        NaN                  -7.5                  NaN   \n",
-       "2012-03-01 09:00:00        NaN                  -7.5                  NaN   \n",
-       "2012-03-01 10:00:00        NaN                  -7.3                  NaN   \n",
-       "2012-03-01 11:00:00        NaN                  -6.8                  NaN   \n",
-       "2012-03-01 12:00:00        NaN                  -6.8                  NaN   \n",
-       "2012-03-01 13:00:00        NaN                  -6.9                  NaN   \n",
-       "2012-03-01 14:00:00        NaN                  -6.6                  NaN   \n",
-       "2012-03-01 15:00:00        NaN                  -6.2                  NaN   \n",
-       "2012-03-01 16:00:00        NaN                  -5.7                  NaN   \n",
-       "2012-03-01 17:00:00        NaN                  -5.9                  NaN   \n",
-       "2012-03-01 18:00:00        NaN                  -6.0                  NaN   \n",
-       "2012-03-01 19:00:00        NaN                  -6.4                  NaN   \n",
-       "2012-03-01 20:00:00        NaN                  -6.4                  NaN   \n",
-       "2012-03-01 21:00:00        NaN                  -6.7                  NaN   \n",
-       "2012-03-01 22:00:00        NaN                  -6.9                  NaN   \n",
-       "2012-03-01 23:00:00        NaN                  -7.1                  NaN   \n",
-       "2012-03-02 00:00:00        NaN                  -7.3                  NaN   \n",
-       "2012-03-02 01:00:00        NaN                  -7.9                  NaN   \n",
-       "2012-03-02 02:00:00        NaN                  -7.8                  NaN   \n",
-       "2012-03-02 03:00:00        NaN                  -7.9                  NaN   \n",
-       "2012-03-02 04:00:00        NaN                  -8.2                  NaN   \n",
-       "2012-03-02 05:00:00        NaN                  -8.3                  NaN   \n",
-       "...                        ...                   ...                  ...   \n",
-       "2012-03-30 18:00:00        NaN                  -7.9                  NaN   \n",
-       "2012-03-30 19:00:00        NaN                  -6.7                  NaN   \n",
-       "2012-03-30 20:00:00        NaN                  -8.4                  NaN   \n",
-       "2012-03-30 21:00:00        NaN                  -9.0                  NaN   \n",
-       "2012-03-30 22:00:00        NaN                  -8.1                  NaN   \n",
-       "2012-03-30 23:00:00        NaN                  -7.7                  NaN   \n",
-       "2012-03-31 00:00:00        NaN                  -8.6                  NaN   \n",
-       "2012-03-31 01:00:00        NaN                  -9.6                  NaN   \n",
-       "2012-03-31 02:00:00        NaN                  -9.7                  NaN   \n",
-       "2012-03-31 03:00:00        NaN                  -8.8                  NaN   \n",
-       "2012-03-31 04:00:00        NaN                  -8.5                  NaN   \n",
-       "2012-03-31 05:00:00        NaN                  -9.2                  NaN   \n",
-       "2012-03-31 06:00:00        NaN                  -9.2                  NaN   \n",
-       "2012-03-31 07:00:00        NaN                  -9.2                  NaN   \n",
-       "2012-03-31 08:00:00        NaN                  -8.5                  NaN   \n",
-       "2012-03-31 09:00:00        NaN                  -7.8                  NaN   \n",
-       "2012-03-31 10:00:00        NaN                  -8.1                  NaN   \n",
-       "2012-03-31 11:00:00        NaN                  -9.7                  NaN   \n",
-       "2012-03-31 12:00:00        NaN                  -7.1                  NaN   \n",
-       "2012-03-31 13:00:00        NaN                  -9.7                  NaN   \n",
-       "2012-03-31 14:00:00        NaN                  -8.5                  NaN   \n",
-       "2012-03-31 15:00:00        NaN                  -8.6                  NaN   \n",
-       "2012-03-31 16:00:00        NaN                  -7.7                  NaN   \n",
-       "2012-03-31 17:00:00        NaN                  -8.1                  NaN   \n",
-       "2012-03-31 18:00:00        NaN                  -8.2                  NaN   \n",
-       "2012-03-31 19:00:00        NaN                  -8.0                  NaN   \n",
-       "2012-03-31 20:00:00        NaN                  -7.2                  NaN   \n",
-       "2012-03-31 21:00:00        NaN                  -6.3                  NaN   \n",
-       "2012-03-31 22:00:00        NaN                  -6.7                  NaN   \n",
-       "2012-03-31 23:00:00        NaN                  -6.9                  NaN   \n",
+       "                     Dew Point Temp (°C)  Dew Point Temp Flag  Rel Hum (%)  \\\n",
+       "Date/Time                                                                     \n",
+       "2012-03-01 00:00:00                  -9.7                  NaN           72   \n",
+       "2012-03-01 01:00:00                  -8.7                  NaN           79   \n",
+       "2012-03-01 02:00:00                  -8.3                  NaN           80   \n",
+       "2012-03-01 03:00:00                  -7.7                  NaN           79   \n",
+       "2012-03-01 04:00:00                  -7.8                  NaN           83   \n",
+       "2012-03-01 05:00:00                  -7.9                  NaN           82   \n",
+       "2012-03-01 06:00:00                  -7.8                  NaN           82   \n",
+       "2012-03-01 07:00:00                  -7.4                  NaN           83   \n",
+       "2012-03-01 08:00:00                  -7.5                  NaN           83   \n",
+       "2012-03-01 09:00:00                  -7.5                  NaN           82   \n",
+       "2012-03-01 10:00:00                  -7.3                  NaN           82   \n",
+       "2012-03-01 11:00:00                  -6.8                  NaN           83   \n",
+       "2012-03-01 12:00:00                  -6.8                  NaN           83   \n",
+       "2012-03-01 13:00:00                  -6.9                  NaN           82   \n",
+       "2012-03-01 14:00:00                  -6.6                  NaN           81   \n",
+       "2012-03-01 15:00:00                  -6.2                  NaN           80   \n",
+       "2012-03-01 16:00:00                  -5.7                  NaN           80   \n",
+       "2012-03-01 17:00:00                  -5.9                  NaN           80   \n",
+       "2012-03-01 18:00:00                  -6.0                  NaN           80   \n",
+       "2012-03-01 19:00:00                  -6.4                  NaN           81   \n",
+       "2012-03-01 20:00:00                  -6.4                  NaN           81   \n",
+       "2012-03-01 21:00:00                  -6.7                  NaN           81   \n",
+       "2012-03-01 22:00:00                  -6.9                  NaN           82   \n",
+       "2012-03-01 23:00:00                  -7.1                  NaN           81   \n",
+       "2012-03-02 00:00:00                  -7.3                  NaN           83   \n",
+       "2012-03-02 01:00:00                  -7.9                  NaN           82   \n",
+       "2012-03-02 02:00:00                  -7.8                  NaN           82   \n",
+       "2012-03-02 03:00:00                  -7.9                  NaN           83   \n",
+       "2012-03-02 04:00:00                  -8.2                  NaN           82   \n",
+       "2012-03-02 05:00:00                  -8.3                  NaN           81   \n",
+       "...                                   ...                  ...          ...   \n",
+       "2012-03-30 18:00:00                  -7.9                  NaN           42   \n",
+       "2012-03-30 19:00:00                  -6.7                  NaN           49   \n",
+       "2012-03-30 20:00:00                  -8.4                  NaN           43   \n",
+       "2012-03-30 21:00:00                  -9.0                  NaN           45   \n",
+       "2012-03-30 22:00:00                  -8.1                  NaN           53   \n",
+       "2012-03-30 23:00:00                  -7.7                  NaN           51   \n",
+       "2012-03-31 00:00:00                  -8.6                  NaN           47   \n",
+       "2012-03-31 01:00:00                  -9.6                  NaN           44   \n",
+       "2012-03-31 02:00:00                  -9.7                  NaN           44   \n",
+       "2012-03-31 03:00:00                  -8.8                  NaN           49   \n",
+       "2012-03-31 04:00:00                  -8.5                  NaN           56   \n",
+       "2012-03-31 05:00:00                  -9.2                  NaN           52   \n",
+       "2012-03-31 06:00:00                  -9.2                  NaN           52   \n",
+       "2012-03-31 07:00:00                  -9.2                  NaN           51   \n",
+       "2012-03-31 08:00:00                  -8.5                  NaN           50   \n",
+       "2012-03-31 09:00:00                  -7.8                  NaN           50   \n",
+       "2012-03-31 10:00:00                  -8.1                  NaN           44   \n",
+       "2012-03-31 11:00:00                  -9.7                  NaN           35   \n",
+       "2012-03-31 12:00:00                  -7.1                  NaN           37   \n",
+       "2012-03-31 13:00:00                  -9.7                  NaN           30   \n",
+       "2012-03-31 14:00:00                  -8.5                  NaN           31   \n",
+       "2012-03-31 15:00:00                  -8.6                  NaN           30   \n",
+       "2012-03-31 16:00:00                  -7.7                  NaN           31   \n",
+       "2012-03-31 17:00:00                  -8.1                  NaN           31   \n",
+       "2012-03-31 18:00:00                  -8.2                  NaN           33   \n",
+       "2012-03-31 19:00:00                  -8.0                  NaN           36   \n",
+       "2012-03-31 20:00:00                  -7.2                  NaN           43   \n",
+       "2012-03-31 21:00:00                  -6.3                  NaN           52   \n",
+       "2012-03-31 22:00:00                  -6.7                  NaN           50   \n",
+       "2012-03-31 23:00:00                  -6.9                  NaN           54   \n",
        "\n",
-       "                     Rel Hum (%)      ...        Wind Spd Flag  \\\n",
-       "Date/Time                             ...                        \n",
-       "2012-03-01 00:00:00           72      ...                  NaN   \n",
-       "2012-03-01 01:00:00           79      ...                  NaN   \n",
-       "2012-03-01 02:00:00           80      ...                  NaN   \n",
-       "2012-03-01 03:00:00           79      ...                  NaN   \n",
-       "2012-03-01 04:00:00           83      ...                  NaN   \n",
-       "2012-03-01 05:00:00           82      ...                  NaN   \n",
-       "2012-03-01 06:00:00           82      ...                  NaN   \n",
-       "2012-03-01 07:00:00           83      ...                  NaN   \n",
-       "2012-03-01 08:00:00           83      ...                  NaN   \n",
-       "2012-03-01 09:00:00           82      ...                  NaN   \n",
-       "2012-03-01 10:00:00           82      ...                  NaN   \n",
-       "2012-03-01 11:00:00           83      ...                  NaN   \n",
-       "2012-03-01 12:00:00           83      ...                  NaN   \n",
-       "2012-03-01 13:00:00           82      ...                  NaN   \n",
-       "2012-03-01 14:00:00           81      ...                  NaN   \n",
-       "2012-03-01 15:00:00           80      ...                  NaN   \n",
-       "2012-03-01 16:00:00           80      ...                  NaN   \n",
-       "2012-03-01 17:00:00           80      ...                  NaN   \n",
-       "2012-03-01 18:00:00           80      ...                  NaN   \n",
-       "2012-03-01 19:00:00           81      ...                  NaN   \n",
-       "2012-03-01 20:00:00           81      ...                  NaN   \n",
-       "2012-03-01 21:00:00           81      ...                  NaN   \n",
-       "2012-03-01 22:00:00           82      ...                  NaN   \n",
-       "2012-03-01 23:00:00           81      ...                  NaN   \n",
-       "2012-03-02 00:00:00           83      ...                  NaN   \n",
-       "2012-03-02 01:00:00           82      ...                  NaN   \n",
-       "2012-03-02 02:00:00           82      ...                  NaN   \n",
-       "2012-03-02 03:00:00           83      ...                  NaN   \n",
-       "2012-03-02 04:00:00           82      ...                  NaN   \n",
-       "2012-03-02 05:00:00           81      ...                  NaN   \n",
-       "...                          ...      ...                  ...   \n",
-       "2012-03-30 18:00:00           42      ...                  NaN   \n",
-       "2012-03-30 19:00:00           49      ...                  NaN   \n",
-       "2012-03-30 20:00:00           43      ...                  NaN   \n",
-       "2012-03-30 21:00:00           45      ...                  NaN   \n",
-       "2012-03-30 22:00:00           53      ...                  NaN   \n",
-       "2012-03-30 23:00:00           51      ...                  NaN   \n",
-       "2012-03-31 00:00:00           47      ...                  NaN   \n",
-       "2012-03-31 01:00:00           44      ...                  NaN   \n",
-       "2012-03-31 02:00:00           44      ...                  NaN   \n",
-       "2012-03-31 03:00:00           49      ...                  NaN   \n",
-       "2012-03-31 04:00:00           56      ...                  NaN   \n",
-       "2012-03-31 05:00:00           52      ...                  NaN   \n",
-       "2012-03-31 06:00:00           52      ...                  NaN   \n",
-       "2012-03-31 07:00:00           51      ...                  NaN   \n",
-       "2012-03-31 08:00:00           50      ...                  NaN   \n",
-       "2012-03-31 09:00:00           50      ...                  NaN   \n",
-       "2012-03-31 10:00:00           44      ...                  NaN   \n",
-       "2012-03-31 11:00:00           35      ...                  NaN   \n",
-       "2012-03-31 12:00:00           37      ...                  NaN   \n",
-       "2012-03-31 13:00:00           30      ...                  NaN   \n",
-       "2012-03-31 14:00:00           31      ...                  NaN   \n",
-       "2012-03-31 15:00:00           30      ...                  NaN   \n",
-       "2012-03-31 16:00:00           31      ...                  NaN   \n",
-       "2012-03-31 17:00:00           31      ...                  NaN   \n",
-       "2012-03-31 18:00:00           33      ...                  NaN   \n",
-       "2012-03-31 19:00:00           36      ...                  NaN   \n",
-       "2012-03-31 20:00:00           43      ...                  NaN   \n",
-       "2012-03-31 21:00:00           52      ...                  NaN   \n",
-       "2012-03-31 22:00:00           50      ...                  NaN   \n",
-       "2012-03-31 23:00:00           54      ...                  NaN   \n",
+       "                     Rel Hum Flag      ...        Wind Spd Flag  \\\n",
+       "Date/Time                              ...                        \n",
+       "2012-03-01 00:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 01:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 02:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 03:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 04:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 05:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 06:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 07:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 08:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 09:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 10:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 11:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 12:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 13:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 14:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 15:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 16:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 17:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 18:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 19:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 20:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 21:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 22:00:00           NaN      ...                  NaN   \n",
+       "2012-03-01 23:00:00           NaN      ...                  NaN   \n",
+       "2012-03-02 00:00:00           NaN      ...                  NaN   \n",
+       "2012-03-02 01:00:00           NaN      ...                  NaN   \n",
+       "2012-03-02 02:00:00           NaN      ...                  NaN   \n",
+       "2012-03-02 03:00:00           NaN      ...                  NaN   \n",
+       "2012-03-02 04:00:00           NaN      ...                  NaN   \n",
+       "2012-03-02 05:00:00           NaN      ...                  NaN   \n",
+       "...                           ...      ...                  ...   \n",
+       "2012-03-30 18:00:00           NaN      ...                  NaN   \n",
+       "2012-03-30 19:00:00           NaN      ...                  NaN   \n",
+       "2012-03-30 20:00:00           NaN      ...                  NaN   \n",
+       "2012-03-30 21:00:00           NaN      ...                  NaN   \n",
+       "2012-03-30 22:00:00           NaN      ...                  NaN   \n",
+       "2012-03-30 23:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 00:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 01:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 02:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 03:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 04:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 05:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 06:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 07:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 08:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 09:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 10:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 11:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 12:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 13:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 14:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 15:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 16:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 17:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 18:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 19:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 20:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 21:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 22:00:00           NaN      ...                  NaN   \n",
+       "2012-03-31 23:00:00           NaN      ...                  NaN   \n",
        "\n",
-       "                     Visibility (km)  Visibility Flag  Stn Press (kPa)  \\\n",
-       "Date/Time                                                                \n",
-       "2012-03-01 00:00:00              4.0              NaN           100.97   \n",
-       "2012-03-01 01:00:00              2.4              NaN           100.87   \n",
-       "2012-03-01 02:00:00              4.8              NaN           100.80   \n",
-       "2012-03-01 03:00:00              4.0              NaN           100.69   \n",
-       "2012-03-01 04:00:00              1.6              NaN           100.62   \n",
-       "2012-03-01 05:00:00              2.4              NaN           100.58   \n",
-       "2012-03-01 06:00:00              4.0              NaN           100.57   \n",
-       "2012-03-01 07:00:00              1.6              NaN           100.59   \n",
-       "2012-03-01 08:00:00              1.2              NaN           100.59   \n",
-       "2012-03-01 09:00:00              1.6              NaN           100.60   \n",
-       "2012-03-01 10:00:00              1.2              NaN           100.62   \n",
-       "2012-03-01 11:00:00              1.0              NaN           100.66   \n",
-       "2012-03-01 12:00:00              1.2              NaN           100.66   \n",
-       "2012-03-01 13:00:00              1.2              NaN           100.65   \n",
-       "2012-03-01 14:00:00              1.2              NaN           100.67   \n",
-       "2012-03-01 15:00:00              1.6              NaN           100.71   \n",
-       "2012-03-01 16:00:00              2.4              NaN           100.74   \n",
-       "2012-03-01 17:00:00              4.0              NaN           100.80   \n",
-       "2012-03-01 18:00:00              4.0              NaN           100.87   \n",
-       "2012-03-01 19:00:00              3.2              NaN           100.93   \n",
-       "2012-03-01 20:00:00              4.8              NaN           100.95   \n",
-       "2012-03-01 21:00:00              6.4              NaN           100.98   \n",
-       "2012-03-01 22:00:00              2.4              NaN           101.00   \n",
-       "2012-03-01 23:00:00              4.8              NaN           101.04   \n",
-       "2012-03-02 00:00:00              3.2              NaN           101.04   \n",
-       "2012-03-02 01:00:00              4.8              NaN           101.09   \n",
-       "2012-03-02 02:00:00              6.4              NaN           101.11   \n",
-       "2012-03-02 03:00:00              4.8              NaN           101.15   \n",
-       "2012-03-02 04:00:00              6.4              NaN           101.15   \n",
-       "2012-03-02 05:00:00             12.9              NaN           101.15   \n",
-       "...                              ...              ...              ...   \n",
-       "2012-03-30 18:00:00             24.1              NaN           101.26   \n",
-       "2012-03-30 19:00:00             25.0              NaN           101.29   \n",
-       "2012-03-30 20:00:00             25.0              NaN           101.30   \n",
-       "2012-03-30 21:00:00             25.0              NaN           101.32   \n",
-       "2012-03-30 22:00:00             25.0              NaN           101.30   \n",
-       "2012-03-30 23:00:00             25.0              NaN           101.34   \n",
-       "2012-03-31 00:00:00             25.0              NaN           101.33   \n",
-       "2012-03-31 01:00:00             25.0              NaN           101.31   \n",
-       "2012-03-31 02:00:00             25.0              NaN           101.29   \n",
-       "2012-03-31 03:00:00             25.0              NaN           101.30   \n",
-       "2012-03-31 04:00:00             25.0              NaN           101.32   \n",
-       "2012-03-31 05:00:00             25.0              NaN           101.30   \n",
-       "2012-03-31 06:00:00             48.3              NaN           101.32   \n",
-       "2012-03-31 07:00:00             48.3              NaN           101.32   \n",
-       "2012-03-31 08:00:00             48.3              NaN           101.33   \n",
-       "2012-03-31 09:00:00             48.3              NaN           101.34   \n",
-       "2012-03-31 10:00:00             48.3              NaN           101.30   \n",
-       "2012-03-31 11:00:00             48.3              NaN           101.24   \n",
-       "2012-03-31 12:00:00             48.3              NaN           101.16   \n",
-       "2012-03-31 13:00:00             48.3              NaN           101.08   \n",
-       "2012-03-31 14:00:00             48.3              NaN           101.01   \n",
-       "2012-03-31 15:00:00             48.3              NaN           100.94   \n",
-       "2012-03-31 16:00:00             48.3              NaN           100.89   \n",
-       "2012-03-31 17:00:00             48.3              NaN           100.88   \n",
-       "2012-03-31 18:00:00             48.3              NaN           100.87   \n",
-       "2012-03-31 19:00:00             25.0              NaN           100.88   \n",
-       "2012-03-31 20:00:00             25.0              NaN           100.85   \n",
-       "2012-03-31 21:00:00             25.0              NaN           100.86   \n",
-       "2012-03-31 22:00:00             25.0              NaN           100.82   \n",
-       "2012-03-31 23:00:00             25.0              NaN           100.79   \n",
+       "                     Visibility (km)  Visibility Flag Stn Press (kPa)  \\\n",
+       "Date/Time                                                               \n",
+       "2012-03-01 00:00:00              4.0              NaN          100.97   \n",
+       "2012-03-01 01:00:00              2.4              NaN          100.87   \n",
+       "2012-03-01 02:00:00              4.8              NaN          100.80   \n",
+       "2012-03-01 03:00:00              4.0              NaN          100.69   \n",
+       "2012-03-01 04:00:00              1.6              NaN          100.62   \n",
+       "2012-03-01 05:00:00              2.4              NaN          100.58   \n",
+       "2012-03-01 06:00:00              4.0              NaN          100.57   \n",
+       "2012-03-01 07:00:00              1.6              NaN          100.59   \n",
+       "2012-03-01 08:00:00              1.2              NaN          100.59   \n",
+       "2012-03-01 09:00:00              1.6              NaN          100.60   \n",
+       "2012-03-01 10:00:00              1.2              NaN          100.62   \n",
+       "2012-03-01 11:00:00              1.0              NaN          100.66   \n",
+       "2012-03-01 12:00:00              1.2              NaN          100.66   \n",
+       "2012-03-01 13:00:00              1.2              NaN          100.65   \n",
+       "2012-03-01 14:00:00              1.2              NaN          100.67   \n",
+       "2012-03-01 15:00:00              1.6              NaN          100.71   \n",
+       "2012-03-01 16:00:00              2.4              NaN          100.74   \n",
+       "2012-03-01 17:00:00              4.0              NaN          100.80   \n",
+       "2012-03-01 18:00:00              4.0              NaN          100.87   \n",
+       "2012-03-01 19:00:00              3.2              NaN          100.93   \n",
+       "2012-03-01 20:00:00              4.8              NaN          100.95   \n",
+       "2012-03-01 21:00:00              6.4              NaN          100.98   \n",
+       "2012-03-01 22:00:00              2.4              NaN          101.00   \n",
+       "2012-03-01 23:00:00              4.8              NaN          101.04   \n",
+       "2012-03-02 00:00:00              3.2              NaN          101.04   \n",
+       "2012-03-02 01:00:00              4.8              NaN          101.09   \n",
+       "2012-03-02 02:00:00              6.4              NaN          101.11   \n",
+       "2012-03-02 03:00:00              4.8              NaN          101.15   \n",
+       "2012-03-02 04:00:00              6.4              NaN          101.15   \n",
+       "2012-03-02 05:00:00             12.9              NaN          101.15   \n",
+       "...                              ...              ...             ...   \n",
+       "2012-03-30 18:00:00             24.1              NaN          101.26   \n",
+       "2012-03-30 19:00:00             25.0              NaN          101.29   \n",
+       "2012-03-30 20:00:00             25.0              NaN          101.30   \n",
+       "2012-03-30 21:00:00             25.0              NaN          101.32   \n",
+       "2012-03-30 22:00:00             25.0              NaN          101.30   \n",
+       "2012-03-30 23:00:00             25.0              NaN          101.34   \n",
+       "2012-03-31 00:00:00             25.0              NaN          101.33   \n",
+       "2012-03-31 01:00:00             25.0              NaN          101.31   \n",
+       "2012-03-31 02:00:00             25.0              NaN          101.29   \n",
+       "2012-03-31 03:00:00             25.0              NaN          101.30   \n",
+       "2012-03-31 04:00:00             25.0              NaN          101.32   \n",
+       "2012-03-31 05:00:00             25.0              NaN          101.30   \n",
+       "2012-03-31 06:00:00             48.3              NaN          101.32   \n",
+       "2012-03-31 07:00:00             48.3              NaN          101.32   \n",
+       "2012-03-31 08:00:00             48.3              NaN          101.33   \n",
+       "2012-03-31 09:00:00             48.3              NaN          101.34   \n",
+       "2012-03-31 10:00:00             48.3              NaN          101.30   \n",
+       "2012-03-31 11:00:00             48.3              NaN          101.24   \n",
+       "2012-03-31 12:00:00             48.3              NaN          101.16   \n",
+       "2012-03-31 13:00:00             48.3              NaN          101.08   \n",
+       "2012-03-31 14:00:00             48.3              NaN          101.01   \n",
+       "2012-03-31 15:00:00             48.3              NaN          100.94   \n",
+       "2012-03-31 16:00:00             48.3              NaN          100.89   \n",
+       "2012-03-31 17:00:00             48.3              NaN          100.88   \n",
+       "2012-03-31 18:00:00             48.3              NaN          100.87   \n",
+       "2012-03-31 19:00:00             25.0              NaN          100.88   \n",
+       "2012-03-31 20:00:00             25.0              NaN          100.85   \n",
+       "2012-03-31 21:00:00             25.0              NaN          100.86   \n",
+       "2012-03-31 22:00:00             25.0              NaN          100.82   \n",
+       "2012-03-31 23:00:00             25.0              NaN          100.79   \n",
        "\n",
-       "                    Stn Press Flag  Hmdx  Hmdx Flag  Wind Chill  \\\n",
-       "Date/Time                                                         \n",
-       "2012-03-01 00:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 01:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 02:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 03:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-01 04:00:00            NaN   NaN        NaN         -14   \n",
-       "2012-03-01 05:00:00            NaN   NaN        NaN         -14   \n",
-       "2012-03-01 06:00:00            NaN   NaN        NaN         -14   \n",
-       "2012-03-01 07:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 08:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 09:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 10:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-01 11:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-01 12:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-01 13:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-01 14:00:00            NaN   NaN        NaN         -11   \n",
-       "2012-03-01 15:00:00            NaN   NaN        NaN         -10   \n",
-       "2012-03-01 16:00:00            NaN   NaN        NaN          -8   \n",
-       "2012-03-01 17:00:00            NaN   NaN        NaN          -9   \n",
-       "2012-03-01 18:00:00            NaN   NaN        NaN          -9   \n",
-       "2012-03-01 19:00:00            NaN   NaN        NaN          -9   \n",
-       "2012-03-01 20:00:00            NaN   NaN        NaN         -10   \n",
-       "2012-03-01 21:00:00            NaN   NaN        NaN         -10   \n",
-       "2012-03-01 22:00:00            NaN   NaN        NaN         -11   \n",
-       "2012-03-01 23:00:00            NaN   NaN        NaN         -11   \n",
-       "2012-03-02 00:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-02 01:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-02 02:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-02 03:00:00            NaN   NaN        NaN         -12   \n",
-       "2012-03-02 04:00:00            NaN   NaN        NaN         -13   \n",
-       "2012-03-02 05:00:00            NaN   NaN        NaN         -12   \n",
-       "...                            ...   ...        ...         ...   \n",
-       "2012-03-30 18:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-30 19:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-30 20:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-30 21:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-30 22:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-30 23:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 00:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 01:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 02:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 03:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 04:00:00            NaN   NaN        NaN          -5   \n",
-       "2012-03-31 05:00:00            NaN   NaN        NaN          -5   \n",
-       "2012-03-31 06:00:00            NaN   NaN        NaN          -5   \n",
-       "2012-03-31 07:00:00            NaN   NaN        NaN          -5   \n",
-       "2012-03-31 08:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 09:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 10:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 11:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 12:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 13:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 14:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 15:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 16:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 17:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 18:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 19:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 20:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 21:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 22:00:00            NaN   NaN        NaN         NaN   \n",
-       "2012-03-31 23:00:00            NaN   NaN        NaN         NaN   \n",
+       "                     Stn Press Flag  Hmdx  Hmdx Flag  Wind Chill  \\\n",
+       "Date/Time                                                          \n",
+       "2012-03-01 00:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 01:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 02:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 03:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-01 04:00:00             NaN   NaN        NaN       -14.0   \n",
+       "2012-03-01 05:00:00             NaN   NaN        NaN       -14.0   \n",
+       "2012-03-01 06:00:00             NaN   NaN        NaN       -14.0   \n",
+       "2012-03-01 07:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 08:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 09:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 10:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-01 11:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-01 12:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-01 13:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-01 14:00:00             NaN   NaN        NaN       -11.0   \n",
+       "2012-03-01 15:00:00             NaN   NaN        NaN       -10.0   \n",
+       "2012-03-01 16:00:00             NaN   NaN        NaN        -8.0   \n",
+       "2012-03-01 17:00:00             NaN   NaN        NaN        -9.0   \n",
+       "2012-03-01 18:00:00             NaN   NaN        NaN        -9.0   \n",
+       "2012-03-01 19:00:00             NaN   NaN        NaN        -9.0   \n",
+       "2012-03-01 20:00:00             NaN   NaN        NaN       -10.0   \n",
+       "2012-03-01 21:00:00             NaN   NaN        NaN       -10.0   \n",
+       "2012-03-01 22:00:00             NaN   NaN        NaN       -11.0   \n",
+       "2012-03-01 23:00:00             NaN   NaN        NaN       -11.0   \n",
+       "2012-03-02 00:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-02 01:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-02 02:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-02 03:00:00             NaN   NaN        NaN       -12.0   \n",
+       "2012-03-02 04:00:00             NaN   NaN        NaN       -13.0   \n",
+       "2012-03-02 05:00:00             NaN   NaN        NaN       -12.0   \n",
+       "...                             ...   ...        ...         ...   \n",
+       "2012-03-30 18:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-30 19:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-30 20:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-30 21:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-30 22:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-30 23:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 00:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 01:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 02:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 03:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 04:00:00             NaN   NaN        NaN        -5.0   \n",
+       "2012-03-31 05:00:00             NaN   NaN        NaN        -5.0   \n",
+       "2012-03-31 06:00:00             NaN   NaN        NaN        -5.0   \n",
+       "2012-03-31 07:00:00             NaN   NaN        NaN        -5.0   \n",
+       "2012-03-31 08:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 09:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 10:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 11:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 12:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 13:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 14:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 15:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 16:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 17:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 18:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 19:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 20:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 21:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 22:00:00             NaN   NaN        NaN         NaN   \n",
+       "2012-03-31 23:00:00             NaN   NaN        NaN         NaN   \n",
        "\n",
        "                     Wind Chill Flag        Weather  \n",
        "Date/Time                                            \n",
@@ -3408,7 +2056,7 @@
        "2012-03-31 22:00:00              NaN          Clear  \n",
        "2012-03-31 23:00:00              NaN          Clear  \n",
        "\n",
-       "[744 rows x 24 columns]"
+       "[744 rows x 23 columns]"
       ]
      },
      "execution_count": 5,
@@ -3431,13 +2079,13 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": false
+    "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fbac690cd50>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f414e99dc18>"
       ]
      },
      "execution_count": 6,
@@ -3446,655 +2094,14 @@
     },
     {
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbac690c5d0>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -4116,13 +2123,11 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "weather_mar2012.columns = [\n",
-    "    u'Year', u'Month', u'Day', u'Time', u'Data Quality', u'Temp (C)', \n",
+    "    u'Year', u'Month', u'Day', u'Time', u'Temp (C)', \n",
     "    u'Temp Flag', u'Dew Point Temp (C)', u'Dew Point Temp Flag', \n",
     "    u'Rel Hum (%)', u'Rel Hum Flag', u'Wind Dir (10s deg)', u'Wind Dir Flag', \n",
     "    u'Wind Spd (km/h)', u'Wind Spd Flag', u'Visibility (km)', u'Visibility Flag',\n",
@@ -4144,14 +2149,25 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -4160,7 +2176,6 @@
        "      <th>Month</th>\n",
        "      <th>Day</th>\n",
        "      <th>Time</th>\n",
-       "      <th>Data Quality</th>\n",
        "      <th>Temp (C)</th>\n",
        "      <th>Dew Point Temp (C)</th>\n",
        "      <th>Rel Hum (%)</th>\n",
@@ -4182,113 +2197,107 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-03-01 00:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 1</td>\n",
-       "      <td> 00:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>00:00</td>\n",
        "      <td>-5.5</td>\n",
        "      <td>-9.7</td>\n",
-       "      <td> 72</td>\n",
-       "      <td> 24</td>\n",
-       "      <td> 4.0</td>\n",
-       "      <td> 100.97</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>72</td>\n",
+       "      <td>24</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>100.97</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 01:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 1</td>\n",
-       "      <td> 01:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>01:00</td>\n",
        "      <td>-5.7</td>\n",
        "      <td>-8.7</td>\n",
-       "      <td> 79</td>\n",
-       "      <td> 26</td>\n",
-       "      <td> 2.4</td>\n",
-       "      <td> 100.87</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>79</td>\n",
+       "      <td>26</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>100.87</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 02:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 1</td>\n",
-       "      <td> 02:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>02:00</td>\n",
        "      <td>-5.4</td>\n",
        "      <td>-8.3</td>\n",
-       "      <td> 80</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 4.8</td>\n",
-       "      <td> 100.80</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>80</td>\n",
+       "      <td>28</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>100.80</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 03:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 1</td>\n",
-       "      <td> 03:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>03:00</td>\n",
        "      <td>-4.7</td>\n",
        "      <td>-7.7</td>\n",
-       "      <td> 79</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 4.0</td>\n",
-       "      <td> 100.69</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>79</td>\n",
+       "      <td>28</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>100.69</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 04:00:00</th>\n",
-       "      <td> 2012</td>\n",
-       "      <td> 3</td>\n",
-       "      <td> 1</td>\n",
-       "      <td> 04:00</td>\n",
-       "      <td>  </td>\n",
+       "      <td>2012</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>04:00</td>\n",
        "      <td>-5.4</td>\n",
        "      <td>-7.8</td>\n",
-       "      <td> 83</td>\n",
-       "      <td> 35</td>\n",
-       "      <td> 1.6</td>\n",
-       "      <td> 100.62</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>83</td>\n",
+       "      <td>35</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>100.62</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                     Year  Month  Day   Time Data Quality  Temp (C)  \\\n",
-       "Date/Time                                                             \n",
-       "2012-03-01 00:00:00  2012      3    1  00:00                   -5.5   \n",
-       "2012-03-01 01:00:00  2012      3    1  01:00                   -5.7   \n",
-       "2012-03-01 02:00:00  2012      3    1  02:00                   -5.4   \n",
-       "2012-03-01 03:00:00  2012      3    1  03:00                   -4.7   \n",
-       "2012-03-01 04:00:00  2012      3    1  04:00                   -5.4   \n",
+       "                     Year  Month  Day   Time  Temp (C)  Dew Point Temp (C)  \\\n",
+       "Date/Time                                                                    \n",
+       "2012-03-01 00:00:00  2012      3    1  00:00      -5.5                -9.7   \n",
+       "2012-03-01 01:00:00  2012      3    1  01:00      -5.7                -8.7   \n",
+       "2012-03-01 02:00:00  2012      3    1  02:00      -5.4                -8.3   \n",
+       "2012-03-01 03:00:00  2012      3    1  03:00      -4.7                -7.7   \n",
+       "2012-03-01 04:00:00  2012      3    1  04:00      -5.4                -7.8   \n",
        "\n",
-       "                     Dew Point Temp (C)  Rel Hum (%)  Wind Spd (km/h)  \\\n",
-       "Date/Time                                                               \n",
-       "2012-03-01 00:00:00                -9.7           72               24   \n",
-       "2012-03-01 01:00:00                -8.7           79               26   \n",
-       "2012-03-01 02:00:00                -8.3           80               28   \n",
-       "2012-03-01 03:00:00                -7.7           79               28   \n",
-       "2012-03-01 04:00:00                -7.8           83               35   \n",
+       "                     Rel Hum (%)  Wind Spd (km/h)  Visibility (km)  \\\n",
+       "Date/Time                                                            \n",
+       "2012-03-01 00:00:00           72               24              4.0   \n",
+       "2012-03-01 01:00:00           79               26              2.4   \n",
+       "2012-03-01 02:00:00           80               28              4.8   \n",
+       "2012-03-01 03:00:00           79               28              4.0   \n",
+       "2012-03-01 04:00:00           83               35              1.6   \n",
        "\n",
-       "                     Visibility (km)  Stn Press (kPa) Weather  \n",
-       "Date/Time                                                      \n",
-       "2012-03-01 00:00:00              4.0           100.97    Snow  \n",
-       "2012-03-01 01:00:00              2.4           100.87    Snow  \n",
-       "2012-03-01 02:00:00              4.8           100.80    Snow  \n",
-       "2012-03-01 03:00:00              4.0           100.69    Snow  \n",
-       "2012-03-01 04:00:00              1.6           100.62    Snow  "
+       "                     Stn Press (kPa) Weather  \n",
+       "Date/Time                                     \n",
+       "2012-03-01 00:00:00           100.97    Snow  \n",
+       "2012-03-01 01:00:00           100.87    Snow  \n",
+       "2012-03-01 02:00:00           100.80    Snow  \n",
+       "2012-03-01 03:00:00           100.69    Snow  \n",
+       "2012-03-01 04:00:00           100.62    Snow  "
       ]
      },
      "execution_count": 8,
@@ -4305,7 +2314,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The Year/Month/Day/Time columns are redundant, though, and the Data Quality column doesn't look too useful. Let's get rid of those.\n",
+    "The Year/Month/Day/Time columns are redundant, though. Let's get rid of those.\n",
     "\n",
     "The `axis=1` argument means \"Drop columns\", like before. The default for operations like `dropna` and `drop` is always to operate on rows."
    ]
@@ -4313,14 +2322,25 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -4349,51 +2369,51 @@
        "      <th>2012-03-01 00:00:00</th>\n",
        "      <td>-5.5</td>\n",
        "      <td>-9.7</td>\n",
-       "      <td> 72</td>\n",
-       "      <td> 24</td>\n",
-       "      <td> 4.0</td>\n",
-       "      <td> 100.97</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>72</td>\n",
+       "      <td>24</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>100.97</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 01:00:00</th>\n",
        "      <td>-5.7</td>\n",
        "      <td>-8.7</td>\n",
-       "      <td> 79</td>\n",
-       "      <td> 26</td>\n",
-       "      <td> 2.4</td>\n",
-       "      <td> 100.87</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>79</td>\n",
+       "      <td>26</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>100.87</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 02:00:00</th>\n",
        "      <td>-5.4</td>\n",
        "      <td>-8.3</td>\n",
-       "      <td> 80</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 4.8</td>\n",
-       "      <td> 100.80</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>80</td>\n",
+       "      <td>28</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>100.80</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 03:00:00</th>\n",
        "      <td>-4.7</td>\n",
        "      <td>-7.7</td>\n",
-       "      <td> 79</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 4.0</td>\n",
-       "      <td> 100.69</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>79</td>\n",
+       "      <td>28</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>100.69</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 04:00:00</th>\n",
        "      <td>-5.4</td>\n",
        "      <td>-7.8</td>\n",
-       "      <td> 83</td>\n",
-       "      <td> 35</td>\n",
-       "      <td> 1.6</td>\n",
-       "      <td> 100.62</td>\n",
-       "      <td> Snow</td>\n",
+       "      <td>83</td>\n",
+       "      <td>35</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>100.62</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -4423,7 +2443,7 @@
     }
    ],
    "source": [
-    "weather_mar2012 = weather_mar2012.drop(['Year', 'Month', 'Day', 'Time', 'Data Quality'], axis=1)\n",
+    "weather_mar2012 = weather_mar2012.drop(['Year', 'Month', 'Day', 'Time'], axis=1)\n",
     "weather_mar2012[:5]"
    ]
   },
@@ -4451,15 +2471,13 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<bound method DataFrame.head of                      Temp (C)\n",
+      "<bound method NDFrame.head of                      Temp (C)\n",
       "Date/Time                    \n",
       "2012-03-01 00:00:00      -5.5\n",
       "2012-03-01 01:00:00      -5.7\n",
@@ -4529,7 +2547,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fbac6876b10>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f414e92cf60>"
       ]
      },
      "execution_count": 10,
@@ -4538,275 +2556,14 @@
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbac67dfa90>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -4845,19 +2602,17 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def download_weather_month(year, month):\n",
     "    if month == 1:\n",
     "        year += 1\n",
     "    url = url_template.format(year=year, month=month)\n",
-    "    weather_data = pd.read_csv(url, skiprows=15, index_col='Date/Time', parse_dates=True, header=True)\n",
+    "    weather_data = pd.read_csv(url, skiprows=15, index_col='Date/Time', parse_dates=True)\n",
     "    weather_data = weather_data.dropna(axis=1)\n",
     "    weather_data.columns = [col.replace('\\xb0', '') for col in weather_data.columns]\n",
-    "    weather_data = weather_data.drop(['Year', 'Day', 'Month', 'Time', 'Data Quality'], axis=1)\n",
+    "    weather_data = weather_data.drop(['Year', 'Day', 'Month', 'Time'], axis=1)\n",
     "    return weather_data"
    ]
   },
@@ -4871,14 +2626,25 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -4906,52 +2672,52 @@
        "    <tr>\n",
        "      <th>2013-01-01 00:00:00</th>\n",
        "      <td>-1.0</td>\n",
-       "      <td> -1.7</td>\n",
-       "      <td> 95</td>\n",
-       "      <td> 35</td>\n",
-       "      <td>  6.4</td>\n",
-       "      <td>  99.89</td>\n",
-       "      <td>         Snow</td>\n",
+       "      <td>-1.7</td>\n",
+       "      <td>95</td>\n",
+       "      <td>35</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>99.89</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 01:00:00</th>\n",
        "      <td>-2.0</td>\n",
-       "      <td> -5.1</td>\n",
-       "      <td> 79</td>\n",
-       "      <td> 35</td>\n",
-       "      <td> 16.1</td>\n",
-       "      <td>  99.93</td>\n",
-       "      <td> Mainly Clear</td>\n",
+       "      <td>-5.1</td>\n",
+       "      <td>79</td>\n",
+       "      <td>35</td>\n",
+       "      <td>16.1</td>\n",
+       "      <td>99.93</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 02:00:00</th>\n",
        "      <td>-2.7</td>\n",
-       "      <td> -6.0</td>\n",
-       "      <td> 78</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 100.08</td>\n",
-       "      <td>         Snow</td>\n",
+       "      <td>-6.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>28</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.08</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 03:00:00</th>\n",
        "      <td>-5.6</td>\n",
        "      <td>-11.7</td>\n",
-       "      <td> 62</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.21</td>\n",
-       "      <td>        Clear</td>\n",
+       "      <td>62</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.21</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 04:00:00</th>\n",
        "      <td>-7.7</td>\n",
        "      <td>-12.6</td>\n",
-       "      <td> 68</td>\n",
-       "      <td> 35</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 100.32</td>\n",
-       "      <td> Mainly Clear</td>\n",
+       "      <td>68</td>\n",
+       "      <td>35</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.32</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -5002,9 +2768,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "data_by_month = [download_weather_month(2012, i) for i in range(1, 13)]"
@@ -5020,14 +2784,25 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -5054,303 +2829,303 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2013-01-01 00:00:00</th>\n",
-       "      <td> -1.0</td>\n",
-       "      <td> -1.7</td>\n",
-       "      <td> 95</td>\n",
-       "      <td> 35</td>\n",
-       "      <td>  6.4</td>\n",
-       "      <td>  99.89</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1.7</td>\n",
+       "      <td>95</td>\n",
+       "      <td>35</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>99.89</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 01:00:00</th>\n",
-       "      <td> -2.0</td>\n",
-       "      <td> -5.1</td>\n",
-       "      <td> 79</td>\n",
-       "      <td> 35</td>\n",
-       "      <td> 16.1</td>\n",
-       "      <td>  99.93</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>-5.1</td>\n",
+       "      <td>79</td>\n",
+       "      <td>35</td>\n",
+       "      <td>16.1</td>\n",
+       "      <td>99.93</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 02:00:00</th>\n",
-       "      <td> -2.7</td>\n",
-       "      <td> -6.0</td>\n",
-       "      <td> 78</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 100.08</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-2.7</td>\n",
+       "      <td>-6.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>28</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.08</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 03:00:00</th>\n",
-       "      <td> -5.6</td>\n",
+       "      <td>-5.6</td>\n",
        "      <td>-11.7</td>\n",
-       "      <td> 62</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.21</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>62</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.21</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 04:00:00</th>\n",
-       "      <td> -7.7</td>\n",
+       "      <td>-7.7</td>\n",
        "      <td>-12.6</td>\n",
-       "      <td> 68</td>\n",
-       "      <td> 35</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 100.32</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>68</td>\n",
+       "      <td>35</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.32</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 05:00:00</th>\n",
-       "      <td> -9.7</td>\n",
+       "      <td>-9.7</td>\n",
        "      <td>-14.8</td>\n",
-       "      <td> 66</td>\n",
-       "      <td> 33</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.47</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>66</td>\n",
+       "      <td>33</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.47</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 06:00:00</th>\n",
        "      <td>-11.1</td>\n",
        "      <td>-17.0</td>\n",
-       "      <td> 62</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.65</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>62</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.65</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 07:00:00</th>\n",
        "      <td>-12.2</td>\n",
        "      <td>-17.2</td>\n",
-       "      <td> 66</td>\n",
-       "      <td> 20</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.78</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>66</td>\n",
+       "      <td>20</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.78</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 08:00:00</th>\n",
        "      <td>-13.0</td>\n",
        "      <td>-17.7</td>\n",
-       "      <td> 68</td>\n",
-       "      <td> 13</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.87</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>68</td>\n",
+       "      <td>13</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.87</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 09:00:00</th>\n",
        "      <td>-13.0</td>\n",
        "      <td>-17.3</td>\n",
-       "      <td> 70</td>\n",
-       "      <td> 20</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.86</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>70</td>\n",
+       "      <td>20</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.86</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 10:00:00</th>\n",
        "      <td>-12.6</td>\n",
        "      <td>-17.8</td>\n",
-       "      <td> 65</td>\n",
-       "      <td> 19</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.90</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>65</td>\n",
+       "      <td>19</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.90</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 11:00:00</th>\n",
        "      <td>-12.2</td>\n",
        "      <td>-17.6</td>\n",
-       "      <td> 64</td>\n",
-       "      <td> 22</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.88</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>64</td>\n",
+       "      <td>22</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.88</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 12:00:00</th>\n",
        "      <td>-11.8</td>\n",
        "      <td>-17.2</td>\n",
-       "      <td> 64</td>\n",
-       "      <td> 26</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.87</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>64</td>\n",
+       "      <td>26</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.87</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 13:00:00</th>\n",
        "      <td>-11.3</td>\n",
        "      <td>-17.4</td>\n",
-       "      <td> 61</td>\n",
-       "      <td> 26</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.83</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>61</td>\n",
+       "      <td>26</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.83</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 14:00:00</th>\n",
        "      <td>-11.3</td>\n",
        "      <td>-17.4</td>\n",
-       "      <td> 61</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.82</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>61</td>\n",
+       "      <td>28</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.82</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 15:00:00</th>\n",
        "      <td>-11.4</td>\n",
        "      <td>-17.6</td>\n",
-       "      <td> 60</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.85</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>60</td>\n",
+       "      <td>30</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.85</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 16:00:00</th>\n",
        "      <td>-12.0</td>\n",
        "      <td>-18.0</td>\n",
-       "      <td> 61</td>\n",
-       "      <td> 22</td>\n",
-       "      <td> 24.1</td>\n",
-       "      <td> 100.81</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>61</td>\n",
+       "      <td>22</td>\n",
+       "      <td>24.1</td>\n",
+       "      <td>100.81</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 17:00:00</th>\n",
        "      <td>-13.0</td>\n",
        "      <td>-18.4</td>\n",
-       "      <td> 64</td>\n",
-       "      <td> 19</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.90</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>64</td>\n",
+       "      <td>19</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.90</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 18:00:00</th>\n",
        "      <td>-13.4</td>\n",
        "      <td>-18.4</td>\n",
-       "      <td> 66</td>\n",
-       "      <td> 24</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.96</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>66</td>\n",
+       "      <td>24</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.96</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 19:00:00</th>\n",
        "      <td>-14.1</td>\n",
        "      <td>-18.7</td>\n",
-       "      <td> 68</td>\n",
-       "      <td> 20</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.02</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>68</td>\n",
+       "      <td>20</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.02</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 20:00:00</th>\n",
        "      <td>-14.3</td>\n",
        "      <td>-19.0</td>\n",
-       "      <td> 67</td>\n",
-       "      <td> 15</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.04</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>67</td>\n",
+       "      <td>15</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.04</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 21:00:00</th>\n",
        "      <td>-14.8</td>\n",
        "      <td>-19.5</td>\n",
-       "      <td> 67</td>\n",
-       "      <td> 15</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.98</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>67</td>\n",
+       "      <td>15</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.98</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 22:00:00</th>\n",
        "      <td>-16.3</td>\n",
        "      <td>-20.2</td>\n",
-       "      <td> 72</td>\n",
-       "      <td>  7</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.98</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>72</td>\n",
+       "      <td>7</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.98</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-01 23:00:00</th>\n",
        "      <td>-15.4</td>\n",
        "      <td>-19.8</td>\n",
-       "      <td> 69</td>\n",
-       "      <td> 11</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.99</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>69</td>\n",
+       "      <td>11</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.99</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02 00:00:00</th>\n",
        "      <td>-14.0</td>\n",
        "      <td>-18.4</td>\n",
-       "      <td> 69</td>\n",
-       "      <td> 11</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 100.96</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>69</td>\n",
+       "      <td>11</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.96</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02 01:00:00</th>\n",
        "      <td>-14.1</td>\n",
        "      <td>-18.3</td>\n",
-       "      <td> 70</td>\n",
-       "      <td> 11</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.91</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>70</td>\n",
+       "      <td>11</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.91</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02 02:00:00</th>\n",
        "      <td>-14.3</td>\n",
        "      <td>-18.3</td>\n",
-       "      <td> 72</td>\n",
-       "      <td> 13</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 100.94</td>\n",
-       "      <td>  Snow Showers</td>\n",
+       "      <td>72</td>\n",
+       "      <td>13</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.94</td>\n",
+       "      <td>Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02 03:00:00</th>\n",
        "      <td>-14.7</td>\n",
        "      <td>-18.0</td>\n",
-       "      <td> 76</td>\n",
-       "      <td>  9</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 100.91</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>76</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.91</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02 04:00:00</th>\n",
        "      <td>-14.2</td>\n",
        "      <td>-17.1</td>\n",
-       "      <td> 79</td>\n",
-       "      <td>  6</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.83</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>79</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.83</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2013-01-02 05:00:00</th>\n",
        "      <td>-14.3</td>\n",
        "      <td>-17.0</td>\n",
-       "      <td> 80</td>\n",
-       "      <td>  0</td>\n",
-       "      <td>  6.4</td>\n",
-       "      <td> 100.81</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>80</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>100.81</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -5366,301 +3141,301 @@
        "      <th>2012-12-30 18:00:00</th>\n",
        "      <td>-12.6</td>\n",
        "      <td>-16.0</td>\n",
-       "      <td> 76</td>\n",
-       "      <td> 24</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.36</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>76</td>\n",
+       "      <td>24</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.36</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-30 19:00:00</th>\n",
        "      <td>-13.4</td>\n",
        "      <td>-16.5</td>\n",
-       "      <td> 77</td>\n",
-       "      <td> 26</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.47</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>77</td>\n",
+       "      <td>26</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.47</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-30 20:00:00</th>\n",
        "      <td>-13.8</td>\n",
        "      <td>-16.5</td>\n",
-       "      <td> 80</td>\n",
-       "      <td> 24</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.52</td>\n",
-       "      <td>         Clear</td>\n",
+       "      <td>80</td>\n",
+       "      <td>24</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.52</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-30 21:00:00</th>\n",
        "      <td>-13.8</td>\n",
        "      <td>-16.5</td>\n",
-       "      <td> 80</td>\n",
-       "      <td> 20</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.50</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>80</td>\n",
+       "      <td>20</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.50</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-30 22:00:00</th>\n",
        "      <td>-13.7</td>\n",
        "      <td>-16.3</td>\n",
-       "      <td> 81</td>\n",
-       "      <td> 19</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.54</td>\n",
-       "      <td>  Mainly Clear</td>\n",
+       "      <td>81</td>\n",
+       "      <td>19</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.54</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-30 23:00:00</th>\n",
        "      <td>-12.1</td>\n",
        "      <td>-15.1</td>\n",
-       "      <td> 78</td>\n",
-       "      <td> 28</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.52</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>78</td>\n",
+       "      <td>28</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.52</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 00:00:00</th>\n",
        "      <td>-11.1</td>\n",
        "      <td>-14.4</td>\n",
-       "      <td> 77</td>\n",
-       "      <td> 26</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.51</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>77</td>\n",
+       "      <td>26</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.51</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 01:00:00</th>\n",
        "      <td>-10.7</td>\n",
        "      <td>-14.0</td>\n",
-       "      <td> 77</td>\n",
-       "      <td> 15</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.50</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>77</td>\n",
+       "      <td>15</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.50</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 02:00:00</th>\n",
        "      <td>-10.1</td>\n",
        "      <td>-13.4</td>\n",
-       "      <td> 77</td>\n",
-       "      <td>  9</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.45</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>77</td>\n",
+       "      <td>9</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.45</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 03:00:00</th>\n",
        "      <td>-11.8</td>\n",
        "      <td>-14.4</td>\n",
-       "      <td> 81</td>\n",
-       "      <td>  6</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.42</td>\n",
-       "      <td> Mostly Cloudy</td>\n",
+       "      <td>81</td>\n",
+       "      <td>6</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.42</td>\n",
+       "      <td>Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 04:00:00</th>\n",
        "      <td>-10.5</td>\n",
        "      <td>-12.8</td>\n",
-       "      <td> 83</td>\n",
-       "      <td> 11</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.34</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>83</td>\n",
+       "      <td>11</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.34</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 05:00:00</th>\n",
        "      <td>-10.2</td>\n",
        "      <td>-12.4</td>\n",
-       "      <td> 84</td>\n",
-       "      <td>  6</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.28</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.28</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 06:00:00</th>\n",
-       "      <td> -9.7</td>\n",
+       "      <td>-9.7</td>\n",
        "      <td>-11.7</td>\n",
-       "      <td> 85</td>\n",
-       "      <td>  4</td>\n",
-       "      <td> 25.0</td>\n",
-       "      <td> 101.23</td>\n",
-       "      <td>        Cloudy</td>\n",
+       "      <td>85</td>\n",
+       "      <td>4</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>101.23</td>\n",
+       "      <td>Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 07:00:00</th>\n",
-       "      <td> -9.3</td>\n",
+       "      <td>-9.3</td>\n",
        "      <td>-11.3</td>\n",
-       "      <td> 85</td>\n",
-       "      <td>  0</td>\n",
-       "      <td> 19.3</td>\n",
-       "      <td> 101.19</td>\n",
-       "      <td>  Snow Showers</td>\n",
+       "      <td>85</td>\n",
+       "      <td>0</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>101.19</td>\n",
+       "      <td>Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 08:00:00</th>\n",
-       "      <td> -8.6</td>\n",
+       "      <td>-8.6</td>\n",
        "      <td>-10.3</td>\n",
-       "      <td> 87</td>\n",
-       "      <td>  4</td>\n",
-       "      <td>  3.2</td>\n",
-       "      <td> 101.14</td>\n",
-       "      <td>  Snow Showers</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>101.14</td>\n",
+       "      <td>Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 09:00:00</th>\n",
-       "      <td> -8.1</td>\n",
-       "      <td> -9.6</td>\n",
-       "      <td> 89</td>\n",
-       "      <td>  4</td>\n",
-       "      <td>  2.4</td>\n",
-       "      <td> 101.09</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-8.1</td>\n",
+       "      <td>-9.6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>101.09</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 10:00:00</th>\n",
-       "      <td> -7.4</td>\n",
-       "      <td> -8.9</td>\n",
-       "      <td> 89</td>\n",
-       "      <td>  4</td>\n",
-       "      <td>  6.4</td>\n",
-       "      <td> 101.05</td>\n",
-       "      <td>      Snow,Fog</td>\n",
+       "      <td>-7.4</td>\n",
+       "      <td>-8.9</td>\n",
+       "      <td>89</td>\n",
+       "      <td>4</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>101.05</td>\n",
+       "      <td>Snow,Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 11:00:00</th>\n",
-       "      <td> -6.7</td>\n",
-       "      <td> -7.9</td>\n",
-       "      <td> 91</td>\n",
-       "      <td>  9</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.93</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-6.7</td>\n",
+       "      <td>-7.9</td>\n",
+       "      <td>91</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.93</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 12:00:00</th>\n",
-       "      <td> -5.8</td>\n",
-       "      <td> -7.5</td>\n",
-       "      <td> 88</td>\n",
-       "      <td>  4</td>\n",
-       "      <td> 12.9</td>\n",
-       "      <td> 100.78</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-5.8</td>\n",
+       "      <td>-7.5</td>\n",
+       "      <td>88</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12.9</td>\n",
+       "      <td>100.78</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 13:00:00</th>\n",
-       "      <td> -4.6</td>\n",
-       "      <td> -6.6</td>\n",
-       "      <td> 86</td>\n",
-       "      <td>  4</td>\n",
-       "      <td> 12.9</td>\n",
-       "      <td> 100.63</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-4.6</td>\n",
+       "      <td>-6.6</td>\n",
+       "      <td>86</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12.9</td>\n",
+       "      <td>100.63</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 14:00:00</th>\n",
-       "      <td> -3.4</td>\n",
-       "      <td> -5.7</td>\n",
-       "      <td> 84</td>\n",
-       "      <td>  6</td>\n",
-       "      <td> 11.3</td>\n",
-       "      <td> 100.57</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-3.4</td>\n",
+       "      <td>-5.7</td>\n",
+       "      <td>84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11.3</td>\n",
+       "      <td>100.57</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 15:00:00</th>\n",
-       "      <td> -2.3</td>\n",
-       "      <td> -4.6</td>\n",
-       "      <td> 84</td>\n",
-       "      <td>  9</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.47</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-2.3</td>\n",
+       "      <td>-4.6</td>\n",
+       "      <td>84</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.47</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 16:00:00</th>\n",
-       "      <td> -1.4</td>\n",
-       "      <td> -4.0</td>\n",
-       "      <td> 82</td>\n",
-       "      <td> 13</td>\n",
-       "      <td> 12.9</td>\n",
-       "      <td> 100.40</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-1.4</td>\n",
+       "      <td>-4.0</td>\n",
+       "      <td>82</td>\n",
+       "      <td>13</td>\n",
+       "      <td>12.9</td>\n",
+       "      <td>100.40</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 17:00:00</th>\n",
-       "      <td> -1.1</td>\n",
-       "      <td> -3.3</td>\n",
-       "      <td> 85</td>\n",
-       "      <td> 19</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.30</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-1.1</td>\n",
+       "      <td>-3.3</td>\n",
+       "      <td>85</td>\n",
+       "      <td>19</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.30</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 18:00:00</th>\n",
-       "      <td> -1.3</td>\n",
-       "      <td> -3.1</td>\n",
-       "      <td> 88</td>\n",
-       "      <td> 17</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.19</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-1.3</td>\n",
+       "      <td>-3.1</td>\n",
+       "      <td>88</td>\n",
+       "      <td>17</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.19</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 19:00:00</th>\n",
-       "      <td>  0.1</td>\n",
-       "      <td> -2.7</td>\n",
-       "      <td> 81</td>\n",
-       "      <td> 30</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.13</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>-2.7</td>\n",
+       "      <td>81</td>\n",
+       "      <td>30</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.13</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 20:00:00</th>\n",
-       "      <td>  0.2</td>\n",
-       "      <td> -2.4</td>\n",
-       "      <td> 83</td>\n",
-       "      <td> 24</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td> 100.03</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>-2.4</td>\n",
+       "      <td>83</td>\n",
+       "      <td>24</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>100.03</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 21:00:00</th>\n",
-       "      <td> -0.5</td>\n",
-       "      <td> -1.5</td>\n",
-       "      <td> 93</td>\n",
-       "      <td> 28</td>\n",
-       "      <td>  4.8</td>\n",
-       "      <td>  99.95</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>93</td>\n",
+       "      <td>28</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>99.95</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 22:00:00</th>\n",
-       "      <td> -0.2</td>\n",
-       "      <td> -1.8</td>\n",
-       "      <td> 89</td>\n",
-       "      <td> 28</td>\n",
-       "      <td>  9.7</td>\n",
-       "      <td>  99.91</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>-0.2</td>\n",
+       "      <td>-1.8</td>\n",
+       "      <td>89</td>\n",
+       "      <td>28</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>99.91</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31 23:00:00</th>\n",
-       "      <td>  0.0</td>\n",
-       "      <td> -2.1</td>\n",
-       "      <td> 86</td>\n",
-       "      <td> 30</td>\n",
-       "      <td> 11.3</td>\n",
-       "      <td>  99.89</td>\n",
-       "      <td>          Snow</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-2.1</td>\n",
+       "      <td>86</td>\n",
+       "      <td>30</td>\n",
+       "      <td>11.3</td>\n",
+       "      <td>99.89</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -5890,9 +3665,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "weather_2012.to_csv('../data/weather_2012.csv')"
@@ -5908,23 +3681,23 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
-   "name": "python2"
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.8"
-  },
-  "signature": "sha256:b30cddcdda4ccce9aaafa59c0e24cbf9e66ca9362289410aeba3df769257302e"
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/cookbook/Chapter 6 - String Operations- Which month was the snowiest.ipynb b/cookbook/Chapter 6 - String Operations- Which month was the snowiest.ipynb
index 356fa1e55..db9a7fe79 100644
--- a/cookbook/Chapter 6 - String Operations- Which month was the snowiest.ipynb	
+++ b/cookbook/Chapter 6 - String Operations- Which month was the snowiest.ipynb	
@@ -2,19 +2,15 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 1,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "%matplotlib inline\n",
-    "\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "\n",
-    "pd.set_option('display.mpl_style', 'default')\n",
+    "plt.style.use('ggplot')\n",
     "plt.rcParams['figure.figsize'] = (15, 3)\n",
     "plt.rcParams['font.family'] = 'sans-serif'"
    ]
@@ -28,15 +24,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -62,89 +69,86 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>2012-01-01 00:00:00</th>\n",
-       "      <td>-1.8</td>\n",
-       "      <td>-3.9</td>\n",
-       "      <td> 86</td>\n",
-       "      <td> 4</td>\n",
-       "      <td> 8.0</td>\n",
-       "      <td> 101.24</td>\n",
-       "      <td>                  Fog</td>\n",
+       "      <th>2013-01-01 00:00:00</th>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1.7</td>\n",
+       "      <td>95</td>\n",
+       "      <td>35</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>99.89</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2012-01-01 01:00:00</th>\n",
-       "      <td>-1.8</td>\n",
-       "      <td>-3.7</td>\n",
-       "      <td> 87</td>\n",
-       "      <td> 4</td>\n",
-       "      <td> 8.0</td>\n",
-       "      <td> 101.24</td>\n",
-       "      <td>                  Fog</td>\n",
+       "      <th>2013-01-01 01:00:00</th>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>-5.1</td>\n",
+       "      <td>79</td>\n",
+       "      <td>35</td>\n",
+       "      <td>16.1</td>\n",
+       "      <td>99.93</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2012-01-01 02:00:00</th>\n",
-       "      <td>-1.8</td>\n",
-       "      <td>-3.4</td>\n",
-       "      <td> 89</td>\n",
-       "      <td> 7</td>\n",
-       "      <td> 4.0</td>\n",
-       "      <td> 101.26</td>\n",
-       "      <td> Freezing Drizzle,Fog</td>\n",
+       "      <th>2013-01-01 02:00:00</th>\n",
+       "      <td>-2.7</td>\n",
+       "      <td>-6.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>28</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.08</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2012-01-01 03:00:00</th>\n",
-       "      <td>-1.5</td>\n",
-       "      <td>-3.2</td>\n",
-       "      <td> 88</td>\n",
-       "      <td> 6</td>\n",
-       "      <td> 4.0</td>\n",
-       "      <td> 101.27</td>\n",
-       "      <td> Freezing Drizzle,Fog</td>\n",
+       "      <th>2013-01-01 03:00:00</th>\n",
+       "      <td>-5.6</td>\n",
+       "      <td>-11.7</td>\n",
+       "      <td>62</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.21</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2012-01-01 04:00:00</th>\n",
-       "      <td>-1.5</td>\n",
-       "      <td>-3.3</td>\n",
-       "      <td> 88</td>\n",
-       "      <td> 7</td>\n",
-       "      <td> 4.8</td>\n",
-       "      <td> 101.23</td>\n",
-       "      <td>                  Fog</td>\n",
+       "      <th>2013-01-01 04:00:00</th>\n",
+       "      <td>-7.7</td>\n",
+       "      <td>-12.6</td>\n",
+       "      <td>68</td>\n",
+       "      <td>35</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.32</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 7 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "                     Temp (C)  Dew Point Temp (C)  Rel Hum (%)  \\\n",
        "Date/Time                                                        \n",
-       "2012-01-01 00:00:00      -1.8                -3.9           86   \n",
-       "2012-01-01 01:00:00      -1.8                -3.7           87   \n",
-       "2012-01-01 02:00:00      -1.8                -3.4           89   \n",
-       "2012-01-01 03:00:00      -1.5                -3.2           88   \n",
-       "2012-01-01 04:00:00      -1.5                -3.3           88   \n",
+       "2013-01-01 00:00:00      -1.0                -1.7           95   \n",
+       "2013-01-01 01:00:00      -2.0                -5.1           79   \n",
+       "2013-01-01 02:00:00      -2.7                -6.0           78   \n",
+       "2013-01-01 03:00:00      -5.6               -11.7           62   \n",
+       "2013-01-01 04:00:00      -7.7               -12.6           68   \n",
        "\n",
        "                     Wind Spd (km/h)  Visibility (km)  Stn Press (kPa)  \\\n",
        "Date/Time                                                                \n",
-       "2012-01-01 00:00:00                4              8.0           101.24   \n",
-       "2012-01-01 01:00:00                4              8.0           101.24   \n",
-       "2012-01-01 02:00:00                7              4.0           101.26   \n",
-       "2012-01-01 03:00:00                6              4.0           101.27   \n",
-       "2012-01-01 04:00:00                7              4.8           101.23   \n",
+       "2013-01-01 00:00:00               35              6.4            99.89   \n",
+       "2013-01-01 01:00:00               35             16.1            99.93   \n",
+       "2013-01-01 02:00:00               28             19.3           100.08   \n",
+       "2013-01-01 03:00:00               30             25.0           100.21   \n",
+       "2013-01-01 04:00:00               35             19.3           100.32   \n",
        "\n",
-       "                                  Weather  \n",
-       "Date/Time                                  \n",
-       "2012-01-01 00:00:00                   Fog  \n",
-       "2012-01-01 01:00:00                   Fog  \n",
-       "2012-01-01 02:00:00  Freezing Drizzle,Fog  \n",
-       "2012-01-01 03:00:00  Freezing Drizzle,Fog  \n",
-       "2012-01-01 04:00:00                   Fog  \n",
-       "\n",
-       "[5 rows x 7 columns]"
+       "                          Weather  \n",
+       "Date/Time                          \n",
+       "2013-01-01 00:00:00          Snow  \n",
+       "2013-01-01 01:00:00  Mainly Clear  \n",
+       "2013-01-01 02:00:00          Snow  \n",
+       "2013-01-01 03:00:00         Clear  \n",
+       "2013-01-01 04:00:00  Mainly Clear  "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -172,10 +176,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [],
    "source": [
     "weather_description = weather_2012['Weather']\n",
@@ -191,24 +193,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
        "Date/Time\n",
-       "2012-01-01 00:00:00    False\n",
-       "2012-01-01 01:00:00    False\n",
-       "2012-01-01 02:00:00    False\n",
-       "2012-01-01 03:00:00    False\n",
-       "2012-01-01 04:00:00    False\n",
+       "2013-01-01 00:00:00     True\n",
+       "2013-01-01 01:00:00    False\n",
+       "2013-01-01 02:00:00     True\n",
+       "2013-01-01 03:00:00    False\n",
+       "2013-01-01 04:00:00    False\n",
        "Name: Weather, dtype: bool"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -218,473 +218,77 @@
     "is_snowing[:5]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can think of snowiness as being a bunch of 1s and 0s instead of `True`s and `False`s:"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 5,
    "metadata": {
-    "collapsed": false
+    "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes.AxesSubplot at 0x10b930650>"
+       "Date/Time\n",
+       "2013-01-01 00:00:00    1.0\n",
+       "2013-01-01 01:00:00    0.0\n",
+       "2013-01-01 02:00:00    1.0\n",
+       "2013-01-01 03:00:00    0.0\n",
+       "2013-01-01 04:00:00    0.0\n",
+       "2013-01-01 05:00:00    0.0\n",
+       "2013-01-01 06:00:00    0.0\n",
+       "2013-01-01 07:00:00    0.0\n",
+       "2013-01-01 08:00:00    0.0\n",
+       "2013-01-01 09:00:00    0.0\n",
+       "Name: Weather, dtype: float64"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
-    },
+    }
+   ],
+   "source": [
+    "is_snowing.astype(float)[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
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-       "5s+fj759+6K2thZ33XWXqw+EEEJ6L9yCnxBCCCGEEEJSBNMdCSGEEEIIISRFMEgjhBBCCCGEqBTp\n",
-       "fQAAADtJREFUkBTBII0QQgghhBBCUgSDNEL+//brWAAAAABgkL/1NHaURQAAMCJpAAAAI5IGAAAw\n",
-       "ImkAAAAjAdG6ACCSV96JAAAAAElFTkSuQmCC\n"
-      ],
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x10b9364d0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2fd8b828d0>"
       ]
      },
+     "execution_count": 6,
      "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
     "# More useful!\n",
-    "is_snowing.plot()"
+    "is_snowing.astype(float).plot()"
    ]
   },
   {
@@ -703,249 +307,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes.AxesSubplot at 0x10bd89810>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2fd976bc18>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x10bc3aed0>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -964,61 +348,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "So we can think of snowiness as being a bunch of 1s and 0s instead of `True`s and `False`s:"
+    "So we can use `resample` to find the percentage of time it was snowing each month"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Date/Time\n",
-       "2012-01-01 00:00:00    0\n",
-       "2012-01-01 01:00:00    0\n",
-       "2012-01-01 02:00:00    0\n",
-       "2012-01-01 03:00:00    0\n",
-       "2012-01-01 04:00:00    0\n",
-       "2012-01-01 05:00:00    0\n",
-       "2012-01-01 06:00:00    0\n",
-       "2012-01-01 07:00:00    0\n",
-       "2012-01-01 08:00:00    0\n",
-       "2012-01-01 09:00:00    0\n",
-       "Name: Weather, dtype: float64"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "is_snowing.astype(float)[:10]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 8,
    "metadata": {},
-   "source": [
-    "and then use `resample` to find the percentage of time it was snowing each month"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "Date/Time\n",
-       "2012-01-31    0.240591\n",
        "2012-02-29    0.162356\n",
        "2012-03-31    0.087366\n",
        "2012-04-30    0.015278\n",
@@ -1030,10 +371,11 @@
        "2012-10-31    0.000000\n",
        "2012-11-30    0.038889\n",
        "2012-12-31    0.251344\n",
+       "2013-01-31    0.197581\n",
        "Freq: M, Name: Weather, dtype: float64"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1044,250 +386,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes.AxesSubplot at 0x10c189890>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2fd96c5160>"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x10bc3a090>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1299,7 +420,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "So now we know! In 2012, December was the snowiest month. Also, this graph suggests something that I feel -- it starts snowing pretty abruptly in November, and then tapers off slowly and takes a long time to stop, with the last snow usually being in April or May."
+    "Now we know! In 2012, December was the snowiest month. Also, this graph suggests something that I feel -- it starts snowing pretty abruptly in November, and then tapers off slowly and takes a long time to stop, with the last snow usually being in April or May."
    ]
   },
   {
@@ -1318,10 +439,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [],
    "source": [
     "temperature = weather_2012['Temp (C)'].resample('M').apply(np.median)\n",
@@ -1342,15 +461,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1358,76 +488,80 @@
        "      <th>Temperature</th>\n",
        "      <th>Snowiness</th>\n",
        "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
        "    <tr>\n",
-       "      <th>2012-01-31</th>\n",
-       "      <td> -7.05</td>\n",
-       "      <td> 0.240591</td>\n",
+       "      <th>Date/Time</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-02-29</th>\n",
-       "      <td> -4.10</td>\n",
-       "      <td> 0.162356</td>\n",
+       "      <td>-4.10</td>\n",
+       "      <td>0.162356</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-31</th>\n",
-       "      <td>  2.60</td>\n",
-       "      <td> 0.087366</td>\n",
+       "      <td>2.60</td>\n",
+       "      <td>0.087366</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-04-30</th>\n",
-       "      <td>  6.30</td>\n",
-       "      <td> 0.015278</td>\n",
+       "      <td>6.30</td>\n",
+       "      <td>0.015278</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-05-31</th>\n",
-       "      <td> 16.05</td>\n",
-       "      <td> 0.000000</td>\n",
+       "      <td>16.05</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-06-30</th>\n",
-       "      <td> 19.60</td>\n",
-       "      <td> 0.000000</td>\n",
+       "      <td>19.60</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-07-31</th>\n",
-       "      <td> 22.90</td>\n",
-       "      <td> 0.000000</td>\n",
+       "      <td>22.90</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-08-31</th>\n",
-       "      <td> 22.20</td>\n",
-       "      <td> 0.000000</td>\n",
+       "      <td>22.20</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-09-30</th>\n",
-       "      <td> 16.10</td>\n",
-       "      <td> 0.000000</td>\n",
+       "      <td>16.10</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-10-31</th>\n",
-       "      <td> 11.30</td>\n",
-       "      <td> 0.000000</td>\n",
+       "      <td>11.30</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-11-30</th>\n",
-       "      <td>  1.05</td>\n",
-       "      <td> 0.038889</td>\n",
+       "      <td>1.05</td>\n",
+       "      <td>0.038889</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-12-31</th>\n",
-       "      <td> -2.85</td>\n",
-       "      <td> 0.251344</td>\n",
+       "      <td>-2.85</td>\n",
+       "      <td>0.251344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013-01-31</th>\n",
+       "      <td>-8.10</td>\n",
+       "      <td>0.197581</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>12 rows × 2 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "            Temperature  Snowiness\n",
-       "2012-01-31        -7.05   0.240591\n",
+       "Date/Time                         \n",
        "2012-02-29        -4.10   0.162356\n",
        "2012-03-31         2.60   0.087366\n",
        "2012-04-30         6.30   0.015278\n",
@@ -1439,11 +573,10 @@
        "2012-10-31        11.30   0.000000\n",
        "2012-11-30         1.05   0.038889\n",
        "2012-12-31        -2.85   0.251344\n",
-       "\n",
-       "[12 rows x 2 columns]"
+       "2013-01-31        -8.10   0.197581"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1455,284 +588,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes.AxesSubplot at 0x10c51f690>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2fd9631908>"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x10bcc7bd0>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1749,423 +627,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([<matplotlib.axes.AxesSubplot object at 0x10c268650>,\n",
-       "       <matplotlib.axes.AxesSubplot object at 0x10c7c1390>], dtype=object)"
+       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f2fd961acc0>,\n",
+       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f2fd95c2978>],\n",
+       "      dtype=object)"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x10c695e10>"
+       "<Figure size 1080x720 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2223,23 +709,23 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
+   "display_name": "pandas-cookbook",
    "language": "python",
-   "name": "python2"
+   "name": "pandas-cookbook"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/cookbook/Chapter 7 - Cleaning up messy data.ipynb b/cookbook/Chapter 7 - Cleaning up messy data.ipynb
index 88d2d2b65..7c3832d54 100644
--- a/cookbook/Chapter 7 - Cleaning up messy data.ipynb	
+++ b/cookbook/Chapter 7 - Cleaning up messy data.ipynb	
@@ -2,22 +2,16 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 1,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# The usual preamble\n",
-    "%matplotlib inline\n",
-    "\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "\n",
-    "# Make the graphs a bit prettier, and bigger\n",
-    "pd.set_option('display.mpl_style', 'default')\n",
-    "plt.rcParams['figure.figsize'] = (15, 5)\n",
+    "plt.style.use('ggplot')\n",
+    "plt.rcParams['figure.figsize'] = (15, 3)\n",
     "plt.rcParams['font.family'] = 'sans-serif'\n",
     "\n",
     "# This is necessary to show lots of columns in pandas 0.12. \n",
@@ -37,11 +31,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/gabriela/.local/share/virtualenvs/pandas-cookbook-M4OY_8hn/lib/python3.5/site-packages/IPython/core/interactiveshell.py:3018: DtypeWarning: Columns (8) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  interactivity=interactivity, compiler=compiler, result=result)\n"
+     ]
+    }
+   ],
    "source": [
     "requests = pd.read_csv('../data/311-service-requests.csv')"
    ]
@@ -79,10 +80,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -113,46 +112,47 @@
        "       10454.0, 10451.0, 11436.0, 11426.0, 10153.0, 11004.0, 11428.0,\n",
        "       11427.0, 11001.0, 11363.0, 10004.0, 10474.0, 11430.0, 10000.0,\n",
        "       10307.0, 11239.0, 10119.0, 10006.0, 10048.0, 11697.0, 11692.0,\n",
-       "       11693.0, 10573.0, 83.0, 11559.0, 10020.0, 77056.0, 11776.0, 70711.0,\n",
-       "       10282.0, 11109.0, 10044.0, '10452', '11233', '10468', '10310',\n",
-       "       '11105', '10462', '10029', '10301', '10457', '10467', '10469',\n",
-       "       '11225', '10035', '10031', '11226', '10454', '11221', '10025',\n",
-       "       '11229', '11235', '11422', '10472', '11208', '11102', '10032',\n",
-       "       '11216', '10473', '10463', '11213', '10040', '10302', '11231',\n",
-       "       '10470', '11204', '11104', '11212', '10466', '11416', '11214',\n",
-       "       '10009', '11692', '11385', '11423', '11201', '10024', '11435',\n",
-       "       '10312', '10030', '11106', '10033', '10303', '11215', '11222',\n",
-       "       '11354', '10016', '10034', '11420', '10304', '10019', '11237',\n",
-       "       '11249', '11230', '11372', '11207', '11378', '11419', '11361',\n",
-       "       '10011', '11357', '10012', '11358', '10003', '10002', '11374',\n",
-       "       '10007', '11234', '10065', '11369', '11434', '11205', '11206',\n",
-       "       '11415', '11236', '11218', '11413', '10458', '11101', '10306',\n",
-       "       '11355', '10023', '11368', '10314', '11421', '10010', '10018',\n",
-       "       '11223', '10455', '11377', '11433', '11375', '10037', '11209',\n",
-       "       '10459', '10128', '10014', '10282', '11373', '10451', '11238',\n",
-       "       '11211', '10038', '11694', '11203', '11691', '11232', '10305',\n",
-       "       '10021', '11228', '10036', '10001', '10017', '11217', '11219',\n",
-       "       '10308', '10465', '11379', '11414', '10460', '11417', '11220',\n",
-       "       '11366', '10027', '11370', '10309', '11412', '11356', '10456',\n",
-       "       '11432', '10022', '10013', '11367', '11040', '10026', '10475',\n",
-       "       '11210', '11364', '11426', '10471', '10119', '11224', '11418',\n",
-       "       '11429', '11365', '10461', '11239', '10039', '00083', '11411',\n",
-       "       '10075', '11004', '11360', '10453', '10028', '11430', '10307',\n",
-       "       '11103', '10004', '10069', '10005', '10474', '11428', '11436',\n",
-       "       '10020', '11001', '11362', '11693', '10464', '11427', '10044',\n",
-       "       '11363', '10006', '10000', '02061', '77092-2016', '10280', '11109',\n",
-       "       '14225', '55164-0737', '19711', '07306', '000000', 'NO CLUE',\n",
-       "       '90010', '10281', '11747', '23541', '11776', '11697', '11788',\n",
-       "       '07604', 10112.0, 11788.0, 11563.0, 11580.0, 7087.0, 11042.0,\n",
-       "       7093.0, 11501.0, 92123.0, 0.0, 11575.0, 7109.0, 11797.0, '10803',\n",
-       "       '11716', '11722', '11549-3650', '10162', '92123', '23502', '11518',\n",
-       "       '07020', '08807', '11577', '07114', '11003', '07201', '11563',\n",
-       "       '61702', '10103', '29616-0759', '35209-3114', '11520', '11735',\n",
-       "       '10129', '11005', '41042', '11590', 6901.0, 7208.0, 11530.0,\n",
-       "       13221.0, 10954.0, 11735.0, 10103.0, 7114.0, 11111.0, 10107.0], dtype=object)"
+       "       11693.0, 10573.0, 83.0, 11559.0, 10020.0, 77056.0, 11776.0,\n",
+       "       70711.0, 10282.0, 11109.0, 10044.0, '10452', '11233', '10468',\n",
+       "       '10310', '11105', '10462', '10029', '10301', '10457', '10467',\n",
+       "       '10469', '11225', '10035', '10031', '11226', '10454', '11221',\n",
+       "       '10025', '11229', '11235', '11422', '10472', '11208', '11102',\n",
+       "       '10032', '11216', '10473', '10463', '11213', '10040', '10302',\n",
+       "       '11231', '10470', '11204', '11104', '11212', '10466', '11416',\n",
+       "       '11214', '10009', '11692', '11385', '11423', '11201', '10024',\n",
+       "       '11435', '10312', '10030', '11106', '10033', '10303', '11215',\n",
+       "       '11222', '11354', '10016', '10034', '11420', '10304', '10019',\n",
+       "       '11237', '11249', '11230', '11372', '11207', '11378', '11419',\n",
+       "       '11361', '10011', '11357', '10012', '11358', '10003', '10002',\n",
+       "       '11374', '10007', '11234', '10065', '11369', '11434', '11205',\n",
+       "       '11206', '11415', '11236', '11218', '11413', '10458', '11101',\n",
+       "       '10306', '11355', '10023', '11368', '10314', '11421', '10010',\n",
+       "       '10018', '11223', '10455', '11377', '11433', '11375', '10037',\n",
+       "       '11209', '10459', '10128', '10014', '10282', '11373', '10451',\n",
+       "       '11238', '11211', '10038', '11694', '11203', '11691', '11232',\n",
+       "       '10305', '10021', '11228', '10036', '10001', '10017', '11217',\n",
+       "       '11219', '10308', '10465', '11379', '11414', '10460', '11417',\n",
+       "       '11220', '11366', '10027', '11370', '10309', '11412', '11356',\n",
+       "       '10456', '11432', '10022', '10013', '11367', '11040', '10026',\n",
+       "       '10475', '11210', '11364', '11426', '10471', '10119', '11224',\n",
+       "       '11418', '11429', '11365', '10461', '11239', '10039', '00083',\n",
+       "       '11411', '10075', '11004', '11360', '10453', '10028', '11430',\n",
+       "       '10307', '11103', '10004', '10069', '10005', '10474', '11428',\n",
+       "       '11436', '10020', '11001', '11362', '11693', '10464', '11427',\n",
+       "       '10044', '11363', '10006', '10000', '02061', '77092-2016', '10280',\n",
+       "       '11109', '14225', '55164-0737', '19711', '07306', '000000',\n",
+       "       'NO CLUE', '90010', '10281', '11747', '23541', '11776', '11697',\n",
+       "       '11788', '07604', 10112.0, 11788.0, 11563.0, 11580.0, 7087.0,\n",
+       "       11042.0, 7093.0, 11501.0, 92123.0, 0.0, 11575.0, 7109.0, 11797.0,\n",
+       "       '10803', '11716', '11722', '11549-3650', '10162', '92123', '23502',\n",
+       "       '11518', '07020', '08807', '11577', '07114', '11003', '07201',\n",
+       "       '11563', '61702', '10103', '29616-0759', '35209-3114', '11520',\n",
+       "       '11735', '10129', '11005', '41042', '11590', 6901.0, 7208.0,\n",
+       "       11530.0, 13221.0, 10954.0, 11735.0, 10103.0, 7114.0, 11111.0,\n",
+       "       10107.0], dtype=object)"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -177,10 +177,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [],
    "source": [
     "na_values = ['NO CLUE', 'N/A', '0']\n",
@@ -189,10 +187,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -225,17 +221,17 @@
        "       '10307', '11239', '10119', '10006', '10048', '11697', '11692',\n",
        "       '11693', '10573', '00083', '11559', '10020', '77056', '11776',\n",
        "       '70711', '10282', '11109', '10044', '02061', '77092-2016', '14225',\n",
-       "       '55164-0737', '19711', '07306', '000000', '90010', '11747', '23541',\n",
-       "       '11788', '07604', '10112', '11563', '11580', '07087', '11042',\n",
-       "       '07093', '11501', '92123', '00000', '11575', '07109', '11797',\n",
-       "       '10803', '11716', '11722', '11549-3650', '10162', '23502', '11518',\n",
-       "       '07020', '08807', '11577', '07114', '11003', '07201', '61702',\n",
-       "       '10103', '29616-0759', '35209-3114', '11520', '11735', '10129',\n",
-       "       '11005', '41042', '11590', '06901', '07208', '11530', '13221',\n",
-       "       '10954', '11111', '10107'], dtype=object)"
+       "       '55164-0737', '19711', '07306', '000000', '90010', '11747',\n",
+       "       '23541', '11788', '07604', '10112', '11563', '11580', '07087',\n",
+       "       '11042', '07093', '11501', '92123', '00000', '11575', '07109',\n",
+       "       '11797', '10803', '11716', '11722', '11549-3650', '10162', '23502',\n",
+       "       '11518', '07020', '08807', '11577', '07114', '11003', '07201',\n",
+       "       '61702', '10103', '29616-0759', '35209-3114', '11520', '11735',\n",
+       "       '10129', '11005', '41042', '11590', '06901', '07208', '11530',\n",
+       "       '13221', '10954', '11111', '10107'], dtype=object)"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -253,10 +249,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -264,7 +258,7 @@
        "5"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -276,15 +270,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -346,278 +351,278 @@
        "  <tbody>\n",
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-       "      <td> 26550551</td>\n",
-       "      <td> 10/24/2013 06:16:34 PM</td>\n",
-       "      <td>                    NaN</td>\n",
-       "      <td> DCA</td>\n",
-       "      <td> Department of Consumer Affairs</td>\n",
-       "      <td> Consumer Complaint</td>\n",
-       "      <td> False Advertising</td>\n",
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-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>    HOUSTON</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Assigned</td>\n",
-       "      <td> 11/13/2013 11:15:20 AM</td>\n",
-       "      <td> 10/29/2013 11:16:16 AM</td>\n",
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-       "      <td>NaN</td>\n",
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-       "      <td> N</td>\n",
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-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
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+       "      <td>Consumer Complaint</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>77092-2016</td>\n",
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+       "      <td>EAST SELTICE WAY</td>\n",
+       "      <td>NaN</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>HOUSTON</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>11/13/2013 11:15:20 AM</td>\n",
+       "      <td>10/29/2013 11:16:16 AM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
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-       "      <td>                    NaN</td>\n",
-       "      <td> DCA</td>\n",
-       "      <td> Department of Consumer Affairs</td>\n",
-       "      <td> Consumer Complaint</td>\n",
-       "      <td>        Harassment</td>\n",
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-       "      <td> NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
+       "      <td>26548831</td>\n",
+       "      <td>10/24/2013 09:35:10 AM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>DCA</td>\n",
+       "      <td>Department of Consumer Affairs</td>\n",
+       "      <td>Consumer Complaint</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>55164-0737</td>\n",
+       "      <td>P.O. BOX 64437</td>\n",
+       "      <td>64437</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ST. PAUL</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>11/13/2013 02:30:21 PM</td>\n",
+       "      <td>10/29/2013 02:31:06 PM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>70539</th>\n",
-       "      <td> 26488417</td>\n",
-       "      <td> 10/15/2013 03:40:33 PM</td>\n",
-       "      <td>                    NaN</td>\n",
-       "      <td> TLC</td>\n",
-       "      <td>  Taxi and Limousine Commission</td>\n",
-       "      <td>     Taxi Complaint</td>\n",
-       "      <td>  Driver Complaint</td>\n",
-       "      <td> Street</td>\n",
-       "      <td> 11549-3650</td>\n",
-       "      <td> 365 HOFSTRA UNIVERSITY</td>\n",
-       "      <td> HOFSTRA UNIVERSITY</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>   HEMSTEAD</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Assigned</td>\n",
-       "      <td> 11/30/2013 01:20:33 PM</td>\n",
-       "      <td> 10/16/2013 01:21:39 PM</td>\n",
-       "      <td> 0 Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> La Guardia Airport</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
+       "      <td>26488417</td>\n",
+       "      <td>10/15/2013 03:40:33 PM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>TLC</td>\n",
+       "      <td>Taxi and Limousine Commission</td>\n",
+       "      <td>Taxi Complaint</td>\n",
+       "      <td>Driver Complaint</td>\n",
+       "      <td>Street</td>\n",
+       "      <td>11549-3650</td>\n",
+       "      <td>365 HOFSTRA UNIVERSITY</td>\n",
+       "      <td>HOFSTRA UNIVERSITY</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>HEMSTEAD</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>11/30/2013 01:20:33 PM</td>\n",
+       "      <td>10/16/2013 01:21:39 PM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>La Guardia Airport</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>85821</th>\n",
-       "      <td> 26468296</td>\n",
-       "      <td> 10/10/2013 12:36:43 PM</td>\n",
-       "      <td> 10/26/2013 01:07:07 AM</td>\n",
-       "      <td> DCA</td>\n",
-       "      <td> Department of Consumer Affairs</td>\n",
-       "      <td> Consumer Complaint</td>\n",
-       "      <td>     Debt Not Owed</td>\n",
-       "      <td>    NaN</td>\n",
-       "      <td> 29616-0759</td>\n",
-       "      <td>           PO BOX 25759</td>\n",
-       "      <td>          BOX 25759</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> GREENVILLE</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>   Closed</td>\n",
-       "      <td> 10/26/2013 09:20:28 AM</td>\n",
-       "      <td> 10/26/2013 01:07:07 AM</td>\n",
-       "      <td> 0 Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>                NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
+       "      <td>26468296</td>\n",
+       "      <td>10/10/2013 12:36:43 PM</td>\n",
+       "      <td>10/26/2013 01:07:07 AM</td>\n",
+       "      <td>DCA</td>\n",
+       "      <td>Department of Consumer Affairs</td>\n",
+       "      <td>Consumer Complaint</td>\n",
+       "      <td>Debt Not Owed</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>29616-0759</td>\n",
+       "      <td>PO BOX 25759</td>\n",
+       "      <td>BOX 25759</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>GREENVILLE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/26/2013 09:20:28 AM</td>\n",
+       "      <td>10/26/2013 01:07:07 AM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>89304</th>\n",
-       "      <td> 26461137</td>\n",
-       "      <td> 10/09/2013 05:23:46 PM</td>\n",
-       "      <td> 10/25/2013 01:06:41 AM</td>\n",
-       "      <td> DCA</td>\n",
-       "      <td> Department of Consumer Affairs</td>\n",
-       "      <td> Consumer Complaint</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>    NaN</td>\n",
-       "      <td> 35209-3114</td>\n",
-       "      <td>        600 BEACON PKWY</td>\n",
-       "      <td>        BEACON PKWY</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> BIRMINGHAM</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>   Closed</td>\n",
-       "      <td> 10/25/2013 02:43:42 PM</td>\n",
-       "      <td> 10/25/2013 01:06:41 AM</td>\n",
-       "      <td> 0 Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>                NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
+       "      <td>26461137</td>\n",
+       "      <td>10/09/2013 05:23:46 PM</td>\n",
+       "      <td>10/25/2013 01:06:41 AM</td>\n",
+       "      <td>DCA</td>\n",
+       "      <td>Department of Consumer Affairs</td>\n",
+       "      <td>Consumer Complaint</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>35209-3114</td>\n",
+       "      <td>600 BEACON PKWY</td>\n",
+       "      <td>BEACON PKWY</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>BIRMINGHAM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Closed</td>\n",
+       "      <td>10/25/2013 02:43:42 PM</td>\n",
+       "      <td>10/25/2013 01:06:41 AM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -632,7 +637,7 @@
        "89304    26461137  10/09/2013 05:23:46 PM  10/25/2013 01:06:41 AM    DCA  Department of Consumer Affairs  Consumer Complaint         Harassment           NaN   35209-3114         600 BEACON PKWY         BEACON PKWY            NaN            NaN                   NaN                   NaN          NaN  BIRMINGHAM      NaN           NaN    Closed  10/25/2013 02:43:42 PM         10/25/2013 01:06:41 AM   0 Unspecified  Unspecified                         NaN                         NaN        Unspecified  Unspecified  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN       NaN        NaN      NaN"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -654,10 +659,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -666,7 +669,7 @@
        "       '35209-3114'], dtype=object)"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -685,10 +688,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
     "requests['Incident Zip'] = requests['Incident Zip'].str.slice(0, 5)"
@@ -710,15 +711,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -780,113 +792,113 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>42600</th>\n",
-       "      <td> 26529313</td>\n",
-       "      <td> 10/22/2013 02:51:06 PM</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> TLC</td>\n",
-       "      <td> Taxi and Limousine Commission</td>\n",
-       "      <td> Taxi Complaint</td>\n",
-       "      <td> Driver Complaint</td>\n",
-       "      <td>    NaN</td>\n",
-       "      <td> 00000</td>\n",
-       "      <td>          EWR EWR</td>\n",
-       "      <td>            EWR</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NEWARK</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Assigned</td>\n",
-       "      <td> 12/07/2013 09:53:51 AM</td>\n",
-       "      <td> 10/23/2013 09:54:43 AM</td>\n",
-       "      <td> 0 Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Other</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
+       "      <td>26529313</td>\n",
+       "      <td>10/22/2013 02:51:06 PM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>TLC</td>\n",
+       "      <td>Taxi and Limousine Commission</td>\n",
+       "      <td>Taxi Complaint</td>\n",
+       "      <td>Driver Complaint</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>00000</td>\n",
+       "      <td>EWR EWR</td>\n",
+       "      <td>EWR</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NEWARK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>12/07/2013 09:53:51 AM</td>\n",
+       "      <td>10/23/2013 09:54:43 AM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Other</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>60843</th>\n",
-       "      <td> 26507389</td>\n",
-       "      <td> 10/17/2013 05:48:44 PM</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> TLC</td>\n",
-       "      <td> Taxi and Limousine Commission</td>\n",
-       "      <td> Taxi Complaint</td>\n",
-       "      <td> Driver Complaint</td>\n",
-       "      <td> Street</td>\n",
-       "      <td> 00000</td>\n",
-       "      <td> 1 NEWARK AIRPORT</td>\n",
-       "      <td> NEWARK AIRPORT</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NEWARK</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Assigned</td>\n",
-       "      <td> 12/02/2013 11:59:46 AM</td>\n",
-       "      <td> 10/18/2013 12:01:08 PM</td>\n",
-       "      <td> 0 Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> Unspecified</td>\n",
-       "      <td> N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> Other</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td> NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td> NaN</td>\n",
+       "      <td>26507389</td>\n",
+       "      <td>10/17/2013 05:48:44 PM</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>TLC</td>\n",
+       "      <td>Taxi and Limousine Commission</td>\n",
+       "      <td>Taxi Complaint</td>\n",
+       "      <td>Driver Complaint</td>\n",
+       "      <td>Street</td>\n",
+       "      <td>00000</td>\n",
+       "      <td>1 NEWARK AIRPORT</td>\n",
+       "      <td>NEWARK AIRPORT</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NEWARK</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Assigned</td>\n",
+       "      <td>12/02/2013 11:59:46 AM</td>\n",
+       "      <td>10/18/2013 12:01:08 PM</td>\n",
+       "      <td>0 Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>Unspecified</td>\n",
+       "      <td>N</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Other</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -898,7 +910,7 @@
        "60843    26507389  10/17/2013 05:48:44 PM         NaN    TLC  Taxi and Limousine Commission  Taxi Complaint  Driver Complaint        Street        00000  1 NEWARK AIRPORT  NEWARK AIRPORT            NaN            NaN                   NaN                   NaN          NaN  NEWARK      NaN           NaN  Assigned  12/02/2013 11:59:46 AM         10/18/2013 12:01:08 PM   0 Unspecified  Unspecified                         NaN                         NaN        Unspecified  Unspecified  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                 Other                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN       NaN        NaN      NaN"
       ]
      },
-     "execution_count": 46,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -916,14 +928,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [],
    "source": [
     "zero_zips = requests['Incident Zip'] == '00000'\n",
-    "requests.loc[zero_zips, 'Incident Zip'] = np.nan"
+    "requests.loc[zero_zips, 'Incident Zip'] = ''"
    ]
   },
   {
@@ -935,15 +945,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([nan, '00083', '02061', '06901', '07020', '07087', '07093', '07109',\n",
+       "array(['', '00083', '02061', '06901', '07020', '07087', '07093', '07109',\n",
        "       '07114', '07201', '07208', '07306', '07604', '08807', '10000',\n",
        "       '10001', '10002', '10003', '10004', '10005', '10006', '10007',\n",
        "       '10009', '10010', '10011', '10012', '10013', '10014', '10016',\n",
@@ -977,16 +985,17 @@
        "       '11590', '11691', '11692', '11693', '11694', '11697', '11716',\n",
        "       '11722', '11735', '11747', '11776', '11788', '11797', '13221',\n",
        "       '14225', '19711', '23502', '23541', '29616', '35209', '41042',\n",
-       "       '55164', '61702', '70711', '77056', '77092', '90010', '92123'], dtype=object)"
+       "       '55164', '61702', '70711', '77056', '77092', '90010', '92123',\n",
+       "       'nan'], dtype=object)"
       ]
      },
-     "execution_count": 48,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "unique_zips = requests['Incident Zip'].unique()\n",
+    "unique_zips = requests['Incident Zip'].astype('str').unique()\n",
     "unique_zips.sort()\n",
     "unique_zips"
    ]
@@ -1002,10 +1011,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [],
    "source": [
     "zips = requests['Incident Zip']\n",
@@ -1017,10 +1024,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1029,9 +1034,11 @@
        "13450    70711\n",
        "29136    77092\n",
        "30939    55164\n",
+       "42600         \n",
        "44008    90010\n",
        "47048    23541\n",
        "57636    92123\n",
+       "60843         \n",
        "71001    92123\n",
        "71834    23502\n",
        "80573    61702\n",
@@ -1041,7 +1048,7 @@
        "Name: Incident Zip, dtype: object"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1052,15 +1059,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -1072,82 +1090,94 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
+       "      <th>42600</th>\n",
+       "      <td></td>\n",
+       "      <td>Driver Complaint</td>\n",
+       "      <td>NEWARK</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60843</th>\n",
+       "      <td></td>\n",
+       "      <td>Driver Complaint</td>\n",
+       "      <td>NEWARK</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>71834</th>\n",
-       "      <td> 23502</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>     NORFOLK</td>\n",
+       "      <td>23502</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>NORFOLK</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>47048</th>\n",
-       "      <td> 23541</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>     NORFOLK</td>\n",
+       "      <td>23541</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>NORFOLK</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>85821</th>\n",
-       "      <td> 29616</td>\n",
-       "      <td>     Debt Not Owed</td>\n",
-       "      <td>  GREENVILLE</td>\n",
+       "      <td>29616</td>\n",
+       "      <td>Debt Not Owed</td>\n",
+       "      <td>GREENVILLE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>89304</th>\n",
-       "      <td> 35209</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>  BIRMINGHAM</td>\n",
+       "      <td>35209</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>BIRMINGHAM</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>94201</th>\n",
-       "      <td> 41042</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>    FLORENCE</td>\n",
+       "      <td>41042</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>FLORENCE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>30939</th>\n",
-       "      <td> 55164</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>    ST. PAUL</td>\n",
+       "      <td>55164</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>ST. PAUL</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>80573</th>\n",
-       "      <td> 61702</td>\n",
-       "      <td>   Billing Dispute</td>\n",
-       "      <td>  BLOOMIGTON</td>\n",
+       "      <td>61702</td>\n",
+       "      <td>Billing Dispute</td>\n",
+       "      <td>BLOOMIGTON</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13450</th>\n",
-       "      <td> 70711</td>\n",
-       "      <td>  Contract Dispute</td>\n",
-       "      <td>     CLIFTON</td>\n",
+       "      <td>70711</td>\n",
+       "      <td>Contract Dispute</td>\n",
+       "      <td>CLIFTON</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12102</th>\n",
-       "      <td> 77056</td>\n",
-       "      <td>     Debt Not Owed</td>\n",
-       "      <td>     HOUSTON</td>\n",
+       "      <td>77056</td>\n",
+       "      <td>Debt Not Owed</td>\n",
+       "      <td>HOUSTON</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29136</th>\n",
-       "      <td> 77092</td>\n",
-       "      <td> False Advertising</td>\n",
-       "      <td>     HOUSTON</td>\n",
+       "      <td>77092</td>\n",
+       "      <td>False Advertising</td>\n",
+       "      <td>HOUSTON</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>44008</th>\n",
-       "      <td> 90010</td>\n",
-       "      <td>   Billing Dispute</td>\n",
-       "      <td> LOS ANGELES</td>\n",
+       "      <td>90010</td>\n",
+       "      <td>Billing Dispute</td>\n",
+       "      <td>LOS ANGELES</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>57636</th>\n",
-       "      <td> 92123</td>\n",
-       "      <td>        Harassment</td>\n",
-       "      <td>   SAN DIEGO</td>\n",
+       "      <td>92123</td>\n",
+       "      <td>Harassment</td>\n",
+       "      <td>SAN DIEGO</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>71001</th>\n",
-       "      <td> 92123</td>\n",
-       "      <td>   Billing Dispute</td>\n",
-       "      <td>   SAN DIEGO</td>\n",
+       "      <td>92123</td>\n",
+       "      <td>Billing Dispute</td>\n",
+       "      <td>SAN DIEGO</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1155,6 +1185,8 @@
       ],
       "text/plain": [
        "      Incident Zip         Descriptor         City\n",
+       "42600                Driver Complaint       NEWARK\n",
+       "60843                Driver Complaint       NEWARK\n",
        "71834        23502         Harassment      NORFOLK\n",
        "47048        23541         Harassment      NORFOLK\n",
        "85821        29616      Debt Not Owed   GREENVILLE\n",
@@ -1170,13 +1202,13 @@
        "71001        92123    Billing Dispute    SAN DIEGO"
       ]
      },
-     "execution_count": 51,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "requests[is_far][['Incident Zip', 'Descriptor', 'City']].sort('Incident Zip')"
+    "requests[is_far][['Incident Zip', 'Descriptor', 'City']].sort_values('Incident Zip')"
    ]
   },
   {
@@ -1188,49 +1220,77 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "BROOKLYN            31662\n",
-       "NEW YORK            22664\n",
-       "BRONX               18438\n",
-       "STATEN ISLAND        4766\n",
-       "JAMAICA              2246\n",
-       "FLUSHING             1803\n",
-       "ASTORIA              1568\n",
-       "RIDGEWOOD            1073\n",
-       "CORONA                707\n",
-       "OZONE PARK            693\n",
-       "LONG ISLAND CITY      678\n",
-       "FAR ROCKAWAY          652\n",
-       "ELMHURST              647\n",
-       "WOODSIDE              609\n",
-       "EAST ELMHURST         562\n",
-       "...\n",
-       "MELVILLE                  1\n",
-       "PORT JEFFERSON STATION    1\n",
-       "NORWELL                   1\n",
-       "EAST ROCKAWAY             1\n",
-       "BIRMINGHAM                1\n",
-       "ROSLYN                    1\n",
-       "LOS ANGELES               1\n",
-       "MINEOLA                   1\n",
-       "JERSEY CITY               1\n",
-       "ST. PAUL                  1\n",
-       "CLIFTON                   1\n",
-       "COL.ANVURES               1\n",
-       "EDGEWATER                 1\n",
-       "ROSELYN                   1\n",
-       "CENTRAL ISLIP             1\n",
-       "Length: 100, dtype: int64"
+       "BROOKLYN               31662\n",
+       "NEW YORK               22664\n",
+       "BRONX                  18438\n",
+       "STATEN ISLAND           4766\n",
+       "JAMAICA                 2246\n",
+       "FLUSHING                1803\n",
+       "ASTORIA                 1568\n",
+       "RIDGEWOOD               1073\n",
+       "CORONA                   707\n",
+       "OZONE PARK               693\n",
+       "LONG ISLAND CITY         678\n",
+       "FAR ROCKAWAY             652\n",
+       "ELMHURST                 647\n",
+       "WOODSIDE                 609\n",
+       "EAST ELMHURST            562\n",
+       "QUEENS VILLAGE           549\n",
+       "FOREST HILLS             541\n",
+       "JACKSON HEIGHTS          541\n",
+       "SOUTH RICHMOND HILL      521\n",
+       "MASPETH                  473\n",
+       "WOODHAVEN                464\n",
+       "FRESH MEADOWS            435\n",
+       "SPRINGFIELD GARDENS      434\n",
+       "BAYSIDE                  411\n",
+       "SOUTH OZONE PARK         410\n",
+       "RICHMOND HILL            404\n",
+       "REGO PARK                402\n",
+       "MIDDLE VILLAGE           396\n",
+       "SAINT ALBANS             387\n",
+       "WHITESTONE               348\n",
+       "                       ...  \n",
+       "CLIFTON                    1\n",
+       "COL.ANVURES                1\n",
+       "RYEBROOK                   1\n",
+       "BIRMINGHAM                 1\n",
+       "BRIARWOOD                  1\n",
+       "BOHIEMA                    1\n",
+       "BLOOMIGTON                 1\n",
+       "STAMFORD                   1\n",
+       "NJ                         1\n",
+       "CHEEKTOWAGA                1\n",
+       "ELIZABETH                  1\n",
+       "NANUET                     1\n",
+       "LOS ANGELES                1\n",
+       "FARMINGDALE                1\n",
+       "SYRACUSE                   1\n",
+       "GREENVILLE                 1\n",
+       "ROSELYN                    1\n",
+       "MINEOLA                    1\n",
+       "NEW YOR                    1\n",
+       "NEW YORK CITY              1\n",
+       "WOODBURY                   1\n",
+       "LYNBROOK                   1\n",
+       "VALLEY STREAM              1\n",
+       "JERSEY CITY                1\n",
+       "BELLEVILLE                 1\n",
+       "NEWARK AIRPORT             1\n",
+       "EAST ROCKAWAY              1\n",
+       "NORWELL                    1\n",
+       "ST. PAUL                   1\n",
+       "FREEPORT                   1\n",
+       "Name: City, Length: 100, dtype: int64"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1262,10 +1322,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 17,
+   "metadata": {},
    "outputs": [],
    "source": [
     "na_values = ['NO CLUE', 'N/A', '0']\n",
@@ -1276,10 +1334,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def fix_zip_codes(zips):\n",
@@ -1295,10 +1351,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [],
    "source": [
     "requests['Incident Zip'] = fix_zip_codes(requests['Incident Zip'])"
@@ -1306,10 +1360,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 20,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1348,10 +1400,11 @@
        "       '11722', '11549', '10162', '23502', '11518', '07020', '08807',\n",
        "       '11577', '07114', '11003', '07201', '61702', '10103', '29616',\n",
        "       '35209', '11520', '11735', '10129', '11005', '41042', '11590',\n",
-       "       '06901', '07208', '11530', '13221', '10954', '11111', '10107'], dtype=object)"
+       "       '06901', '07208', '11530', '13221', '10954', '11111', '10107'],\n",
+       "      dtype=object)"
       ]
      },
-     "execution_count": 56,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1410,23 +1463,23 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
+   "display_name": "pandas-cookbook",
    "language": "python",
-   "name": "python2"
+   "name": "pandas-cookbook"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/cookbook/Chapter 8 - How to deal with timestamps.ipynb b/cookbook/Chapter 8 - How to deal with timestamps.ipynb
index 60c23b11c..4d1c74caf 100644
--- a/cookbook/Chapter 8 - How to deal with timestamps.ipynb	
+++ b/cookbook/Chapter 8 - How to deal with timestamps.ipynb	
@@ -1 +1,596 @@
-{"nbformat": 4, "metadata": {"orig_nbformat": 3}, "cells": [{"cell_type": "code", "execution_count": 1, "outputs": [], "source": "import pandas as pd", "metadata": {"collapsed": false, "trusted": false}}, {"source": "# 8.1 Parsing Unix timestamps", "cell_type": "markdown", "metadata": {}}, {"source": "It's not obvious how to deal with Unix timestamps in pandas -- it took me quite a while to figure this out. The file we're using here is a popularity-contest file I found on my system at `/var/log/popularity-contest`.\n\nHere's an [explanation of how this file works](http://popcon.ubuntu.com/README).\n\nI'm going to hope that nothing in it is sensitive :)", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 2, "outputs": [], "source": "# Read it, and remove the last row\npopcon = pd.read_csv('../data/popularity-contest', sep=' ', )[:-1]\npopcon.columns = ['atime', 'ctime', 'package-name', 'mru-program', 'tag']", "metadata": {"collapsed": false, "trusted": false}}, {"source": "The colums are the access time, created time, package name, recently used program, and a tag", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 3, "outputs": [{"execution_count": 3, "output_type": "execute_result", "data": {"text/plain": "        atime       ctime  package-name                                   mru-program             tag\n0  1387295797  1367633260     perl-base                                 /usr/bin/perl             NaN\n1  1387295796  1354370480         login                                       /bin/su             NaN\n2  1387295743  1354341275    libtalloc2  /usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7             NaN\n3  1387295743  1387224204  libwbclient0    /usr/lib/x86_64-linux-gnu/libwbclient.so.0  <RECENT-CTIME>\n4  1387295742  1354341253   libselinux1         /lib/x86_64-linux-gnu/libselinux.so.1             NaN", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>atime</th>\n      <th>ctime</th>\n      <th>package-name</th>\n      <th>mru-program</th>\n      <th>tag</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td> 1387295797</td>\n      <td> 1367633260</td>\n      <td>    perl-base</td>\n      <td>                                /usr/bin/perl</td>\n      <td>            NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td> 1387295796</td>\n      <td> 1354370480</td>\n      <td>        login</td>\n      <td>                                      /bin/su</td>\n      <td>            NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td> 1387295743</td>\n      <td> 1354341275</td>\n      <td>   libtalloc2</td>\n      <td> /usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7</td>\n      <td>            NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td> 1387295743</td>\n      <td> 1387224204</td>\n      <td> libwbclient0</td>\n      <td>   /usr/lib/x86_64-linux-gnu/libwbclient.so.0</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td> 1387295742</td>\n      <td> 1354341253</td>\n      <td>  libselinux1</td>\n      <td>        /lib/x86_64-linux-gnu/libselinux.so.1</td>\n      <td>            NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"}, "metadata": {}}], "source": "popcon[:5]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "The magical part about parsing timestamps in pandas is that numpy datetimes are already stored as Unix timestamps. So all we need to do is tell pandas that these integers are actually datetimes -- it doesn't need to do any conversion at all.\n\nWe need to convert these to ints to start:", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 4, "outputs": [], "source": "popcon['atime'] = popcon['atime'].astype(int)\npopcon['ctime'] = popcon['ctime'].astype(int)", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Every numpy array and pandas series has a dtype -- this is usually `int64`, `float64`, or `object`. Some of the time types available are `datetime64[s]`, `datetime64[ms]`, and `datetime64[us]`. There are also `timedelta` types, similarly.\n\nWe can use the `pd.to_datetime` function to convert our integer timestamps into datetimes. This is a constant-time operation -- we're not actually changing any of the data, just how pandas thinks about it.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 5, "outputs": [], "source": "popcon['atime'] = pd.to_datetime(popcon['atime'], unit='s')\npopcon['ctime'] = pd.to_datetime(popcon['ctime'], unit='s')", "metadata": {"collapsed": false, "trusted": false}}, {"source": "If we look at the dtype now, it's `<M8[ns]`. As far as I can tell `M8` is secret code for `datetime64`.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 6, "outputs": [{"execution_count": 6, "output_type": "execute_result", "data": {"text/plain": "dtype('<M8[ns]')"}, "metadata": {}}], "source": "popcon['atime'].dtype", "metadata": {"collapsed": false, "trusted": false}}, {"source": "So now we can look at our `atime` and `ctime` as dates!", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 7, "outputs": [{"execution_count": 7, "output_type": "execute_result", "data": {"text/plain": "                atime               ctime  package-name                                   mru-program             tag\n0 2013-12-17 15:56:37 2013-05-04 02:07:40     perl-base                                 /usr/bin/perl             NaN\n1 2013-12-17 15:56:36 2012-12-01 14:01:20         login                                       /bin/su             NaN\n2 2013-12-17 15:55:43 2012-12-01 05:54:35    libtalloc2  /usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7             NaN\n3 2013-12-17 15:55:43 2013-12-16 20:03:24  libwbclient0    /usr/lib/x86_64-linux-gnu/libwbclient.so.0  <RECENT-CTIME>\n4 2013-12-17 15:55:42 2012-12-01 05:54:13   libselinux1         /lib/x86_64-linux-gnu/libselinux.so.1             NaN", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>atime</th>\n      <th>ctime</th>\n      <th>package-name</th>\n      <th>mru-program</th>\n      <th>tag</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2013-12-17 15:56:37</td>\n      <td>2013-05-04 02:07:40</td>\n      <td>    perl-base</td>\n      <td>                                /usr/bin/perl</td>\n      <td>            NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2013-12-17 15:56:36</td>\n      <td>2012-12-01 14:01:20</td>\n      <td>        login</td>\n      <td>                                      /bin/su</td>\n      <td>            NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2013-12-17 15:55:43</td>\n      <td>2012-12-01 05:54:35</td>\n      <td>   libtalloc2</td>\n      <td> /usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7</td>\n      <td>            NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2013-12-17 15:55:43</td>\n      <td>2013-12-16 20:03:24</td>\n      <td> libwbclient0</td>\n      <td>   /usr/lib/x86_64-linux-gnu/libwbclient.so.0</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2013-12-17 15:55:42</td>\n      <td>2012-12-01 05:54:13</td>\n      <td>  libselinux1</td>\n      <td>        /lib/x86_64-linux-gnu/libselinux.so.1</td>\n      <td>            NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"}, "metadata": {}}], "source": "popcon[:5]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Now suppose we want to look at all packages that aren't libraries.\n\nFirst, I want to get rid of everything with timestamp 0. Notice how we can just use a string in this comparison, even though it's actually a timestamp on the inside? That is because pandas is amazing.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 8, "outputs": [], "source": "popcon = popcon[popcon['atime'] > '1970-01-01']", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Now we can use pandas' magical string abilities to just look at rows where the package name doesn't contain 'lib'.", "cell_type": "markdown", "metadata": {}}, {"cell_type": "code", "execution_count": 9, "outputs": [], "source": "nonlibraries = popcon[~popcon['package-name'].str.contains('lib')]", "metadata": {"collapsed": false, "trusted": false}}, {"cell_type": "code", "execution_count": 10, "outputs": [{"execution_count": 10, "output_type": "execute_result", "data": {"text/plain": "                  atime               ctime               package-name  \\\n57  2013-12-17 04:55:39 2013-12-17 04:55:42                        ddd   \n450 2013-12-16 20:03:20 2013-12-16 20:05:13                     nodejs   \n454 2013-12-16 20:03:20 2013-12-16 20:05:04  switchboard-plug-keyboard   \n445 2013-12-16 20:03:20 2013-12-16 20:05:04      thunderbird-locale-en   \n396 2013-12-16 20:08:27 2013-12-16 20:05:03            software-center   \n449 2013-12-16 20:03:20 2013-12-16 20:05:00           samba-common-bin   \n397 2013-12-16 20:08:25 2013-12-16 20:04:59      postgresql-client-9.1   \n398 2013-12-16 20:08:23 2013-12-16 20:04:58             postgresql-9.1   \n452 2013-12-16 20:03:20 2013-12-16 20:04:55                   php5-dev   \n440 2013-12-16 20:03:20 2013-12-16 20:04:54                   php-pear   \n\n                                           mru-program             tag  \n57                                        /usr/bin/ddd  <RECENT-CTIME>  \n450                                       /usr/bin/npm  <RECENT-CTIME>  \n454       /usr/lib/plugs/pantheon/keyboard/options.txt  <RECENT-CTIME>  \n445  /usr/lib/thunderbird-addons/extensions/langpac...  <RECENT-CTIME>  \n396                   /usr/sbin/update-software-center  <RECENT-CTIME>  \n449                                /usr/bin/net.samba3  <RECENT-CTIME>  \n397                   /usr/lib/postgresql/9.1/bin/psql  <RECENT-CTIME>  \n398             /usr/lib/postgresql/9.1/bin/postmaster  <RECENT-CTIME>  \n452                  /usr/include/php5/main/snprintf.h  <RECENT-CTIME>  \n440                        /usr/share/php/XML/Util.php  <RECENT-CTIME>  ", "text/html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>atime</th>\n      <th>ctime</th>\n      <th>package-name</th>\n      <th>mru-program</th>\n      <th>tag</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>57 </th>\n      <td>2013-12-17 04:55:39</td>\n      <td>2013-12-17 04:55:42</td>\n      <td>                       ddd</td>\n      <td>                                      /usr/bin/ddd</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>450</th>\n      <td>2013-12-16 20:03:20</td>\n      <td>2013-12-16 20:05:13</td>\n      <td>                    nodejs</td>\n      <td>                                      /usr/bin/npm</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>454</th>\n      <td>2013-12-16 20:03:20</td>\n      <td>2013-12-16 20:05:04</td>\n      <td> switchboard-plug-keyboard</td>\n      <td>      /usr/lib/plugs/pantheon/keyboard/options.txt</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>445</th>\n      <td>2013-12-16 20:03:20</td>\n      <td>2013-12-16 20:05:04</td>\n      <td>     thunderbird-locale-en</td>\n      <td> /usr/lib/thunderbird-addons/extensions/langpac...</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>396</th>\n      <td>2013-12-16 20:08:27</td>\n      <td>2013-12-16 20:05:03</td>\n      <td>           software-center</td>\n      <td>                  /usr/sbin/update-software-center</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>449</th>\n      <td>2013-12-16 20:03:20</td>\n      <td>2013-12-16 20:05:00</td>\n      <td>          samba-common-bin</td>\n      <td>                               /usr/bin/net.samba3</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>397</th>\n      <td>2013-12-16 20:08:25</td>\n      <td>2013-12-16 20:04:59</td>\n      <td>     postgresql-client-9.1</td>\n      <td>                  /usr/lib/postgresql/9.1/bin/psql</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>398</th>\n      <td>2013-12-16 20:08:23</td>\n      <td>2013-12-16 20:04:58</td>\n      <td>            postgresql-9.1</td>\n      <td>            /usr/lib/postgresql/9.1/bin/postmaster</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>452</th>\n      <td>2013-12-16 20:03:20</td>\n      <td>2013-12-16 20:04:55</td>\n      <td>                  php5-dev</td>\n      <td>                 /usr/include/php5/main/snprintf.h</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n    <tr>\n      <th>440</th>\n      <td>2013-12-16 20:03:20</td>\n      <td>2013-12-16 20:04:54</td>\n      <td>                  php-pear</td>\n      <td>                       /usr/share/php/XML/Util.php</td>\n      <td> &lt;RECENT-CTIME&gt;</td>\n    </tr>\n  </tbody>\n</table>\n</div>"}, "metadata": {}}], "source": "nonlibraries.sort('ctime', ascending=False)[:10]", "metadata": {"collapsed": false, "trusted": false}}, {"source": "Okay, cool, it says that I I installed ddd recently. And postgresql! I remember installing those things. Neat.", "cell_type": "markdown", "metadata": {}}, {"source": "The whole message here is that if you have a timestamp in seconds or milliseconds or nanoseconds, then you can just \"cast\" it to a `'datetime64[the-right-thing]'` and pandas/numpy will take care of the rest.", "cell_type": "markdown", "metadata": {}}, {"source": "<style>\n    @font-face {\n        font-family: \"Computer Modern\";\n        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n    }\n    div.cell{\n        width:800px;\n        margin-left:16% !important;\n        margin-right:auto;\n    }\n    h1 {\n        font-family: Helvetica, serif;\n    }\n    h4{\n        margin-top:12px;\n        margin-bottom: 3px;\n       }\n    div.text_cell_render{\n        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n        line-height: 145%;\n        font-size: 130%;\n        width:800px;\n        margin-left:auto;\n        margin-right:auto;\n    }\n    .CodeMirror{\n            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n    }\n    .text_cell_render h5 {\n        font-weight: 300;\n        font-size: 22pt;\n        color: #4057A1;\n        font-style: italic;\n        margin-bottom: .5em;\n        margin-top: 0.5em;\n        display: block;\n    }\n    \n    .warning{\n        color: rgb( 240, 20, 20 )\n        }  ", "cell_type": "markdown", "metadata": {}}], "nbformat_minor": 0}
\ No newline at end of file
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 8.1 Parsing Unix timestamps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It's not obvious how to deal with Unix timestamps in pandas -- it took me quite a while to figure this out. The file we're using here is a popularity-contest file I found on my system at `/var/log/popularity-contest`.\n",
+    "\n",
+    "Here's an [explanation of how this file works](http://popcon.ubuntu.com/README).\n",
+    "\n",
+    "I'm going to hope that nothing in it is sensitive :)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read it, and remove the last row\n",
+    "popcon = pd.read_csv('../data/popularity-contest', sep=' ', )[:-1]\n",
+    "popcon.columns = ['atime', 'ctime', 'package-name', 'mru-program', 'tag']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The colums are the access time, created time, package name, recently used program, and a tag"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>atime</th>\n",
+       "      <th>ctime</th>\n",
+       "      <th>package-name</th>\n",
+       "      <th>mru-program</th>\n",
+       "      <th>tag</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1387295797</td>\n",
+       "      <td>1367633260</td>\n",
+       "      <td>perl-base</td>\n",
+       "      <td>/usr/bin/perl</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1387295796</td>\n",
+       "      <td>1354370480</td>\n",
+       "      <td>login</td>\n",
+       "      <td>/bin/su</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1387295743</td>\n",
+       "      <td>1354341275</td>\n",
+       "      <td>libtalloc2</td>\n",
+       "      <td>/usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1387295743</td>\n",
+       "      <td>1387224204</td>\n",
+       "      <td>libwbclient0</td>\n",
+       "      <td>/usr/lib/x86_64-linux-gnu/libwbclient.so.0</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1387295742</td>\n",
+       "      <td>1354341253</td>\n",
+       "      <td>libselinux1</td>\n",
+       "      <td>/lib/x86_64-linux-gnu/libselinux.so.1</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        atime       ctime  package-name  \\\n",
+       "0  1387295797  1367633260     perl-base   \n",
+       "1  1387295796  1354370480         login   \n",
+       "2  1387295743  1354341275    libtalloc2   \n",
+       "3  1387295743  1387224204  libwbclient0   \n",
+       "4  1387295742  1354341253   libselinux1   \n",
+       "\n",
+       "                                    mru-program             tag  \n",
+       "0                                 /usr/bin/perl             NaN  \n",
+       "1                                       /bin/su             NaN  \n",
+       "2  /usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7             NaN  \n",
+       "3    /usr/lib/x86_64-linux-gnu/libwbclient.so.0  <RECENT-CTIME>  \n",
+       "4         /lib/x86_64-linux-gnu/libselinux.so.1             NaN  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "popcon[:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The magical part about parsing timestamps in pandas is that numpy datetimes are already stored as Unix timestamps. So all we need to do is tell pandas that these integers are actually datetimes -- it doesn't need to do any conversion at all.\n",
+    "\n",
+    "We need to convert these to ints to start:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "popcon['atime'] = popcon['atime'].astype(int)\n",
+    "popcon['ctime'] = popcon['ctime'].astype(int)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Every numpy array and pandas series has a dtype -- this is usually `int64`, `float64`, or `object`. Some of the time types available are `datetime64[s]`, `datetime64[ms]`, and `datetime64[us]`. There are also `timedelta` types, similarly.\n",
+    "\n",
+    "We can use the `pd.to_datetime` function to convert our integer timestamps into datetimes. This is a constant-time operation -- we're not actually changing any of the data, just how pandas thinks about it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "popcon['atime'] = pd.to_datetime(popcon['atime'], unit='s')\n",
+    "popcon['ctime'] = pd.to_datetime(popcon['ctime'], unit='s')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we look at the dtype now, it's `<M8[ns]`. As far as I can tell `M8` is secret code for `datetime64`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dtype('<M8[ns]')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "popcon['atime'].dtype"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So now we can look at our `atime` and `ctime` as dates!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>atime</th>\n",
+       "      <th>ctime</th>\n",
+       "      <th>package-name</th>\n",
+       "      <th>mru-program</th>\n",
+       "      <th>tag</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2013-12-17 15:56:37</td>\n",
+       "      <td>2013-05-04 02:07:40</td>\n",
+       "      <td>perl-base</td>\n",
+       "      <td>/usr/bin/perl</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2013-12-17 15:56:36</td>\n",
+       "      <td>2012-12-01 14:01:20</td>\n",
+       "      <td>login</td>\n",
+       "      <td>/bin/su</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2013-12-17 15:55:43</td>\n",
+       "      <td>2012-12-01 05:54:35</td>\n",
+       "      <td>libtalloc2</td>\n",
+       "      <td>/usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2013-12-17 15:55:43</td>\n",
+       "      <td>2013-12-16 20:03:24</td>\n",
+       "      <td>libwbclient0</td>\n",
+       "      <td>/usr/lib/x86_64-linux-gnu/libwbclient.so.0</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2013-12-17 15:55:42</td>\n",
+       "      <td>2012-12-01 05:54:13</td>\n",
+       "      <td>libselinux1</td>\n",
+       "      <td>/lib/x86_64-linux-gnu/libselinux.so.1</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                atime               ctime  package-name  \\\n",
+       "0 2013-12-17 15:56:37 2013-05-04 02:07:40     perl-base   \n",
+       "1 2013-12-17 15:56:36 2012-12-01 14:01:20         login   \n",
+       "2 2013-12-17 15:55:43 2012-12-01 05:54:35    libtalloc2   \n",
+       "3 2013-12-17 15:55:43 2013-12-16 20:03:24  libwbclient0   \n",
+       "4 2013-12-17 15:55:42 2012-12-01 05:54:13   libselinux1   \n",
+       "\n",
+       "                                    mru-program             tag  \n",
+       "0                                 /usr/bin/perl             NaN  \n",
+       "1                                       /bin/su             NaN  \n",
+       "2  /usr/lib/x86_64-linux-gnu/libtalloc.so.2.0.7             NaN  \n",
+       "3    /usr/lib/x86_64-linux-gnu/libwbclient.so.0  <RECENT-CTIME>  \n",
+       "4         /lib/x86_64-linux-gnu/libselinux.so.1             NaN  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "popcon[:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now suppose we want to look at all packages that aren't libraries.\n",
+    "\n",
+    "First, I want to get rid of everything with timestamp 0. Notice how we can just use a string in this comparison, even though it's actually a timestamp on the inside? That is because pandas is amazing."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "popcon = popcon[popcon['atime'] > '1970-01-01']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use pandas' magical string abilities to just look at rows where the package name doesn't contain 'lib'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nonlibraries = popcon[~popcon['package-name'].str.contains('lib')]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>atime</th>\n",
+       "      <th>ctime</th>\n",
+       "      <th>package-name</th>\n",
+       "      <th>mru-program</th>\n",
+       "      <th>tag</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>2013-12-17 04:55:39</td>\n",
+       "      <td>2013-12-17 04:55:42</td>\n",
+       "      <td>ddd</td>\n",
+       "      <td>/usr/bin/ddd</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>450</th>\n",
+       "      <td>2013-12-16 20:03:20</td>\n",
+       "      <td>2013-12-16 20:05:13</td>\n",
+       "      <td>nodejs</td>\n",
+       "      <td>/usr/bin/npm</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>454</th>\n",
+       "      <td>2013-12-16 20:03:20</td>\n",
+       "      <td>2013-12-16 20:05:04</td>\n",
+       "      <td>switchboard-plug-keyboard</td>\n",
+       "      <td>/usr/lib/plugs/pantheon/keyboard/options.txt</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>445</th>\n",
+       "      <td>2013-12-16 20:03:20</td>\n",
+       "      <td>2013-12-16 20:05:04</td>\n",
+       "      <td>thunderbird-locale-en</td>\n",
+       "      <td>/usr/lib/thunderbird-addons/extensions/langpac...</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>396</th>\n",
+       "      <td>2013-12-16 20:08:27</td>\n",
+       "      <td>2013-12-16 20:05:03</td>\n",
+       "      <td>software-center</td>\n",
+       "      <td>/usr/sbin/update-software-center</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>449</th>\n",
+       "      <td>2013-12-16 20:03:20</td>\n",
+       "      <td>2013-12-16 20:05:00</td>\n",
+       "      <td>samba-common-bin</td>\n",
+       "      <td>/usr/bin/net.samba3</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>397</th>\n",
+       "      <td>2013-12-16 20:08:25</td>\n",
+       "      <td>2013-12-16 20:04:59</td>\n",
+       "      <td>postgresql-client-9.1</td>\n",
+       "      <td>/usr/lib/postgresql/9.1/bin/psql</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>398</th>\n",
+       "      <td>2013-12-16 20:08:23</td>\n",
+       "      <td>2013-12-16 20:04:58</td>\n",
+       "      <td>postgresql-9.1</td>\n",
+       "      <td>/usr/lib/postgresql/9.1/bin/postmaster</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>452</th>\n",
+       "      <td>2013-12-16 20:03:20</td>\n",
+       "      <td>2013-12-16 20:04:55</td>\n",
+       "      <td>php5-dev</td>\n",
+       "      <td>/usr/include/php5/main/snprintf.h</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>440</th>\n",
+       "      <td>2013-12-16 20:03:20</td>\n",
+       "      <td>2013-12-16 20:04:54</td>\n",
+       "      <td>php-pear</td>\n",
+       "      <td>/usr/share/php/XML/Util.php</td>\n",
+       "      <td>&lt;RECENT-CTIME&gt;</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  atime               ctime               package-name  \\\n",
+       "57  2013-12-17 04:55:39 2013-12-17 04:55:42                        ddd   \n",
+       "450 2013-12-16 20:03:20 2013-12-16 20:05:13                     nodejs   \n",
+       "454 2013-12-16 20:03:20 2013-12-16 20:05:04  switchboard-plug-keyboard   \n",
+       "445 2013-12-16 20:03:20 2013-12-16 20:05:04      thunderbird-locale-en   \n",
+       "396 2013-12-16 20:08:27 2013-12-16 20:05:03            software-center   \n",
+       "449 2013-12-16 20:03:20 2013-12-16 20:05:00           samba-common-bin   \n",
+       "397 2013-12-16 20:08:25 2013-12-16 20:04:59      postgresql-client-9.1   \n",
+       "398 2013-12-16 20:08:23 2013-12-16 20:04:58             postgresql-9.1   \n",
+       "452 2013-12-16 20:03:20 2013-12-16 20:04:55                   php5-dev   \n",
+       "440 2013-12-16 20:03:20 2013-12-16 20:04:54                   php-pear   \n",
+       "\n",
+       "                                           mru-program             tag  \n",
+       "57                                        /usr/bin/ddd  <RECENT-CTIME>  \n",
+       "450                                       /usr/bin/npm  <RECENT-CTIME>  \n",
+       "454       /usr/lib/plugs/pantheon/keyboard/options.txt  <RECENT-CTIME>  \n",
+       "445  /usr/lib/thunderbird-addons/extensions/langpac...  <RECENT-CTIME>  \n",
+       "396                   /usr/sbin/update-software-center  <RECENT-CTIME>  \n",
+       "449                                /usr/bin/net.samba3  <RECENT-CTIME>  \n",
+       "397                   /usr/lib/postgresql/9.1/bin/psql  <RECENT-CTIME>  \n",
+       "398             /usr/lib/postgresql/9.1/bin/postmaster  <RECENT-CTIME>  \n",
+       "452                  /usr/include/php5/main/snprintf.h  <RECENT-CTIME>  \n",
+       "440                        /usr/share/php/XML/Util.php  <RECENT-CTIME>  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nonlibraries.sort_values('ctime', ascending=False)[:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Okay, cool, it says that I I installed ddd recently. And postgresql! I remember installing those things. Neat."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The whole message here is that if you have a timestamp in seconds or milliseconds or nanoseconds, then you can just \"cast\" it to a `'datetime64[the-right-thing]'` and pandas/numpy will take care of the rest."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<style>\n",
+    "    @font-face {\n",
+    "        font-family: \"Computer Modern\";\n",
+    "        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
+    "    }\n",
+    "    div.cell{\n",
+    "        width:800px;\n",
+    "        margin-left:16% !important;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    h1 {\n",
+    "        font-family: Helvetica, serif;\n",
+    "    }\n",
+    "    h4{\n",
+    "        margin-top:12px;\n",
+    "        margin-bottom: 3px;\n",
+    "       }\n",
+    "    div.text_cell_render{\n",
+    "        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
+    "        line-height: 145%;\n",
+    "        font-size: 130%;\n",
+    "        width:800px;\n",
+    "        margin-left:auto;\n",
+    "        margin-right:auto;\n",
+    "    }\n",
+    "    .CodeMirror{\n",
+    "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
+    "    }\n",
+    "    .text_cell_render h5 {\n",
+    "        font-weight: 300;\n",
+    "        font-size: 22pt;\n",
+    "        color: #4057A1;\n",
+    "        font-style: italic;\n",
+    "        margin-bottom: .5em;\n",
+    "        margin-top: 0.5em;\n",
+    "        display: block;\n",
+    "    }\n",
+    "    \n",
+    "    .warning{\n",
+    "        color: rgb( 240, 20, 20 )\n",
+    "        }  "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/cookbook/Chapter 9 - Loading data from SQL databases.ipynb b/cookbook/Chapter 9 - Loading data from SQL databases.ipynb
index c09e04cbc..c02d8cd36 100644
--- a/cookbook/Chapter 9 - Loading data from SQL databases.ipynb	
+++ b/cookbook/Chapter 9 - Loading data from SQL databases.ipynb	
@@ -3,9 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd\n",
@@ -35,14 +33,25 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -55,20 +64,20 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td> 1</td>\n",
-       "      <td> 2012-01-01 00:00:00</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2012-01-01 00:00:00</td>\n",
        "      <td>-1.8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td> 2</td>\n",
-       "      <td> 2012-01-01 01:00:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2012-01-01 01:00:00</td>\n",
        "      <td>-1.8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td> 3</td>\n",
-       "      <td> 2012-01-01 02:00:00</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2012-01-01 02:00:00</td>\n",
        "      <td>-1.8</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -105,14 +114,25 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -129,17 +149,17 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td> 2012-01-01 00:00:00</td>\n",
+       "      <td>2012-01-01 00:00:00</td>\n",
        "      <td>-1.8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td> 2012-01-01 01:00:00</td>\n",
+       "      <td>2012-01-01 01:00:00</td>\n",
        "      <td>-1.8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td> 2012-01-01 02:00:00</td>\n",
+       "      <td>2012-01-01 02:00:00</td>\n",
        "      <td>-1.8</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -174,14 +194,25 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -253,16 +284,14 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/usr/lib64/python2.7/site-packages/pandas/io/sql.py:1309: UserWarning: The spaces in these column names will not be changed. In pandas versions < 0.14, spaces were converted to underscores.\n",
-      "  warnings.warn(_SAFE_NAMES_WARNING)\n"
+      "/home/gabriela/.local/share/virtualenvs/pandas-cookbook-M4OY_8hn/lib/python3.5/site-packages/pandas/core/generic.py:2130: UserWarning: The spaces in these column names will not be changed. In pandas versions < 0.14, spaces were converted to underscores.\n",
+      "  dtype=dtype)\n"
      ]
     }
    ],
@@ -283,14 +312,25 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -309,39 +349,39 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td> 0</td>\n",
-       "      <td> 2012-01-01 00:00:00</td>\n",
-       "      <td>-1.8</td>\n",
-       "      <td>-3.9</td>\n",
-       "      <td> 86</td>\n",
-       "      <td> 4</td>\n",
-       "      <td> 8</td>\n",
-       "      <td> 101.24</td>\n",
-       "      <td>                  Fog</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2013-01-01 00:00:00</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1.7</td>\n",
+       "      <td>95</td>\n",
+       "      <td>35</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>99.89</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td> 1</td>\n",
-       "      <td> 2012-01-01 01:00:00</td>\n",
-       "      <td>-1.8</td>\n",
-       "      <td>-3.7</td>\n",
-       "      <td> 87</td>\n",
-       "      <td> 4</td>\n",
-       "      <td> 8</td>\n",
-       "      <td> 101.24</td>\n",
-       "      <td>                  Fog</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2013-01-01 01:00:00</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>-5.1</td>\n",
+       "      <td>79</td>\n",
+       "      <td>35</td>\n",
+       "      <td>16.1</td>\n",
+       "      <td>99.93</td>\n",
+       "      <td>Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td> 2</td>\n",
-       "      <td> 2012-01-01 02:00:00</td>\n",
-       "      <td>-1.8</td>\n",
-       "      <td>-3.4</td>\n",
-       "      <td> 89</td>\n",
-       "      <td> 7</td>\n",
-       "      <td> 4</td>\n",
-       "      <td> 101.26</td>\n",
-       "      <td> Freezing Drizzle,Fog</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2013-01-01 02:00:00</td>\n",
+       "      <td>-2.7</td>\n",
+       "      <td>-6.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>28</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>100.08</td>\n",
+       "      <td>Snow</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -349,14 +389,14 @@
       ],
       "text/plain": [
        "   index            Date/Time  Temp (C)  Dew Point Temp (C)  Rel Hum (%)  \\\n",
-       "0      0  2012-01-01 00:00:00      -1.8                -3.9           86   \n",
-       "1      1  2012-01-01 01:00:00      -1.8                -3.7           87   \n",
-       "2      2  2012-01-01 02:00:00      -1.8                -3.4           89   \n",
+       "0      0  2013-01-01 00:00:00      -1.0                -1.7           95   \n",
+       "1      1  2013-01-01 01:00:00      -2.0                -5.1           79   \n",
+       "2      2  2013-01-01 02:00:00      -2.7                -6.0           78   \n",
        "\n",
-       "   Wind Spd (km/h)  Visibility (km)  Stn Press (kPa)               Weather  \n",
-       "0                4                8           101.24                   Fog  \n",
-       "1                4                8           101.24                   Fog  \n",
-       "2                7                4           101.26  Freezing Drizzle,Fog  "
+       "   Wind Spd (km/h)  Visibility (km)  Stn Press (kPa)       Weather  \n",
+       "0               35              6.4            99.89          Snow  \n",
+       "1               35             16.1            99.93  Mainly Clear  \n",
+       "2               28             19.3           100.08          Snow  "
       ]
      },
      "execution_count": 6,
@@ -380,14 +420,25 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
@@ -406,39 +457,39 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>  67</td>\n",
-       "      <td> 2012-01-03 19:00:00</td>\n",
-       "      <td>-16.9</td>\n",
-       "      <td>-24.8</td>\n",
-       "      <td> 50</td>\n",
-       "      <td> 24</td>\n",
-       "      <td> 25</td>\n",
-       "      <td> 101.74</td>\n",
-       "      <td> Clear</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2013-01-01 03:00:00</td>\n",
+       "      <td>-5.6</td>\n",
+       "      <td>-11.7</td>\n",
+       "      <td>62</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.21</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td> 114</td>\n",
-       "      <td> 2012-01-05 18:00:00</td>\n",
-       "      <td> -7.1</td>\n",
-       "      <td>-14.4</td>\n",
-       "      <td> 56</td>\n",
-       "      <td> 11</td>\n",
-       "      <td> 25</td>\n",
-       "      <td> 100.71</td>\n",
-       "      <td> Clear</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2013-01-01 05:00:00</td>\n",
+       "      <td>-9.7</td>\n",
+       "      <td>-14.8</td>\n",
+       "      <td>66</td>\n",
+       "      <td>33</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.47</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td> 115</td>\n",
-       "      <td> 2012-01-05 19:00:00</td>\n",
-       "      <td> -9.2</td>\n",
-       "      <td>-15.4</td>\n",
-       "      <td> 61</td>\n",
-       "      <td>  7</td>\n",
-       "      <td> 25</td>\n",
-       "      <td> 100.80</td>\n",
-       "      <td> Clear</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2013-01-01 06:00:00</td>\n",
+       "      <td>-11.1</td>\n",
+       "      <td>-17.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>30</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>100.65</td>\n",
+       "      <td>Clear</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -446,14 +497,14 @@
       ],
       "text/plain": [
        "   index            Date/Time  Temp (C)  Dew Point Temp (C)  Rel Hum (%)  \\\n",
-       "0     67  2012-01-03 19:00:00     -16.9               -24.8           50   \n",
-       "1    114  2012-01-05 18:00:00      -7.1               -14.4           56   \n",
-       "2    115  2012-01-05 19:00:00      -9.2               -15.4           61   \n",
+       "0      3  2013-01-01 03:00:00      -5.6               -11.7           62   \n",
+       "1      5  2013-01-01 05:00:00      -9.7               -14.8           66   \n",
+       "2      6  2013-01-01 06:00:00     -11.1               -17.0           62   \n",
        "\n",
        "   Wind Spd (km/h)  Visibility (km)  Stn Press (kPa) Weather  \n",
-       "0               24               25           101.74   Clear  \n",
-       "1               11               25           100.71   Clear  \n",
-       "2                7               25           100.80   Clear  "
+       "0               30             25.0           100.21   Clear  \n",
+       "1               33             25.0           100.47   Clear  \n",
+       "2               30             25.0           100.65   Clear  "
       ]
      },
      "execution_count": 7,
@@ -494,9 +545,7 @@
   },
   {
    "cell_type": "raw",
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "source": [
     "import MySQLdb\n",
     "con = MySQLdb.connect(host=\"localhost\", db=\"test\")"
@@ -511,9 +560,7 @@
   },
   {
    "cell_type": "raw",
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "source": [
     "import psycopg2\n",
     "con = psycopg2.connect(host=\"localhost\")"
@@ -569,23 +616,23 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
-   "name": "python2"
+   "display_name": "pandas-cookbook",
+   "language": "python",
+   "name": "pandas-cookbook"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.8"
-  },
-  "signature": "sha256:358c6afeae83edbf449270614551dff12e927538bc48c2d47da9a6a737f6ad31"
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
  },
  "nbformat": 4,
- "nbformat_minor": 0
-}
\ No newline at end of file
+ "nbformat_minor": 1
+}
diff --git a/data/weather_2012.csv b/data/weather_2012.csv
index 0c9347fe0..2fe5a2a06 100644
--- a/data/weather_2012.csv
+++ b/data/weather_2012.csv
@@ -1,748 +1,748 @@
 Date/Time,Temp (C),Dew Point Temp (C),Rel Hum (%),Wind Spd (km/h),Visibility (km),Stn Press (kPa),Weather
-2012-01-01 00:00:00,-1.8,-3.9,86,4,8.0,101.24,Fog
-2012-01-01 01:00:00,-1.8,-3.7,87,4,8.0,101.24,Fog
-2012-01-01 02:00:00,-1.8,-3.4,89,7,4.0,101.26,"Freezing Drizzle,Fog"
-2012-01-01 03:00:00,-1.5,-3.2,88,6,4.0,101.27,"Freezing Drizzle,Fog"
-2012-01-01 04:00:00,-1.5,-3.3,88,7,4.8,101.23,Fog
-2012-01-01 05:00:00,-1.4,-3.3,87,9,6.4,101.27,Fog
-2012-01-01 06:00:00,-1.5,-3.1,89,7,6.4,101.29,Fog
-2012-01-01 07:00:00,-1.4,-3.6,85,7,8.0,101.26,Fog
-2012-01-01 08:00:00,-1.4,-3.6,85,9,8.0,101.23,Fog
-2012-01-01 09:00:00,-1.3,-3.1,88,15,4.0,101.2,Fog
-2012-01-01 10:00:00,-1.0,-2.3,91,9,1.2,101.15,Fog
-2012-01-01 11:00:00,-0.5,-2.1,89,7,4.0,100.98,Fog
-2012-01-01 12:00:00,-0.2,-2.0,88,9,4.8,100.79,Fog
-2012-01-01 13:00:00,0.2,-1.7,87,13,4.8,100.58,Fog
-2012-01-01 14:00:00,0.8,-1.1,87,20,4.8,100.31,Fog
-2012-01-01 15:00:00,1.8,-0.4,85,22,6.4,100.07,Fog
-2012-01-01 16:00:00,2.6,-0.2,82,13,12.9,99.93,Mostly Cloudy
-2012-01-01 17:00:00,3.0,0.0,81,13,16.1,99.81,Cloudy
-2012-01-01 18:00:00,3.8,1.0,82,15,12.9,99.74,Rain
-2012-01-01 19:00:00,3.1,1.3,88,15,12.9,99.68,Rain
-2012-01-01 20:00:00,3.2,1.3,87,19,25.0,99.5,Cloudy
-2012-01-01 21:00:00,4.0,1.7,85,20,25.0,99.39,Cloudy
-2012-01-01 22:00:00,4.4,1.9,84,24,19.3,99.32,Rain Showers
-2012-01-01 23:00:00,5.3,2.0,79,30,25.0,99.31,Cloudy
-2012-01-02 00:00:00,5.2,1.5,77,35,25.0,99.26,Rain Showers
-2012-01-02 01:00:00,4.6,0.0,72,39,25.0,99.26,Cloudy
-2012-01-02 02:00:00,3.9,-0.9,71,32,25.0,99.26,Mostly Cloudy
-2012-01-02 03:00:00,3.7,-1.5,69,33,25.0,99.3,Mostly Cloudy
-2012-01-02 04:00:00,2.9,-2.3,69,32,25.0,99.26,Mostly Cloudy
-2012-01-02 05:00:00,2.6,-2.3,70,32,25.0,99.21,Mostly Cloudy
-2012-01-02 06:00:00,2.3,-2.6,70,26,25.0,99.18,Mostly Cloudy
-2012-01-02 07:00:00,2.0,-2.9,70,33,25.0,99.14,Mostly Cloudy
-2012-01-02 08:00:00,1.9,-3.3,68,39,24.1,99.14,Mostly Cloudy
-2012-01-02 09:00:00,1.8,-3.7,67,44,24.1,99.14,Mostly Cloudy
-2012-01-02 10:00:00,1.5,-4.1,66,43,24.1,99.18,Mostly Cloudy
-2012-01-02 11:00:00,2.2,-3.5,66,30,24.1,99.19,Mostly Cloudy
-2012-01-02 12:00:00,1.7,-6.2,56,48,24.1,99.21,Mainly Clear
-2012-01-02 13:00:00,1.1,-6.5,57,37,24.1,99.27,Mostly Cloudy
-2012-01-02 14:00:00,1.1,-6.8,56,33,24.1,99.33,Mostly Cloudy
-2012-01-02 15:00:00,0.0,-7.0,59,33,24.1,99.41,Mostly Cloudy
-2012-01-02 16:00:00,-0.7,-8.7,55,24,24.1,99.5,Mostly Cloudy
-2012-01-02 17:00:00,-2.1,-9.5,57,22,25.0,99.66,Snow Showers
-2012-01-02 18:00:00,-4.1,-11.4,57,28,25.0,99.86,Mostly Cloudy
-2012-01-02 19:00:00,-4.8,-12.1,57,24,25.0,100.0,Mostly Cloudy
-2012-01-02 20:00:00,-5.6,-13.4,54,24,25.0,100.07,Snow Showers
-2012-01-02 21:00:00,-5.8,-12.8,58,26,25.0,100.15,Snow Showers
-2012-01-02 22:00:00,-7.0,-14.7,54,20,25.0,100.26,Cloudy
-2012-01-02 23:00:00,-7.4,-14.1,59,17,19.3,100.27,Snow Showers
-2012-01-03 00:00:00,-9.0,-16.0,57,28,25.0,100.35,Snow Showers
-2012-01-03 01:00:00,-9.7,-17.2,54,20,25.0,100.43,Cloudy
-2012-01-03 02:00:00,-10.5,-15.8,65,22,12.9,100.53,Snow Showers
-2012-01-03 03:00:00,-11.3,-18.7,54,33,25.0,100.61,Snow Showers
-2012-01-03 04:00:00,-12.6,-20.1,53,24,25.0,100.68,Cloudy
-2012-01-03 05:00:00,-12.9,-19.1,60,22,25.0,100.76,Snow Showers
-2012-01-03 06:00:00,-13.3,-19.3,61,19,25.0,100.85,Snow Showers
-2012-01-03 07:00:00,-14.0,-19.5,63,19,25.0,100.95,Snow
-2012-01-03 08:00:00,-14.8,-21.3,58,26,24.1,101.07,Mostly Cloudy
-2012-01-03 09:00:00,-15.0,-21.9,56,19,24.1,101.2,Mostly Cloudy
-2012-01-03 10:00:00,-15.3,-22.2,56,24,24.1,101.29,Cloudy
-2012-01-03 11:00:00,-14.9,-22.2,54,22,24.1,101.33,Mostly Cloudy
-2012-01-03 12:00:00,-14.9,-22.6,52,20,24.1,101.34,Mainly Clear
-2012-01-03 13:00:00,-15.1,-22.4,54,22,24.1,101.34,Mainly Clear
-2012-01-03 14:00:00,-14.9,-22.9,50,22,24.1,101.38,Mainly Clear
-2012-01-03 15:00:00,-14.8,-22.2,53,19,24.1,101.44,Mainly Clear
-2012-01-03 16:00:00,-15.3,-22.9,52,22,24.1,101.51,Mainly Clear
-2012-01-03 17:00:00,-15.8,-23.2,53,22,24.1,101.58,Mainly Clear
-2012-01-03 18:00:00,-16.3,-23.8,52,24,25.0,101.64,Mainly Clear
-2012-01-03 19:00:00,-16.9,-24.8,50,24,25.0,101.74,Clear
-2012-01-03 20:00:00,-17.3,-25.4,49,24,25.0,101.82,Mainly Clear
-2012-01-03 21:00:00,-17.0,-24.6,52,15,25.0,101.86,Mostly Cloudy
-2012-01-03 22:00:00,-17.1,-24.6,52,20,25.0,101.86,Mostly Cloudy
-2012-01-03 23:00:00,-17.3,-24.2,55,17,25.0,101.87,Mostly Cloudy
-2012-01-04 00:00:00,-17.5,-24.2,56,13,25.0,101.88,Mostly Cloudy
-2012-01-04 01:00:00,-17.9,-24.1,58,11,25.0,101.86,Mainly Clear
-2012-01-04 02:00:00,-18.1,-23.8,61,15,25.0,101.89,Mainly Clear
-2012-01-04 03:00:00,-18.5,-24.6,59,13,25.0,101.88,Mainly Clear
-2012-01-04 04:00:00,-18.5,-24.6,59,13,25.0,101.82,Mainly Clear
-2012-01-04 05:00:00,-18.6,-24.0,62,9,25.0,101.77,Mainly Clear
-2012-01-04 06:00:00,-18.5,-24.1,61,11,25.0,101.74,Cloudy
-2012-01-04 07:00:00,-18.2,-24.1,60,11,25.0,101.75,Cloudy
-2012-01-04 08:00:00,-17.8,-24.2,57,17,24.1,101.73,Mostly Cloudy
-2012-01-04 09:00:00,-16.8,-22.5,61,9,24.1,101.68,Mostly Cloudy
-2012-01-04 10:00:00,-15.2,-20.6,63,7,24.1,101.54,Mostly Cloudy
-2012-01-04 11:00:00,-14.2,-21.1,56,13,24.1,101.41,Mostly Cloudy
-2012-01-04 12:00:00,-13.7,-21.7,51,11,24.1,101.25,Snow
-2012-01-04 13:00:00,-12.4,-20.1,53,11,24.1,101.07,Cloudy
-2012-01-04 14:00:00,-11.3,-19.0,53,7,19.3,100.97,Snow
-2012-01-04 15:00:00,-10.2,-16.3,61,11,9.7,100.89,Snow
-2012-01-04 16:00:00,-9.4,-15.5,61,13,19.3,100.79,Snow
-2012-01-04 17:00:00,-8.9,-13.2,71,9,4.8,100.76,Snow
-2012-01-04 18:00:00,-8.9,-12.6,75,11,9.7,100.69,Snow
-2012-01-04 19:00:00,-8.4,-12.7,71,9,16.1,100.65,Snow
-2012-01-04 20:00:00,-7.8,-12.1,71,9,16.1,100.61,Snow
-2012-01-04 21:00:00,-7.6,-11.6,73,7,11.3,100.54,Snow
-2012-01-04 22:00:00,-9.5,-12.7,77,6,9.7,100.5,Snow
-2012-01-04 23:00:00,-9.6,-12.6,79,6,9.7,100.42,Snow
-2012-01-05 00:00:00,-8.8,-11.7,79,4,9.7,100.32,Snow
-2012-01-05 01:00:00,-7.5,-10.2,81,0,9.7,100.29,Snow
-2012-01-05 02:00:00,-5.4,-8.3,80,9,8.0,100.28,Snow
-2012-01-05 03:00:00,-5.0,-7.7,81,11,9.7,100.24,Snow
-2012-01-05 04:00:00,-4.1,-6.5,83,9,4.8,100.21,Snow
-2012-01-05 05:00:00,-7.0,-9.5,82,4,4.0,100.19,Snow
-2012-01-05 06:00:00,-8.2,-10.7,82,6,6.4,100.26,Snow
-2012-01-05 07:00:00,-7.1,-9.7,82,9,9.7,100.31,Snow
-2012-01-05 08:00:00,-6.1,-9.1,79,11,9.7,100.39,Snow
-2012-01-05 09:00:00,-6.6,-10.1,76,9,24.1,100.42,Mainly Clear
-2012-01-05 10:00:00,-6.0,-10.0,73,17,48.3,100.45,Mainly Clear
-2012-01-05 11:00:00,-5.6,-10.2,70,22,48.3,100.41,Mainly Clear
-2012-01-05 12:00:00,-4.7,-9.6,69,20,48.3,100.38,Mainly Clear
-2012-01-05 13:00:00,-4.4,-9.7,66,26,48.3,100.4,Mainly Clear
-2012-01-05 14:00:00,-5.1,-10.7,65,22,48.3,100.46,Mainly Clear
-2012-01-05 15:00:00,-4.3,-12.0,55,26,48.3,100.52,Mainly Clear
-2012-01-05 16:00:00,-5.0,-12.7,55,19,24.1,100.6,Mainly Clear
-2012-01-05 17:00:00,-6.7,-14.1,56,11,25.0,100.65,Mainly Clear
-2012-01-05 18:00:00,-7.1,-14.4,56,11,25.0,100.71,Clear
-2012-01-05 19:00:00,-9.2,-15.4,61,7,25.0,100.8,Clear
-2012-01-05 20:00:00,-9.8,-15.7,62,9,25.0,100.83,Clear
-2012-01-05 21:00:00,-9.0,-14.8,63,13,25.0,100.83,Clear
-2012-01-05 22:00:00,-9.9,-15.7,63,7,25.0,100.85,Cloudy
-2012-01-05 23:00:00,-9.4,-15.5,61,9,25.0,100.83,Cloudy
-2012-01-06 00:00:00,-9.6,-16.8,56,13,25.0,100.81,Cloudy
-2012-01-06 01:00:00,-10.0,-17.3,55,17,25.0,100.81,Cloudy
-2012-01-06 02:00:00,-10.5,-16.5,61,9,25.0,100.84,Cloudy
-2012-01-06 03:00:00,-10.6,-16.0,64,0,9.7,100.76,Snow
-2012-01-06 04:00:00,-11.3,-16.1,68,15,3.2,100.7,Snow
-2012-01-06 05:00:00,-11.8,-16.0,71,19,2.8,100.61,Snow
-2012-01-06 06:00:00,-12.0,-16.2,71,22,4.8,100.58,Snow
-2012-01-06 07:00:00,-14.4,-16.3,85,22,2.4,100.52,Snow
-2012-01-06 08:00:00,-12.3,-16.2,73,24,11.3,100.51,Snow
-2012-01-06 09:00:00,-12.5,-16.7,71,26,19.3,100.53,Snow
-2012-01-06 10:00:00,-12.3,-16.3,72,28,16.1,100.47,Snow
-2012-01-06 11:00:00,-12.0,-16.0,72,17,24.1,100.36,Snow
-2012-01-06 12:00:00,-11.7,-15.4,74,28,19.3,100.23,Snow
-2012-01-06 13:00:00,-11.9,-15.6,74,20,24.1,100.13,Snow
-2012-01-06 14:00:00,-11.2,-14.8,75,19,19.3,100.07,Snow
-2012-01-06 15:00:00,-11.5,-14.4,79,19,12.9,100.06,Snow
-2012-01-06 16:00:00,-11.6,-14.7,78,19,19.3,100.1,Snow
-2012-01-06 17:00:00,-11.2,-14.3,78,17,25.0,100.15,Snow
-2012-01-06 18:00:00,-10.5,-13.6,78,17,19.3,100.12,Cloudy
-2012-01-06 19:00:00,-10.5,-13.4,79,15,25.0,100.13,Cloudy
-2012-01-06 20:00:00,-10.2,-13.0,80,11,25.0,100.15,Cloudy
-2012-01-06 21:00:00,-9.5,-12.5,79,9,25.0,100.13,Cloudy
-2012-01-06 22:00:00,-9.3,-12.2,79,11,19.3,100.16,Cloudy
-2012-01-06 23:00:00,-9.0,-12.0,79,7,16.1,100.15,Cloudy
-2012-01-07 00:00:00,-8.7,-11.7,79,6,16.1,100.13,Cloudy
-2012-01-07 01:00:00,-8.5,-11.4,80,0,19.3,100.11,Cloudy
-2012-01-07 02:00:00,-8.1,-11.1,79,4,19.3,100.15,Cloudy
-2012-01-07 03:00:00,-7.8,-10.8,79,4,19.3,100.12,Cloudy
-2012-01-07 04:00:00,-7.5,-10.5,79,6,19.3,100.1,Cloudy
-2012-01-07 05:00:00,-6.9,-9.7,80,4,19.3,100.12,Cloudy
-2012-01-07 06:00:00,-6.7,-9.5,80,7,16.1,100.12,Cloudy
-2012-01-07 07:00:00,-7.0,-9.7,81,7,16.1,100.16,Cloudy
-2012-01-07 08:00:00,-6.4,-9.0,82,9,8.0,100.1,"Freezing Drizzle,Fog"
-2012-01-07 09:00:00,-6.1,-8.7,82,7,9.7,100.15,"Freezing Rain,Fog"
-2012-01-07 10:00:00,-5.7,-8.0,84,7,8.0,100.13,Freezing Rain
-2012-01-07 11:00:00,-5.4,-7.7,84,9,9.7,100.08,Freezing Drizzle
-2012-01-07 12:00:00,-5.5,-7.8,84,13,9.7,100.05,Freezing Drizzle
-2012-01-07 13:00:00,-4.8,-7.2,83,15,9.7,100.07,Freezing Rain
-2012-01-07 14:00:00,-4.4,-6.9,83,6,8.0,100.09,Snow
-2012-01-07 15:00:00,-3.7,-6.1,83,11,8.0,100.09,Snow
-2012-01-07 16:00:00,-3.6,-5.9,84,0,8.0,100.15,Snow
-2012-01-07 17:00:00,-3.1,-5.4,84,13,8.0,100.27,Snow
-2012-01-07 18:00:00,-3.2,-5.3,85,6,9.7,100.33,Snow
-2012-01-07 19:00:00,-3.0,-5.0,86,6,8.0,100.41,Snow
-2012-01-07 20:00:00,-1.8,-3.7,87,4,9.7,100.48,Snow
-2012-01-07 21:00:00,-1.3,-3.1,88,0,6.4,100.5,Snow
-2012-01-07 22:00:00,-1.5,-3.0,89,4,4.0,100.54,Fog
-2012-01-07 23:00:00,0.4,-1.5,87,22,9.7,100.62,Snow
-2012-01-08 00:00:00,0.6,-3.2,76,32,25.0,100.72,Cloudy
-2012-01-08 01:00:00,-0.6,-4.6,74,32,25.0,100.8,Mostly Cloudy
-2012-01-08 02:00:00,-1.7,-6.2,71,30,25.0,100.98,Mostly Cloudy
-2012-01-08 03:00:00,-3.5,-8.3,69,32,25.0,101.13,Mainly Clear
-2012-01-08 04:00:00,-4.4,-9.2,69,22,25.0,101.21,Mainly Clear
-2012-01-08 05:00:00,-5.9,-10.5,70,13,25.0,101.33,Mainly Clear
-2012-01-08 06:00:00,-5.8,-10.8,68,13,25.0,101.47,Cloudy
-2012-01-08 07:00:00,-5.6,-10.3,69,11,25.0,101.59,Cloudy
-2012-01-08 08:00:00,-5.9,-10.7,69,11,24.1,101.7,Snow
-2012-01-08 09:00:00,-6.4,-11.9,65,17,24.1,101.81,Snow
-2012-01-08 10:00:00,-6.5,-11.6,67,17,9.7,101.89,Snow
-2012-01-08 11:00:00,-7.1,-12.6,65,22,24.1,101.92,Snow
-2012-01-08 12:00:00,-6.7,-11.9,66,15,24.1,101.9,Snow
-2012-01-08 13:00:00,-6.5,-12.4,63,15,24.1,101.94,Cloudy
-2012-01-08 14:00:00,-6.5,-12.0,65,19,24.1,101.97,Mostly Cloudy
-2012-01-08 15:00:00,-6.6,-12.9,61,20,48.3,102.04,Mostly Cloudy
-2012-01-08 16:00:00,-6.6,-13.3,59,20,24.1,102.09,Mostly Cloudy
-2012-01-08 17:00:00,-7.2,-13.8,59,17,25.0,102.17,Mainly Clear
-2012-01-08 18:00:00,-8.1,-14.1,62,17,25.0,102.23,Mainly Clear
-2012-01-08 19:00:00,-8.0,-13.9,62,15,25.0,102.26,Mostly Cloudy
-2012-01-08 20:00:00,-8.3,-13.7,65,15,25.0,102.28,Mostly Cloudy
-2012-01-08 21:00:00,-8.3,-13.9,64,11,25.0,102.26,Mostly Cloudy
-2012-01-08 22:00:00,-8.7,-14.0,65,7,25.0,102.22,Mostly Cloudy
-2012-01-08 23:00:00,-9.0,-13.9,68,7,25.0,102.22,Mostly Cloudy
-2012-01-09 00:00:00,-9.2,-14.3,66,6,25.0,102.17,Mostly Cloudy
-2012-01-09 01:00:00,-9.8,-14.5,68,0,25.0,102.13,Mostly Cloudy
-2012-01-09 02:00:00,-9.0,-14.1,66,4,25.0,102.15,Mostly Cloudy
-2012-01-09 03:00:00,-8.8,-13.2,70,0,25.0,102.11,Cloudy
-2012-01-09 04:00:00,-8.5,-13.2,69,9,25.0,102.02,Cloudy
-2012-01-09 05:00:00,-8.4,-12.7,71,11,25.0,101.93,Cloudy
-2012-01-09 06:00:00,-7.7,-11.9,72,11,25.0,101.86,Cloudy
-2012-01-09 07:00:00,-6.8,-11.0,72,15,25.0,101.8,Mostly Cloudy
-2012-01-09 08:00:00,-5.9,-10.5,70,13,16.1,101.74,Snow
-2012-01-09 09:00:00,-5.4,-9.2,75,11,12.9,101.68,Snow
-2012-01-09 10:00:00,-4.8,-8.3,76,9,16.1,101.64,Snow
-2012-01-09 11:00:00,-3.7,-7.2,77,7,24.1,101.54,Snow
-2012-01-09 12:00:00,-2.5,-6.6,73,9,24.1,101.4,Cloudy
-2012-01-09 13:00:00,-1.7,-5.8,74,7,24.1,101.27,Cloudy
-2012-01-09 14:00:00,-1.4,-5.1,76,7,24.1,101.2,Cloudy
-2012-01-09 15:00:00,-1.0,-5.1,74,9,24.1,101.13,Mostly Cloudy
-2012-01-09 16:00:00,-1.3,-5.7,72,11,24.1,101.05,Mostly Cloudy
-2012-01-09 17:00:00,-1.4,-5.8,72,15,24.1,100.96,Mostly Cloudy
-2012-01-09 18:00:00,-1.0,-5.6,71,20,25.0,100.9,Mostly Cloudy
-2012-01-09 19:00:00,-1.1,-5.8,70,19,25.0,100.83,Mostly Cloudy
-2012-01-09 20:00:00,-1.5,-6.2,70,15,25.0,100.77,Mostly Cloudy
-2012-01-09 21:00:00,-1.7,-6.3,71,11,25.0,100.64,Mostly Cloudy
-2012-01-09 22:00:00,-0.3,-6.3,64,19,25.0,100.54,Mostly Cloudy
-2012-01-09 23:00:00,-0.2,-6.1,64,17,25.0,100.45,Cloudy
-2012-01-10 00:00:00,2.5,-5.2,57,30,25.0,100.38,Cloudy
-2012-01-10 01:00:00,2.3,-3.4,66,35,25.0,100.28,Snow
-2012-01-10 02:00:00,1.4,-2.5,75,19,6.4,100.23,Snow
-2012-01-10 03:00:00,1.6,-2.0,77,28,25.0,100.16,Snow
-2012-01-10 04:00:00,1.2,-1.7,81,26,25.0,100.07,Cloudy
-2012-01-10 05:00:00,0.8,-1.2,86,30,9.7,100.02,"Rain,Snow"
-2012-01-10 06:00:00,0.7,-1.2,87,30,8.0,100.04,Snow
-2012-01-10 07:00:00,1.5,-0.7,85,20,8.0,100.08,Snow
-2012-01-10 08:00:00,1.2,-1.1,85,24,16.1,100.11,Cloudy
-2012-01-10 09:00:00,1.6,-0.8,84,17,19.3,100.23,Cloudy
-2012-01-10 10:00:00,2.0,-0.9,81,24,24.1,100.27,Mostly Cloudy
-2012-01-10 11:00:00,2.6,-1.1,77,22,24.1,100.29,Mainly Clear
-2012-01-10 12:00:00,1.4,-3.1,72,30,24.1,100.32,Mostly Cloudy
-2012-01-10 13:00:00,0.7,-5.4,64,26,24.1,100.36,Mostly Cloudy
-2012-01-10 14:00:00,-0.2,-6.2,64,26,24.1,100.45,Mainly Clear
-2012-01-10 15:00:00,-1.4,-7.9,61,30,24.1,100.65,Mainly Clear
-2012-01-10 16:00:00,-3.1,-10.9,55,30,24.1,100.81,Mostly Cloudy
-2012-01-10 17:00:00,-4.0,-12.0,54,17,24.1,100.91,Mostly Cloudy
-2012-01-10 18:00:00,-4.9,-12.7,54,15,25.0,101.04,Mostly Cloudy
-2012-01-10 19:00:00,-5.7,-13.8,53,15,25.0,101.15,Mostly Cloudy
-2012-01-10 20:00:00,-6.4,-14.3,53,13,25.0,101.24,Mostly Cloudy
-2012-01-10 21:00:00,-6.6,-13.6,57,9,25.0,101.32,Mostly Cloudy
-2012-01-10 22:00:00,-7.3,-14.7,55,13,25.0,101.34,Mostly Cloudy
-2012-01-10 23:00:00,-8.6,-15.6,57,19,25.0,101.44,Mostly Cloudy
-2012-01-11 00:00:00,-9.5,-16.8,55,17,25.0,101.43,Mostly Cloudy
-2012-01-11 01:00:00,-10.7,-17.8,56,17,25.0,101.49,Clear
-2012-01-11 02:00:00,-12.0,-18.9,56,19,25.0,101.57,Clear
-2012-01-11 03:00:00,-12.7,-19.4,57,19,25.0,101.64,Clear
-2012-01-11 04:00:00,-13.4,-20.1,57,17,25.0,101.66,Clear
-2012-01-11 05:00:00,-13.9,-21.0,55,19,25.0,101.66,Mainly Clear
-2012-01-11 06:00:00,-14.4,-21.1,57,20,25.0,101.72,Mainly Clear
-2012-01-11 07:00:00,-14.4,-21.0,57,13,25.0,101.77,Mostly Cloudy
-2012-01-11 08:00:00,-14.7,-21.4,57,15,24.1,101.8,Mostly Cloudy
-2012-01-11 09:00:00,-14.3,-20.8,58,15,24.1,101.81,Mostly Cloudy
-2012-01-11 10:00:00,-13.9,-20.9,55,11,19.3,101.89,Cloudy
-2012-01-11 11:00:00,-13.4,-20.8,54,15,24.1,101.78,Mostly Cloudy
-2012-01-11 12:00:00,-12.7,-20.4,53,17,24.1,101.68,Cloudy
-2012-01-11 13:00:00,-12.2,-20.0,52,19,24.1,101.63,Mostly Cloudy
-2012-01-11 14:00:00,-11.4,-19.4,52,20,24.1,101.56,Mostly Cloudy
-2012-01-11 15:00:00,-11.6,-19.9,50,20,24.1,101.61,Mostly Cloudy
-2012-01-11 16:00:00,-11.8,-20.9,47,20,24.1,101.6,Mostly Cloudy
-2012-01-11 17:00:00,-11.9,-20.1,51,26,24.1,101.56,Mostly Cloudy
-2012-01-11 18:00:00,-12.0,-19.9,52,24,25.0,101.51,Mostly Cloudy
-2012-01-11 19:00:00,-11.8,-19.2,54,30,25.0,101.43,Mostly Cloudy
-2012-01-11 20:00:00,-11.2,-18.1,57,24,25.0,101.4,Cloudy
-2012-01-11 21:00:00,-11.2,-16.5,65,19,25.0,101.32,Cloudy
-2012-01-11 22:00:00,-10.8,-16.0,65,22,25.0,101.29,Cloudy
-2012-01-11 23:00:00,-10.7,-15.7,67,20,25.0,101.19,Mostly Cloudy
-2012-01-12 00:00:00,-10.0,-15.2,66,19,25.0,101.17,Mostly Cloudy
-2012-01-12 01:00:00,-9.8,-15.2,65,24,25.0,101.13,Mostly Cloudy
-2012-01-12 02:00:00,-9.4,-15.0,64,26,25.0,101.08,Cloudy
-2012-01-12 03:00:00,-9.0,-14.7,63,33,25.0,101.02,Cloudy
-2012-01-12 04:00:00,-8.5,-14.1,64,22,25.0,100.93,Cloudy
-2012-01-12 05:00:00,-8.0,-13.7,64,30,25.0,100.81,Cloudy
-2012-01-12 06:00:00,-7.6,-13.1,65,28,25.0,100.76,Cloudy
-2012-01-12 07:00:00,-7.3,-12.7,65,28,16.1,100.69,Snow Showers
-2012-01-12 08:00:00,-7.1,-11.3,72,33,6.4,100.61,Snow
-2012-01-12 09:00:00,-6.8,-10.5,75,33,3.2,100.54,Snow
-2012-01-12 10:00:00,-6.2,-9.6,77,35,4.8,100.46,Snow
-2012-01-12 11:00:00,-6.0,-9.5,76,32,2.0,100.35,Snow
-2012-01-12 12:00:00,-5.8,-8.9,79,32,4.8,100.22,Snow
-2012-01-12 13:00:00,-5.8,-8.6,81,33,1.2,100.09,Snow
-2012-01-12 14:00:00,-5.7,-8.5,81,28,1.2,99.97,Snow
-2012-01-12 15:00:00,-5.2,-7.6,83,26,0.8,99.9,Moderate Snow
-2012-01-12 16:00:00,-4.9,-7.3,83,33,0.6,99.88,Moderate Snow
-2012-01-12 17:00:00,-5.1,-7.6,83,33,1.0,99.83,Snow
-2012-01-12 18:00:00,-5.4,-8.1,81,35,1.2,99.76,Snow
-2012-01-12 19:00:00,-5.0,-7.6,82,30,4.0,99.72,Snow
-2012-01-12 20:00:00,-5.0,-7.8,81,28,6.4,99.64,Snow
-2012-01-12 21:00:00,-4.7,-7.6,80,24,6.4,99.56,Snow
-2012-01-12 22:00:00,-4.1,-6.8,81,26,25.0,99.47,Snow
-2012-01-12 23:00:00,-4.6,-7.0,83,28,3.2,99.4,Snow
-2012-01-13 00:00:00,-5.1,-7.5,83,28,2.4,99.3,Snow
-2012-01-13 01:00:00,-5.0,-7.7,81,24,4.8,99.24,Snow
-2012-01-13 02:00:00,-4.8,-7.5,81,22,25.0,99.22,Snow
-2012-01-13 03:00:00,-4.5,-6.9,83,19,4.8,99.19,"Freezing Drizzle,Snow"
-2012-01-13 04:00:00,-5.0,-7.4,83,24,11.3,99.13,Cloudy
-2012-01-13 05:00:00,-5.1,-7.7,82,20,12.9,99.06,Cloudy
-2012-01-13 06:00:00,-5.4,-7.8,83,22,16.1,98.94,Cloudy
-2012-01-13 07:00:00,-5.1,-7.7,82,22,16.1,98.84,Cloudy
-2012-01-13 08:00:00,-5.1,-7.5,83,26,8.0,98.69,Freezing Rain
-2012-01-13 09:00:00,-5.0,-7.3,84,32,4.8,98.56,"Freezing Rain,Snow Grains"
-2012-01-13 10:00:00,-4.8,-7.2,83,26,12.9,98.44,Freezing Drizzle
-2012-01-13 11:00:00,-4.8,-7.3,83,28,9.7,98.22,Freezing Rain
-2012-01-13 12:00:00,-4.8,-7.5,81,24,2.0,98.07,Snow
-2012-01-13 13:00:00,-4.9,-7.3,83,20,1.2,97.99,Snow
-2012-01-13 14:00:00,-4.8,-7.0,85,6,2.0,98.07,Snow
-2012-01-13 15:00:00,-4.3,-6.5,85,13,8.0,98.1,Snow
-2012-01-13 16:00:00,-3.7,-6.0,84,11,6.4,98.16,Snow
-2012-01-13 17:00:00,-2.9,-4.8,87,15,1.6,98.23,Snow
-2012-01-13 18:00:00,-1.7,-3.3,89,26,16.1,98.32,Snow
-2012-01-13 19:00:00,-2.5,-4.5,86,33,2.0,98.6,Snow
-2012-01-13 20:00:00,-3.2,-5.1,87,32,2.0,98.89,Snow
-2012-01-13 21:00:00,-4.8,-7.9,79,37,4.8,99.09,"Snow,Blowing Snow"
-2012-01-13 22:00:00,-5.5,-10.1,70,32,12.9,99.28,Snow
-2012-01-13 23:00:00,-7.6,-11.2,75,35,9.7,99.51,"Snow,Blowing Snow"
-2012-01-14 00:00:00,-8.9,-13.1,72,39,9.7,99.67,"Snow,Blowing Snow"
-2012-01-14 01:00:00,-9.7,-14.3,69,24,12.9,99.85,Snow
-2012-01-14 02:00:00,-11.2,-15.5,70,28,9.7,100.01,"Snow,Blowing Snow"
-2012-01-14 03:00:00,-12.0,-16.2,71,24,8.0,100.16,"Snow,Blowing Snow"
-2012-01-14 04:00:00,-13.4,-18.9,63,20,16.1,100.26,Snow
-2012-01-14 05:00:00,-14.3,-19.8,63,24,25.0,100.39,Cloudy
-2012-01-14 06:00:00,-15.2,-20.6,63,24,25.0,100.6,Cloudy
-2012-01-14 07:00:00,-16.8,-22.2,63,26,25.0,100.73,Mostly Cloudy
-2012-01-14 08:00:00,-17.9,-23.5,62,20,24.1,100.84,Mostly Cloudy
-2012-01-14 09:00:00,-18.0,-23.6,61,19,24.1,100.97,Cloudy
-2012-01-14 10:00:00,-18.0,-23.9,60,22,24.1,101.08,Mostly Cloudy
-2012-01-14 11:00:00,-17.8,-23.9,59,20,24.1,101.14,Mostly Cloudy
-2012-01-14 12:00:00,-17.5,-23.8,58,20,48.3,101.16,Mostly Cloudy
-2012-01-14 13:00:00,-17.1,-24.1,55,17,48.3,101.18,Mainly Clear
-2012-01-14 14:00:00,-16.7,-23.4,56,17,48.3,101.2,Mostly Cloudy
-2012-01-14 15:00:00,-16.7,-23.4,56,22,48.3,101.24,Mostly Cloudy
-2012-01-14 16:00:00,-16.7,-24.3,52,19,24.1,101.3,Mostly Cloudy
-2012-01-14 17:00:00,-17.4,-24.4,54,13,25.0,101.36,Mostly Cloudy
-2012-01-14 18:00:00,-17.7,-24.3,56,20,25.0,101.46,Mainly Clear
-2012-01-14 19:00:00,-18.3,-24.4,59,17,25.0,101.56,Mainly Clear
-2012-01-14 20:00:00,-19.6,-25.8,58,13,25.0,101.62,Mainly Clear
-2012-01-14 21:00:00,-20.0,-25.9,59,11,25.0,101.65,Mostly Cloudy
-2012-01-14 22:00:00,-19.9,-26.0,58,13,25.0,101.74,Mostly Cloudy
-2012-01-14 23:00:00,-20.3,-26.2,59,9,25.0,101.79,Mostly Cloudy
-2012-01-15 00:00:00,-21.2,-26.8,61,11,25.0,101.81,Cloudy
-2012-01-15 01:00:00,-21.1,-26.6,61,9,25.0,101.86,Cloudy
-2012-01-15 02:00:00,-21.4,-26.6,63,9,25.0,101.99,Cloudy
-2012-01-15 03:00:00,-20.7,-26.1,62,4,25.0,102.04,Cloudy
-2012-01-15 04:00:00,-21.0,-26.6,61,0,25.0,102.12,Cloudy
-2012-01-15 05:00:00,-21.3,-26.5,63,6,25.0,102.19,Mostly Cloudy
-2012-01-15 06:00:00,-23.2,-28.5,62,7,25.0,102.28,Mostly Cloudy
-2012-01-15 07:00:00,-22.8,-28.0,62,9,25.0,102.37,Mainly Clear
-2012-01-15 08:00:00,-23.3,-28.5,62,7,24.1,102.45,Clear
-2012-01-15 09:00:00,-22.2,-27.8,60,9,48.3,102.57,Mainly Clear
-2012-01-15 10:00:00,-20.6,-26.8,58,9,48.3,102.66,Mainly Clear
-2012-01-15 11:00:00,-19.3,-26.1,55,9,48.3,102.68,Mainly Clear
-2012-01-15 12:00:00,-18.0,-25.5,52,13,48.3,102.67,Mainly Clear
-2012-01-15 13:00:00,-16.8,-24.2,53,20,48.3,102.65,Mainly Clear
-2012-01-15 14:00:00,-16.0,-23.4,53,26,48.3,102.66,Mainly Clear
-2012-01-15 15:00:00,-15.4,-22.8,53,24,48.3,102.71,Clear
-2012-01-15 16:00:00,-15.1,-22.8,52,24,48.3,102.79,Clear
-2012-01-15 17:00:00,-16.2,-23.2,55,15,25.0,102.85,Clear
-2012-01-15 18:00:00,-16.3,-22.9,57,17,25.0,102.89,Clear
-2012-01-15 19:00:00,-16.3,-22.7,58,20,25.0,102.94,Clear
-2012-01-15 20:00:00,-16.7,-22.4,61,17,25.0,102.98,Clear
-2012-01-15 21:00:00,-16.9,-22.2,63,15,25.0,103.02,Clear
-2012-01-15 22:00:00,-16.9,-21.7,66,17,25.0,103.07,Clear
-2012-01-15 23:00:00,-16.9,-21.4,68,15,25.0,103.09,Clear
-2012-01-16 00:00:00,-17.1,-21.9,66,15,25.0,103.09,Clear
-2012-01-16 01:00:00,-17.8,-22.7,65,6,25.0,103.05,Clear
-2012-01-16 02:00:00,-18.5,-23.0,68,6,25.0,103.08,Clear
-2012-01-16 03:00:00,-19.2,-23.8,67,6,25.0,103.07,Clear
-2012-01-16 04:00:00,-18.7,-23.5,66,0,25.0,103.05,Clear
-2012-01-16 05:00:00,-19.1,-23.3,69,0,25.0,103.02,Clear
-2012-01-16 06:00:00,-18.7,-23.2,68,0,25.0,103.01,Clear
-2012-01-16 07:00:00,-17.9,-21.5,73,4,48.3,102.96,Mainly Clear
-2012-01-16 08:00:00,-17.9,-22.6,67,9,48.3,102.9,Mostly Cloudy
-2012-01-16 09:00:00,-14.4,-20.7,59,22,48.3,102.75,Cloudy
-2012-01-16 10:00:00,-13.6,-18.7,65,19,48.3,102.62,Mostly Cloudy
-2012-01-16 11:00:00,-12.7,-17.7,66,20,48.3,102.44,Mostly Cloudy
-2012-01-16 12:00:00,-10.7,-16.9,60,19,48.3,102.17,Mostly Cloudy
-2012-01-16 13:00:00,-10.1,-16.1,61,13,48.3,101.92,Cloudy
-2012-01-16 14:00:00,-9.0,-13.8,68,13,48.3,101.71,Mostly Cloudy
-2012-01-16 15:00:00,-8.0,-13.8,63,17,48.3,101.49,Cloudy
-2012-01-16 16:00:00,-7.1,-14.1,57,9,48.3,101.41,Cloudy
-2012-01-16 17:00:00,-7.6,-14.8,56,4,25.0,101.34,Mostly Cloudy
-2012-01-16 18:00:00,-12.5,-17.5,66,15,25.0,101.31,Mainly Clear
-2012-01-16 19:00:00,-14.8,-19.1,70,15,25.0,101.23,Mainly Clear
-2012-01-16 20:00:00,-14.0,-18.3,70,13,25.0,101.19,Cloudy
-2012-01-16 21:00:00,-12.9,-17.1,71,11,25.0,101.12,Cloudy
-2012-01-16 22:00:00,-12.2,-16.5,70,9,25.0,101.05,Cloudy
-2012-01-16 23:00:00,-11.5,-15.7,71,7,25.0,100.98,Cloudy
-2012-01-17 00:00:00,-10.8,-15.0,71,9,25.0,100.94,Cloudy
-2012-01-17 01:00:00,-10.4,-14.6,71,9,25.0,100.88,Cloudy
-2012-01-17 02:00:00,-9.7,-13.7,73,9,25.0,100.84,Cloudy
-2012-01-17 03:00:00,-9.2,-13.2,73,6,25.0,100.84,Cloudy
-2012-01-17 04:00:00,-9.0,-12.2,78,6,6.4,100.8,Freezing Drizzle
-2012-01-17 05:00:00,-8.3,-10.4,85,6,3.6,100.75,"Freezing Drizzle,Snow"
-2012-01-17 06:00:00,-7.7,-9.9,84,6,2.4,100.72,"Freezing Drizzle,Snow"
-2012-01-17 07:00:00,-7.5,-9.6,85,9,2.0,100.69,Snow
-2012-01-17 08:00:00,-7.4,-9.6,84,9,2.4,100.65,Snow
-2012-01-17 09:00:00,-7.0,-9.5,82,15,4.0,100.59,Snow
-2012-01-17 10:00:00,-6.5,-9.0,82,15,1.2,100.6,Snow
-2012-01-17 11:00:00,-6.1,-8.5,83,15,2.4,100.53,Snow
-2012-01-17 12:00:00,-5.3,-7.9,82,19,2.8,100.38,Snow
-2012-01-17 13:00:00,-5.1,-7.7,82,22,2.4,100.23,Snow
-2012-01-17 14:00:00,-4.3,-6.5,85,22,1.6,100.05,Snow
-2012-01-17 15:00:00,-3.7,-6.0,84,24,1.2,99.9,Snow
-2012-01-17 16:00:00,-3.5,-6.0,83,28,1.2,99.69,Snow
-2012-01-17 17:00:00,-3.6,-5.9,84,22,1.6,99.57,Snow
-2012-01-17 18:00:00,-3.5,-5.8,84,22,2.4,99.38,Snow
-2012-01-17 19:00:00,-3.3,-5.6,84,24,4.8,99.22,"Freezing Drizzle,Snow"
-2012-01-17 20:00:00,-3.6,-5.7,85,24,3.2,98.98,Freezing Rain
-2012-01-17 21:00:00,-2.9,-4.9,86,26,2.8,98.71,Freezing Rain
-2012-01-17 22:00:00,-1.6,-3.2,89,17,3.2,98.47,Freezing Rain
-2012-01-17 23:00:00,-0.6,-2.1,90,7,2.8,98.32,"Freezing Rain,Fog"
-2012-01-18 00:00:00,2.1,0.7,90,11,8.0,98.31,Fog
-2012-01-18 01:00:00,3.7,-2.1,66,83,25.0,98.36,Mostly Cloudy
-2012-01-18 02:00:00,0.5,-4.0,72,70,25.0,98.62,Mostly Cloudy
-2012-01-18 03:00:00,-3.5,-8.2,70,57,25.0,99.0,Mostly Cloudy
-2012-01-18 04:00:00,-6.1,-10.9,69,48,25.0,99.36,Snow
-2012-01-18 05:00:00,-7.7,-12.4,69,46,19.3,99.7,Snow
-2012-01-18 06:00:00,-8.5,-13.9,65,39,19.3,100.0,Mostly Cloudy
-2012-01-18 07:00:00,-9.8,-15.4,64,39,19.3,100.22,Mainly Clear
-2012-01-18 08:00:00,-10.9,-16.6,63,35,24.1,100.43,Mainly Clear
-2012-01-18 09:00:00,-11.2,-17.2,61,43,24.1,100.65,Mainly Clear
-2012-01-18 10:00:00,-11.2,-17.2,61,35,24.1,100.78,Mainly Clear
-2012-01-18 11:00:00,-11.1,-17.7,58,39,24.1,100.92,Mainly Clear
-2012-01-18 12:00:00,-11.0,-17.8,57,37,24.1,101.0,Mainly Clear
-2012-01-18 13:00:00,-10.6,-17.8,55,32,24.1,101.09,Mainly Clear
-2012-01-18 14:00:00,-10.3,-17.6,55,28,48.3,101.19,Mainly Clear
-2012-01-18 15:00:00,-10.4,-18.0,54,30,48.3,101.32,Mainly Clear
-2012-01-18 16:00:00,-10.6,-18.4,53,26,48.3,101.45,Mainly Clear
-2012-01-18 17:00:00,-11.3,-18.8,54,26,48.3,101.54,Clear
-2012-01-18 18:00:00,-12.0,-18.2,60,22,25.0,101.67,Clear
-2012-01-18 19:00:00,-12.7,-18.7,61,22,25.0,101.78,Clear
-2012-01-18 20:00:00,-13.4,-19.2,62,17,25.0,101.83,Clear
-2012-01-18 21:00:00,-13.7,-19.3,63,17,25.0,101.89,Clear
-2012-01-18 22:00:00,-14.2,-19.8,62,13,25.0,101.92,Clear
-2012-01-18 23:00:00,-14.9,-19.9,66,6,25.0,101.93,Clear
-2012-01-19 00:00:00,-16.6,-20.9,69,7,25.0,101.94,Clear
-2012-01-19 01:00:00,-15.2,-18.4,76,4,25.0,101.89,Clear
-2012-01-19 02:00:00,-14.3,-17.4,77,6,25.0,101.86,Clear
-2012-01-19 03:00:00,-18.0,-21.6,73,6,25.0,101.83,Clear
-2012-01-19 04:00:00,-15.4,-18.3,78,7,25.0,101.81,Clear
-2012-01-19 05:00:00,-16.6,-19.9,76,6,25.0,101.85,Clear
-2012-01-19 06:00:00,-15.3,-19.7,69,6,25.0,101.83,Clear
-2012-01-19 07:00:00,-14.6,-19.2,68,6,24.1,101.84,Clear
-2012-01-19 08:00:00,-13.7,-18.4,68,19,48.3,101.84,Clear
-2012-01-19 09:00:00,-12.7,-17.2,69,17,48.3,101.73,Clear
-2012-01-19 10:00:00,-11.7,-17.2,64,20,48.3,101.68,Mainly Clear
-2012-01-19 11:00:00,-11.0,-16.9,62,26,48.3,101.56,Mostly Cloudy
-2012-01-19 12:00:00,-8.8,-15.4,59,15,48.3,101.42,Mostly Cloudy
-2012-01-19 13:00:00,-7.3,-14.7,55,20,48.3,101.22,Mostly Cloudy
-2012-01-19 14:00:00,-7.0,-14.9,53,20,48.3,101.03,Mostly Cloudy
-2012-01-19 15:00:00,-6.7,-15.0,52,26,48.3,100.88,Cloudy
-2012-01-19 16:00:00,-6.7,-14.9,52,24,24.1,100.76,Cloudy
-2012-01-19 17:00:00,-6.9,-14.7,54,17,24.1,100.7,Cloudy
-2012-01-19 18:00:00,-5.0,-12.9,54,19,25.0,100.66,Cloudy
-2012-01-19 19:00:00,-3.6,-12.7,49,30,25.0,100.61,Snow
-2012-01-19 20:00:00,-3.7,-11.9,53,30,16.1,100.63,Snow
-2012-01-19 21:00:00,-5.0,-8.4,77,24,2.0,100.6,Snow
-2012-01-19 22:00:00,-4.2,-9.3,68,32,25.0,100.51,Snow
-2012-01-19 23:00:00,-4.1,-8.9,69,26,25.0,100.47,Snow
-2012-01-20 00:00:00,-4.1,-8.6,71,26,25.0,100.5,Mostly Cloudy
-2012-01-20 01:00:00,-4.1,-8.3,73,20,25.0,100.54,Snow
-2012-01-20 02:00:00,-3.9,-8.1,73,22,9.7,100.64,Snow
-2012-01-20 03:00:00,-4.8,-9.9,67,19,25.0,100.75,Mostly Cloudy
-2012-01-20 04:00:00,-6.0,-10.2,72,19,16.1,100.87,Snow
-2012-01-20 05:00:00,-6.3,-12.2,63,33,25.0,100.98,Snow
-2012-01-20 06:00:00,-7.6,-14.3,59,28,25.0,101.13,Cloudy
-2012-01-20 07:00:00,-8.6,-15.6,57,28,25.0,101.27,Mostly Cloudy
-2012-01-20 08:00:00,-10.4,-16.2,62,33,24.1,101.47,Mainly Clear
-2012-01-20 09:00:00,-12.2,-18.1,61,32,24.1,101.59,Clear
-2012-01-20 10:00:00,-13.7,-20.3,57,33,24.1,101.72,Mainly Clear
-2012-01-20 11:00:00,-14.2,-21.2,55,32,24.1,101.84,Clear
-2012-01-20 12:00:00,-15.2,-22.1,56,30,24.1,101.88,Clear
-2012-01-20 13:00:00,-15.8,-23.7,51,30,24.1,101.96,Clear
-2012-01-20 14:00:00,-15.5,-24.1,48,30,48.3,101.98,Mainly Clear
-2012-01-20 15:00:00,-15.0,-23.9,47,30,48.3,102.09,Mainly Clear
-2012-01-20 16:00:00,-14.8,-24.1,45,24,48.3,102.15,Mainly Clear
-2012-01-20 17:00:00,-15.4,-24.3,46,17,48.3,102.21,Mainly Clear
-2012-01-20 18:00:00,-15.9,-24.3,48,13,25.0,102.27,Mainly Clear
-2012-01-20 19:00:00,-16.3,-24.2,51,13,25.0,102.33,Mainly Clear
-2012-01-20 20:00:00,-16.9,-24.8,50,9,25.0,102.34,Mainly Clear
-2012-01-20 21:00:00,-18.5,-25.6,54,9,25.0,102.37,Mainly Clear
-2012-01-20 22:00:00,-18.1,-25.1,54,9,25.0,102.36,Mainly Clear
-2012-01-20 23:00:00,-17.4,-24.5,54,6,25.0,102.37,Mostly Cloudy
-2012-01-21 00:00:00,-16.4,-23.7,53,6,25.0,102.29,Cloudy
-2012-01-21 01:00:00,-16.1,-23.6,52,0,25.0,102.26,Cloudy
-2012-01-21 02:00:00,-15.3,-22.8,53,0,25.0,102.27,Cloudy
-2012-01-21 03:00:00,-15.9,-21.9,60,7,25.0,102.23,Cloudy
-2012-01-21 04:00:00,-15.3,-21.8,58,7,25.0,102.18,Cloudy
-2012-01-21 05:00:00,-14.8,-22.9,50,11,25.0,102.08,Cloudy
-2012-01-21 06:00:00,-14.3,-22.0,52,9,25.0,101.98,Cloudy
-2012-01-21 07:00:00,-13.9,-22.1,50,9,25.0,102.04,Cloudy
-2012-01-21 08:00:00,-14.0,-21.8,52,9,25.0,102.06,Cloudy
-2012-01-21 09:00:00,-15.9,-21.0,65,13,24.1,102.11,Snow
-2012-01-21 10:00:00,-16.3,-21.4,65,17,24.1,102.12,Snow
-2012-01-21 11:00:00,-15.9,-21.2,64,19,24.1,102.09,Snow
-2012-01-21 12:00:00,-14.6,-20.3,62,15,24.1,102.03,Mostly Cloudy
-2012-01-21 13:00:00,-13.4,-19.8,59,15,24.1,102.01,Mainly Clear
-2012-01-21 14:00:00,-12.5,-19.7,55,13,24.1,102.01,Clear
-2012-01-21 15:00:00,-11.8,-18.9,56,11,24.1,102.06,Clear
-2012-01-21 16:00:00,-11.6,-18.8,55,7,48.3,102.11,Clear
-2012-01-21 17:00:00,-12.1,-19.8,53,11,48.3,102.16,Clear
-2012-01-21 18:00:00,-13.0,-20.2,55,6,25.0,102.24,Clear
-2012-01-21 19:00:00,-13.4,-19.9,58,4,25.0,102.27,Clear
-2012-01-21 20:00:00,-18.5,-24.4,60,4,25.0,102.36,Clear
-2012-01-21 21:00:00,-16.0,-20.8,66,9,25.0,102.47,Clear
-2012-01-21 22:00:00,-17.6,-23.3,61,0,25.0,102.52,Clear
-2012-01-21 23:00:00,-17.4,-21.7,69,0,25.0,102.54,Mainly Clear
-2012-01-22 00:00:00,-18.3,-22.5,70,0,25.0,102.57,Clear
-2012-01-22 01:00:00,-17.5,-21.3,72,4,25.0,102.64,Clear
-2012-01-22 02:00:00,-18.5,-22.6,70,0,25.0,102.71,Clear
-2012-01-22 03:00:00,-18.4,-23.0,67,0,16.1,102.75,Cloudy
-2012-01-22 04:00:00,-17.2,-21.5,69,0,25.0,102.79,Mainly Clear
-2012-01-22 05:00:00,-19.5,-23.4,71,6,16.1,102.84,Mainly Clear
-2012-01-22 06:00:00,-19.0,-22.9,71,6,0.8,102.85,Freezing Fog
-2012-01-22 07:00:00,-18.6,-22.8,69,6,12.9,102.91,Mainly Clear
-2012-01-22 08:00:00,-18.5,-22.0,74,4,24.1,102.98,Mainly Clear
-2012-01-22 09:00:00,-16.2,-19.2,78,7,48.3,103.01,Mostly Cloudy
-2012-01-22 10:00:00,-14.5,-17.2,80,9,8.0,103.02,Fog
-2012-01-22 11:00:00,-13.0,-15.5,81,6,8.0,103.04,Fog
-2012-01-22 12:00:00,-11.5,-15.4,73,9,8.0,102.97,Haze
-2012-01-22 13:00:00,-11.2,-16.0,68,11,8.0,102.86,Haze
-2012-01-22 14:00:00,-9.4,-14.8,65,9,16.1,102.74,Cloudy
-2012-01-22 15:00:00,-8.7,-14.5,63,9,16.1,102.65,Cloudy
-2012-01-22 16:00:00,-8.0,-14.7,59,6,19.3,102.6,Cloudy
-2012-01-22 17:00:00,-9.5,-15.8,60,19,19.3,102.57,Cloudy
-2012-01-22 18:00:00,-10.4,-16.1,63,19,19.3,102.52,Mostly Cloudy
-2012-01-22 19:00:00,-10.4,-16.2,62,19,19.3,102.47,Mostly Cloudy
-2012-01-22 20:00:00,-12.3,-16.8,69,15,19.3,102.44,Mainly Clear
-2012-01-22 21:00:00,-12.9,-17.2,70,15,16.1,102.38,Clear
-2012-01-22 22:00:00,-13.2,-17.0,73,13,16.1,102.33,Mostly Cloudy
-2012-01-22 23:00:00,-13.3,-17.1,73,9,16.1,102.28,Mainly Clear
-2012-01-23 00:00:00,-12.9,-17.0,71,11,25.0,102.22,Mostly Cloudy
-2012-01-23 01:00:00,-12.9,-17.2,70,11,25.0,102.14,Mainly Clear
-2012-01-23 02:00:00,-13.2,-17.1,72,13,25.0,102.1,Mostly Cloudy
-2012-01-23 03:00:00,-12.1,-16.0,73,13,25.0,101.99,Cloudy
-2012-01-23 04:00:00,-11.2,-15.2,72,11,25.0,101.88,Cloudy
-2012-01-23 05:00:00,-9.9,-13.9,73,11,25.0,101.79,Cloudy
-2012-01-23 06:00:00,-8.8,-12.8,73,7,25.0,101.76,Cloudy
-2012-01-23 07:00:00,-8.1,-12.1,73,13,25.0,101.67,Mostly Cloudy
-2012-01-23 08:00:00,-7.2,-11.1,74,11,24.1,101.69,Mostly Cloudy
-2012-01-23 09:00:00,-4.9,-9.2,72,11,48.3,101.59,Mostly Cloudy
-2012-01-23 10:00:00,-3.6,-7.9,72,9,48.3,101.58,Mostly Cloudy
-2012-01-23 11:00:00,1.2,-3.2,72,11,48.3,101.49,Cloudy
-2012-01-23 12:00:00,2.3,-2.4,71,6,48.3,101.33,Cloudy
-2012-01-23 13:00:00,2.5,-1.5,75,22,48.3,101.14,Cloudy
-2012-01-23 14:00:00,2.7,-1.1,76,26,48.3,101.01,Rain
-2012-01-23 15:00:00,2.7,-0.9,77,30,24.1,100.86,Rain
-2012-01-23 16:00:00,3.1,-0.3,78,28,24.1,100.71,Cloudy
-2012-01-23 17:00:00,3.1,-0.4,78,28,16.1,100.61,Rain
-2012-01-23 18:00:00,3.0,1.2,88,19,4.0,100.54,"Rain,Fog"
-2012-01-23 19:00:00,3.2,1.4,88,22,8.0,100.43,"Rain,Fog"
-2012-01-23 20:00:00,2.9,1.2,89,26,9.7,100.32,"Drizzle,Fog"
-2012-01-23 21:00:00,3.3,1.7,89,24,11.3,100.22,Drizzle
-2012-01-23 22:00:00,3.6,2.2,91,28,25.0,100.1,Cloudy
-2012-01-23 23:00:00,4.0,2.5,90,22,25.0,100.08,Cloudy
-2012-01-24 00:00:00,3.5,2.3,92,17,12.9,100.04,Rain
-2012-01-24 01:00:00,3.1,1.9,92,19,16.1,100.04,Cloudy
-2012-01-24 02:00:00,3.1,2.1,93,9,9.7,100.09,Rain
-2012-01-24 03:00:00,5.0,3.6,91,19,9.7,100.19,Rain
-2012-01-24 04:00:00,4.2,1.2,81,30,25.0,100.25,Cloudy
-2012-01-24 05:00:00,3.7,-0.2,76,41,25.0,100.37,Cloudy
-2012-01-24 06:00:00,3.4,-0.6,75,28,25.0,100.45,Cloudy
-2012-01-24 07:00:00,2.9,-1.1,75,26,16.1,100.49,Cloudy
-2012-01-24 08:00:00,3.0,-1.7,71,28,19.3,100.52,Mostly Cloudy
-2012-01-24 09:00:00,2.9,-1.8,71,30,24.1,100.6,Cloudy
-2012-01-24 10:00:00,3.0,-2.0,70,35,24.1,100.65,Cloudy
-2012-01-24 11:00:00,3.1,-1.9,70,33,24.1,100.7,Cloudy
-2012-01-24 12:00:00,3.2,-2.3,67,30,24.1,100.72,Cloudy
-2012-01-24 13:00:00,2.8,-2.4,69,39,24.1,100.73,Cloudy
-2012-01-24 14:00:00,2.4,-2.4,71,35,24.1,100.75,Rain
-2012-01-24 15:00:00,1.9,-2.2,74,26,19.3,100.8,Snow
-2012-01-24 16:00:00,1.7,-2.4,74,30,24.1,100.82,Cloudy
-2012-01-24 17:00:00,1.6,-2.8,73,26,24.1,100.88,Snow Showers
-2012-01-24 18:00:00,1.5,-2.9,72,22,25.0,100.95,Snow Showers
-2012-01-24 19:00:00,1.5,-3.2,71,32,25.0,101.01,Snow Showers
-2012-01-24 20:00:00,1.3,-3.2,72,19,25.0,101.06,Cloudy
-2012-01-24 21:00:00,1.1,-3.0,74,20,25.0,101.11,Mostly Cloudy
-2012-01-24 22:00:00,1.1,-3.4,72,22,25.0,101.13,Mostly Cloudy
-2012-01-24 23:00:00,1.0,-3.4,72,28,25.0,101.16,Snow Showers
-2012-01-25 00:00:00,0.5,-4.6,69,28,25.0,101.2,Cloudy
-2012-01-25 01:00:00,-0.1,-5.2,68,22,25.0,101.26,Mostly Cloudy
-2012-01-25 02:00:00,-0.4,-5.9,66,20,25.0,101.37,Mostly Cloudy
-2012-01-25 03:00:00,-0.5,-6.2,65,24,25.0,101.45,Cloudy
-2012-01-25 04:00:00,-0.7,-6.0,67,24,25.0,101.52,Cloudy
-2012-01-25 05:00:00,-1.7,-7.7,64,33,25.0,101.58,Mostly Cloudy
-2012-01-25 06:00:00,-2.8,-9.0,62,35,25.0,101.66,Mostly Cloudy
-2012-01-25 07:00:00,-3.9,-10.0,63,37,25.0,101.79,Mostly Cloudy
-2012-01-25 08:00:00,-4.7,-10.9,62,26,24.1,101.94,Mostly Cloudy
-2012-01-25 09:00:00,-5.2,-11.3,62,28,24.1,102.05,Cloudy
-2012-01-25 10:00:00,-5.3,-11.4,62,22,24.1,102.09,Mostly Cloudy
-2012-01-25 11:00:00,-5.3,-11.9,60,19,24.1,102.14,Mostly Cloudy
-2012-01-25 12:00:00,-5.0,-11.8,59,20,24.1,102.06,Mostly Cloudy
-2012-01-25 13:00:00,-4.7,-11.7,58,20,24.1,102.01,Mainly Clear
-2012-01-25 14:00:00,-4.5,-11.0,60,22,24.1,101.98,Mainly Clear
-2012-01-25 15:00:00,-4.4,-11.2,59,22,24.1,101.94,Mainly Clear
-2012-01-25 16:00:00,-4.4,-11.3,59,19,24.1,101.96,Mostly Cloudy
-2012-01-25 17:00:00,-4.8,-11.4,60,20,24.1,102.01,Mainly Clear
-2012-01-25 18:00:00,-5.1,-11.4,61,11,25.0,102.07,Mainly Clear
-2012-01-25 19:00:00,-5.4,-11.5,62,13,25.0,102.14,Mostly Cloudy
-2012-01-25 20:00:00,-4.9,-11.6,59,7,25.0,102.07,Mostly Cloudy
-2012-01-25 21:00:00,-5.4,-11.1,64,7,25.0,102.01,Mostly Cloudy
-2012-01-25 22:00:00,-5.5,-11.3,64,0,25.0,101.99,Mostly Cloudy
-2012-01-25 23:00:00,-5.4,-11.4,63,6,25.0,102.01,Mostly Cloudy
-2012-01-26 00:00:00,-5.9,-11.7,64,6,25.0,101.99,Mostly Cloudy
-2012-01-26 01:00:00,-7.0,-12.1,67,4,25.0,101.95,Clear
-2012-01-26 02:00:00,-8.2,-12.6,71,6,25.0,101.99,Clear
-2012-01-26 03:00:00,-8.1,-12.5,71,0,25.0,101.97,Clear
-2012-01-26 04:00:00,-8.5,-13.5,67,0,25.0,101.95,Clear
-2012-01-26 05:00:00,-9.0,-13.9,68,6,25.0,102.02,Clear
-2012-01-26 06:00:00,-11.2,-15.0,73,6,25.0,102.06,Clear
-2012-01-26 07:00:00,-10.6,-14.4,74,6,24.1,102.01,Mainly Clear
-2012-01-26 08:00:00,-9.2,-13.3,72,6,24.1,102.08,Clear
-2012-01-26 09:00:00,-7.9,-12.4,70,11,24.1,102.01,Mainly Clear
-2012-01-26 10:00:00,-5.7,-12.4,59,11,24.1,102.04,Mainly Clear
-2012-01-26 11:00:00,-5.0,-12.1,57,7,24.1,102.05,Mainly Clear
-2012-01-26 12:00:00,-4.6,-12.5,54,11,24.1,101.88,Mainly Clear
-2012-01-26 13:00:00,-4.0,-12.0,54,15,24.1,101.71,Mostly Cloudy
-2012-01-26 14:00:00,-3.4,-12.5,49,11,24.1,101.6,Mostly Cloudy
-2012-01-26 15:00:00,-3.0,-14.1,42,13,24.1,101.53,Mostly Cloudy
-2012-01-26 16:00:00,-3.8,-12.2,52,19,24.1,101.52,Cloudy
-2012-01-26 17:00:00,-4.3,-12.2,54,20,24.1,101.4,Cloudy
-2012-01-26 18:00:00,-4.7,-13.7,49,24,25.0,101.28,Cloudy
-2012-01-26 19:00:00,-4.5,-13.5,49,17,25.0,101.25,Cloudy
-2012-01-26 20:00:00,-4.6,-13.0,52,17,25.0,101.15,Snow Showers
-2012-01-26 21:00:00,-5.2,-12.1,58,20,25.0,100.99,Snow
-2012-01-26 22:00:00,-5.3,-10.2,68,22,16.1,100.92,Snow
-2012-01-26 23:00:00,-5.8,-9.1,77,22,6.4,100.81,Snow
-2012-01-27 00:00:00,-5.7,-8.8,79,28,4.8,100.68,Snow
-2012-01-27 01:00:00,-5.5,-8.3,81,24,2.4,100.58,Snow
-2012-01-27 02:00:00,-5.5,-8.2,81,26,3.2,100.47,Snow
-2012-01-27 03:00:00,-5.3,-8.1,81,28,4.0,100.33,Snow
-2012-01-27 04:00:00,-4.9,-7.6,81,26,2.4,100.13,Snow
-2012-01-27 05:00:00,-4.0,-6.6,82,22,16.1,99.98,Snow
-2012-01-27 06:00:00,-2.1,-4.2,86,19,19.3,99.8,Snow
-2012-01-27 07:00:00,-0.8,-2.9,86,22,16.1,99.61,Freezing Rain
-2012-01-27 08:00:00,0.3,-1.7,86,20,12.9,99.47,Freezing Rain
-2012-01-27 09:00:00,0.7,-1.4,86,17,12.9,99.34,Rain
-2012-01-27 10:00:00,0.6,-1.2,88,17,8.0,99.18,"Rain,Fog"
-2012-01-27 11:00:00,0.7,-1.0,88,20,2.4,99.08,"Drizzle,Fog"
-2012-01-27 12:00:00,0.7,-0.9,89,20,2.8,98.91,"Drizzle,Fog"
-2012-01-27 13:00:00,0.7,-1.0,88,22,3.2,98.76,"Drizzle,Fog"
-2012-01-27 14:00:00,0.5,-1.3,88,20,2.4,98.69,"Drizzle,Fog"
-2012-01-27 15:00:00,0.3,-1.6,87,19,2.4,98.65,"Drizzle,Fog"
-2012-01-27 16:00:00,-0.3,-2.3,86,19,8.0,98.74,"Freezing Drizzle,Fog"
-2012-01-27 17:00:00,-0.6,-2.3,88,22,2.8,98.97,Snow
-2012-01-27 18:00:00,-0.3,-1.8,90,11,2.4,99.13,Snow
-2012-01-27 19:00:00,0.1,-1.6,88,30,12.9,99.31,Snow
-2012-01-27 20:00:00,-0.7,-2.7,86,32,16.1,99.54,Cloudy
-2012-01-27 21:00:00,-1.3,-3.9,82,19,24.1,99.75,Cloudy
-2012-01-27 22:00:00,-1.5,-4.4,81,19,25.0,99.88,Mostly Cloudy
-2012-01-27 23:00:00,-1.6,-4.5,81,20,25.0,100.03,Mainly Clear
-2012-01-28 00:00:00,-1.5,-4.3,81,19,25.0,100.19,Mainly Clear
-2012-01-28 01:00:00,-0.2,-2.9,82,22,25.0,100.34,Snow Showers
-2012-01-28 02:00:00,0.2,-2.6,81,24,25.0,100.49,Mostly Cloudy
-2012-01-28 03:00:00,0.4,-3.0,78,17,25.0,100.59,Mostly Cloudy
-2012-01-28 04:00:00,0.1,-3.4,77,15,25.0,100.64,Mostly Cloudy
-2012-01-28 05:00:00,0.3,-2.7,80,19,25.0,100.72,Mostly Cloudy
-2012-01-28 06:00:00,-1.7,-5.4,76,9,25.0,100.79,Mostly Cloudy
-2012-01-28 07:00:00,-1.2,-4.6,78,11,25.0,100.85,Mainly Clear
-2012-01-28 08:00:00,-2.1,-5.1,80,7,48.3,100.91,Mainly Clear
-2012-01-28 09:00:00,-1.6,-4.5,81,13,24.1,100.93,Mostly Cloudy
-2012-01-28 10:00:00,-1.1,-4.4,78,13,48.3,100.94,Cloudy
-2012-01-28 11:00:00,-0.6,-3.6,80,6,48.3,100.9,Cloudy
-2012-01-28 12:00:00,-0.3,-3.4,80,7,48.3,100.74,Mostly Cloudy
-2012-01-28 13:00:00,0.9,-3.5,72,4,48.3,100.58,Cloudy
-2012-01-28 14:00:00,1.2,-3.5,71,9,48.3,100.48,Cloudy
-2012-01-28 15:00:00,1.2,-3.7,70,15,48.3,100.28,Cloudy
-2012-01-28 16:00:00,1.4,-3.7,69,22,48.3,100.14,Cloudy
-2012-01-28 17:00:00,1.2,-3.5,71,11,48.3,100.16,Cloudy
-2012-01-28 18:00:00,1.6,-3.4,69,9,25.0,100.08,Cloudy
-2012-01-28 19:00:00,2.2,-2.6,71,19,19.3,100.09,Snow
-2012-01-28 20:00:00,1.7,-1.2,81,24,19.3,100.05,Snow
-2012-01-28 21:00:00,2.1,-1.7,76,24,25.0,99.95,Mainly Clear
-2012-01-28 22:00:00,2.3,-2.0,73,37,25.0,99.85,Mostly Cloudy
-2012-01-28 23:00:00,1.2,-1.7,81,52,16.1,99.87,"Rain,Snow"
-2012-01-29 00:00:00,1.5,-5.0,62,57,25.0,99.96,Mainly Clear
-2012-01-29 01:00:00,0.9,-5.3,63,52,25.0,100.09,Mainly Clear
-2012-01-29 02:00:00,0.3,-5.8,64,52,25.0,100.21,Mainly Clear
-2012-01-29 03:00:00,-0.2,-6.0,65,43,25.0,100.34,Mainly Clear
-2012-01-29 04:00:00,-0.9,-7.0,63,43,25.0,100.47,Mainly Clear
-2012-01-29 05:00:00,-1.5,-7.8,62,43,25.0,100.59,Mainly Clear
-2012-01-29 06:00:00,-2.0,-8.1,63,44,25.0,100.68,Mainly Clear
-2012-01-29 07:00:00,-1.9,-8.2,62,32,24.1,100.74,Mainly Clear
-2012-01-29 08:00:00,-2.2,-8.3,63,32,24.1,100.81,Mostly Cloudy
-2012-01-29 09:00:00,-2.1,-8.5,62,32,24.1,100.88,Cloudy
-2012-01-29 10:00:00,-1.8,-8.3,61,24,24.1,100.87,Mostly Cloudy
-2012-01-29 11:00:00,-0.8,-7.7,59,33,24.1,100.84,Mainly Clear
-2012-01-29 12:00:00,0.1,-7.6,56,37,24.1,100.77,Mainly Clear
-2012-01-29 13:00:00,0.5,-8.8,50,33,24.1,100.7,Mostly Cloudy
-2012-01-29 14:00:00,0.4,-7.9,54,19,24.1,100.63,Mostly Cloudy
-2012-01-29 15:00:00,0.2,-7.5,56,17,24.1,100.65,Mostly Cloudy
-2012-01-29 16:00:00,0.7,-8.3,51,20,24.1,100.67,Mostly Cloudy
-2012-01-29 17:00:00,-0.7,-8.4,56,11,24.1,100.74,Mainly Clear
-2012-01-29 18:00:00,-1.1,-9.3,54,17,25.0,100.77,Mainly Clear
-2012-01-29 19:00:00,-1.6,-9.3,56,17,25.0,100.81,Mainly Clear
-2012-01-29 20:00:00,-2.0,-9.1,58,17,25.0,100.83,Mainly Clear
-2012-01-29 21:00:00,-1.7,-8.4,60,9,25.0,100.85,Mainly Clear
-2012-01-29 22:00:00,-2.3,-7.0,70,15,25.0,100.84,Mainly Clear
-2012-01-29 23:00:00,-3.4,-7.6,73,15,25.0,100.85,Clear
-2012-01-30 00:00:00,-3.7,-8.8,68,11,25.0,100.89,Clear
-2012-01-30 01:00:00,-4.4,-10.0,65,15,25.0,100.92,Mainly Clear
-2012-01-30 02:00:00,-5.1,-10.0,68,15,25.0,100.99,Clear
-2012-01-30 03:00:00,-6.1,-10.3,72,11,25.0,101.07,Clear
-2012-01-30 04:00:00,-7.7,-11.8,72,11,25.0,101.19,Clear
-2012-01-30 05:00:00,-7.9,-13.8,63,13,25.0,101.33,Clear
-2012-01-30 06:00:00,-8.9,-15.1,61,15,25.0,101.47,Clear
-2012-01-30 07:00:00,-9.8,-16.0,61,15,25.0,101.55,Clear
-2012-01-30 08:00:00,-10.5,-17.0,59,9,48.3,101.68,Clear
-2012-01-30 09:00:00,-9.5,-16.6,56,13,48.3,101.75,Mainly Clear
-2012-01-30 10:00:00,-8.8,-16.0,56,17,48.3,101.82,Mostly Cloudy
-2012-01-30 11:00:00,-7.7,-14.7,57,19,48.3,101.86,Mostly Cloudy
-2012-01-30 12:00:00,-7.0,-14.2,56,22,48.3,101.83,Mainly Clear
-2012-01-30 13:00:00,-7.5,-15.2,54,22,48.3,101.8,Mainly Clear
-2012-01-30 14:00:00,-6.7,-15.0,52,22,48.3,101.81,Clear
-2012-01-30 15:00:00,-6.9,-15.3,51,22,48.3,101.83,Mainly Clear
-2012-01-30 16:00:00,-7.3,-15.8,51,17,48.3,101.86,Mostly Cloudy
-2012-01-30 17:00:00,-7.4,-15.7,51,13,48.3,101.9,Mostly Cloudy
-2012-01-30 18:00:00,-7.4,-15.6,52,15,25.0,101.94,Mainly Clear
-2012-01-30 19:00:00,-8.8,-15.9,56,7,25.0,101.96,Mainly Clear
-2012-01-30 20:00:00,-9.5,-16.0,59,4,25.0,101.95,Mainly Clear
-2012-01-30 21:00:00,-8.4,-15.5,57,4,25.0,101.96,Mostly Cloudy
-2012-01-30 22:00:00,-7.8,-15.2,55,4,25.0,101.98,Mostly Cloudy
-2012-01-30 23:00:00,-8.6,-13.8,66,6,25.0,101.96,Mostly Cloudy
-2012-01-31 00:00:00,-7.0,-13.1,62,7,25.0,101.92,Mostly Cloudy
-2012-01-31 01:00:00,-7.1,-13.2,62,6,25.0,101.88,Cloudy
-2012-01-31 02:00:00,-6.5,-13.1,59,11,25.0,101.81,Snow
-2012-01-31 03:00:00,-6.8,-12.4,64,15,19.3,101.76,Snow
-2012-01-31 04:00:00,-7.1,-12.4,66,17,8.0,101.71,Snow
-2012-01-31 05:00:00,-7.1,-12.2,67,17,9.7,101.7,Snow
-2012-01-31 06:00:00,-7.0,-11.8,69,13,6.4,101.65,Snow
-2012-01-31 07:00:00,-9.6,-13.5,73,17,12.9,101.6,Snow
-2012-01-31 08:00:00,-9.8,-13.9,72,19,16.1,101.61,Snow
-2012-01-31 09:00:00,-10.1,-14.4,71,17,24.1,101.59,Snow
-2012-01-31 10:00:00,-9.7,-14.2,70,19,19.3,101.54,Cloudy
-2012-01-31 11:00:00,-9.3,-14.2,67,20,19.3,101.46,Cloudy
-2012-01-31 12:00:00,-8.6,-13.3,69,22,4.0,101.36,Snow
-2012-01-31 13:00:00,-8.3,-12.3,73,20,1.6,101.29,Snow
-2012-01-31 14:00:00,-8.4,-12.1,75,20,1.2,101.23,Snow
-2012-01-31 15:00:00,-8.2,-12.0,74,17,1.0,101.22,Snow
-2012-01-31 16:00:00,-8.0,-11.5,76,20,1.0,101.2,Snow
-2012-01-31 17:00:00,-7.7,-11.1,77,19,1.0,101.19,Snow
-2012-01-31 18:00:00,-7.8,-11.2,77,20,1.6,101.18,Snow
-2012-01-31 19:00:00,-7.7,-10.9,78,19,1.6,101.14,Snow
-2012-01-31 20:00:00,-7.4,-10.7,77,20,1.6,101.09,Snow
-2012-01-31 21:00:00,-7.1,-10.5,77,20,12.9,101.02,Cloudy
-2012-01-31 22:00:00,-7.1,-10.4,77,19,9.7,100.95,Snow
-2012-01-31 23:00:00,-6.8,-9.9,79,22,9.7,100.86,"Freezing Drizzle,Snow"
+2013-01-01 00:00:00,-1.0,-1.7,95,35,6.4,99.89,Snow
+2013-01-01 01:00:00,-2.0,-5.1,79,35,16.1,99.93,Mainly Clear
+2013-01-01 02:00:00,-2.7,-6.0,78,28,19.3,100.08,Snow
+2013-01-01 03:00:00,-5.6,-11.7,62,30,25.0,100.21,Clear
+2013-01-01 04:00:00,-7.7,-12.6,68,35,19.3,100.32,Mainly Clear
+2013-01-01 05:00:00,-9.7,-14.8,66,33,25.0,100.47,Clear
+2013-01-01 06:00:00,-11.1,-17.0,62,30,25.0,100.65,Clear
+2013-01-01 07:00:00,-12.2,-17.2,66,20,25.0,100.78,Clear
+2013-01-01 08:00:00,-13.0,-17.7,68,13,24.1,100.87,Clear
+2013-01-01 09:00:00,-13.0,-17.3,70,20,24.1,100.86,Clear
+2013-01-01 10:00:00,-12.6,-17.8,65,19,24.1,100.9,Clear
+2013-01-01 11:00:00,-12.2,-17.6,64,22,24.1,100.88,Mainly Clear
+2013-01-01 12:00:00,-11.8,-17.2,64,26,24.1,100.87,Mainly Clear
+2013-01-01 13:00:00,-11.3,-17.4,61,26,24.1,100.83,Mainly Clear
+2013-01-01 14:00:00,-11.3,-17.4,61,28,24.1,100.82,Mainly Clear
+2013-01-01 15:00:00,-11.4,-17.6,60,30,24.1,100.85,Mainly Clear
+2013-01-01 16:00:00,-12.0,-18.0,61,22,24.1,100.81,Mainly Clear
+2013-01-01 17:00:00,-13.0,-18.4,64,19,25.0,100.9,Clear
+2013-01-01 18:00:00,-13.4,-18.4,66,24,25.0,100.96,Clear
+2013-01-01 19:00:00,-14.1,-18.7,68,20,25.0,101.02,Clear
+2013-01-01 20:00:00,-14.3,-19.0,67,15,25.0,101.04,Clear
+2013-01-01 21:00:00,-14.8,-19.5,67,15,25.0,100.98,Mainly Clear
+2013-01-01 22:00:00,-16.3,-20.2,72,7,25.0,100.98,Mostly Cloudy
+2013-01-01 23:00:00,-15.4,-19.8,69,11,25.0,100.99,Cloudy
+2013-01-02 00:00:00,-14.0,-18.4,69,11,19.3,100.96,Snow
+2013-01-02 01:00:00,-14.1,-18.3,70,11,25.0,100.91,Mostly Cloudy
+2013-01-02 02:00:00,-14.3,-18.3,72,13,25.0,100.94,Snow Showers
+2013-01-02 03:00:00,-14.7,-18.0,76,9,19.3,100.91,Snow
+2013-01-02 04:00:00,-14.2,-17.1,79,6,9.7,100.83,Snow
+2013-01-02 05:00:00,-14.3,-17.0,80,0,6.4,100.81,Snow
+2013-01-02 06:00:00,-14.4,-16.8,82,4,6.4,100.84,Snow
+2013-01-02 07:00:00,-14.9,-17.6,80,9,8.0,100.92,Snow
+2013-01-02 08:00:00,-15.8,-18.3,81,7,24.1,101.01,Mostly Cloudy
+2013-01-02 09:00:00,-15.0,-18.0,78,9,24.1,101.15,Mostly Cloudy
+2013-01-02 10:00:00,-15.1,-18.8,73,9,24.1,101.33,Mainly Clear
+2013-01-02 11:00:00,-14.6,-20.2,62,9,24.1,101.41,Mostly Cloudy
+2013-01-02 12:00:00,-14.6,-19.3,67,7,4.8,101.42,Snow Showers
+2013-01-02 13:00:00,-14.7,-19.4,67,17,12.9,101.47,Snow
+2013-01-02 14:00:00,-15.3,-22.8,53,19,24.1,101.53,Mostly Cloudy
+2013-01-02 15:00:00,-15.6,-24.2,48,15,24.1,101.66,Mainly Clear
+2013-01-02 16:00:00,-17.0,-25.0,50,19,24.1,101.79,Mainly Clear
+2013-01-02 17:00:00,-18.1,-25.5,52,17,24.1,101.9,Mainly Clear
+2013-01-02 18:00:00,-18.5,-25.7,53,15,25.0,101.97,Clear
+2013-01-02 19:00:00,-19.5,-26.1,56,9,25.0,101.99,Clear
+2013-01-02 20:00:00,-20.1,-26.4,57,17,25.0,102.03,Clear
+2013-01-02 21:00:00,-20.5,-26.7,58,11,25.0,102.05,Clear
+2013-01-02 22:00:00,-20.7,-26.0,62,6,25.0,102.07,Clear
+2013-01-02 23:00:00,-21.7,-26.3,66,9,25.0,102.13,Clear
+2013-01-03 00:00:00,-21.2,-26.4,63,7,25.0,102.07,Mostly Cloudy
+2013-01-03 01:00:00,-21.2,-25.9,66,4,25.0,102.1,Cloudy
+2013-01-03 02:00:00,-20.8,-25.8,64,13,25.0,102.13,Cloudy
+2013-01-03 03:00:00,-20.9,-25.6,66,4,25.0,102.11,Cloudy
+2013-01-03 04:00:00,-21.4,-26.2,65,4,25.0,102.05,Mostly Cloudy
+2013-01-03 05:00:00,-22.6,-27.7,63,6,25.0,101.98,Mostly Cloudy
+2013-01-03 06:00:00,-21.9,-26.4,67,6,25.0,101.99,Cloudy
+2013-01-03 07:00:00,-23.1,-26.6,73,6,25.0,101.95,Mostly Cloudy
+2013-01-03 08:00:00,-22.3,-26.7,67,6,48.3,101.91,Mostly Cloudy
+2013-01-03 09:00:00,-19.8,-25.1,63,6,48.3,101.87,Mainly Clear
+2013-01-03 10:00:00,-18.4,-24.8,57,9,48.3,101.87,Mainly Clear
+2013-01-03 11:00:00,-17.9,-24.3,57,11,48.3,101.77,Mostly Cloudy
+2013-01-03 12:00:00,-17.6,-23.8,58,9,24.1,101.66,Mostly Cloudy
+2013-01-03 13:00:00,-17.0,-21.5,68,9,24.1,101.55,Cloudy
+2013-01-03 14:00:00,-16.4,-21.7,64,4,16.1,101.44,Snow
+2013-01-03 15:00:00,-16.0,-21.4,63,6,12.9,101.37,Snow
+2013-01-03 16:00:00,-15.9,-21.2,64,6,6.4,101.33,Snow
+2013-01-03 17:00:00,-15.4,-19.9,68,6,8.0,101.25,Snow
+2013-01-03 18:00:00,-15.0,-18.3,76,7,16.1,101.15,Snow Showers
+2013-01-03 19:00:00,-14.5,-17.5,78,7,25.0,101.09,Snow Showers
+2013-01-03 20:00:00,-14.0,-17.0,78,7,16.1,100.97,Snow Showers
+2013-01-03 21:00:00,-13.2,-16.1,79,7,8.0,100.9,Snow Showers
+2013-01-03 22:00:00,-13.9,-16.4,81,9,4.8,100.84,Snow
+2013-01-03 23:00:00,-14.0,-16.6,81,7,4.8,100.78,Snow
+2013-01-04 00:00:00,-14.6,-17.3,80,13,2.8,100.74,Snow
+2013-01-04 01:00:00,-15.3,-18.3,78,6,11.3,100.69,Snow
+2013-01-04 02:00:00,-14.3,-17.5,77,7,12.9,100.68,Snow
+2013-01-04 03:00:00,-13.7,-16.6,79,13,12.9,100.73,Snow
+2013-01-04 04:00:00,-13.1,-15.9,79,13,16.1,100.64,Snow
+2013-01-04 05:00:00,-12.3,-14.7,82,11,19.3,100.57,Snow
+2013-01-04 06:00:00,-11.6,-13.4,86,15,3.2,100.52,Snow
+2013-01-04 07:00:00,-10.8,-12.0,91,15,12.9,100.38,Snow
+2013-01-04 08:00:00,-8.8,-9.9,92,13,16.1,100.26,Cloudy
+2013-01-04 09:00:00,-8.8,-9.9,92,7,16.1,100.27,Cloudy
+2013-01-04 10:00:00,-6.2,-8.0,87,19,4.0,100.18,"Snow,Fog"
+2013-01-04 11:00:00,-1.4,-3.7,84,46,8.0,100.09,"Snow,Blowing Snow"
+2013-01-04 12:00:00,-0.7,-3.7,80,46,6.4,100.01,"Snow,Blowing Snow"
+2013-01-04 13:00:00,-0.3,-3.6,78,48,12.9,100.0,Snow
+2013-01-04 14:00:00,0.1,-3.9,74,39,24.1,100.01,Snow
+2013-01-04 15:00:00,0.2,-3.9,74,37,24.1,100.05,Snow
+2013-01-04 16:00:00,0.1,-3.8,75,32,25.0,100.11,Snow
+2013-01-04 17:00:00,0.1,-3.5,77,33,25.0,100.15,Snow
+2013-01-04 18:00:00,0.1,-3.4,77,30,25.0,100.19,Snow
+2013-01-04 19:00:00,0.1,-3.6,76,37,25.0,100.2,Cloudy
+2013-01-04 20:00:00,-0.3,-3.4,80,33,25.0,100.22,Snow
+2013-01-04 21:00:00,-0.4,-3.0,83,37,25.0,100.19,Snow
+2013-01-04 22:00:00,-1.2,-2.7,90,35,6.4,100.16,Snow
+2013-01-04 23:00:00,-0.9,-3.0,86,43,6.4,100.14,"Snow,Blowing Snow"
+2013-01-05 00:00:00,-1.0,-3.0,86,44,4.0,100.13,"Snow,Blowing Snow"
+2013-01-05 01:00:00,-0.7,-2.7,86,41,9.7,100.2,"Snow,Blowing Snow"
+2013-01-05 02:00:00,0.3,-3.3,77,41,16.1,100.33,Snow
+2013-01-05 03:00:00,-1.0,-4.6,77,30,19.3,100.59,Mostly Cloudy
+2013-01-05 04:00:00,-2.1,-7.4,67,28,25.0,100.74,Clear
+2013-01-05 05:00:00,-2.5,-7.9,66,22,25.0,100.91,Mostly Cloudy
+2013-01-05 06:00:00,-3.9,-10.4,61,35,25.0,101.23,Mainly Clear
+2013-01-05 07:00:00,-6.1,-14.3,52,20,25.0,101.47,Mainly Clear
+2013-01-05 08:00:00,-7.4,-15.2,54,20,24.1,101.69,Mainly Clear
+2013-01-05 09:00:00,-7.9,-14.8,58,19,24.1,101.83,Mainly Clear
+2013-01-05 10:00:00,-7.7,-15.3,54,15,24.1,101.96,Mainly Clear
+2013-01-05 11:00:00,-7.6,-15.6,53,19,48.3,102.0,Mainly Clear
+2013-01-05 12:00:00,-7.2,-15.2,53,20,48.3,102.04,Mainly Clear
+2013-01-05 13:00:00,-7.4,-14.9,55,17,48.3,102.0,Mainly Clear
+2013-01-05 14:00:00,-6.8,-14.9,52,17,48.3,102.0,Clear
+2013-01-05 15:00:00,-6.9,-14.7,54,11,48.3,102.02,Clear
+2013-01-05 16:00:00,-8.2,-15.1,58,7,48.3,102.0,Clear
+2013-01-05 17:00:00,-9.4,-14.9,64,7,25.0,102.02,Mainly Clear
+2013-01-05 18:00:00,-9.2,-14.9,63,6,25.0,101.96,Mainly Clear
+2013-01-05 19:00:00,-9.7,-15.4,63,4,25.0,101.92,Mainly Clear
+2013-01-05 20:00:00,-12.9,-16.2,76,6,25.0,101.95,Mainly Clear
+2013-01-05 21:00:00,-11.6,-13.7,84,7,25.0,101.92,Mainly Clear
+2013-01-05 22:00:00,-9.5,-12.3,80,7,25.0,101.83,Cloudy
+2013-01-05 23:00:00,-9.0,-12.6,75,7,25.0,101.78,Cloudy
+2013-01-06 00:00:00,-8.6,-12.0,76,6,25.0,101.71,Snow
+2013-01-06 01:00:00,-8.1,-12.3,72,7,25.0,101.63,Snow
+2013-01-06 02:00:00,-8.1,-11.8,75,9,25.0,101.54,Snow
+2013-01-06 03:00:00,-7.6,-11.0,77,11,25.0,101.36,Snow
+2013-01-06 04:00:00,-7.2,-10.4,78,13,25.0,101.22,Snow
+2013-01-06 05:00:00,-7.4,-10.3,80,13,25.0,101.13,Snow
+2013-01-06 06:00:00,-8.5,-10.4,86,11,4.0,101.11,Snow
+2013-01-06 07:00:00,-9.8,-11.5,87,11,3.2,101.1,Snow
+2013-01-06 08:00:00,-10.5,-12.2,87,17,3.2,101.03,Snow
+2013-01-06 09:00:00,-10.4,-12.1,87,15,3.2,100.99,Snow
+2013-01-06 10:00:00,-10.5,-12.1,88,17,2.0,100.99,Snow
+2013-01-06 11:00:00,-10.5,-12.3,87,17,4.0,100.91,Snow
+2013-01-06 12:00:00,-10.2,-12.3,85,13,12.9,100.84,Snow
+2013-01-06 13:00:00,-9.6,-11.3,87,19,1.6,100.78,Snow
+2013-01-06 14:00:00,-9.0,-10.6,88,15,1.6,100.8,Snow
+2013-01-06 15:00:00,-8.6,-10.4,87,17,2.8,100.84,Snow
+2013-01-06 16:00:00,-8.6,-10.3,87,17,1.6,100.88,Snow
+2013-01-06 17:00:00,-8.2,-9.8,88,19,1.6,100.91,Snow
+2013-01-06 18:00:00,-7.5,-9.0,89,17,1.6,100.96,Snow
+2013-01-06 19:00:00,-7.2,-9.0,87,28,3.2,101.02,Snow
+2013-01-06 20:00:00,-7.3,-9.2,86,26,2.4,101.06,Snow
+2013-01-06 21:00:00,-7.8,-9.6,87,30,1.6,101.14,Snow
+2013-01-06 22:00:00,-8.1,-10.0,86,24,6.4,101.22,Snow
+2013-01-06 23:00:00,-8.4,-10.5,85,26,9.7,101.34,Snow
+2013-01-07 00:00:00,-8.9,-11.5,81,20,12.9,101.44,Snow
+2013-01-07 01:00:00,-9.4,-12.1,81,17,25.0,101.52,Snow
+2013-01-07 02:00:00,-9.6,-12.5,79,7,25.0,101.71,Snow
+2013-01-07 03:00:00,-9.5,-12.4,79,13,25.0,101.82,Snow
+2013-01-07 04:00:00,-10.4,-14.6,71,20,25.0,101.94,Snow
+2013-01-07 05:00:00,-11.4,-16.9,64,19,25.0,102.03,Snow
+2013-01-07 06:00:00,-12.3,-18.1,62,15,25.0,102.16,Snow
+2013-01-07 07:00:00,-12.3,-18.3,61,11,25.0,102.31,Snow
+2013-01-07 08:00:00,-12.8,-18.6,62,15,24.1,102.43,Snow
+2013-01-07 09:00:00,-13.4,-19.4,61,13,24.1,102.5,Snow
+2013-01-07 10:00:00,-13.7,-19.5,62,11,24.1,102.59,Snow
+2013-01-07 11:00:00,-13.7,-19.7,60,6,24.1,102.63,Snow
+2013-01-07 12:00:00,-13.4,-19.8,59,6,24.1,102.55,Mostly Cloudy
+2013-01-07 13:00:00,-11.6,-19.1,54,4,24.1,102.46,Mostly Cloudy
+2013-01-07 14:00:00,-11.8,-17.1,65,4,24.1,102.49,Mainly Clear
+2013-01-07 15:00:00,-11.0,-14.2,77,11,24.1,102.43,Snow
+2013-01-07 16:00:00,-12.3,-15.0,80,17,24.1,102.42,Snow
+2013-01-07 17:00:00,-12.3,-15.2,79,9,48.3,102.42,Mostly Cloudy
+2013-01-07 18:00:00,-10.9,-13.8,79,13,25.0,102.31,Cloudy
+2013-01-07 19:00:00,-10.0,-13.0,79,13,25.0,102.2,Cloudy
+2013-01-07 20:00:00,-9.9,-13.1,77,22,25.0,102.06,Snow
+2013-01-07 21:00:00,-9.4,-11.9,82,20,25.0,101.93,Snow
+2013-01-07 22:00:00,-6.4,-9.7,77,22,25.0,101.82,Cloudy
+2013-01-07 23:00:00,-6.5,-9.5,79,13,25.0,101.74,Cloudy
+2013-01-08 00:00:00,-7.9,-10.9,79,19,25.0,101.62,Mainly Clear
+2013-01-08 01:00:00,-10.4,-12.6,84,15,25.0,101.57,Mainly Clear
+2013-01-08 02:00:00,-9.4,-11.4,85,15,25.0,101.59,Mostly Cloudy
+2013-01-08 03:00:00,-6.9,-9.2,84,19,25.0,101.51,Mostly Cloudy
+2013-01-08 04:00:00,-6.2,-8.8,82,15,25.0,101.49,Cloudy
+2013-01-08 05:00:00,-2.9,-6.7,75,24,25.0,101.5,Cloudy
+2013-01-08 06:00:00,-0.1,-4.5,72,35,25.0,101.52,Cloudy
+2013-01-08 07:00:00,0.1,-4.1,73,32,25.0,101.59,Cloudy
+2013-01-08 08:00:00,0.1,-3.9,74,33,19.3,101.65,Cloudy
+2013-01-08 09:00:00,0.7,-3.7,72,28,19.3,101.72,Cloudy
+2013-01-08 10:00:00,1.0,-3.5,72,30,19.3,101.78,Cloudy
+2013-01-08 11:00:00,1.1,-3.3,72,32,19.3,101.83,Cloudy
+2013-01-08 12:00:00,1.1,-3.2,73,33,19.3,101.81,Cloudy
+2013-01-08 13:00:00,1.5,-2.7,74,30,19.3,101.79,Cloudy
+2013-01-08 14:00:00,1.6,-2.6,74,26,24.1,101.85,Mainly Clear
+2013-01-08 15:00:00,1.7,-2.8,72,24,24.1,101.95,Mainly Clear
+2013-01-08 16:00:00,1.1,-3.1,74,20,24.1,102.0,Mainly Clear
+2013-01-08 17:00:00,0.5,-3.1,77,19,25.0,102.1,Mainly Clear
+2013-01-08 18:00:00,1.1,-2.4,77,13,25.0,102.17,Cloudy
+2013-01-08 19:00:00,-0.2,-2.9,82,11,25.0,102.26,Mainly Clear
+2013-01-08 20:00:00,-0.1,-2.8,82,7,25.0,102.32,Mainly Clear
+2013-01-08 21:00:00,-2.8,-4.6,87,7,25.0,102.3,Mostly Cloudy
+2013-01-08 22:00:00,-2.1,-3.8,88,9,25.0,102.3,Cloudy
+2013-01-08 23:00:00,-2.0,-3.6,89,6,12.9,102.29,Mostly Cloudy
+2013-01-09 00:00:00,-3.6,-4.7,92,7,9.7,102.3,Fog
+2013-01-09 01:00:00,-4.6,-5.1,96,4,2.4,102.28,Fog
+2013-01-09 02:00:00,-3.9,-4.8,93,7,4.8,102.25,Fog
+2013-01-09 03:00:00,-4.5,-5.3,94,9,8.0,102.27,Fog
+2013-01-09 04:00:00,-4.5,-5.6,92,7,9.7,102.14,Fog
+2013-01-09 05:00:00,-5.5,-7.1,88,6,12.9,102.1,Mainly Clear
+2013-01-09 06:00:00,-3.7,-6.0,84,7,12.9,102.09,Clear
+2013-01-09 07:00:00,-4.5,-6.2,88,11,12.9,102.03,Clear
+2013-01-09 08:00:00,-5.7,-7.0,91,7,12.9,101.97,Mainly Clear
+2013-01-09 09:00:00,-3.9,-6.5,82,9,12.9,101.83,Mainly Clear
+2013-01-09 10:00:00,-2.2,-5.2,80,9,16.1,101.7,Mostly Cloudy
+2013-01-09 11:00:00,-1.4,-4.6,79,20,16.1,101.29,Cloudy
+2013-01-09 12:00:00,-0.2,-4.2,74,13,16.1,101.33,Cloudy
+2013-01-09 13:00:00,0.4,-3.9,73,13,16.1,101.05,Cloudy
+2013-01-09 14:00:00,0.8,-4.0,70,15,19.3,100.82,Rain Showers
+2013-01-09 15:00:00,1.0,-3.4,72,22,19.3,100.7,Snow
+2013-01-09 16:00:00,1.3,-2.4,76,20,24.1,100.56,"Rain,Snow"
+2013-01-09 17:00:00,1.1,-1.5,83,20,16.1,100.51,Rain
+2013-01-09 18:00:00,5.2,0.1,70,35,25.0,100.53,Cloudy
+2013-01-09 19:00:00,4.7,-0.3,70,39,25.0,100.61,Cloudy
+2013-01-09 20:00:00,4.4,-1.0,68,32,25.0,100.67,Cloudy
+2013-01-09 21:00:00,4.3,-1.6,65,37,25.0,100.76,Cloudy
+2013-01-09 22:00:00,4.2,-1.6,66,39,25.0,100.83,Cloudy
+2013-01-09 23:00:00,3.4,-0.7,74,32,25.0,100.93,Rain Showers
+2013-01-10 00:00:00,2.7,-1.0,77,35,25.0,101.05,Mainly Clear
+2013-01-10 01:00:00,2.7,-1.3,75,41,25.0,101.2,Mainly Clear
+2013-01-10 02:00:00,2.7,-1.9,72,44,25.0,101.42,Mainly Clear
+2013-01-10 03:00:00,2.5,-2.8,68,35,25.0,101.6,Mainly Clear
+2013-01-10 04:00:00,2.3,-2.5,71,37,25.0,101.74,Mainly Clear
+2013-01-10 05:00:00,2.3,-2.7,69,30,25.0,101.88,Mostly Cloudy
+2013-01-10 06:00:00,2.1,-2.9,69,32,25.0,101.96,Mainly Clear
+2013-01-10 07:00:00,2.0,-2.9,70,28,25.0,102.1,Mainly Clear
+2013-01-10 08:00:00,1.3,-3.2,72,24,24.1,102.32,Mostly Cloudy
+2013-01-10 09:00:00,1.3,-3.4,71,33,24.1,102.47,Mostly Cloudy
+2013-01-10 10:00:00,1.4,-3.3,71,22,24.1,102.58,Cloudy
+2013-01-10 11:00:00,1.9,-2.9,70,26,24.1,102.65,Cloudy
+2013-01-10 12:00:00,1.9,-2.9,70,20,48.3,102.67,Cloudy
+2013-01-10 13:00:00,2.2,-2.9,69,26,48.3,102.69,Mostly Cloudy
+2013-01-10 14:00:00,2.4,-2.9,68,24,48.3,102.77,Mostly Cloudy
+2013-01-10 15:00:00,2.4,-3.0,67,20,48.3,102.89,Mostly Cloudy
+2013-01-10 16:00:00,2.2,-3.3,67,17,48.3,102.96,Mostly Cloudy
+2013-01-10 17:00:00,1.9,-3.2,69,15,25.0,103.01,Mostly Cloudy
+2013-01-10 18:00:00,1.9,-3.5,67,4,25.0,103.03,Mostly Cloudy
+2013-01-10 19:00:00,1.3,-3.1,72,4,25.0,103.03,Mostly Cloudy
+2013-01-10 20:00:00,0.5,-2.7,79,9,25.0,103.09,Mostly Cloudy
+2013-01-10 21:00:00,0.6,-3.0,77,6,25.0,103.09,Mostly Cloudy
+2013-01-10 22:00:00,0.6,-4.4,69,7,25.0,103.03,Mostly Cloudy
+2013-01-10 23:00:00,-0.5,-5.1,71,11,25.0,102.99,Clear
+2013-01-11 00:00:00,-2.1,-5.4,78,9,25.0,102.95,Clear
+2013-01-11 01:00:00,-2.3,-5.5,79,6,25.0,102.94,Mostly Cloudy
+2013-01-11 02:00:00,-1.6,-5.6,74,7,25.0,102.93,Mostly Cloudy
+2013-01-11 03:00:00,-1.1,-5.6,71,11,25.0,102.83,Mostly Cloudy
+2013-01-11 04:00:00,-1.8,-6.2,72,11,25.0,102.74,Mostly Cloudy
+2013-01-11 05:00:00,-1.5,-6.1,71,9,25.0,102.65,Mostly Cloudy
+2013-01-11 06:00:00,-2.0,-6.1,73,13,25.0,102.62,Mostly Cloudy
+2013-01-11 07:00:00,-2.5,-6.2,76,15,25.0,102.61,Mostly Cloudy
+2013-01-11 08:00:00,-2.3,-6.7,72,15,24.1,102.54,Cloudy
+2013-01-11 09:00:00,-2.1,-6.4,72,11,24.1,102.43,Cloudy
+2013-01-11 10:00:00,-1.5,-6.1,71,15,24.1,102.3,Cloudy
+2013-01-11 11:00:00,-0.1,-5.7,66,19,24.1,102.12,Cloudy
+2013-01-11 12:00:00,0.4,-5.1,67,17,24.1,102.0,Cloudy
+2013-01-11 13:00:00,0.8,-5.6,62,15,24.1,101.88,Cloudy
+2013-01-11 14:00:00,0.8,-4.7,67,26,24.1,101.66,Rain
+2013-01-11 15:00:00,1.1,-3.9,69,15,24.1,101.65,Rain
+2013-01-11 16:00:00,1.8,-3.2,69,15,24.1,101.51,Cloudy
+2013-01-11 17:00:00,2.7,-3.5,64,19,24.1,101.41,Cloudy
+2013-01-11 18:00:00,2.6,-3.3,65,11,25.0,101.37,Cloudy
+2013-01-11 19:00:00,2.1,-2.2,73,9,25.0,101.35,Cloudy
+2013-01-11 20:00:00,1.9,-1.4,79,9,25.0,101.29,Drizzle
+2013-01-11 21:00:00,1.8,-0.8,83,7,25.0,101.31,Drizzle
+2013-01-11 22:00:00,1.8,-0.7,83,4,25.0,101.32,Cloudy
+2013-01-11 23:00:00,2.2,-0.4,83,13,25.0,101.25,Cloudy
+2013-01-12 00:00:00,2.1,-0.2,85,15,25.0,101.22,Cloudy
+2013-01-12 01:00:00,2.0,0.1,87,9,25.0,101.24,Cloudy
+2013-01-12 02:00:00,1.9,0.4,90,11,25.0,101.21,Cloudy
+2013-01-12 03:00:00,1.9,0.4,90,9,25.0,101.22,Cloudy
+2013-01-12 04:00:00,2.1,0.8,91,7,25.0,101.2,Drizzle
+2013-01-12 05:00:00,1.7,0.8,94,6,16.1,101.22,Drizzle
+2013-01-12 06:00:00,1.8,1.1,95,6,6.4,101.25,"Drizzle,Fog"
+2013-01-12 07:00:00,2.3,1.6,95,7,6.4,101.28,"Drizzle,Fog"
+2013-01-12 08:00:00,2.2,1.4,94,13,6.4,101.28,"Drizzle,Fog"
+2013-01-12 09:00:00,1.9,1.2,95,6,8.0,101.32,"Drizzle,Fog"
+2013-01-12 10:00:00,2.0,1.3,95,9,16.1,101.27,Cloudy
+2013-01-12 11:00:00,2.9,1.5,90,4,16.1,101.21,Cloudy
+2013-01-12 12:00:00,3.2,1.9,91,7,16.1,101.1,Cloudy
+2013-01-12 13:00:00,4.4,2.4,87,9,48.3,101.12,Cloudy
+2013-01-12 14:00:00,5.1,2.8,85,17,48.3,101.09,Cloudy
+2013-01-12 15:00:00,4.6,2.3,85,11,48.3,101.09,Cloudy
+2013-01-12 16:00:00,4.4,1.9,84,11,48.3,101.06,Cloudy
+2013-01-12 17:00:00,3.5,1.8,89,9,48.3,101.01,Cloudy
+2013-01-12 18:00:00,3.6,2.0,89,6,25.0,101.08,Cloudy
+2013-01-12 19:00:00,4.0,2.6,91,4,25.0,101.12,Cloudy
+2013-01-12 20:00:00,3.4,2.0,91,7,25.0,101.12,Cloudy
+2013-01-12 21:00:00,3.1,1.8,91,4,25.0,101.13,Cloudy
+2013-01-12 22:00:00,3.0,1.7,91,9,25.0,101.15,Cloudy
+2013-01-12 23:00:00,2.4,1.4,93,6,25.0,101.13,Cloudy
+2013-01-13 00:00:00,3.4,2.5,94,6,25.0,101.19,Cloudy
+2013-01-13 01:00:00,2.4,1.7,95,9,19.3,101.24,Mostly Cloudy
+2013-01-13 02:00:00,3.0,2.3,95,7,19.3,101.3,Mostly Cloudy
+2013-01-13 03:00:00,3.0,2.3,95,4,19.3,101.31,Cloudy
+2013-01-13 04:00:00,2.9,1.9,93,4,19.3,101.3,Cloudy
+2013-01-13 05:00:00,2.4,1.7,95,13,25.0,101.17,Mostly Cloudy
+2013-01-13 06:00:00,3.1,2.4,95,9,25.0,101.1,Cloudy
+2013-01-13 07:00:00,2.9,1.8,92,6,25.0,101.1,Mostly Cloudy
+2013-01-13 08:00:00,3.4,2.6,94,6,19.3,101.14,Mostly Cloudy
+2013-01-13 09:00:00,3.3,2.4,94,15,19.3,101.1,Cloudy
+2013-01-13 10:00:00,4.1,3.0,93,17,16.1,100.96,Cloudy
+2013-01-13 11:00:00,4.0,3.3,95,19,6.4,100.89,"Rain,Fog"
+2013-01-13 12:00:00,4.1,3.4,95,32,6.4,100.63,"Rain,Fog"
+2013-01-13 13:00:00,4.5,3.5,93,24,19.3,100.41,Cloudy
+2013-01-13 14:00:00,4.0,3.2,95,9,6.4,100.39,"Rain,Fog"
+2013-01-13 15:00:00,4.2,3.5,95,9,24.1,100.39,Cloudy
+2013-01-13 16:00:00,5.0,4.2,95,0,24.1,100.41,Cloudy
+2013-01-13 17:00:00,4.5,3.2,91,7,19.3,100.44,Cloudy
+2013-01-13 18:00:00,3.7,2.6,93,7,16.1,100.51,Cloudy
+2013-01-13 19:00:00,3.7,3.3,97,4,4.8,100.54,"Drizzle,Fog"
+2013-01-13 20:00:00,4.1,3.5,96,9,3.2,100.51,"Drizzle,Fog"
+2013-01-13 21:00:00,3.9,3.7,99,13,2.0,100.56,"Drizzle,Fog"
+2013-01-13 22:00:00,3.1,2.9,99,13,4.8,100.56,Fog
+2013-01-13 23:00:00,4.4,4.2,99,13,12.9,100.57,Cloudy
+2013-01-14 00:00:00,4.2,3.7,97,7,12.9,100.54,Cloudy
+2013-01-14 01:00:00,3.4,3.1,98,17,12.9,100.39,Drizzle
+2013-01-14 02:00:00,5.0,4.5,97,9,12.9,100.3,Drizzle
+2013-01-14 03:00:00,4.3,3.2,93,9,16.1,100.2,Drizzle
+2013-01-14 04:00:00,4.5,4.0,97,17,19.3,100.05,Drizzle
+2013-01-14 05:00:00,5.8,5.0,95,19,9.7,100.09,"Rain,Fog"
+2013-01-14 06:00:00,5.9,4.9,93,19,25.0,100.29,Mostly Cloudy
+2013-01-14 07:00:00,5.4,3.8,89,30,25.0,100.61,Mostly Cloudy
+2013-01-14 08:00:00,4.3,1.6,83,41,24.1,100.88,Mainly Clear
+2013-01-14 09:00:00,3.7,-0.6,73,32,24.1,101.13,Mostly Cloudy
+2013-01-14 10:00:00,4.1,-0.4,72,28,24.1,101.29,Mainly Clear
+2013-01-14 11:00:00,4.2,-0.5,71,28,48.3,101.36,Mostly Cloudy
+2013-01-14 12:00:00,2.9,-1.3,74,32,24.1,101.45,Mainly Clear
+2013-01-14 13:00:00,3.0,-2.9,65,30,48.3,101.54,Mostly Cloudy
+2013-01-14 14:00:00,3.6,-3.4,60,24,48.3,101.63,Mostly Cloudy
+2013-01-14 15:00:00,3.4,-3.7,60,28,48.3,101.74,Mainly Clear
+2013-01-14 16:00:00,2.9,-4.4,59,22,48.3,101.81,Mostly Cloudy
+2013-01-14 17:00:00,1.7,-5.5,59,19,24.1,101.84,Mainly Clear
+2013-01-14 18:00:00,0.9,-6.1,59,17,25.0,101.88,Mainly Clear
+2013-01-14 19:00:00,1.1,-6.6,56,17,25.0,101.99,Mostly Cloudy
+2013-01-14 20:00:00,0.6,-5.6,63,17,25.0,102.09,Mostly Cloudy
+2013-01-14 21:00:00,0.5,-5.6,64,11,25.0,102.08,Mostly Cloudy
+2013-01-14 22:00:00,0.3,-5.3,66,15,25.0,102.02,Mostly Cloudy
+2013-01-14 23:00:00,0.0,-5.0,69,11,25.0,102.07,Mostly Cloudy
+2013-01-15 00:00:00,0.0,-5.2,68,13,25.0,102.13,Mostly Cloudy
+2013-01-15 01:00:00,-0.3,-6.2,64,15,25.0,102.19,Mostly Cloudy
+2013-01-15 02:00:00,-0.6,-6.3,65,15,25.0,102.2,Mostly Cloudy
+2013-01-15 03:00:00,-1.2,-5.5,73,7,25.0,102.13,Mostly Cloudy
+2013-01-15 04:00:00,-1.4,-6.1,70,9,25.0,102.13,Mostly Cloudy
+2013-01-15 05:00:00,-1.5,-7.0,66,11,25.0,102.13,Mostly Cloudy
+2013-01-15 06:00:00,-1.8,-7.5,65,15,25.0,102.17,Mostly Cloudy
+2013-01-15 07:00:00,-2.7,-7.6,69,13,25.0,102.26,Cloudy
+2013-01-15 08:00:00,-2.9,-7.0,73,7,24.1,102.33,Mostly Cloudy
+2013-01-15 09:00:00,-3.2,-8.3,68,15,24.1,102.4,Mostly Cloudy
+2013-01-15 10:00:00,-3.0,-9.0,63,6,24.1,102.42,Snow
+2013-01-15 11:00:00,-2.4,-10.5,54,6,24.1,102.38,Mostly Cloudy
+2013-01-15 12:00:00,-2.0,-10.4,53,9,24.1,102.31,Mostly Cloudy
+2013-01-15 13:00:00,-1.3,-10.1,51,11,24.1,102.17,Mostly Cloudy
+2013-01-15 14:00:00,-1.3,-9.5,54,17,48.3,102.16,Mostly Cloudy
+2013-01-15 15:00:00,-1.4,-8.3,59,20,48.3,102.14,Mostly Cloudy
+2013-01-15 16:00:00,-1.1,-8.1,59,19,48.3,102.13,Mostly Cloudy
+2013-01-15 17:00:00,-0.7,-8.7,55,20,24.1,102.04,Mostly Cloudy
+2013-01-15 18:00:00,-0.6,-8.2,56,24,25.0,102.08,Mostly Cloudy
+2013-01-15 19:00:00,-0.6,-6.9,62,15,25.0,102.08,Mostly Cloudy
+2013-01-15 20:00:00,-0.8,-7.5,60,20,25.0,102.0,Mostly Cloudy
+2013-01-15 21:00:00,-1.1,-7.3,63,19,25.0,101.99,Mainly Clear
+2013-01-15 22:00:00,-1.4,-6.6,68,19,25.0,101.93,Clear
+2013-01-15 23:00:00,-1.5,-7.3,65,19,25.0,101.94,Mostly Cloudy
+2013-01-16 00:00:00,-1.7,-7.9,63,13,25.0,101.9,Cloudy
+2013-01-16 01:00:00,-2.3,-7.8,66,13,25.0,101.86,Cloudy
+2013-01-16 02:00:00,-2.4,-7.8,66,9,25.0,101.86,Mostly Cloudy
+2013-01-16 03:00:00,-2.8,-7.7,69,7,25.0,101.74,Cloudy
+2013-01-16 04:00:00,-3.2,-7.9,70,4,25.0,101.64,Cloudy
+2013-01-16 05:00:00,-3.2,-7.6,72,4,25.0,101.53,Cloudy
+2013-01-16 06:00:00,-2.9,-6.8,74,9,25.0,101.51,Cloudy
+2013-01-16 07:00:00,-2.6,-6.9,72,6,25.0,101.43,Mostly Cloudy
+2013-01-16 08:00:00,-2.4,-6.9,71,4,24.1,101.4,Mostly Cloudy
+2013-01-16 09:00:00,-2.5,-7.1,71,7,24.1,101.28,Mostly Cloudy
+2013-01-16 10:00:00,-1.5,-6.4,69,9,24.1,101.19,Cloudy
+2013-01-16 11:00:00,-1.0,-5.6,71,7,24.1,101.07,Cloudy
+2013-01-16 12:00:00,-0.6,-5.5,69,13,24.1,100.87,Cloudy
+2013-01-16 13:00:00,-0.5,-5.7,68,13,24.1,100.72,Mostly Cloudy
+2013-01-16 14:00:00,0.4,-6.6,59,9,24.1,100.57,Mainly Clear
+2013-01-16 15:00:00,0.2,-5.3,66,15,24.1,100.49,Mainly Clear
+2013-01-16 16:00:00,-0.7,-3.5,81,17,24.1,100.44,Mostly Cloudy
+2013-01-16 17:00:00,-1.3,-3.3,86,13,24.1,100.35,Mostly Cloudy
+2013-01-16 18:00:00,-0.8,-2.7,87,17,25.0,100.3,Cloudy
+2013-01-16 19:00:00,-0.8,-3.0,85,20,25.0,100.23,Cloudy
+2013-01-16 20:00:00,0.0,-3.0,80,19,25.0,100.23,Cloudy
+2013-01-16 21:00:00,0.1,-2.9,80,19,25.0,100.23,Mostly Cloudy
+2013-01-16 22:00:00,-0.1,-3.3,79,17,25.0,100.15,Mainly Clear
+2013-01-16 23:00:00,1.3,-3.3,71,26,25.0,100.16,Cloudy
+2013-01-17 00:00:00,1.3,-2.9,74,26,25.0,100.15,Cloudy
+2013-01-17 01:00:00,1.7,-3.5,68,33,25.0,100.16,Cloudy
+2013-01-17 02:00:00,1.5,-3.4,70,37,25.0,100.19,Snow Showers
+2013-01-17 03:00:00,-0.4,-1.4,93,32,4.0,100.24,Snow
+2013-01-17 04:00:00,-0.3,-1.3,93,33,4.8,100.23,Snow
+2013-01-17 05:00:00,0.6,-1.5,86,35,16.1,100.27,Snow
+2013-01-17 06:00:00,-2.8,-5.8,80,33,12.9,100.47,Snow
+2013-01-17 07:00:00,-4.1,-10.9,59,24,25.0,100.66,Snow
+2013-01-17 08:00:00,-7.2,-14.8,55,30,24.1,100.93,Mostly Cloudy
+2013-01-17 09:00:00,-10.9,-19.6,49,28,24.1,101.28,Mainly Clear
+2013-01-17 10:00:00,-12.3,-20.9,49,28,24.1,101.52,Mainly Clear
+2013-01-17 11:00:00,-13.1,-22.6,45,28,24.1,101.65,Mainly Clear
+2013-01-17 12:00:00,-13.4,-23.4,43,22,24.1,101.7,Mainly Clear
+2013-01-17 13:00:00,-13.4,-23.9,41,17,24.1,101.72,Mainly Clear
+2013-01-17 14:00:00,-13.1,-25.0,36,20,24.1,101.76,Mainly Clear
+2013-01-17 15:00:00,-13.1,-24.9,36,19,24.1,101.76,Mainly Clear
+2013-01-17 16:00:00,-13.7,-25.5,36,15,24.1,101.8,Mainly Clear
+2013-01-17 17:00:00,-14.8,-27.0,35,19,24.1,101.8,Mainly Clear
+2013-01-17 18:00:00,-14.7,-26.4,36,13,25.0,101.88,Mainly Clear
+2013-01-17 19:00:00,-15.8,-25.3,44,19,25.0,101.91,Mainly Clear
+2013-01-17 20:00:00,-16.3,-25.7,44,11,25.0,102.02,Clear
+2013-01-17 21:00:00,-17.3,-25.4,49,13,25.0,102.02,Mostly Cloudy
+2013-01-17 22:00:00,-17.1,-26.6,43,11,25.0,101.97,Mainly Clear
+2013-01-17 23:00:00,-18.2,-28.0,42,11,25.0,101.89,Mainly Clear
+2013-01-18 00:00:00,-18.7,-27.6,45,6,25.0,101.88,Clear
+2013-01-18 01:00:00,-18.6,-28.1,43,4,25.0,101.96,Clear
+2013-01-18 02:00:00,-19.3,-26.8,51,7,25.0,101.95,Clear
+2013-01-18 03:00:00,-19.8,-26.6,55,9,25.0,101.99,Clear
+2013-01-18 04:00:00,-20.2,-26.8,56,13,25.0,102.06,Clear
+2013-01-18 05:00:00,-20.6,-28.1,51,7,25.0,102.1,Clear
+2013-01-18 06:00:00,-20.7,-27.5,54,6,25.0,102.18,Clear
+2013-01-18 07:00:00,-20.9,-26.6,60,4,24.1,102.24,Clear
+2013-01-18 08:00:00,-18.9,-27.5,47,7,48.3,102.3,Clear
+2013-01-18 09:00:00,-17.6,-26.9,44,17,24.1,102.35,Mainly Clear
+2013-01-18 10:00:00,-16.1,-26.7,40,20,48.3,102.39,Clear
+2013-01-18 11:00:00,-14.8,-24.7,43,26,48.3,102.37,Clear
+2013-01-18 12:00:00,-14.3,-23.9,44,28,48.3,102.32,Clear
+2013-01-18 13:00:00,-13.6,-23.7,42,28,48.3,102.33,Clear
+2013-01-18 14:00:00,-13.1,-23.5,41,24,48.3,102.34,Clear
+2013-01-18 15:00:00,-12.2,-23.3,39,24,48.3,102.27,Mainly Clear
+2013-01-18 16:00:00,-12.1,-23.5,38,20,48.3,102.28,Mainly Clear
+2013-01-18 17:00:00,-11.9,-22.5,41,15,48.3,102.24,Mainly Clear
+2013-01-18 18:00:00,-11.9,-21.7,44,6,25.0,102.16,Mostly Cloudy
+2013-01-18 19:00:00,-11.7,-21.1,46,4,25.0,102.15,Mostly Cloudy
+2013-01-18 20:00:00,-10.6,-18.4,53,7,25.0,102.1,Mostly Cloudy
+2013-01-18 21:00:00,-9.8,-17.0,56,17,25.0,102.03,Snow
+2013-01-18 22:00:00,-9.4,-15.0,64,20,25.0,101.91,Snow
+2013-01-18 23:00:00,-8.5,-14.3,63,19,25.0,101.76,Snow
+2013-01-19 00:00:00,-7.5,-13.4,63,22,25.0,101.65,Snow
+2013-01-19 01:00:00,-7.4,-10.7,77,26,25.0,101.52,Snow
+2013-01-19 02:00:00,-7.5,-9.4,86,24,4.0,101.41,Snow
+2013-01-19 03:00:00,-7.2,-8.7,89,26,2.4,101.31,Snow
+2013-01-19 04:00:00,-6.8,-8.3,89,28,3.2,101.15,Snow
+2013-01-19 05:00:00,-6.5,-7.9,90,20,2.0,101.04,Snow
+2013-01-19 06:00:00,-6.1,-7.4,90,20,2.0,100.95,Snow
+2013-01-19 07:00:00,-5.4,-6.5,92,19,2.0,100.89,Snow
+2013-01-19 08:00:00,-4.6,-5.6,93,20,2.0,100.85,Snow
+2013-01-19 09:00:00,-4.1,-5.2,92,17,1.6,100.83,Snow
+2013-01-19 10:00:00,-3.4,-4.3,93,15,1.2,100.82,Snow
+2013-01-19 11:00:00,-2.1,-2.8,95,19,1.2,100.76,Snow
+2013-01-19 12:00:00,-2.5,-3.2,95,20,1.0,100.68,Snow
+2013-01-19 13:00:00,-2.4,-3.0,96,13,1.0,100.62,Snow
+2013-01-19 14:00:00,-1.8,-2.6,94,15,12.9,100.61,Snow
+2013-01-19 15:00:00,-1.0,-2.0,93,15,12.9,100.61,"Freezing Drizzle,Snow"
+2013-01-19 16:00:00,-0.8,-2.6,88,4,24.1,100.59,Snow
+2013-01-19 17:00:00,0.3,-2.6,81,9,25.0,100.57,Cloudy
+2013-01-19 18:00:00,-3.4,-4.6,91,9,6.4,100.6,Snow
+2013-01-19 19:00:00,-3.0,-4.1,92,9,6.4,100.59,"Snow,Ice Pellets"
+2013-01-19 20:00:00,-1.5,-2.4,94,11,6.4,100.52,Snow
+2013-01-19 21:00:00,0.6,-0.3,94,9,6.4,100.42,"Rain,Snow,Fog"
+2013-01-19 22:00:00,-0.7,-2.1,90,11,2.8,100.28,"Snow,Fog"
+2013-01-19 23:00:00,-3.1,-3.9,94,13,1.6,100.13,"Snow,Fog"
+2013-01-20 00:00:00,0.3,-0.4,95,7,8.0,99.91,"Snow,Fog"
+2013-01-20 01:00:00,1.0,-0.6,89,13,16.1,99.72,"Rain,Snow"
+2013-01-20 02:00:00,1.3,-0.6,87,15,25.0,99.66,Rain
+2013-01-20 03:00:00,1.7,-0.5,85,17,25.0,99.47,Cloudy
+2013-01-20 04:00:00,2.1,-1.2,79,20,25.0,99.19,Cloudy
+2013-01-20 05:00:00,2.8,-1.7,72,30,25.0,98.97,Cloudy
+2013-01-20 06:00:00,3.1,-1.9,70,32,25.0,98.73,Cloudy
+2013-01-20 07:00:00,3.3,-2.1,68,30,25.0,98.61,Mostly Cloudy
+2013-01-20 08:00:00,3.1,0.2,81,57,24.1,98.84,"Thunderstorms,Rain Showers"
+2013-01-20 09:00:00,2.5,-1.0,78,48,24.1,98.88,Cloudy
+2013-01-20 10:00:00,2.6,-1.6,74,46,24.1,98.98,Mostly Cloudy
+2013-01-20 11:00:00,-0.4,-1.5,92,35,1.2,99.09,Snow Showers
+2013-01-20 12:00:00,0.4,-2.2,83,50,19.3,99.17,Snow Showers
+2013-01-20 13:00:00,-1.4,-2.5,92,43,0.8,99.31,"Snow Showers,Blowing Snow"
+2013-01-20 14:00:00,-3.2,-6.2,80,50,3.2,99.62,"Snow Showers,Blowing Snow"
+2013-01-20 15:00:00,-5.6,-10.6,68,43,24.1,99.87,Mainly Clear
+2013-01-20 16:00:00,-8.0,-14.1,61,41,24.1,100.22,Mainly Clear
+2013-01-20 17:00:00,-9.4,-15.9,59,35,24.1,100.46,Clear
+2013-01-20 18:00:00,-10.5,-17.1,58,35,25.0,100.61,Clear
+2013-01-20 19:00:00,-11.5,-17.7,60,35,25.0,100.73,Clear
+2013-01-20 20:00:00,-12.5,-18.6,60,37,25.0,100.83,Clear
+2013-01-20 21:00:00,-13.4,-19.1,62,35,25.0,100.93,Clear
+2013-01-20 22:00:00,-14.1,-19.8,62,35,25.0,101.03,Clear
+2013-01-20 23:00:00,-14.8,-20.5,62,33,25.0,101.11,Clear
+2013-01-21 00:00:00,-15.2,-20.8,62,30,25.0,101.17,Clear
+2013-01-21 01:00:00,-15.9,-21.4,63,20,25.0,101.23,Clear
+2013-01-21 02:00:00,-16.6,-21.7,65,22,25.0,101.26,Clear
+2013-01-21 03:00:00,-17.0,-23.5,57,24,25.0,101.3,Clear
+2013-01-21 04:00:00,-17.4,-23.6,58,19,25.0,101.32,Clear
+2013-01-21 05:00:00,-17.7,-23.2,62,11,25.0,101.35,Clear
+2013-01-21 06:00:00,-18.7,-24.2,62,11,25.0,101.36,Clear
+2013-01-21 07:00:00,-19.3,-24.7,62,17,25.0,101.38,Mainly Clear
+2013-01-21 08:00:00,-19.6,-25.6,59,17,24.1,101.45,Mainly Clear
+2013-01-21 09:00:00,-19.2,-25.8,56,13,24.1,101.49,Mainly Clear
+2013-01-21 10:00:00,-18.8,-26.0,53,15,24.1,101.52,Mostly Cloudy
+2013-01-21 11:00:00,-18.1,-25.2,54,7,48.3,101.48,Mostly Cloudy
+2013-01-21 12:00:00,-17.5,-25.6,49,13,48.3,101.38,Mostly Cloudy
+2013-01-21 13:00:00,-17.0,-25.5,48,13,48.3,101.29,Cloudy
+2013-01-21 14:00:00,-16.4,-25.5,45,6,48.3,101.22,Cloudy
+2013-01-21 15:00:00,-15.9,-25.5,43,4,48.3,101.19,Cloudy
+2013-01-21 16:00:00,-15.9,-25.3,44,4,48.3,101.16,Mostly Cloudy
+2013-01-21 17:00:00,-16.3,-24.3,50,6,25.0,101.13,Cloudy
+2013-01-21 18:00:00,-16.5,-24.2,51,6,25.0,101.14,Cloudy
+2013-01-21 19:00:00,-16.0,-24.5,48,7,25.0,101.11,Cloudy
+2013-01-21 20:00:00,-16.1,-22.7,57,9,25.0,101.09,Cloudy
+2013-01-21 21:00:00,-15.9,-21.6,62,9,25.0,101.08,Snow Showers
+2013-01-21 22:00:00,-16.5,-21.3,66,19,25.0,101.03,Mostly Cloudy
+2013-01-21 23:00:00,-16.8,-22.5,61,17,25.0,100.96,Cloudy
+2013-01-22 00:00:00,-16.6,-23.2,57,15,25.0,100.85,Mostly Cloudy
+2013-01-22 01:00:00,-16.9,-23.3,58,13,25.0,100.76,Mostly Cloudy
+2013-01-22 02:00:00,-18.1,-22.8,67,17,25.0,100.77,Mainly Clear
+2013-01-22 03:00:00,-19.0,-23.6,67,17,25.0,100.76,Mainly Clear
+2013-01-22 04:00:00,-19.6,-23.7,70,17,25.0,100.8,Mostly Cloudy
+2013-01-22 05:00:00,-19.4,-24.2,66,20,25.0,100.8,Cloudy
+2013-01-22 06:00:00,-19.5,-25.4,59,19,25.0,100.87,Snow
+2013-01-22 07:00:00,-19.9,-24.9,64,20,2.4,100.94,Snow
+2013-01-22 08:00:00,-19.7,-25.0,63,15,4.0,100.98,Snow
+2013-01-22 09:00:00,-19.2,-24.6,62,15,19.3,101.02,Mostly Cloudy
+2013-01-22 10:00:00,-18.6,-24.0,62,11,24.1,101.08,Snow
+2013-01-22 11:00:00,-18.1,-23.3,64,11,24.1,101.05,Mostly Cloudy
+2013-01-22 12:00:00,-17.4,-23.3,60,6,24.1,101.03,Cloudy
+2013-01-22 13:00:00,-16.8,-22.7,60,6,12.9,101.0,Snow Showers
+2013-01-22 14:00:00,-15.9,-22.2,58,17,24.1,101.03,Mostly Cloudy
+2013-01-22 15:00:00,-16.2,-22.4,59,20,24.1,101.1,Mostly Cloudy
+2013-01-22 16:00:00,-15.8,-23.1,53,30,24.1,101.13,Mainly Clear
+2013-01-22 17:00:00,-16.1,-23.2,54,32,24.1,101.22,Mostly Cloudy
+2013-01-22 18:00:00,-17.2,-25.3,49,20,25.0,101.33,Mainly Clear
+2013-01-22 19:00:00,-18.2,-26.8,47,30,25.0,101.43,Mostly Cloudy
+2013-01-22 20:00:00,-19.2,-27.3,49,15,25.0,101.46,Mainly Clear
+2013-01-22 21:00:00,-20.3,-27.5,53,7,25.0,101.48,Mainly Clear
+2013-01-22 22:00:00,-21.2,-27.9,55,13,25.0,101.54,Clear
+2013-01-22 23:00:00,-20.9,-27.8,54,15,25.0,101.6,Mainly Clear
+2013-01-23 00:00:00,-22.0,-29.1,53,24,25.0,101.63,Clear
+2013-01-23 01:00:00,-23.1,-30.0,53,22,25.0,101.65,Clear
+2013-01-23 02:00:00,-23.8,-30.5,54,15,25.0,101.72,Clear
+2013-01-23 03:00:00,-24.5,-30.7,56,20,25.0,101.74,Clear
+2013-01-23 04:00:00,-25.2,-31.6,55,19,25.0,101.75,Clear
+2013-01-23 05:00:00,-25.9,-32.7,53,22,25.0,101.78,Clear
+2013-01-23 06:00:00,-26.5,-33.2,53,13,25.0,101.85,Clear
+2013-01-23 07:00:00,-26.8,-33.3,54,13,24.1,101.89,Clear
+2013-01-23 08:00:00,-27.1,-33.9,52,15,24.1,101.95,Clear
+2013-01-23 09:00:00,-26.8,-34.1,50,19,24.1,102.01,Clear
+2013-01-23 10:00:00,-26.2,-33.7,49,24,24.1,102.05,Clear
+2013-01-23 11:00:00,-25.6,-33.2,49,20,24.1,102.02,Clear
+2013-01-23 12:00:00,-24.4,-32.6,47,26,24.1,101.96,Clear
+2013-01-23 13:00:00,-23.7,-32.6,44,30,24.1,101.89,Clear
+2013-01-23 14:00:00,-23.3,-32.6,42,24,24.1,101.88,Clear
+2013-01-23 15:00:00,-22.8,-32.2,42,22,24.1,101.87,Mainly Clear
+2013-01-23 16:00:00,-22.8,-32.6,40,22,24.1,101.88,Mainly Clear
+2013-01-23 17:00:00,-23.2,-32.3,43,20,48.3,101.88,Mainly Clear
+2013-01-23 18:00:00,-23.5,-32.3,44,17,25.0,101.9,Mainly Clear
+2013-01-23 19:00:00,-23.5,-31.9,46,19,25.0,101.92,Clear
+2013-01-23 20:00:00,-23.8,-32.1,46,15,25.0,101.9,Clear
+2013-01-23 21:00:00,-23.8,-32.2,46,17,25.0,101.88,Clear
+2013-01-23 22:00:00,-24.0,-31.5,50,17,25.0,101.84,Clear
+2013-01-23 23:00:00,-24.0,-32.0,48,13,25.0,101.85,Clear
+2013-01-24 00:00:00,-24.5,-31.9,50,13,25.0,101.83,Clear
+2013-01-24 01:00:00,-24.1,-31.8,49,13,25.0,101.8,Mainly Clear
+2013-01-24 02:00:00,-23.5,-31.6,47,17,25.0,101.82,Mostly Cloudy
+2013-01-24 03:00:00,-23.4,-31.2,49,20,25.0,101.81,Mostly Cloudy
+2013-01-24 04:00:00,-23.3,-30.9,50,22,25.0,101.79,Mostly Cloudy
+2013-01-24 05:00:00,-23.0,-30.4,51,24,25.0,101.79,Cloudy
+2013-01-24 06:00:00,-23.2,-30.7,50,22,25.0,101.82,Cloudy
+2013-01-24 07:00:00,-23.5,-30.9,51,26,24.1,101.86,Mostly Cloudy
+2013-01-24 08:00:00,-23.5,-30.6,52,24,48.3,101.97,Mostly Cloudy
+2013-01-24 09:00:00,-23.0,-30.4,51,28,24.1,102.01,Mostly Cloudy
+2013-01-24 10:00:00,-22.0,-29.8,49,28,24.1,102.04,Cloudy
+2013-01-24 11:00:00,-21.3,-29.1,49,35,48.3,101.98,Mostly Cloudy
+2013-01-24 12:00:00,-21.1,-28.8,50,32,48.3,101.95,Cloudy
+2013-01-24 13:00:00,-20.3,-28.0,50,33,48.3,101.89,Cloudy
+2013-01-24 14:00:00,-19.1,-27.1,49,39,48.3,101.88,Mostly Cloudy
+2013-01-24 15:00:00,-18.4,-26.8,48,35,48.3,101.97,Mostly Cloudy
+2013-01-24 16:00:00,-17.7,-26.6,46,41,48.3,102.02,Mostly Cloudy
+2013-01-24 17:00:00,-17.8,-26.3,47,28,48.3,102.08,Mostly Cloudy
+2013-01-24 18:00:00,-18.5,-26.5,49,28,25.0,102.2,Mostly Cloudy
+2013-01-24 19:00:00,-18.5,-26.6,49,33,25.0,102.28,Mostly Cloudy
+2013-01-24 20:00:00,-18.1,-25.8,51,32,25.0,102.32,Mostly Cloudy
+2013-01-24 21:00:00,-17.3,-25.2,50,32,25.0,102.34,Mostly Cloudy
+2013-01-24 22:00:00,-17.6,-25.2,51,28,25.0,102.4,Mostly Cloudy
+2013-01-24 23:00:00,-17.8,-24.9,54,30,25.0,102.44,Mostly Cloudy
+2013-01-25 00:00:00,-18.4,-25.5,54,30,25.0,102.46,Mostly Cloudy
+2013-01-25 01:00:00,-17.2,-18.9,87,22,25.0,102.46,Mainly Clear
+2013-01-25 02:00:00,-19.3,-26.0,55,15,25.0,102.48,Mainly Clear
+2013-01-25 03:00:00,-19.5,-26.0,56,19,25.0,102.48,Mainly Clear
+2013-01-25 04:00:00,-20.0,-25.9,59,17,25.0,102.5,Clear
+2013-01-25 05:00:00,-20.4,-26.2,60,22,25.0,102.48,Clear
+2013-01-25 06:00:00,-20.6,-26.4,60,20,25.0,102.48,Mainly Clear
+2013-01-25 07:00:00,-20.6,-26.4,60,22,25.0,102.46,Mainly Clear
+2013-01-25 08:00:00,-20.7,-26.3,61,22,24.1,102.49,Mostly Cloudy
+2013-01-25 09:00:00,-19.7,-25.8,58,28,24.1,102.49,Mostly Cloudy
+2013-01-25 10:00:00,-19.1,-25.6,56,24,48.3,102.48,Mostly Cloudy
+2013-01-25 11:00:00,-17.9,-24.5,56,20,48.3,102.38,Cloudy
+2013-01-25 12:00:00,-16.9,-24.6,51,15,48.3,102.27,Cloudy
+2013-01-25 13:00:00,-16.0,-23.5,52,19,48.3,102.11,Cloudy
+2013-01-25 14:00:00,-15.3,-23.6,49,17,48.3,101.99,Cloudy
+2013-01-25 15:00:00,-15.1,-22.8,52,15,48.3,101.96,Cloudy
+2013-01-25 16:00:00,-15.2,-23.6,49,20,48.3,101.96,Cloudy
+2013-01-25 17:00:00,-15.1,-23.0,51,9,48.3,101.9,Cloudy
+2013-01-25 18:00:00,-14.9,-23.2,49,9,25.0,101.84,Cloudy
+2013-01-25 19:00:00,-15.3,-22.7,53,9,25.0,101.82,Cloudy
+2013-01-25 20:00:00,-15.6,-23.3,52,9,25.0,101.78,Cloudy
+2013-01-25 21:00:00,-15.7,-23.1,53,13,25.0,101.73,Cloudy
+2013-01-25 22:00:00,-15.9,-22.6,56,9,25.0,101.68,Cloudy
+2013-01-25 23:00:00,-16.0,-22.7,56,6,25.0,101.68,Mainly Clear
+2013-01-26 00:00:00,-16.6,-22.9,58,4,25.0,101.68,Mainly Clear
+2013-01-26 01:00:00,-18.7,-23.6,65,6,25.0,101.66,Mainly Clear
+2013-01-26 02:00:00,-18.4,-23.2,66,4,25.0,101.68,Mainly Clear
+2013-01-26 03:00:00,-18.2,-23.8,61,7,25.0,101.67,Clear
+2013-01-26 04:00:00,-20.1,-24.5,68,6,25.0,101.71,Mainly Clear
+2013-01-26 05:00:00,-20.8,-24.8,70,6,25.0,101.72,Mainly Clear
+2013-01-26 06:00:00,-20.7,-24.6,71,7,25.0,101.76,Mainly Clear
+2013-01-26 07:00:00,-20.5,-24.4,71,4,25.0,101.81,Mainly Clear
+2013-01-26 08:00:00,-20.5,-24.6,70,6,24.1,101.87,Mostly Cloudy
+2013-01-26 09:00:00,-18.8,-23.6,66,4,48.3,101.89,Mostly Cloudy
+2013-01-26 10:00:00,-15.0,-22.1,55,4,48.3,101.93,Cloudy
+2013-01-26 11:00:00,-14.2,-20.7,58,7,48.3,101.95,Cloudy
+2013-01-26 12:00:00,-13.4,-21.5,51,11,48.3,101.89,Cloudy
+2013-01-26 13:00:00,-12.7,-21.5,48,17,48.3,101.87,Cloudy
+2013-01-26 14:00:00,-12.6,-21.0,49,17,48.3,101.89,Cloudy
+2013-01-26 15:00:00,-11.7,-19.3,53,24,48.3,101.91,Cloudy
+2013-01-26 16:00:00,-11.5,-18.9,54,26,48.3,101.92,Cloudy
+2013-01-26 17:00:00,-12.0,-19.0,56,22,25.0,101.96,Mainly Clear
+2013-01-26 18:00:00,-12.5,-18.5,61,15,25.0,102.04,Mostly Cloudy
+2013-01-26 19:00:00,-13.1,-18.7,63,13,25.0,102.06,Mainly Clear
+2013-01-26 20:00:00,-13.4,-19.0,63,15,25.0,102.1,Clear
+2013-01-26 21:00:00,-13.7,-19.3,63,15,25.0,102.13,Clear
+2013-01-26 22:00:00,-14.3,-19.3,66,13,25.0,102.18,Clear
+2013-01-26 23:00:00,-14.1,-19.0,66,13,25.0,102.23,Clear
+2013-01-27 00:00:00,-15.3,-20.0,67,13,25.0,102.29,Clear
+2013-01-27 01:00:00,-16.5,-20.8,69,9,25.0,102.33,Clear
+2013-01-27 02:00:00,-15.8,-20.8,65,11,25.0,102.41,Clear
+2013-01-27 03:00:00,-16.5,-21.8,64,13,25.0,102.49,Clear
+2013-01-27 04:00:00,-17.4,-22.3,66,11,25.0,102.53,Clear
+2013-01-27 05:00:00,-17.3,-22.6,63,13,25.0,102.61,Mainly Clear
+2013-01-27 06:00:00,-17.5,-22.8,63,13,25.0,102.71,Mainly Clear
+2013-01-27 07:00:00,-17.7,-23.6,60,15,25.0,102.8,Clear
+2013-01-27 08:00:00,-18.1,-24.1,59,11,24.1,102.84,Mainly Clear
+2013-01-27 09:00:00,-17.1,-23.6,57,19,48.3,102.95,Mainly Clear
+2013-01-27 10:00:00,-15.8,-22.9,54,15,48.3,102.99,Clear
+2013-01-27 11:00:00,-14.6,-22.2,52,13,48.3,103.03,Clear
+2013-01-27 12:00:00,-13.4,-21.5,51,13,48.3,102.97,Clear
+2013-01-27 13:00:00,-12.8,-21.2,49,11,48.3,102.92,Clear
+2013-01-27 14:00:00,-12.1,-21.0,47,19,48.3,102.88,Clear
+2013-01-27 15:00:00,-11.2,-20.7,45,19,48.3,102.89,Clear
+2013-01-27 16:00:00,-11.3,-20.6,46,15,48.3,102.87,Clear
+2013-01-27 17:00:00,-12.0,-21.6,45,19,48.3,102.93,Clear
+2013-01-27 18:00:00,-12.6,-21.6,47,19,25.0,102.96,Mainly Clear
+2013-01-27 19:00:00,-13.0,-21.3,50,13,25.0,102.92,Mainly Clear
+2013-01-27 20:00:00,-13.4,-21.3,51,7,25.0,102.89,Mainly Clear
+2013-01-27 21:00:00,-13.9,-21.5,53,0,25.0,102.83,Mainly Clear
+2013-01-27 22:00:00,-14.6,-21.3,57,4,25.0,102.79,Mainly Clear
+2013-01-27 23:00:00,-14.6,-20.8,59,6,25.0,102.82,Mainly Clear
+2013-01-28 00:00:00,-14.0,-20.5,58,6,25.0,102.78,Mostly Cloudy
+2013-01-28 01:00:00,-13.6,-20.4,56,6,25.0,102.71,Mainly Clear
+2013-01-28 02:00:00,-14.0,-19.8,61,4,25.0,102.71,Mainly Clear
+2013-01-28 03:00:00,-12.5,-17.7,65,7,25.0,102.62,Mainly Clear
+2013-01-28 04:00:00,-12.8,-17.1,70,6,25.0,102.53,Mostly Cloudy
+2013-01-28 05:00:00,-11.6,-17.2,63,7,25.0,102.51,Mostly Cloudy
+2013-01-28 06:00:00,-11.6,-16.5,67,9,25.0,102.47,Mostly Cloudy
+2013-01-28 07:00:00,-11.2,-16.2,67,9,24.1,102.41,Cloudy
+2013-01-28 08:00:00,-10.4,-15.0,69,9,24.1,102.35,Cloudy
+2013-01-28 09:00:00,-9.8,-13.9,72,13,24.1,102.22,Cloudy
+2013-01-28 10:00:00,-9.0,-14.1,66,13,24.1,102.11,Cloudy
+2013-01-28 11:00:00,-8.0,-13.9,62,13,19.3,102.03,Cloudy
+2013-01-28 12:00:00,-7.2,-11.3,72,15,6.4,101.84,Snow
+2013-01-28 13:00:00,-6.9,-9.4,82,11,2.8,101.7,Snow
+2013-01-28 14:00:00,-6.6,-8.3,88,15,1.6,101.57,Snow
+2013-01-28 15:00:00,-6.6,-8.4,87,17,2.8,101.44,Snow
+2013-01-28 16:00:00,-7.2,-9.1,86,24,2.0,101.37,Snow
+2013-01-28 17:00:00,-8.3,-10.2,86,28,1.6,101.32,Snow
+2013-01-28 18:00:00,-8.4,-10.7,83,24,8.0,101.29,Snow
+2013-01-28 19:00:00,-8.3,-10.3,85,22,3.2,101.27,Snow
+2013-01-28 20:00:00,-8.6,-10.4,87,28,2.0,101.25,Snow
+2013-01-28 21:00:00,-9.1,-11.0,86,24,4.8,101.27,Snow
+2013-01-28 22:00:00,-9.0,-11.5,82,20,8.0,101.26,Snow
+2013-01-28 23:00:00,-9.1,-12.9,74,22,25.0,101.26,Mostly Cloudy
+2013-01-29 00:00:00,-9.0,-14.0,67,20,25.0,101.35,Cloudy
+2013-01-29 01:00:00,-9.5,-14.8,65,17,25.0,101.35,Mostly Cloudy
+2013-01-29 02:00:00,-10.7,-15.7,67,13,25.0,101.41,Mainly Clear
+2013-01-29 03:00:00,-10.8,-16.1,65,13,25.0,101.49,Mainly Clear
+2013-01-29 04:00:00,-10.8,-16.3,64,17,25.0,101.54,Mainly Clear
+2013-01-29 05:00:00,-9.8,-15.6,63,7,25.0,101.51,Mainly Clear
+2013-01-29 06:00:00,-9.0,-14.8,63,4,25.0,101.55,Cloudy
+2013-01-29 07:00:00,-9.7,-14.2,70,7,24.1,101.55,Cloudy
+2013-01-29 08:00:00,-9.0,-13.7,69,9,24.1,101.71,Cloudy
+2013-01-29 09:00:00,-8.9,-14.3,65,11,24.1,101.81,Cloudy
+2013-01-29 10:00:00,-7.6,-12.8,66,13,24.1,101.77,Cloudy
+2013-01-29 11:00:00,-5.5,-10.4,68,13,19.3,101.71,Cloudy
+2013-01-29 12:00:00,-4.9,-8.9,73,9,24.1,101.67,Cloudy
+2013-01-29 13:00:00,-4.6,-8.8,72,9,24.1,101.54,Cloudy
+2013-01-29 14:00:00,-4.0,-8.1,73,17,24.1,101.38,Cloudy
+2013-01-29 15:00:00,-3.5,-7.7,73,17,24.1,101.41,Cloudy
+2013-01-29 16:00:00,-3.2,-7.9,70,15,19.3,101.38,Cloudy
+2013-01-29 17:00:00,-2.6,-6.6,74,19,19.3,101.25,Cloudy
+2013-01-29 18:00:00,-2.1,-6.0,75,15,25.0,101.21,Cloudy
+2013-01-29 19:00:00,-2.1,-6.0,75,20,25.0,101.08,Cloudy
+2013-01-29 20:00:00,-2.3,-6.0,76,15,25.0,100.99,Cloudy
+2013-01-29 21:00:00,-1.4,-5.0,76,15,6.4,100.92,Freezing Drizzle
+2013-01-29 22:00:00,-1.5,-3.0,89,13,3.2,100.77,Freezing Rain
+2013-01-29 23:00:00,-0.3,-1.2,94,9,2.0,100.64,Freezing Rain
+2013-01-30 00:00:00,1.6,0.7,94,6,4.8,100.57,"Rain,Fog"
+2013-01-30 01:00:00,1.7,1.0,95,6,2.4,100.46,"Rain,Fog"
+2013-01-30 02:00:00,1.8,1.2,96,11,8.0,100.34,"Rain,Fog"
+2013-01-30 03:00:00,2.4,1.4,93,20,6.4,100.19,"Rain,Fog"
+2013-01-30 04:00:00,2.4,1.3,92,32,12.9,99.99,Cloudy
+2013-01-30 05:00:00,2.6,1.3,91,28,16.1,99.83,Mostly Cloudy
+2013-01-30 06:00:00,3.0,1.6,90,32,16.1,99.71,Rain Showers
+2013-01-30 07:00:00,3.1,2.0,92,33,16.1,99.59,Rain Showers
+2013-01-30 08:00:00,3.4,2.2,92,32,16.1,99.5,Cloudy
+2013-01-30 09:00:00,4.1,2.5,89,32,19.3,99.34,Cloudy
+2013-01-30 10:00:00,4.8,2.7,86,33,48.3,99.21,Cloudy
+2013-01-30 11:00:00,5.8,3.4,85,37,24.1,99.14,Cloudy
+2013-01-30 12:00:00,6.6,3.9,83,28,48.3,98.98,Cloudy
+2013-01-30 13:00:00,6.9,4.3,83,28,24.1,98.82,Cloudy
+2013-01-30 14:00:00,7.4,4.6,82,28,19.3,98.7,Rain Showers
+2013-01-30 15:00:00,7.4,5.5,88,28,24.1,98.64,Rain Showers
+2013-01-30 16:00:00,7.1,5.5,90,22,24.1,98.58,Rain Showers
+2013-01-30 17:00:00,6.2,4.7,90,6,24.1,98.83,Cloudy
+2013-01-30 18:00:00,6.3,4.9,91,13,25.0,98.71,Cloudy
+2013-01-30 19:00:00,5.4,4.0,91,13,25.0,98.8,Cloudy
+2013-01-30 20:00:00,6.4,5.3,93,7,25.0,98.75,Cloudy
+2013-01-30 21:00:00,5.5,4.7,95,11,16.1,98.66,Cloudy
+2013-01-30 22:00:00,4.9,4.6,98,13,9.7,98.5,Fog
+2013-01-30 23:00:00,5.9,5.7,99,9,3.2,98.36,Fog
+2013-01-31 00:00:00,6.1,5.9,99,17,8.0,98.29,Fog
+2013-01-31 01:00:00,6.1,5.9,99,19,8.0,98.14,"Rain,Fog"
+2013-01-31 02:00:00,7.6,7.2,97,20,9.7,97.94,"Rain,Fog"
+2013-01-31 03:00:00,7.3,7.1,99,9,2.4,97.68,"Rain,Fog"
+2013-01-31 04:00:00,8.0,7.7,98,24,9.7,97.35,"Rain,Fog"
+2013-01-31 05:00:00,8.8,8.1,95,33,11.3,97.13,Rain
+2013-01-31 06:00:00,8.3,7.7,96,30,6.4,97.07,"Rain,Fog"
+2013-01-31 07:00:00,6.5,4.7,88,50,11.3,97.18,Rain
+2013-01-31 08:00:00,4.2,2.1,86,54,24.1,97.4,Rain
+2013-01-31 09:00:00,3.6,0.8,82,44,24.1,97.4,Mostly Cloudy
+2013-01-31 10:00:00,3.5,-2.1,67,48,19.3,97.64,Cloudy
+2013-01-31 11:00:00,1.9,-6.0,56,63,48.3,97.81,Mostly Cloudy
+2013-01-31 12:00:00,1.5,-5.4,60,54,24.1,97.87,Cloudy
+2013-01-31 13:00:00,0.6,-6.7,58,50,24.1,98.0,Snow
+2013-01-31 14:00:00,-0.4,-8.6,54,69,24.1,98.13,Cloudy
+2013-01-31 15:00:00,-1.8,-7.2,67,39,24.1,98.41,Snow
+2013-01-31 16:00:00,-2.1,-10.5,53,50,19.3,98.51,Snow
+2013-01-31 17:00:00,-6.1,-9.6,76,54,2.0,98.7,Snow
+2013-01-31 18:00:00,-6.8,-14.8,53,43,25.0,98.9,Mostly Cloudy
+2013-01-31 19:00:00,-9.5,-18.1,50,52,25.0,99.21,Mostly Cloudy
+2013-01-31 20:00:00,-10.0,-17.6,54,39,25.0,99.31,Mainly Clear
+2013-01-31 21:00:00,-10.1,-17.7,54,37,25.0,99.42,Mainly Clear
+2013-01-31 22:00:00,-10.5,-17.6,56,33,25.0,99.49,Mainly Clear
+2013-01-31 23:00:00,-10.9,-18.2,55,35,25.0,99.56,Mainly Clear
 2012-02-01 00:00:00,-6.7,-9.7,79,19,11.3,100.82,Snow
 2012-02-01 01:00:00,-6.7,-9.5,80,15,9.7,100.69,Snow
 2012-02-01 02:00:00,-6.8,-9.3,82,19,4.8,100.61,Freezing Drizzle
diff --git a/requirements.txt b/requirements.txt
index 1b7639b50..749c61147 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,3 @@
-matplotlib==2.0.2
-numpy==1.13.1
-pandas==0.20.3
+matplotlib==2.2.3
+numpy==1.15.2
+pandas==0.23.4
diff --git a/runtime.txt b/runtime.txt
deleted file mode 100644
index 16e821432..000000000
--- a/runtime.txt
+++ /dev/null
@@ -1 +0,0 @@
-python-2.7