MTA Turnstile EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The MTA Turnstile EDA\n",
    "### By Sarah Alabdulwahab\n",
    "\n",
    "## Table of Contents\n",
    "<ul>\n",
    "<li><a href=\"#intro\">Introduction</a></li>\n",
    "<li><a href=\"#wrangling\">Data Wrangling</a></li>\n",
    "<li><a href=\"#eda\">Exploratory Data Analysis</a></li>\n",
    "<li><a href=\"#conclusions\">Conclusions</a></li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='intro'></a>\n",
    "## Introduction\n",
    "The Metropolitan Transportation Authority (MTA) is North America's largest transportation network, covering a 5,000-square-mile travel area surrounding New York City through Long Island, southeastern New York State, and Connecticut.\n",
    "\n",
    "\n",
    "The MTA is planning on adding more turnstiles to reduce the crowds of people in the busiest stations, therefore, my goal would be to find the best place to add them.\n",
    "\n",
    "\n",
    "For this project, I chose to gather the data of the past four months to find the busiest station."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sqlalchemy import create_engine\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='wrangling'></a>\n",
    "## Data Wrangling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The purpose of this section is to familarize myself with the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#collecting the data\n",
    "def get_data(dates):\n",
    "    url = \"http://web.mta.info/developers/data/nyct/turnstile/turnstile_{}.txt\"\n",
    "    dfs = []\n",
    "    for date in dates:\n",
    "        file_url = url.format(date)\n",
    "        dfs.append(pd.read_csv(file_url))\n",
    "    return pd.concat(dfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#the dates of (approx.) the past four months\n",
    "dates = [210605, 210612, 210619, 210626, \n",
    "         210703, 210710, 210717, 210724, \n",
    "         210731, 210807, 210814, 210821, \n",
    "         210828, 210904, 210911, 210918]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating the database -> empty\n",
    "engine = create_engine('sqlite:///C:/Users/Sarah/Desktop/SDAIA/MTA_turnstile.db', echo=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#filling the database\n",
    "sql.to_sql(get_data(dates), con=engine, name='MTA_turnstile',if_exists='replace',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-09-30 10:46:08,949 INFO sqlalchemy.engine.base.Engine SELECT CAST('test plain returns' AS VARCHAR(60)) AS anon_1\n",
      "2021-09-30 10:46:08,953 INFO sqlalchemy.engine.base.Engine ()\n",
      "2021-09-30 10:46:08,954 INFO sqlalchemy.engine.base.Engine SELECT CAST('test unicode returns' AS VARCHAR(60)) AS anon_1\n",
      "2021-09-30 10:46:08,955 INFO sqlalchemy.engine.base.Engine ()\n",
      "2021-09-30 10:46:08,956 INFO sqlalchemy.engine.base.Engine SELECT * FROM MTA_turnstile\n",
      "2021-09-30 10:46:08,957 INFO sqlalchemy.engine.base.Engine ()\n"
     ]
    }
   ],
   "source": [
    "#reading from the database\n",
    "turnstiles_df = pd.read_sql_query(\"SELECT * FROM MTA_turnstile\", engine);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C/A</th>\n",
       "      <th>UNIT</th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
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       "      <td>0</td>\n",
       "      <td>A002</td>\n",
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       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
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       "      <td>05/29/2021</td>\n",
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       "      <td>1</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>05/29/2021</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7578740</td>\n",
       "      <td>2590327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
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       "      <td>05/29/2021</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7578749</td>\n",
       "      <td>2590340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
       "      <td>BMT</td>\n",
       "      <td>05/29/2021</td>\n",
       "      <td>12:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7578789</td>\n",
       "      <td>2590386</td>\n",
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       "      <td>4</td>\n",
       "      <td>A002</td>\n",
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       "      <td>59 ST</td>\n",
       "      <td>NQR456W</td>\n",
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       "      <td>05/29/2021</td>\n",
       "      <td>16:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>7578897</td>\n",
       "      <td>2590418</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "    C/A  UNIT       SCP STATION LINENAME DIVISION        DATE      TIME  \\\n",
       "0  A002  R051  02-00-00   59 ST  NQR456W      BMT  05/29/2021  00:00:00   \n",
       "1  A002  R051  02-00-00   59 ST  NQR456W      BMT  05/29/2021  04:00:00   \n",
       "2  A002  R051  02-00-00   59 ST  NQR456W      BMT  05/29/2021  08:00:00   \n",
       "3  A002  R051  02-00-00   59 ST  NQR456W      BMT  05/29/2021  12:00:00   \n",
       "4  A002  R051  02-00-00   59 ST  NQR456W      BMT  05/29/2021  16:00:00   \n",
       "\n",
       "      DESC  ENTRIES  \\\n",
       "0  REGULAR  7578734   \n",
       "1  REGULAR  7578740   \n",
       "2  REGULAR  7578749   \n",
       "3  REGULAR  7578789   \n",
       "4  REGULAR  7578897   \n",
       "\n",
       "   EXITS                                                                 \n",
       "0                                            2590325                     \n",
       "1                                            2590327                     \n",
       "2                                            2590340                     \n",
       "3                                            2590386                     \n",
       "4                                            2590418                     "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "turnstiles_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3351726, 11)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#num of rows and columns\n",
    "turnstiles_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ENTRIES</th>\n",
       "      <th>EXITS</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>3.351726e+06</td>\n",
       "      <td>3.351726e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>4.159043e+07</td>\n",
       "      <td>3.325419e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>2.183052e+08</td>\n",
       "      <td>1.918333e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>2.186650e+05</td>\n",
       "      <td>1.006620e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>1.402711e+06</td>\n",
       "      <td>8.538525e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>6.010322e+06</td>\n",
       "      <td>3.970752e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
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      "text/plain": [
       "            ENTRIES  \\\n",
       "count  3.351726e+06   \n",
       "mean   4.159043e+07   \n",
       "std    2.183052e+08   \n",
       "min    0.000000e+00   \n",
       "25%    2.186650e+05   \n",
       "50%    1.402711e+06   \n",
       "75%    6.010322e+06   \n",
       "max    2.147417e+09   \n",
       "\n",
       "       EXITS                                                                 \n",
       "count                                       3.351726e+06                     \n",
       "mean                                        3.325419e+07                     \n",
       "std                                         1.918333e+08                     \n",
       "min                                         0.000000e+00                     \n",
       "25%                                         1.006620e+05                     \n",
       "50%                                         8.538525e+05                     \n",
       "75%                                         3.970752e+06                     \n",
       "max                                         2.133797e+09                     "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#descriptive statistics\n",
    "turnstiles_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3351726 entries, 0 to 3351725\n",
      "Data columns (total 11 columns):\n",
      "C/A                                                                     object\n",
      "UNIT                                                                    object\n",
      "SCP                                                                     object\n",
      "STATION                                                                 object\n",
      "LINENAME                                                                object\n",
      "DIVISION                                                                object\n",
      "DATE                                                                    object\n",
      "TIME                                                                    object\n",
      "DESC                                                                    object\n",
      "ENTRIES                                                                 int64\n",
      "EXITS                                                                   int64\n",
      "dtypes: int64(2), object(9)\n",
      "memory usage: 281.3+ MB\n"
     ]
    }
   ],
   "source": [
    "#summary of data\n",
    "turnstiles_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "C/A                                                                     0\n",
       "UNIT                                                                    0\n",
       "SCP                                                                     0\n",
       "STATION                                                                 0\n",
       "LINENAME                                                                0\n",
       "DIVISION                                                                0\n",
       "DATE                                                                    0\n",
       "TIME                                                                    0\n",
       "DESC                                                                    0\n",
       "ENTRIES                                                                 0\n",
       "EXITS                                                                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for null values\n",
    "turnstiles_df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C/A', 'UNIT', 'SCP', 'STATION', 'LINENAME', 'DIVISION', 'DATE', 'TIME',\n",
       "       'DESC', 'ENTRIES', 'EXITS'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the column names -> without white spaces\n",
    "turnstiles_df.columns = turnstiles_df.columns.str.strip()\n",
    "turnstiles_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "379"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of stations\n",
    "turnstiles_df.STATION.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "05/29/2021    29939\n",
       "05/30/2021    29812\n",
       "05/31/2021    29997\n",
       "06/01/2021    29889\n",
       "06/02/2021    29870\n",
       "              ...  \n",
       "09/13/2021    30103\n",
       "09/14/2021    30292\n",
       "09/15/2021    29833\n",
       "09/16/2021    29928\n",
       "09/17/2021    29884\n",
       "Name: DATE, Length: 112, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#four months of data\n",
    "turnstiles_df.DATE.value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning & Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#convert the DATE to datetime \n",
    "turnstiles_df[\"DATE\"] = pd.to_datetime(turnstiles_df.DATE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "112"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#looking for duplicated rows\n",
    "turnstiles_df[['C/A','UNIT', 'SCP', 'STATION', 'DATE', 'TIME']].duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dropping duplicates\n",
    "turnstiles_df.drop_duplicates(subset=['C/A','UNIT', 'SCP', 'STATION', 'DATE', 'TIME'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "vUMhPFNhG36X"
   },
   "outputs": [],
   "source": [
    "#drop DESC & DIVISION columns because i will not be needing them for my analysis\n",
    "turnstiles_df.drop(['DESC', 'DIVISION','LINENAME', 'TIME'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#reset index after dropping\n",
    "turnstiles_df.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <td>A002</td>\n",
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       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-05-29</td>\n",
       "      <td>7578789</td>\n",
       "      <td>2590386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-05-29</td>\n",
       "      <td>7578897</td>\n",
       "      <td>2590418</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    C/A  UNIT       SCP STATION       DATE  ENTRIES    EXITS\n",
       "0  A002  R051  02-00-00   59 ST 2021-05-29  7578734  2590325\n",
       "1  A002  R051  02-00-00   59 ST 2021-05-29  7578740  2590327\n",
       "2  A002  R051  02-00-00   59 ST 2021-05-29  7578749  2590340\n",
       "3  A002  R051  02-00-00   59 ST 2021-05-29  7578789  2590386\n",
       "4  A002  R051  02-00-00   59 ST 2021-05-29  7578897  2590418"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unique Turnstile\n",
    "Each turnstile is identified by the combination of C/A, Unit, SCP, and the station."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "turnstiles_df['UNIQUE_TURNSTILE'] = (turnstiles_df[\"C/A\"] + turnstiles_df[\"UNIT\"] + \n",
    "                                     turnstiles_df[\"SCP\"] + turnstiles_df[\"STATION\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5032"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of turnstiles\n",
    "turnstiles_df.UNIQUE_TURNSTILE.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>7578789</td>\n",
       "      <td>2590386</td>\n",
       "      <td>A002R05102-00-0059 ST</td>\n",
       "    </tr>\n",
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       "      <td>4</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
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       "      <td>2590418</td>\n",
       "      <td>A002R05102-00-0059 ST</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    C/A  UNIT       SCP STATION       DATE  ENTRIES    EXITS  \\\n",
       "0  A002  R051  02-00-00   59 ST 2021-05-29  7578734  2590325   \n",
       "1  A002  R051  02-00-00   59 ST 2021-05-29  7578740  2590327   \n",
       "2  A002  R051  02-00-00   59 ST 2021-05-29  7578749  2590340   \n",
       "3  A002  R051  02-00-00   59 ST 2021-05-29  7578789  2590386   \n",
       "4  A002  R051  02-00-00   59 ST 2021-05-29  7578897  2590418   \n",
       "\n",
       "        UNIQUE_TURNSTILE  \n",
       "0  A002R05102-00-0059 ST  \n",
       "1  A002R05102-00-0059 ST  \n",
       "2  A002R05102-00-0059 ST  \n",
       "3  A002R05102-00-0059 ST  \n",
       "4  A002R05102-00-0059 ST  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily Entries & Exits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For each unique turnstile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Y_3ZfAA0G36b"
   },
   "outputs": [],
   "source": [
    "#cummulative entries and exits\n",
    "turnstiles_daily = (turnstiles_df.groupby([\"C/A\", \"UNIT\", \"SCP\", \"STATION\", \"DATE\"],as_index=False)\n",
    "                    ['ENTRIES','EXITS'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "dG_c1f06G36f",
    "outputId": "def7d2e7-4d07-48d8-fc27-b98309a861e0",
    "scrolled": false
   },
   "outputs": [
    {
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      ],
      "text/plain": [
       "    C/A  UNIT       SCP STATION       DATE  ENTRIES    EXITS\n",
       "0  A002  R051  02-00-00   59 ST 2021-05-29  7579021  2590439\n",
       "1  A002  R051  02-00-00   59 ST 2021-05-30  7579275  2590548\n",
       "2  A002  R051  02-00-00   59 ST 2021-05-31  7579593  2590641\n",
       "3  A002  R051  02-00-00   59 ST 2021-06-01  7580178  2590917\n",
       "4  A002  R051  02-00-00   59 ST 2021-06-02  7580754  2591200"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_daily.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Adding Columns: `PREV_DATE`, `PREV_ENTRIES`, and `PREV_EXITS`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "cg8RtfZLG36j"
   },
   "outputs": [],
   "source": [
    "turnstiles_daily[[\"PREV_DATE\", \"PREV_ENTRIES\", \"PREV_EXITS\"]] = (turnstiles_daily\n",
    "                                                       .groupby([\"C/A\", \"UNIT\", \"SCP\", \"STATION\"])\n",
    "                                                                 [\"DATE\", \"ENTRIES\",\"EXITS\"]\n",
    "                                                       .apply(lambda grp: grp.shift(1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "HEzUNsNVG36n",
    "outputId": "acd0b8b4-6e30-445d-ffee-fbf704951223"
   },
   "outputs": [
    {
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       "      <td>A002</td>\n",
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      "text/plain": [
       "    C/A  UNIT       SCP STATION       DATE  ENTRIES    EXITS  PREV_DATE  \\\n",
       "0  A002  R051  02-00-00   59 ST 2021-05-29  7579021  2590439        NaT   \n",
       "1  A002  R051  02-00-00   59 ST 2021-05-30  7579275  2590548 2021-05-29   \n",
       "2  A002  R051  02-00-00   59 ST 2021-05-31  7579593  2590641 2021-05-30   \n",
       "3  A002  R051  02-00-00   59 ST 2021-06-01  7580178  2590917 2021-05-31   \n",
       "4  A002  R051  02-00-00   59 ST 2021-06-02  7580754  2591200 2021-06-01   \n",
       "\n",
       "   PREV_ENTRIES  PREV_EXITS  \n",
       "0           NaN         NaN  \n",
       "1     7579021.0   2590439.0  \n",
       "2     7579275.0   2590548.0  \n",
       "3     7579593.0   2590641.0  \n",
       "4     7580178.0   2590917.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_daily.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "jxS3lJ6nG36x"
   },
   "outputs": [],
   "source": [
    "# Drop the rows for the earliest date in the df\n",
    "turnstiles_daily.dropna(subset=[\"PREV_DATE\"], axis=0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5IDEKSRgG361"
   },
   "source": [
    "#### Reverse Entries & Exits\n",
    "Need to investigate the reversed data and fix it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Lv-VA714G362",
    "outputId": "d66e798b-4275-4dec-e6d0-48f9d155e5ce"
   },
   "outputs": [
    {
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       "      <td>489575869</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>885601403.0</td>\n",
       "      <td>489576371.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4372</td>\n",
       "      <td>A011</td>\n",
       "      <td>R080</td>\n",
       "      <td>01-03-00</td>\n",
       "      <td>57 ST-7 AV</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>885601049</td>\n",
       "      <td>489575017</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>885601292.0</td>\n",
       "      <td>489575869.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4373</td>\n",
       "      <td>A011</td>\n",
       "      <td>R080</td>\n",
       "      <td>01-03-00</td>\n",
       "      <td>57 ST-7 AV</td>\n",
       "      <td>2021-06-03</td>\n",
       "      <td>885600810</td>\n",
       "      <td>489574126</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>885601049.0</td>\n",
       "      <td>489575017.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       C/A  UNIT       SCP     STATION       DATE    ENTRIES      EXITS  \\\n",
       "4369  A011  R080  01-03-00  57 ST-7 AV 2021-05-30  885601566  489576902   \n",
       "4370  A011  R080  01-03-00  57 ST-7 AV 2021-05-31  885601403  489576371   \n",
       "4371  A011  R080  01-03-00  57 ST-7 AV 2021-06-01  885601292  489575869   \n",
       "4372  A011  R080  01-03-00  57 ST-7 AV 2021-06-02  885601049  489575017   \n",
       "4373  A011  R080  01-03-00  57 ST-7 AV 2021-06-03  885600810  489574126   \n",
       "\n",
       "      PREV_DATE  PREV_ENTRIES   PREV_EXITS  \n",
       "4369 2021-05-29   885601748.0  489577552.0  \n",
       "4370 2021-05-30   885601566.0  489576902.0  \n",
       "4371 2021-05-31   885601403.0  489576371.0  \n",
       "4372 2021-06-01   885601292.0  489575869.0  \n",
       "4373 2021-06-02   885601049.0  489575017.0  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_daily[(turnstiles_daily[\"ENTRIES\"] < turnstiles_daily[\"PREV_ENTRIES\"])\n",
    "                | (turnstiles_daily[\"EXITS\"] < turnstiles_daily[\"PREV_EXITS\"])].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hXcZXN01G37N",
    "outputId": "77e890e0-1fc7-4e04-b66b-1d88f0818da9"
   },
   "outputs": [],
   "source": [
    "#function to calculate the daily entries \n",
    "def get_daily_entries(row, max_entries):\n",
    "    num = abs(row[\"ENTRIES\"] - row[\"PREV_ENTRIES\"])\n",
    "    \n",
    "    #could be reset to a random number\n",
    "    if num > max_entries:\n",
    "        return 0\n",
    "    \n",
    "    return num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hXcZXN01G37N",
    "outputId": "77e890e0-1fc7-4e04-b66b-1d88f0818da9"
   },
   "outputs": [],
   "source": [
    "turnstiles_daily[\"DAILY_ENTRIES\"] = turnstiles_daily.apply(get_daily_entries, axis=1, max_entries=100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hXcZXN01G37N",
    "outputId": "77e890e0-1fc7-4e04-b66b-1d88f0818da9"
   },
   "outputs": [],
   "source": [
    "#function to calculate the daily exits \n",
    "def get_daily_exits(row, max_exits):\n",
    "    num = abs(row[\"EXITS\"] - row[\"PREV_EXITS\"])\n",
    "    \n",
    "    #could be reset to a random number\n",
    "    if num > max_exits:\n",
    "        return 0\n",
    "    \n",
    "    return num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hXcZXN01G37N",
    "outputId": "77e890e0-1fc7-4e04-b66b-1d88f0818da9"
   },
   "outputs": [],
   "source": [
    "turnstiles_daily[\"DAILY_EXITS\"] = turnstiles_daily.apply(get_daily_exits, axis=1, max_exits=100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "nnL7k1dgG37Q",
    "outputId": "75df1787-bc82-48bd-befd-fd3c90836f1b"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C/A</th>\n",
       "      <th>UNIT</th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXITS</th>\n",
       "      <th>PREV_DATE</th>\n",
       "      <th>PREV_ENTRIES</th>\n",
       "      <th>PREV_EXITS</th>\n",
       "      <th>DAILY_ENTRIES</th>\n",
       "      <th>DAILY_EXITS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>7579275</td>\n",
       "      <td>2590548</td>\n",
       "      <td>2021-05-29</td>\n",
       "      <td>7579021.0</td>\n",
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       "      <td>254.0</td>\n",
       "      <td>109.0</td>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>7579593</td>\n",
       "      <td>2590641</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>7579275.0</td>\n",
       "      <td>2590548.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>7580178</td>\n",
       "      <td>2590917</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>7579593.0</td>\n",
       "      <td>2590641.0</td>\n",
       "      <td>585.0</td>\n",
       "      <td>276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>7580754</td>\n",
       "      <td>2591200</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>7580178.0</td>\n",
       "      <td>2590917.0</td>\n",
       "      <td>576.0</td>\n",
       "      <td>283.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>A002</td>\n",
       "      <td>R051</td>\n",
       "      <td>02-00-00</td>\n",
       "      <td>59 ST</td>\n",
       "      <td>2021-06-03</td>\n",
       "      <td>7581328</td>\n",
       "      <td>2591445</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>7580754.0</td>\n",
       "      <td>2591200.0</td>\n",
       "      <td>574.0</td>\n",
       "      <td>245.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    C/A  UNIT       SCP STATION       DATE  ENTRIES    EXITS  PREV_DATE  \\\n",
       "1  A002  R051  02-00-00   59 ST 2021-05-30  7579275  2590548 2021-05-29   \n",
       "2  A002  R051  02-00-00   59 ST 2021-05-31  7579593  2590641 2021-05-30   \n",
       "3  A002  R051  02-00-00   59 ST 2021-06-01  7580178  2590917 2021-05-31   \n",
       "4  A002  R051  02-00-00   59 ST 2021-06-02  7580754  2591200 2021-06-01   \n",
       "5  A002  R051  02-00-00   59 ST 2021-06-03  7581328  2591445 2021-06-02   \n",
       "\n",
       "   PREV_ENTRIES  PREV_EXITS  DAILY_ENTRIES  DAILY_EXITS  \n",
       "1     7579021.0   2590439.0          254.0        109.0  \n",
       "2     7579275.0   2590548.0          318.0         93.0  \n",
       "3     7579593.0   2590641.0          585.0        276.0  \n",
       "4     7580178.0   2590917.0          576.0        283.0  \n",
       "5     7580754.0   2591200.0          574.0        245.0  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_daily.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='eda'></a>\n",
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily Entries & Exits For Each Station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAILY_ENTRIES</th>\n",
       "      <th>DAILY_EXITS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>4575.0</td>\n",
       "      <td>8830.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>4943.0</td>\n",
       "      <td>8936.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>7487.0</td>\n",
       "      <td>12730.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>7993.0</td>\n",
       "      <td>13067.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-06-03</td>\n",
       "      <td>7844.0</td>\n",
       "      <td>13031.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  STATION       DATE  DAILY_ENTRIES  DAILY_EXITS\n",
       "0    1 AV 2021-05-30         4575.0       8830.0\n",
       "1    1 AV 2021-05-31         4943.0       8936.0\n",
       "2    1 AV 2021-06-01         7487.0      12730.0\n",
       "3    1 AV 2021-06-02         7993.0      13067.0\n",
       "4    1 AV 2021-06-03         7844.0      13031.0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_daily = turnstiles_daily.groupby([\"STATION\", \"DATE\"], as_index = False)[['DAILY_ENTRIES','DAILY_EXITS']].sum()\n",
    "station_daily.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#the total traffic in a station is the sum of entries and exits\n",
    "station_daily['TOTAL'] = station_daily.DAILY_ENTRIES + station_daily.DAILY_EXITS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAILY_ENTRIES</th>\n",
       "      <th>DAILY_EXITS</th>\n",
       "      <th>TOTAL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>4575.0</td>\n",
       "      <td>8830.0</td>\n",
       "      <td>13405.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>4943.0</td>\n",
       "      <td>8936.0</td>\n",
       "      <td>13879.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>7487.0</td>\n",
       "      <td>12730.0</td>\n",
       "      <td>20217.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>7993.0</td>\n",
       "      <td>13067.0</td>\n",
       "      <td>21060.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1 AV</td>\n",
       "      <td>2021-06-03</td>\n",
       "      <td>7844.0</td>\n",
       "      <td>13031.0</td>\n",
       "      <td>20875.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  STATION       DATE  DAILY_ENTRIES  DAILY_EXITS    TOTAL\n",
       "0    1 AV 2021-05-30         4575.0       8830.0  13405.0\n",
       "1    1 AV 2021-05-31         4943.0       8936.0  13879.0\n",
       "2    1 AV 2021-06-01         7487.0      12730.0  20217.0\n",
       "3    1 AV 2021-06-02         7993.0      13067.0  21060.0\n",
       "4    1 AV 2021-06-03         7844.0      13031.0  20875.0"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_daily.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stations with the Highest Daily Entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STATION\n",
       "34 ST-PENN STA     4893954.0\n",
       "34 ST-HERALD SQ    3760882.0\n",
       "GRD CNTRL-42 ST    3513460.0\n",
       "42 ST-PORT AUTH    3332572.0\n",
       "86 ST              3198710.0\n",
       "23 ST              3187259.0\n",
       "14 ST-UNION SQ     3045658.0\n",
       "125 ST             3044055.0\n",
       "TIMES SQ-42 ST     2736867.0\n",
       "PATH NEW WTC       2641813.0\n",
       "Name: DAILY_ENTRIES, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_entries = station_daily.groupby('STATION')['DAILY_ENTRIES'].sum().sort_values(ascending=False)\n",
    "station_entries.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 Stations with the Highest Daily Entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "plt.bar(x=station_entries.index[:10], height=station_entries[:10])\n",
    "plt.xlabel('Stations', fontsize=15)\n",
    "plt.ylabel('Number of turnstile entries', fontsize=15)\n",
    "plt.title('Top 10 Stations with the Highest Daily Entries', fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stations with the Highest Daily Exits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STATION\n",
       "34 ST-PENN STA     6554273.0\n",
       "GRD CNTRL-42 ST    5084956.0\n",
       "34 ST-HERALD SQ    5030650.0\n",
       "14 ST-UNION SQ     4414206.0\n",
       "86 ST              4411253.0\n",
       "42 ST-PORT AUTH    4081519.0\n",
       "125 ST             3818434.0\n",
       "TIMES SQ-42 ST     3784189.0\n",
       "23 ST              3723680.0\n",
       "FULTON ST          3403336.0\n",
       "Name: DAILY_EXITS, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_exits = station_daily.groupby('STATION')['DAILY_EXITS'].sum().sort_values(ascending=False)\n",
    "station_exits.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 Stations with the Highest Daily Exits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "plt.bar(x=station_exits.index[:10], height=station_exits[:10], color='orange')\n",
    "plt.xlabel('Stations', fontsize=15)\n",
    "plt.ylabel('Number of turnstile exits', fontsize=15)\n",
    "plt.title('Top 10 Stations with the Highest Daily Exits', fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stations with the Highest Daily Traffic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STATION\n",
       "34 ST-PENN STA     11448227.0\n",
       "34 ST-HERALD SQ     8791532.0\n",
       "GRD CNTRL-42 ST     8598416.0\n",
       "86 ST               7609963.0\n",
       "14 ST-UNION SQ      7459864.0\n",
       "42 ST-PORT AUTH     7414091.0\n",
       "23 ST               6910939.0\n",
       "125 ST              6862489.0\n",
       "TIMES SQ-42 ST      6521056.0\n",
       "FULTON ST           6005811.0\n",
       "Name: TOTAL, dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_totals = station_daily.groupby('STATION')['TOTAL'].sum().sort_values(ascending=False)\n",
    "station_totals.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 Stations with the Highest Daily Traffic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/Tp5ue/30PW/tvCojPQdV9deq+lZV/QdL55wa9Evy1JxIT6IZ6nRqV90OLJ0vaND5k5bnmC2vUe/rR+3PnUe0vZGpqstpeiHdJ0mvJPOjRrSrFToGVXVhVX2UZj6um2juxDdltt8br2+3fUYtvePaJjR3yfxuj2TS3VmagFpRH6a5hjyf5o6aAB8d0baX132B67qTSa1lfkfMgqn30p7TtpIkLbfVJqFUVd+jmZTwNknuk+QbSc5KckY7jrvbM4DPjiVISVq1fBv4Lc1/vW/3B3mS/Wnm4Tm7qnollJ7fY9Lqt9J8sTqqz8TUo/CR9uehbc8ZANpeC1NDQI4eZENJDm7X61W3O02vnBu4/fwhf2x/btZjtUvan7t2bevewPv7hDHd9vr5NM0X54OSbNqxnwBvo5nD5JMrcg6S7N72quo21UtlmQmI+5hKEr2ijaszaXQazRwwr+5YHsTyHLPlNep9fZcmQfusJM/o1SDJdm0iYmU4mmaS4//uLEzyj7TDHkfgczRDlA5K8tjuyjRum7A9yf36fE43oumJ3/lenJX3RpI7JXkLzfv4epr5jKZcRjO0b8ck63Wssy5NEujOjMZXae6OdwBNEvanVXXmiLa9vC4B7pTknzoLkzwT2GcM+/8ozZDig5M8pLsyybwxxCBJq7XVZshbHwtobi366yQ70vzivu2Pk7Zb8JaMdpJPSVotVNXNSZ5NM6HpV5OcQDOR9gOAJwPX0NyyupdvAz9pJ2y+kmaY8Y40w80OGTSGJIfSXKehufsVwIuTTPVI/XZV3TZHSFV9K8kCmi9V57Qxr09zu+k7A//eZ0LhXp4H/E+Sc2mSRr9vt/Fgmt4PAP9RVdd0rHMqzfCao5J8mSaBdWVVLaBJFvwMeHaSLWj+e35vmrlyFtL7bltnsPQL0TyWDtt4T795Ydq5iV5Pc4v3c5J8nuZc7UZzDH/OEOegj48Ad0/yXZovjbfQnN+dac7xlwbZSFX9NslFNLedv4XbT+b+PZov4vcALhlwCB0sxzFbASPdV1VVkqfTvI+OTXIQcCbNcLNNaSZ03pqmV8s1fTc0e95C05vseUkeRPP304Y08wCdRtMbaIWSxe0k008FTgZOTfI94Bya279vRtNrbXOaz+JN7fLRSX4CnEfzOb1nG0toPgdT276y/Tw/IcmnaSalvxX4QlX9csAQD0jypHbbG9AMpd2FZo6p3wLPqarbJiBv53g6gmZI3i+SnESTWN+t/fl94JHDHaVlVdUt7bXvzW3Ryu6dBE2ifG/g9PY6dDXNPyJ2BY4Hnj6bO2+HAr6AZtL/M5N8FbiQZhL4h9Fccx4+zSYkSTNYbRNKSTaguRXp8c0/ZYFlJ/7bj+aPiFuQJC2jqr6bZAea24Q/huZL2hLgKODN03zJfwvNF8IDab5w/Zkmyf/GIW/j/WSWvQPVLixN6FzLspPOvgg4q/35YpqkxJnA26vqW0Ps+xnAXjSvezeaOYmKphfA0cDhPW5r/sV2At79aXoprEPzJXdBVd3UJsI67xr3W+ADND2Hlpk4tqquSPIvNHOwPJ9mOBk0d27qm7CoqncmuYBm0uz9aHr/XNLu+x3LczepLm+iOTfb08wLdUv7Wg4DPtjeFnxQp9IklM6qqtvmdaqqv7ZJgkcwxD9+lveYLY/Z2FdVXZxkO+DlwFOAZ9MkL66geS+9i/HfIXEqtr8k2Znm8/0Umh45F9NcH86juT6s8Jw9VfWTNmF1EE3C9fk0n+MraBKxr2Npz6PvA++kGUL1RJqJmP/Qlr+/qrqHSv4/mom796ZJAoXmLnGDJpRe0P68hWbY6xU0SfevAV/sk0g8qG33bJpr0tXAN2iO2wcG3O8gjqRJKP2V9iYCK1NVnd72bj0U2JcmeXcW8DiaRPGsJpTaGI5qr4WvoUl4P5mmp9q5wCdme/+StLpL1UB3T14ltP/xPamqHpjkLsCFVdXrP75T7X8GvLSqfjCmECVptZbk3TRfnv6p87/0klZv7STL7wWeVVXHrOx41kRtz6mvAkdU1VgmIpckrdlWmzmUurV3tfhN23V8asz9beOn2/H2dwd+uJJClCRJWqW0c351l92HptfQDTQ9bzRm7RxpU/ONHb4yY5EkrTlWmyFvST5LMyZ7oySLabrXPhP4SJI30kzseRzN3BHQDGU4rlanLlqSJEmz65QkfwPOphnK+o808yqtB7ysqv443coarSTb09zleCeaocDHVdW5KzcqSdKaYqwJpSRH0vzRcWVVPbBH/TOB17aL1wIvrqqfd7frpap63g2F5pdsr/aHDbJdSZIk3eaTNPNyPR24C818PWfQzFf0tZUZ2BrqETRzo/2JZt6kUd1tT5KkGY11DqUku9Akio7qk1B6BHBBVV3TTuJ3WFXtOLYAJUmSJEmSNKOx9lCqqu+1E2f3q++cHPtHwLzZjkmSJEmSJEnDmeQ5lJ5HcxvWnpIcABwAsP766z9s6623HldckiRJkiRJq72zzjrrqqqa26tuIhNKSR5Dk1B6VL82VbUAWAAwf/78WrjQu1NLkiRJkiSNSpJL+9VNXEIpyYOBjwN7eqcQSZIkSZKkybPWyg6gU5LNgBOAf6uqX63seCRJkiRJkrSssfZQSvJZYFdgoySLgUOBOwBU1RHAIcCGwIeTANxcVfPHGaMkSZIkSZKmN+67vD1jhvrnA88fUziSJEmSJElaDhM15E2SJEmSJEmTz4SSJEmSJEmShmJCSZIkSZIkSUMxoSRJkiRJkqShmFCSJEmSJEnSUEwoSZIkSZIkaSgmlCRJkiRJkjSUtVd2ALq9i+buvLJDWG3cZ8kZKzsESZIkSZJWS/ZQkiRJkiRJ0lBMKEmSJEmSJGkoJpQkSZIkSZI0FBNKkiRJkiRJGooJJUmSJEmSJA3FhJIkSZIkSZKGYkJJkiRJkiRJQzGhJEmSJEmSpKGYUJIkSZIkSdJQTChJkiRJkiRpKCaUJEmSJEmSNBQTSpIkSZIkSRqKCSVJkiRJkiQNxYSSJEmSJEmShmJCSZIkSZIkSUMxoSRJkiRJkqShmFCSJEmSJEnSUEwoSZIkSZIkaSgmlCRJkiRJkjQUE0qSJEmSJEkaigklSZIkSZIkDcWEkiRJkiRJkoZiQkmSJEmSJElDMaEkSZIkSZKkoZhQkiRJkiRJ0lBMKEmSJEmSJGkoJpQkSZIkSZI0FBNKkiRJkiRJGspYE0pJjkxyZZJz+9QnyQeSLEpyTpLtxxmfJEmSJEmSZjbuHkqfAvaYpn5PYKv2cQDwkTHEJEmSJEmSpCGMNaFUVd8Drp6myT7AUdX4EXC3JBuPJzpJkiRJkiQNYtLmUNoEuKxjeXFbJkmSJEmSpAkxaQml9Cirng2TA5IsTLJwyZIlsxyWJEmSJEmSpkxaQmkxsGnH8jzg8l4Nq2pBVc2vqvlz584dS3CSJEmSJEmavITSicCz27u97QT8uaquWNlBSZIkSZIkaam1x7mzJJ8FdgU2SrIYOBS4A0BVHQGcDOwFLAKuA547zvgkSZIkSZI0s7EmlKrqGTPUF/DSMYUjSZIkSZKk5TDwkLck6VreJcmLkjxg9GFJkiRJkiRpUg3UQynJ8TRD0J7TLr8I+DBwK3Bzkn2q6pRZi1KSJEmSJEkTY9AeSg8HTupYPhj4ILAucDRwyIjjkiRJkiRJ0oQaNKG0EXAFQDvEbR7woaq6Bfgs4LA3SZIkSZKkNcSgCaUrgc3a508ALquqX7fL6448KkmSJEmSJE2sQe/ydgLwtiTbAAcAH+uoeyiwaNSBSZIkSZIkaTINmlB6Lc2k3DsBRwH/3VH3SOCLI45LkiRJkiRJE2qghFJV/R14fZ+6J400IkmSJEmSJE20geZQSnJdkvl96rZLct1ow5IkSZIkSdKkGnRS7vWmabsuMGc04UiSJEmSJGnS9R3yluTewLyOom2TdDdbD3gucOnoQ5MkSZIkSdIkmm4OpRcAhwLVPj7Ro02AG4EXjj40SZIkSZIkTaLpEkoLgJNokkY/oemJdG5XmxuB31TVtbMTniRJkiRJkiZN34RSVV0BXAGQZBvgkvZub5IkSZIkSVqDTTeH0lpVdWu7+Oupsn7tO9pKkiRJkiRpNTbdXd5uSrJD+/xm4KYZHpIkSZIkSVoDTDeH0kuAizue1+yHI0mSJEmSpEk33RxKH+14fsR4wpEkSZIkSdKkm27I222SPGqG+ueNJhxJkiRJkiRNuoESSsB3k7w7ybqdhUk2TnIy8JHRhyZJkiRJkqRJNGhC6dnAc4GfJZkPkORZwHnAFsAjZyU6SZIkSZIkTZyBEkpVdQzwIOA3wA+S/BD4JHAksF1VnTl7IUqSJEmSJGmSTHeXt9upqsuTfBJ4LLAj8HPgvVX199kKTpokF83deWWHsNq4z5IzVnYIkiRJkqQVMOik3HdLcixwHLCAZojbWsC57dA3SZIkSZIkrSEG7aF0PnADsHtVnQ7QzqX0JuCTSZ5WVU+ZpRglSZIkSZI0QQadlPtk4CFTySSAqrqpql4PPArYejaCkyRJkiRJ0uQZqIdSVT1/mrofJ3no6EKSpOE5x9XoOMeVJEmSpJn07aGUZPskd5xpA0nuDjxxpFFJkiRJkiRpYk035O1M4EFTC0nWSnJdj95I9wOOn43gJEmSJEmSNHmmSyilx/J6M6wjSZIkSZKk1ZzJIUmSJEmSJA3FhJIkSZIkSZKGMlNCqQYskyRJkiRJ0hpi7RnqFyT5a1fZJ5Jc27F85xHHJEmSJEmSpAk2XULp8yzbG+lzfdr+cjThSJIkSZIkadL1TShV1X7jDESSJEmSJEmrhrFPyp1kjyQXJlmU5HU96jdLcnqSnyU5J8le445RkiRJkiRJ/Y01oZRkDnA4sCewLfCMJNt2NXsj8Pmq2g7YD/jwOGOUJEmSJEnS9MbdQ2kHYFFVXVxVNwLHAft0tSngLu3zuwKXjzE+SZIkSZIkzWCmu7yN2ibAZR3Li4Edu9ocBnwzyX8A6wOPG09okiRJkiRJGsS4eyilR1n3neSeAXyqquYBewFHJ1kmziQHJFmYZOGSJUtmIVRJkiRJkiT1MnRCKck6Pcp2GHD1xcCmHcvzWHZI2/OAzwNU1Q+B9YCNujdUVQuqan5VzZ87d+6Au5ckSZIkSdKKWp4eSn9LcmqSJwO0P08bcN0zga2SbNkmpvYDTuxq81tgt3bb29AklOyCJEmSJEmSNCGWZw6lfwe2Az6d5ALgn4DPDLJiVd2c5EDgFGAOcGRVnZfkzcDCqjoROAj4WJJX0AyH27+quofFSZIkSZIkaSXpm1BKEuAO7d3YblNVR9PMa/Qnmgm0fwe8eNAdVtXJwMldZYd0PD8feOSg25MkSZIkSdJ4TTfk7eP0GcqW5J3AG4GXAH+i6VUkSZIkSZKkNcB0CaXdgY91FiSZk+QzwIHA06vqCOD9wL/NXoiSJEmSJEmaJNPNofQPNHdlAyDJ+sCXaOZM2qOqvtdWXQRsOWsRSpIkSZIkaaJM10PpF8B/JtkwyU7AD4AHArt0JJMAtgWumcUYJUmSJEmSNEGm66H0SuAk4Mp2eQlwE3BfmmQTSR4AvIGuSbYlSep00dydV3YIq4X7LDljZYcgSZIkAdMklKrqh0nuD+wC3AJ8G9gB+HKS9wB/BbamucvbwWOIVZIkSZIkSRNguh5KVNVVwAkdRacneRDwfGAz4Fjgo1X1p9kLUZIkSZIkSZNk2oRSL1X1W+CQWYhFkiSNmcMRR8chiZIkaU0ydEJJkiRJ42HCbzRM9kmSNHrT3eVNkiRJkiRJWoYJJUmSJEmSJA3FhJIkSZIkSZKGYkJJkiRJkiRJQxkooZRkpyR7dizfPcmRSX6U5K1J5sxeiJIkSZIkSZokg/ZQeg8wv2P5f4G9gV8CLwUOHXFckiRJkiRJmlCDJpS2BhYCJLkjsC/w8qraH3gN8K+zEp0kSZIkSZImzqAJpfWA69rnjwDWAb7aLl8A3HvEcUmSJEmSJGlCDZpQuhB4XPt8P+BHVfWXdnlj4JpRByZJkiRJkqTJtPaA7d4KfDbJ/jQJpKd21O0OnD3iuCRJkiRJkjShBkooVdUXkzwE2B44p6p+0VF9DnDUbAQnSZIkSZKkyTNoDzKlu5cAACAASURBVCWq6gKa+ZK6yz840ogkSZKkCXfR3J1XdgirjfssOWNlhyBJWg4DJ5SS3B94PTAfmAc8uqrOTnIY8P2q+tbshChJkiRJgzPhNxom+yRNZ6BJuZM8jmZo2/2BLwMbdKwb4OWzEp0kSZIkSZImzqB3eXsHcFxV7QQcSpNEmvJTYLtRByZJkiRJkqTJNGhC6QHA0e3z6qr7E7DhyCKSJEmSJEnSRBs0oXQVsHmfum2AxaMJR5IkSZIkSZNu0ITS54G3JJnfUVZJtgReCxw38sgkSZIkSZI0kQZNKL0BOA/4MfCrtux44AJgEfDm0YcmSZIkSZKkSbT2II2q6npg9yRPBHYDNgKuBk4FTqqq7nmVJEmSJEm6nYvm7ryyQ1ht3GfJGSs7BK3hBkooTamqrwFfm6VYJEmSJEmStArom1BKslZV3Tr1fKYNTbWVJEmSJEnS6m26RNFNSXZon98M3DTDQ5IkSZIkSWuA6Ya8vQS4uOO58yRJkiRJkiSpf0Kpqj4KkGRt4Ezgsqq6clyBSZIkSZIkaTLNODcScCvwQ+DBsxyLJEmSJEmSVgGDTra9CNho9sORJEmSJEnSpBukhxLAocAhSe63ojtMskeSC5MsSvK6Pm3+Jcn5Sc5LcuyK7lOSJEmSJEmjM92k3J1eBmwInJ/kYuAPdE3SXVW7zLSRJHOAw4HdgcXAmUlOrKrzO9psBRwMPLKqrklyjwFjlCRJkiRJ0hgMmlD6HU0CaEXtACyqqosBkhwH7AOc39HmBcDhVXUNgBOBS5IkSZIkTZaBEkpVtd+I9rcJcFnH8mJgx6429wNI8n1gDnBYVX1jRPuXJEmSJEnSChoooZTkw8A7qurSHnWbAgdX1UsG2VSPsupaXhvYCtgVmAeckeSBVfWnrv0eABwAsNlmmw2wa0mSJEmS1M9Fc3de2SGsFu6z5IyVHcJYDDop94uAe/apuwfwwgG3sxjYtGN5HnB5jzZfqaqbquo3wIU0CabbqaoFVTW/qubPnTt3wN1LkiRJkiRpRQ2aUIJlexJNuT9w1YDbOBPYKsmWSdYB9gNO7GrzZeAxAEk2ohkCd/EQcUqSJEmSJGkW9R3yluSlwEvbxQI+l+SGrmbr0fQ4OnaQnVXVzUkOBE6hmR/pyKo6L8mbgYVVdWJb9/gk5wO3AK+uqj8O86IkSZIkSZI0e6abQ+li4NT2+dbAQuAPXW1uBH4JHDPoDqvqZODkrrJDOp4X8Mr2IUmSJEmSpAnTN6FUVV8Hvg6Q5Frg8KpaPK7AJEmSJEmSNJkGustbVR0824FIkiRJkiRp1TBQQgkgyZOAp9LcmW297vqq2mWEcUmSJEmSJGlCDZRQSvIG4C3AhcD5gJNkS5IkSZIkraEG7aH0QuC9VfWq2QxGkiRJkiRJk2+tAdvdlXaCbkmSJEmSJK3ZBk0oHQ/sNpuBSJIkSZIkadUw6JC3rwLvTXJ34FvAn7obVNVpowxMkiRJkiRJk2nQhNKX2p8vbB/dCpgzkogkSZIkSZI00QZNKG0zq1FIkiRJkiRplTFQQqmqLpztQCRJkiRJkrRq6Dspd5KnJrlbV9k9kqzVVXavJK+crQAlSZIkSZI0Waa7y9vxwP2mFpLMAa4AHtrVbnPgXaMPTZIkSZIkSZNouoRSBiyTJEmSJEnSGmS6hJIkSZIkSZK0DBNKkiRJkiRJGspMCaUasEySJEmSJElriLVnqP9qkhu7yk5OclPH8jojjkmSJEmSJEkTbLqE0jvGFoUkSZIkSZJWGX0TSlV18DgDkSRJkiRJ0qrBSbklSZIkSZI0FBNKkiRJkiRJGooJJUmSJEmSJA3FhJIkSZIkSZKG0jehlOQ1Se7VPr9HkjnjC0uSJEmSJEmTaroeSm8DNm2fXwE8bPbDkSRJkiRJ0qSbLqF0FbBV+zxAzX44kiRJkiRJmnRrT1N3InBUknfSJJO+muTGfo2rarNRBydJkiRJkqTJM11C6UXAd4BtgNcDpwCXjyEmSZIkSZIkTbC+CaWqugU4BiDJbsDbq+qCcQUmSZIkSZKkyTRdD6XbVNXDZzsQSZIkSZIkrRqmm5T7dpLMT/KlJEuS3Nz+PCHJ9rMZoCRJkiRJkibLQD2UkuxKM4fSpcDHgD8A9wSeBvwgyROq6ruzFaQkSZIkSZImx0AJJeDtwDeAp1TVrVOFSd4IfLmtd1icJEmSJEnSGmDQIW8PBj7SmUwCaJc/DDxk1IFJkiRJkiRpMg2aUPorsHmfus3bekmSJEmSJK0BBk0ofRF4e5J9k8wBSDInyb7A24AvzFaAkiRJkiRJmiyDJpReDZwGfB64PskfgOvb5dPa+oEk2SPJhUkWJXndNO32TVJJ5g+6bUmSJEmSJM2+gSblrqq/AU9L8hBgB2Bj4ArgJ1X180F31vZuOhzYHVgMnJnkxKo6v6vdnYGXAT8edNuSJEmSJEkaj0Hv8gZAmzwaOIHUww7Aoqq6GCDJccA+wPld7d4CvBN41QrsS5IkSZIkSbNg0CFvo7IJcFnH8uK27DZJtgM2raqTpttQkgOSLEyycMmSJaOPVJIkSZIkST2NO6GUHmV1W2WyFvA+4KCZNlRVC6pqflXNnzt37ghDlCRJkiRJ0nTGnVBaDGzasTwPuLxj+c7AA4HvJLkE2Ak40Ym5JUmSJEmSJse4E0pnAlsl2TLJOsB+wIlTlVX156raqKq2qKotgB8Be1fVwjHHKUmSJEmSpD7GmlCqqpuBA4FTgAuAz1fVeUnenGTvccYiSZIkSZKk5dP3Lm9J/n2YDVXVkQO2Oxk4uavskD5tdx0mBkmSJEmSJM2+vgkl4ONDbKeAgRJKkiRJkiRJWrVNl1C649iikCRJkiRJ0iqjb0Kpqv4+zkAkSZIkSZK0apiuh9IykswFtgLW666rqtNGFZQkSZIkSZIm10AJpSTrA58BngykT7M5owpKkiRJkiRJk2utAdu9FdgWeDxNQukZwJ7AMcAlwM6zEZwkSZIkSZImz6AJpScD/w18t12+uKq+WVXPBr4GHDgbwUmSJEmSJGnyDJpQuhdwSVXdAlwHbNhRdyKw16gDkyRJkiRJ0mQaNKG0mKVJpEXAHh112wE3jDIoSZIkSZIkTa5B7/J2KvBY4MvAB4CPJ3kI8HfgccCHZic8SZIkSZIkTZpBE0qvBe4MUFVHJrke2Be4I/Aa4IOzE54kSZIkSZImzUAJpar6K/DXjuXPAp+draAkSZIkSZI0uQaaQynJdUnm96nbLsl1ow1LkiRJkiRJk2rQSbnXm6btusCc0YQjSZIkSZKkSdd3yFuSewPzOoq2TdLdbD3gucClow9NkiRJkiRJk2i6OZReABwKVPv4RI82AW4EXjj60CRJkiRJkjSJpksoLQBOokka/YSmJ9K5XW1uBH5TVdfOTniSJEmSJEmaNH0TSlV1BXAFQJJtgEuq6u/jCkySJEmSJEmTaboeSrepqguTrJVkH+BRwD8AVwNnACdV1a2zGKMkSZIkSZImyEAJpSQbAl8H5gO/B/4A3BM4CDgzyZ5VdfWsRSlJkiRJkqSJsdaA7d4DbAo8uqruXVXbVdW9gUfT3AnuPbMVoCRJkiRJkibLoAmlJwGvqaozOgvb5YOBJ486MEmSJEmSJE2mQRNKd6SZM6mXq9t6SZIkSZIkrQEGTSidCbw6yXqdhe3yq4CfjDowSZIkSZIkTaaBJuWmSRqdBvw2yck0k3LfA9iLpnfSY2YnPEmSJEmSJE2agXooVdVC4H7AscBWwNPb5WOA+1fVWbMWoSRJkiRJkiZK3x5KSXYBflpV1wJU1e+B/xxXYJIkSZIkSZpM0/VQOh3YdlyBSJIkSZIkadUwXUIpY4tCkiRJkiRJq4xB7/ImSZIkSZIkATPf5W2vJFsPsqGqOmoE8UiSJEmSJGnCzZRQOmTA7RRgQkmSJEmSJGkNMFNC6THAwnEEIkmSJEmSpFXDTAml66vqb2OJRJIkSZIkSasEJ+WWJEmSJEnSUEwoSZIkSZIkaSh9E0pVtVZV/WTUO0yyR5ILkyxK8roe9a9Mcn6Sc5KcmmTzUccgSZIkSZKk5TfWHkpJ5gCHA3sC2wLPSLJtV7OfAfOr6sHAF4B3jjNGSZIkSZIkTW/cQ952ABZV1cVVdSNwHLBPZ4OqOr2qrmsXfwTMG3OMkiRJkiRJmsa4E0qbAJd1LC9uy/p5HvD1WY1IkiRJkiRJQ1l7zPtLj7Lq2TB5FjAfeHSf+gOAAwA222yzUcUnSZIkSZKkGYy7h9JiYNOO5XnA5d2NkjwOeAOwd1X9vdeGqmpBVc2vqvlz586dlWAlSZIkSZK0rHEnlM4EtkqyZZJ1gP2AEzsbJNkO+ChNMunKMccnSZIkSZKkGYw1oVRVNwMHAqcAFwCfr6rzkrw5yd5ts3cBGwDHJzk7yYl9NidJkiRJkqSVYNxzKFFVJwMnd5Ud0vH8ceOOSZIkSZIkSYMb95A3SZIkSZIkreJMKEmSJEmSJGkoJpQkSZIkSZI0FBNKkiRJkiRJGooJJUmSJEmSJA3FhJIkSZIkSZKGYkJJkiRJkiRJQzGhJEmSJEmSpKGYUJIkSZIkSdJQTChJkiRJkiRpKCaUJEmSJEmSNBQTSpIkSZIkSRqKCSVJkiRJkiQNxYSSJEmSJEmShmJCSZIkSZIkSUMxoSRJkiRJkqShmFCSJEmSJEnSUEwoSZIkSZIkaSgmlCRJkiRJkjQUE0qSJEmSJEkaigklSZIkSZIkDcWEkiRJkiRJkoZiQkmSJEmSJElDMaEkSZIkSZKkoZhQkiRJkiRJ0lBMKEmSJEmSJGkoJpQkSZIkSZI0FBNKkiRJkiRJGooJJUmSJEmSJA3FhJIkSZIkSZKGYkJJkiRJkiRJQzGhJEmSJEmSpKGYUJIkSZIkSdJQTChJkiRJkiRpKCaUJEmSJEmSNBQTSpIkSZIkSRrK2BNKSfZIcmGSRUle16N+3SSfa+t/nGSLcccoSZIkSZKk/saaUEoyBzgc2BPYFnhGkm27mj0PuKaq7gu8D3jHOGOUJEmSJEnS9MbdQ2kHYFFVXVxVNwLHAft0tdkH+HT7/AvAbkkyxhglSZIkSZI0jXEnlDYBLutYXtyW9WxTVTcDfwY2HEt0kiRJkiRJmtHaY95fr55GtRxtSHIAcEC7eG2SC1cwNg1uI+CqlR3EjNbcjm2Tf348N5PN8zO5PDeTzfMzuTw3k83zM7nW3HMDnp9J5rkZr837VYw7obQY2LRjeR5weZ82i5OsDdwVuLp7Q1W1AFgwS3FqGkkWVtX8lR2HevP8TC7PzWTz/Ewuz81k8/xMLs/NZPP8TDbPz+Ty3EyOcQ95OxPYKsmWSdYB9gNO7GpzIvCc9vm+wGlVtUwPJUmSJEmSJK0cY+2hVFU3JzkQOAWYAxxZVecleTOwsKpOBD4BHJ1kEU3PpP3GGaMkSZIkSZKmN+4hb1TVycDJXWWHdDy/AXj6uOPSUBxqONk8P5PLczPZPD+Ty3Mz2Tw/k8tzM9k8P5PN8zO5PDcTIo4mkyRJkiRJ0jDGPYeSJEmSJEmSVnEmlCZQkvWS/CTJz5Ocl+RNPdp8MMm1fda/Z5KT2vXPT3JykgclObt9XJ3kN+3zb/dY/7Akv2vrz02yd4/yqcfdkuyapJI8uWMbJyXZtX3+nSQLO+rmJ/lOj/2uleQD7T5/keTMdgL3H7f7+m2SJR373qJdb7t2/08Y9ljPZELOxau6yi5JslH7/Jau8/G6tvw7SS5s93tmkod2baPnMev1OrrO+6+TnJBk2z6vd6eO83VBksM66v45yTlJftme4317bWMY7fE9NsnFSc5K8sMkT2nrdk3y5yQ/a/f57o719m/fSz9rX9MpSR4xzX6e3cZ8XnseX9WWf6o9Nuu2yxu156fvOU6yRZLr2+XzkxyV5A4dMZ804Gu/S7vvD7XLd0rytfa1npfk7dMcs+V+T64qkryiPQ7nJvlskvXa8iR5a5Jfte/Rl/VY905JjklzHTo3yf8l2bzjGP0+t78WrjP+Vzh6SY5McmWSc/vUv6q9bmzUo26FjllmvtZVkvd0xXJY97rt+X1j+7n+VZLTkzyga5tf7FjeN8mnBnw9G7R185J8pd3HxUk+NHUNGKUkc9Jco07qKDsmzbX93PZ83WHA2Ic5F1PXx6lr1As66jqv479I8s8ddZ/quHb8PMlubfmX2rJFaa7JU/td5pqbZO0kVyV5W1f5be+FdnnXNNex53Zs78Y2prOTvL19HR/q2s53kqySdwVKsmn7fr4gzbXt5R11b2nPy9lJvpnk3j3WXyOva7Mtfa6bSd7Vfk7OaT8Dd2vLO/8GODvJEX22+6T28z/1u/qFSd7QsV7n33/L/B5bVSTZcJr34HVtmy3S/A54S8d6GyW5KUv/Bur3HaXvtbwrjn9v25zTttunLU9u/zvlu0kePMNr2izJtVn6e6nvZ7drvfu316ipv6EXJHlCx+u5Ns31/+wkRy3/UZ89WfZ7yRYzXYuz7PX9+el9XX9rW//UtuyC9nx1fv/8TJLLpq5fSe6VZl7mXrEe0p6Pc9rP2j8lOTG9f1/tOBvHa7VRVT4m7AEE2KB9fgfgx8BOHfXzgaOBa/us/1Hg5R3LD+6q/xSw7zT7Pwx4Vft8G+AqmuTjbeVd7XcFLgN+1FF2ErBr+/w7wG+BPTvi/06P7TwD+AKwVrs8D7h7R/3+wId6rPdO4AzgU6vzuegouwTYqH3eb7/fAea3z58LfGuQY9Zre90xAP8P+D0wt0fbC4GHtM/nANu2zx8CLAK2bJe3BC4CHraC5+aHwIs6yjYH/qPjfXlS+/yOwC+BR/Z6LwGPaV/TNj32syfwU+De7fJ6wAs6zt9vgRe3yxsBl0x3joEtgHM7jtFpwDO7Yx7g9b8fOHbqdQB3Ah7TPl+nPb97jvo9uSo8gE2A3wB3bJc/D+zf8Xk4iqXXmXv0WP9g4L0dy/cH1u33mVhdHsAuwPZT78+uuk1pbqhxKe31Z5THrFc9t7/W3dCe06nlVwGHda8LHEgzT+Od2uXH01xr1uvY5qXAA9rlfenxu6Pf66G57vwEeG5bPofmZiLvn4Xz8cr2M35SR9lebQwBPkt77RnxudifpdeVewBLgHvS+zq+iPYaQse1g+aa+uuu7e7KDNe39vV9vz1n6fVe6LetHm1uex0dZd+h/d24qj2AjYHt2+d3Bn7F0t+xd+lo9zLgiFG/L3z0PS89r5vttWft9vk7gHe0z7fobttjm3cALgfmtcvrAvfvatPz779V+dH9Hpx6je0xuwj4WUfdi4GzO65VPd+/M73v27J57fbv2i5v0HGd6/U75VJg/WlexxeB41n6e6nvZ7drvVOAfTqWH9RVP/HXr17vy5muxd3X7q52i4G7dSxvD/wa2Lxdvg9wMUt/p3+G5u/yqb/T7wUs6rHdnYH/A9Zpl+cCG3fUPw748so+nqvKwx5KE6gaUz1F7tA+mm/QyRzgXcBrptnExjQfwKntnbMCsVwA3EzzRXk6Pwf+nGT3PvXvAt44wzY2Bq6oqlvbfS+uqmumWyFJaL4Q7A88Pm0vhFGZpHOxAn5I8wUbWPFjVlWfA74J/GuP6nsAV7Ttbqmq89vyVwH/U1W/aet+A/wPcNBQr+T2HgvcWFW3/Xevqi6tqg/2iPl6mj88Numua+tPp5nc74Ae1QfT/FFwedv2hqr6WEf9/wKvSDL0TQ6q6haaL6c94+onycNovuB9s2Nb17Wvg6q6kSYJNq/H6pPwnhyHtYE7tuflTjR/nEPzR+ibO64zV/ZYd2Pgd1MLVXVhVf19luNd6arqezR3V+3lfTTXuupTP9vH7Gaaz+grZmj3Wpqk8nVtHN8EfgA8s6PNu4HXz7Cdfq/nscANVfXJtvyWNqZn9/qv9/JKMg94IvDxzvKqOrn9vVQ0145+n/GRnIv283ERTbK+13X8bf+/vTuP1mw68zj+/REzEbQyLJGKKRE6QaygDVmNdKRbaCxKpUjSoVcGeqFbESoxRUVWIyVUCTGFxDxLhxJjQsdQRVQhhkZRIYhEJMZK4ek/nv2qU+ee973ve+uWquv+PmvVuvWecZ9pn3P2fvY+wNiGWee67/RgNFlYPhPYfCBpfq+KiGcj4t7y/5eBhyj7OCL+Wpl0GZqv02GZr81v7fLNiPhFRLxZft5J87XaznLkPexPZVmzIuKReU3rEPc68JDmRBiOIiuL+tPNeT8CeBl4pUzzSiufo/me8ivmvqe8Qxm1+QTwYGWdba/dhrRWn8/u72L7hpuxwHci4imAiHicLLCtRjhPAA4u72ntrAa8UJ6XiYgXIuLZ+ZTm9zwXKC2klKHu9wF/IKNL7iqj9geu6eeknwScVcIrx6kh9LmHdGwGvE3WUEK+OLfC/26pTX4s7QuN7gBmSfrHDqu7BPh8WfaJkjbuIolbAjNKhnIrWbs5qBaCY1Hd5/cB1WUsVQstHdUw/w7AVZXfg7HP7gU+2jB8AvCIMrz7q5XCqg2Ae2rTTgUam851aYOSjn5JWgFYl3wIaKfdNm1I37RXzSRrOfbuJi21dC0JbAZM7mGeRYATaX6Ja03zAeDzwE0Nowctf1hYRcQzZKHBTLKA8y/lIRCyNmuUpKmSrpO0bsMizgYOVTahPLbNNMOGstnzMxExrcNk78Y+mwSMkbR8m3S+n6w1frw2aiqZX7RcAmwiaZ0O62q3PX3ysvIy/yTQaXm9OokswHu7aaSyqdveNOcdg3YsJK0FrEVGIrXLxzeoz0ff+04361oK2I6McL6QLFyaV6Nq988h2dytTtnkf2Myaro1bLyk35Evukc0zOZ8bcH5CnBd5feHSxObX0rauj5xRLwIXAM8pWyyPabc+4e7i4A9S4H7W8ypKGppekfp5ryfBjwPzJB0TqsJVT/3lD7Pr5KWIQug+nSPUZlmJLVrt2ICcHN5NjmoPMsNNdX3kivnw/K7uQ/NIPdvU8V3y2RgbWUTwklN16F1z5nTQqpEd2xE1mh8StKG5cVvd6BPBEZt3uvJB8AzyBfk30haucckHFQevk4ARpXaUIAJEbFR+TdX4VBE3AbQ4aLsVOBERDxNhqIeRj5E36TSB0MHo8kbDOXvYDyA1tO1oI9FdZ9vxNw30Ner40r0UMv5kp4mb27VdA7GPlPTwIg4hnxgb0UwTa5MX68xbVzGQJUbwjRJUyqDt5Y0nWzO9j8R8VynRczD6r9LFvB0m6euXa6vPwEze4wS+gZwbUT8rmlkici5EDg5Ip6ojx+kc3KhVgoQdyab5KwOLCNprzJ6CTLCZFNyH5xdnz8i7iP30fHAisAUSeu/G2lf2EhaGhhH8wvqOwZhn7WLfHpneCm4OY9s0tOLev7zVknnYW0T0357mvKy1joGhaQdgT9ERKeC7FOBX7Xuu1WDdP6OKnnUhcBXywtuu3y8Oux4SU+QzQ6+2+M6dwRuKZEAlwO7VGqYm/Z5u3Om6uLa/XNqv3Ms5JSRcJcDB1YjkyJiXER8EDifrPCai/O1BUPSODLC8vwy6FlgzYjYmNKstRRczCUi9iULWO8moy/63KuGocnAZ8jn1osbxvd5R+nmvC+RpjuQ0fuPAhNU6QO0Qbv8/uiShnb9qjZeu5V0nEN2NXIp2az3Ts2H/vnms+p7yS5lWL/39x50cx+CvP8cSpvn8rL/NwG+Rj6LXyap54phSy5QWshFxEtkFMkOZIn2OsBjkp4EllabjsYi4sWIuCAi9gamkG28G5VarVbtXUsrU9666YG1g/Hky0dTmm4m+59pG8Zewnqvi4ixZGbwr+2mLQ+auwFHlP1xCvA5Scv1kN6uLcBjMVBjyBfqC8ia/cHcZxuTIbt9RMTjEfFD8kHoE5JWIkN/6zXDmzBvD/cPlmW01rtfWWe1cOS2iPg48PfA11XrnLym3TY9CHyyU0Ii4jGySd0e3SWdx8vLzTrA5iUCpJGkzSq1PTsBWwD7l+N3AtnUptoB94/IvktO6pDers/JIWp7MgrvhYiYDVwBtDoAfpp8oAO4EmjsXLOEvF8REd8gX44HPfpxiFibzEemlXNuDeBeSavWJ+xln0nar3Jer04+0K1Qm2w54KXasJOAfchmPfX1/xV4tUTVVG0C/LY27Cfkeb9muzS22Z4+eVl5GVyF7ENuMGwJ7FT290XAtpJ+WlnfkWQ+9589pr1Rw7GAOQUxm0VEq5a5XT5e3bdjyXztW8C5XWxr1Whg+7Ld9wArkX0xQd/zY0Wyf8dhpUSmXQ6cHxFXtJnsAvI+34fztXeXpC+RBaVjWhWz5Tm31ZTtHrJJ6XpN80fE/RExgSxEaTymw0lk86R7yO4SLu9n8up8/Z73ke6OiOOAPYHd+rmnTJW0SyXv3JSMOP/vkocdCBwuaX/o+tolIn4fEWdHxM5kQeSG3W7nQqzp/j7QPLyb+xAR8XAZtmu7BUXEmxFxS0QcARzQaVrrzAVKCyFJK2vO1yCWIl+OHo6In0fEqhExMiJGAq9FRJ8Qe0nbllplSkHB2mTTj0alVqtVezdPIpuVrEB23tlkPG36HJK0SethtoT2fpzs+K6d7YFpEfHBsk8+RGbWbQuhejWUj0VZ3mzywX7zUiMzz/tM0m5kp4QXNoz7F0mtmpt1yUiAl8iCj8M058t8I8mb7fED2rB0M7CkpK9Xhi3dNGFEPEr29XFo03hJnyb7TzqjYfRx5APCqmXaJdT8RZXxzN2Gu1+RzSW/SedIibsqtT3XRMSYiFiznHcHA+dFROvrfscCy5P7tlGv5+QQNZM855cu5+N2zCksvIrsBwfg02Rt5FwkbVminFB+KeRjdM6L3rPKC82ISl73NNm56FzRfr3us4iYVDmvf082R92pVbgtaVcyr3qrNt+LZJO1fdos+njg5JJfI2l7YCvyJbu6nNlk84LGa6XD9txEViB8sYxblGyCOjGyr7Z5FhGH+68HjwAACFNJREFURcQaZX/vCdwcEXuV9e0LfBYYHaUfsB7S3m599WPRTlM+fji5/dXlvU32g7SIuvz6aimU24qM3Gida/sxJ4L2Vkqz4rLP9wLqze7f00pedhbwUER8vzau2oxnJ/IjFPX5na+9iyTtQD5z7BSl/50yfOVW5F0pqFiX7HOnOu+yKl9KLjbCx6rlRODQVqFcf7o57yWtLmmTyqDq/m66p2wAXBYRV1byzqmRlfCt/Oskss+5iZ2u3Vo6dtCcr/6uShaqP9Nu+iFkCrBl5Tl6UzJavDHSvh8nAN+StGZZ1lrkdXZiw7TjadM9hKT1NXez90/ga2zAeu5E1t4VqwHnlhvOIsAlEdHVp8SLTwITJb1Z5j8zIqb0M0+3DtKcpiPQXBAxHri6aeaIuFbSC03jyE7xztCc8M67gYltpoV80Ky3z72c7HT3Jx3m68XCfCygtFWu/J7cKlxoiYjXlZ/bPpj8IlGnfba0splcS+vG1zruywAPANtGRNNx3JsMFX6NrFkZU14I75N0KPCzcnxHkl8kG3CNfkSEsvPDCZIOIfv5epU2hUbAaWQnfR8uv0dJ2ooshJpB1kb1iVAq5+wqwI3loSBobib1oKR7qURNdekq4CjNaSq6Xe0Y7B4Rd/S3EGWfAuPIF4l7S7nexIg4szbp/D4nF7iIuEvSZWS/WG8CvyEjtwC+RzYHPYjsgHPfhkWsDfywHO9FgJ/TQ23oUCXpQjLM/u/KOXhkRJzV5ezztM8iYrrys8K3Swqyz7qmYwP54NinSU9xClmpcb+kt8jmrju3Kew5i/bNsBu3p+Q7uwCTJH2bjBS6OCLG97+Vg+I08qH3jnKNXxHZ1LjftM/riiOimo8vBswGDolsUlKfNkoB9yHkl4v6sytZcFbtLPdqsjB/CeA75DZNI5s3TCYjDYaTLcl77P2V+/7hEXEt8D1JHyG7C3iKbMZRNyzztfmtQ745kXxpvqFcq3dGxNfIyMhjyj34LfJLtfVOvQUcIul0sjPqV8kPqQx7EfEglQ6va5reUbo57xcDTlBWar9BPk+2rqFTgA8A00u+tziwYUS80UOyO127Vf8E/EBSa9lj65U3Q1FEPC/pAOBaZcDAK/StFJkuqfX7kohojMCNiKnKZqTXKrt4mA38V0Q80DDttHLPaOqvdVmyoHB58jp8hOYP81gXFDGQ5otmZgOnbKK1GfDZKF9YMDMbaiT9AxmtuWt07vPIzMyGMGUfSFcCUyKivy+Fmg0bLlAyMzMzMzMzM7OeuA8lMzMzMzMzMzPriQuUzMzMzMzMzMysJy5QMjMzMzMzMzOznrhAyczMzMzMzMzMeuICJTMzMxu2JH1Z0j2SXpb0Z0m/kfT9yvgRko6SNHIAy168zLtRbfhISSFpx3nfAjMzM7MFwwVKZmZmNixJOgw4E7ge2BX4InA1sFNlshHAkcDIAaxi8TLvRrXhzwJbALcPYJlmZmZmC4X3LegEmJmZmS0g+wOnR8ThlWE/k3T0/FxpRMwC7pyf6zAzMzOb3xyhZGZmZsPVB4Dn6gMjIiCbpgH3l8G3lGZqrXHLSJoo6RFJr0maIWmSpPdXFvVy+XtOa97S3K1PkzdJi5bmcTMlzZL0oKQvVNMl6ceSpkr6jKTpkl6VdLukDWrT7VPmf13SHyX9sj6NmZmZ2bxygZKZmZkNV/cC/yHpS5JWahj/LDCm/H8/spnaFuX30sCiwDjgc8C3gW2BSyvzb1v+HluZ99k2aTmmLOtHZJO7/wXOlzS6Nt2awPHAeGA02STvEkkCkLQNcBrw05KurwC/BpZvtxPMzMzMBsJN3szMzGy42g+4CvgxEJIeAi4HToiIv0bELEnTy7S/jYh3mqlFxAvA11u/Jb0PmAHcLmnNiJgJTCmjH6/OW8p+qPxeETgQODYiji2Dr5e0BnAUcGFl8hWBLSPi/8q8iwBXAh8BHgY+BUyPiOMq81zT014xMzMz64IjlMzMzGxYiojpwPpkRNCpgMhIo6mSlu1vfkl7l6/CvQLMZk4n2+v1mJQNyYinS2vDLwbWkzSiMuzJVmFS8dvyd43y9z5gY0kTJG0jafEe02JmZmbWFRcomZmZ2bAVEbMi4mcRsX9EfAzYF1gX2KfTfJJ2Ac4D7gB2BzYHdimjl+wxGauVv8/Xhrd+r1AZ9lJtmr9V1xkRNwL/BmwD3Ar8UdKpkpbpMU1mZmZmHblAyczMzKyIiLOAF4GP9jPp7sBdEfGNiLguIu4C/jzA1bb6VRpRG75K+ftiLwuLiHMj4pNl/rHAl8nIKzMzM7NB4wIlMzMzG5ZqTclaw1YmO7BuRQfNFQFUsRQwqzZsTO13u3nrHgBeIwupqvYAHi39NfUsIl6IiNOB24CPDWQZZmZmZu24U24zMzMbru6XdDXwC+APwIeAg8nCnXPLNDOB14EvSfoLMDsipgI3AJMkjQPuAv4Z2K668Ij4m6QZwB6SHgDeAKZTExEvSjoJ+JakN4GpwK5lmfWvvHUk6Wiy4+5bgT8CGwOfBr7Zy3LMzMzM+uMCJTMzMxuujgF2Bk4mC2GeA34NjIqIGQAR8YakfweOBH4JLEZ23n06sBZwABmBdAPwBeDO2jq+BpwA3AgsAXy4TVqOAN4kvxy3CvAYsFdEXNTjNk0BDgL2BJYDniK/FPeDHpdjZmZm1pEiYkGnwczMzMzMzMzMhhD3oWRmZmZmZmZmZj1xgZKZmZmZmZmZmfXEBUpmZmZmZmZmZtYTFyiZmZmZmZmZmVlPXKBkZmZmZmZmZmY9cYGSmZmZmZmZmZn1xAVKZmZmZmZmZmbWExcomZmZmZmZmZlZT1ygZGZmZmZmZmZmPfl/ZR13CLh1L0IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "plt.bar(x=station_totals.index[:10], height=station_totals[:10], color='crimson')\n",
    "plt.xlabel('Stations', fontsize=15)\n",
    "plt.ylabel('Total of Entries & Exits', fontsize=15)\n",
    "plt.title('Top 10 Stations with the Highest Daily Traffic', fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top Stations Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "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>STATION</th>\n",
       "      <th>DAILY_ENTRIES</th>\n",
       "      <th>DAILY_EXITS</th>\n",
       "      <th>TOTAL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>34 ST-PENN STA</td>\n",
       "      <td>4893954.0</td>\n",
       "      <td>6554273.0</td>\n",
       "      <td>11448227.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>34 ST-HERALD SQ</td>\n",
       "      <td>3760882.0</td>\n",
       "      <td>5030650.0</td>\n",
       "      <td>8791532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>GRD CNTRL-42 ST</td>\n",
       "      <td>3513460.0</td>\n",
       "      <td>5084956.0</td>\n",
       "      <td>8598416.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>86 ST</td>\n",
       "      <td>3198710.0</td>\n",
       "      <td>4411253.0</td>\n",
       "      <td>7609963.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>14 ST-UNION SQ</td>\n",
       "      <td>3045658.0</td>\n",
       "      <td>4414206.0</td>\n",
       "      <td>7459864.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>374</td>\n",
       "      <td>BEACH 98 ST</td>\n",
       "      <td>23608.0</td>\n",
       "      <td>36772.0</td>\n",
       "      <td>60380.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>375</td>\n",
       "      <td>BEACH 105 ST</td>\n",
       "      <td>15757.0</td>\n",
       "      <td>26237.0</td>\n",
       "      <td>41994.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>376</td>\n",
       "      <td>TOMPKINSVILLE</td>\n",
       "      <td>31864.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>31866.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>377</td>\n",
       "      <td>BROAD CHANNEL</td>\n",
       "      <td>12793.0</td>\n",
       "      <td>7861.0</td>\n",
       "      <td>20654.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>378</td>\n",
       "      <td>ORCHARD BEACH</td>\n",
       "      <td>595.0</td>\n",
       "      <td>484.0</td>\n",
       "      <td>1079.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>379 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             STATION  DAILY_ENTRIES  DAILY_EXITS       TOTAL\n",
       "0     34 ST-PENN STA      4893954.0    6554273.0  11448227.0\n",
       "1    34 ST-HERALD SQ      3760882.0    5030650.0   8791532.0\n",
       "2    GRD CNTRL-42 ST      3513460.0    5084956.0   8598416.0\n",
       "3              86 ST      3198710.0    4411253.0   7609963.0\n",
       "4     14 ST-UNION SQ      3045658.0    4414206.0   7459864.0\n",
       "..               ...            ...          ...         ...\n",
       "374      BEACH 98 ST        23608.0      36772.0     60380.0\n",
       "375     BEACH 105 ST        15757.0      26237.0     41994.0\n",
       "376    TOMPKINSVILLE        31864.0          2.0     31866.0\n",
       "377    BROAD CHANNEL        12793.0       7861.0     20654.0\n",
       "378    ORCHARD BEACH          595.0        484.0      1079.0\n",
       "\n",
       "[379 rows x 4 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stations_all = station_daily.groupby('STATION',as_index = False).sum().sort_values('TOTAL',ascending=False).reset_index(drop=True)\n",
    "stations_all"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 Total VS Entries VS Exits per Station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ind = np.arange(10) \n",
    "width = 0.25\n",
    "plt.figure(figsize=(20,5)) \n",
    " \n",
    "bar1 = plt.bar(ind, stations_all.TOTAL[:10], width, color = 'crimson')\n",
    "bar2 = plt.bar(ind+width, stations_all.DAILY_EXITS[:10], width, color='orange')\n",
    "bar3 = plt.bar(ind+width*2, stations_all.DAILY_ENTRIES[:10], width)\n",
    "  \n",
    "plt.xlabel(\"Stations\", fontsize=15)\n",
    "plt.ylabel('Number of People', fontsize=15)\n",
    "plt.title(\"Traffic per Station\", fontsize=20)\n",
    "\n",
    "plt.xticks(ind+width,stations_all.STATION[:10])\n",
    "plt.legend((bar1, bar2, bar3),('Total', 'Exits', 'Entries'))\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top 10 Stations Daily"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['34 ST-PENN STA', '34 ST-HERALD SQ', 'TIMES SQ-42 ST', '125 ST',\n",
       "       '86 ST', '42 ST-PORT AUTH', 'GRD CNTRL-42 ST', '14 ST-UNION SQ',\n",
       "       '23 ST', 'FULTON ST'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_stations = list(stations_all.STATION[:10])\n",
    "top_stations_daily = station_daily[(station_daily.STATION == top_stations[0])\n",
    "                                   |(station_daily.STATION == top_stations[1])\n",
    "                                   |(station_daily.STATION == top_stations[2])\n",
    "                                   |(station_daily.STATION == top_stations[3])\n",
    "                                   |(station_daily.STATION == top_stations[4])\n",
    "                                   |(station_daily.STATION == top_stations[5])\n",
    "                                   |(station_daily.STATION == top_stations[6])\n",
    "                                   |(station_daily.STATION == top_stations[7])\n",
    "                                   |(station_daily.STATION == top_stations[8])\n",
    "                                   |(station_daily.STATION == top_stations[9])]\n",
    "top_stations_daily.STATION.value_counts().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>STATION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAILY_ENTRIES</th>\n",
       "      <th>DAILY_EXITS</th>\n",
       "      <th>TOTAL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>999</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>14269.0</td>\n",
       "      <td>20181.0</td>\n",
       "      <td>34450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1000</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>18372.0</td>\n",
       "      <td>24021.0</td>\n",
       "      <td>42393.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1001</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>30012.0</td>\n",
       "      <td>36055.0</td>\n",
       "      <td>66067.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1002</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>30748.0</td>\n",
       "      <td>36784.0</td>\n",
       "      <td>67532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1003</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-06-03</td>\n",
       "      <td>29174.0</td>\n",
       "      <td>34890.0</td>\n",
       "      <td>64064.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39260</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-13</td>\n",
       "      <td>28832.0</td>\n",
       "      <td>40016.0</td>\n",
       "      <td>68848.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39261</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-14</td>\n",
       "      <td>30344.0</td>\n",
       "      <td>42119.0</td>\n",
       "      <td>72463.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39262</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-15</td>\n",
       "      <td>31647.0</td>\n",
       "      <td>41689.0</td>\n",
       "      <td>73336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39263</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-16</td>\n",
       "      <td>28532.0</td>\n",
       "      <td>38668.0</td>\n",
       "      <td>67200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39264</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-17</td>\n",
       "      <td>30495.0</td>\n",
       "      <td>42970.0</td>\n",
       "      <td>73465.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1110 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              STATION       DATE  DAILY_ENTRIES  DAILY_EXITS    TOTAL\n",
       "999            125 ST 2021-05-30        14269.0      20181.0  34450.0\n",
       "1000           125 ST 2021-05-31        18372.0      24021.0  42393.0\n",
       "1001           125 ST 2021-06-01        30012.0      36055.0  66067.0\n",
       "1002           125 ST 2021-06-02        30748.0      36784.0  67532.0\n",
       "1003           125 ST 2021-06-03        29174.0      34890.0  64064.0\n",
       "...               ...        ...            ...          ...      ...\n",
       "39260  TIMES SQ-42 ST 2021-09-13        28832.0      40016.0  68848.0\n",
       "39261  TIMES SQ-42 ST 2021-09-14        30344.0      42119.0  72463.0\n",
       "39262  TIMES SQ-42 ST 2021-09-15        31647.0      41689.0  73336.0\n",
       "39263  TIMES SQ-42 ST 2021-09-16        28532.0      38668.0  67200.0\n",
       "39264  TIMES SQ-42 ST 2021-09-17        30495.0      42970.0  73465.0\n",
       "\n",
       "[1110 rows x 5 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_stations_daily"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "green = sns.color_palette()[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>STATION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>DAILY_ENTRIES</th>\n",
       "      <th>DAILY_EXITS</th>\n",
       "      <th>TOTAL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>999</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>14269.0</td>\n",
       "      <td>20181.0</td>\n",
       "      <td>34450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1000</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-05-31</td>\n",
       "      <td>18372.0</td>\n",
       "      <td>24021.0</td>\n",
       "      <td>42393.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1001</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>30012.0</td>\n",
       "      <td>36055.0</td>\n",
       "      <td>66067.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1002</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>30748.0</td>\n",
       "      <td>36784.0</td>\n",
       "      <td>67532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1003</td>\n",
       "      <td>125 ST</td>\n",
       "      <td>2021-06-03</td>\n",
       "      <td>29174.0</td>\n",
       "      <td>34890.0</td>\n",
       "      <td>64064.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39260</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-13</td>\n",
       "      <td>28832.0</td>\n",
       "      <td>40016.0</td>\n",
       "      <td>68848.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39261</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-14</td>\n",
       "      <td>30344.0</td>\n",
       "      <td>42119.0</td>\n",
       "      <td>72463.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39262</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-15</td>\n",
       "      <td>31647.0</td>\n",
       "      <td>41689.0</td>\n",
       "      <td>73336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39263</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-16</td>\n",
       "      <td>28532.0</td>\n",
       "      <td>38668.0</td>\n",
       "      <td>67200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39264</td>\n",
       "      <td>TIMES SQ-42 ST</td>\n",
       "      <td>2021-09-17</td>\n",
       "      <td>30495.0</td>\n",
       "      <td>42970.0</td>\n",
       "      <td>73465.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1110 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              STATION       DATE  DAILY_ENTRIES  DAILY_EXITS    TOTAL\n",
       "999            125 ST 2021-05-30        14269.0      20181.0  34450.0\n",
       "1000           125 ST 2021-05-31        18372.0      24021.0  42393.0\n",
       "1001           125 ST 2021-06-01        30012.0      36055.0  66067.0\n",
       "1002           125 ST 2021-06-02        30748.0      36784.0  67532.0\n",
       "1003           125 ST 2021-06-03        29174.0      34890.0  64064.0\n",
       "...               ...        ...            ...          ...      ...\n",
       "39260  TIMES SQ-42 ST 2021-09-13        28832.0      40016.0  68848.0\n",
       "39261  TIMES SQ-42 ST 2021-09-14        30344.0      42119.0  72463.0\n",
       "39262  TIMES SQ-42 ST 2021-09-15        31647.0      41689.0  73336.0\n",
       "39263  TIMES SQ-42 ST 2021-09-16        28532.0      38668.0  67200.0\n",
       "39264  TIMES SQ-42 ST 2021-09-17        30495.0      42970.0  73465.0\n",
       "\n",
       "[1110 rows x 5 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_stations_daily"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(y='TOTAL', x='STATION', data=top_stations_daily, color=green, height=5, aspect=3)\n",
    "plt.xlabel(\"Stations\", fontsize=15)\n",
    "plt.ylabel('Total of Entries & Exits', fontsize=15)\n",
    "plt.title(\"Total of Entries & Exits per Station\", fontsize=20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#boxplots show more details -> min, max, outliers, and quartiles\n",
    "plt.figure(figsize=(20,5))\n",
    "sns.boxplot(y='TOTAL', x='STATION', data=top_stations_daily, color=green)\n",
    "plt.xlabel(\"Stations\", fontsize=15)\n",
    "plt.ylabel('Total of Entries & Exits', fontsize=15)\n",
    "plt.title(\"Total of Entries & Exits per Station\", fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unique Turnstile Per Station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "turnstiles_per_station = turnstiles_df.groupby(['STATION'])[\"UNIQUE_TURNSTILE\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "turnstiles_per_station.sort_values(ascending=False, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STATION\n",
       "34 ST-PENN STA     102\n",
       "FULTON ST           96\n",
       "GRD CNTRL-42 ST     94\n",
       "23 ST               73\n",
       "86 ST               65\n",
       "                  ... \n",
       "HARLEM 148 ST        3\n",
       "190 ST               3\n",
       "ATLANTIC AV          3\n",
       "CLEVELAND ST         2\n",
       "SUTTER AV            2\n",
       "Name: UNIQUE_TURNSTILE, Length: 379, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "turnstiles_per_station"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Top 10 Total Unique Turnstile Per Station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "plt.bar(x=turnstiles_per_station.index[:10], height=turnstiles_per_station[:10], color='skyblue');\n",
    "plt.xlabel('Stations', fontsize=15)\n",
    "plt.ylabel('Number of unique turnstiles', fontsize=15)\n",
    "plt.title('Top 10 Total Unique Turnstile Per Station', fontsize=20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Percentage\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.pie(turnstiles_per_station[:10], labels = turnstiles_per_station.index[:10], \n",
    "        colors = sns.color_palette('Blues')[:10], autopct='%.1f%%');\n",
    "plt.title('Percentage of Top 10 Total Unique Turnstile Per Station', fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily Entries VS Daily Exits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "sns.scatterplot(data=stations_all, x=\"DAILY_ENTRIES\", y=\"DAILY_EXITS\")\n",
    "plt.title('Daily Entries VS Daily Exits', fontsize=20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+iZVcQ0RERERERERENgaLNsuTKxkcHHQNXRcRERERERERaRwze8TdB+OeW6uWQBERERERERERkboosBIRERERERERkQ1FgZWIiIiIiIiIiGwoCqxERERERERERGRDUWAlIiIiIiIiIiIbSmq9b0BERERERERERK4P7s5cscxcoXzFdQqsRERERERERESkKYqlMrlimblCiVyxTL5Yxt0xsyu+ToGViIiIiIiIiIisWm31VK5YYq5Qpli+ciXVUhRYiYiIiIiIiIhscEeGx7n/oZOcnphh77YO7r7tALf396zrPRVKZeaKZXKFEnM11VONoMBKRERERERERGQDOzI8zj2Hj5FOGlvb04xnc9xz+Bj3wpqFVpXqqUo4tZrqqXoosBIRERERERER2cDuf+gk6aTR0RLFOB0tKWbyRe5/6GTTAqtCqSacanD1VD0UWImIiIiIiIiIbGCnJ2bY2p5ecKw9neTMxExDzl8uh9lTxRK5QvRYKq9dOBVHgZWIiIiIiIiIyAa2d1sH49lctcIKYLZQYs+2jhWdLx/CqUqLX77YvNa+OLlCicfOTl9xjQIrEREREREREZEN7O7bDnDP4WPM5Iu0p5PMFkoUSs7dtx246mvXu3qqVHaeujDD8Mgkw6NZhkaynDw3xdVuQYGViIiIiIiIiMgGdnt/D/cSzbI6MzHDnivsEphfFE6tdfXU2excCKaigOrRsSwz+dKyz6PASkRERERERERkg7u9v+eygKpSPTU/HH1tq6dm8kWOj2arlVPDo5Ocm8rHru1uSzHQ101/byZ67OvmW35r6XMrsBIRERERERER2QTyxTK5Yom5QhRSFUprVz1VKjtPnJtmeHSSoZGogurJ8zPExWPppHGwJ0N/X4aB3m4G+jL0bWnDzKprar+Oo8BKRERERERERGSDKZU9GoxemA+pyr421VPuzlh2juGRSmvfJI+OTTG3RHvhvu0dDPRlqtVTN+3sJJ1MrOoeFFiJiIiIiIiIiKyz2l375grlNa2emsoVo8qp0SzDobVvYqYQu3ZbR5qBvu4QUHVzqDdDV2vj4yUFViIiIiIiIiIia6hSPVUZjL6W1VOFUpnHz05F1VOjWYZHJjk9MRu7ti2V4ODuDAN9mer8qZ5M61Xb+RpBgZWIiIiIiIiISBMtDqfWqnrK3Xn6Yo6h0ckQUE3y2PgUhdLl4VjCYP/Ozqitr7eb/r4M+3d0kkw0P5yKo8BKRERERERERKRBSmWv7tqXK5TIF9eueuriTJ7h0NY3NDrJ8GiWbK4Yu7Yn00p/aOsb6Mtwa0+G9pbkmtxnPRRYiYiIiIiIiIisgLszVyxHv0JItVbVU3OFEifGp6ptfcOjWUYu5WLXdrYkOdQ739bX35thR1frmtznSimwEhERERERERGpQ7FUnh+MHoIqX4PqqbI7T12Yma+cGsly8tw0pfLl104mjAM7O2sGo2fYu72DxBrMnWokBVYiIiIiIiIiIotUq6fC7KlcoUyxvDbVU+en5hgKu/UNjWY5PpplJl+KXdu3pS2qmurrZqA3w8GeLlrTG6e1ryJhRms6QWsqSUsqQWsqccX1CqxERERERERE5LpXLJXJhda+XLFMfo2qp2bzJR4dyzIU2vqGRrKcnZqLXdvdlqqGU5Xh6Fs60k2/x+WqhFMtyQSt6SStqQTp5JUDqsWaHliZ2VbgvcA3Ag78JHAc+AiwHzgF/JC7T1i0L+J9wMuAGeDV7v6VcJ5XAf81nPbt7v6BcPzZwPuBduBvgde7u5vZ9uVeQ0RERERERESufetVPVUqO6fOT1erp4ZHspw6P01MZx/ppHGwp6s6FL2/t5sbtrZhG6y1L2FWrZiKHqMKqtVaiwqr+4BPuvsPmlkL0AH8KvBZd3+Hmb0JeBPwRuClwMHw67nAe4DnhvDpLcAgUej1iJkddveJsOYu4ItEgdVLgE+Ec9Z9jeb/GERERERERERkPRQWzZ5ai+opd2c8W9PaN5LlxFiWXDE+GNu3vSOqmgrh1IFdncuuSmo2qwmnWhsYTsVpamBlZt3AbcCrAdw9D+TN7A7g9rDsA8ARojDpDuCDHn1qvmhmW82sL6z9tLtfCOf9NPASMzsCdLv7P4XjHwS+nyiwWtY13H2kKT8EEREREREREVkzleqp6mD0NaqemsoVOb6gtW+SiZlC7NptHenqjn0Dfd0c2p2hq21jTW2yyyqnoha/tarwavZP4wBwFvhTM/sm4BHg9cDuSkDk7iNm1hPW3wicrnn9mXDsSsfPxBxnBddQYCUiIiIiIiKyyRRK8+FUrlCiUPKmV08VSmVOnp2uVk4Nj2Z56sJM7Nq2VIKDu+crpwb6MvRkWjdUa5+ZkU4aralkGIy+tuFUnGYHVingWcDPu/uXzOw+ota8pcT9JHwFx6+krteY2V1ErYbs27fvKqcUERERERERkWYrl8PsqTB3aq5YohQ3AKqB3J2nL+aqO/YNj0xyYnyKQuny6yYM9u/oXLBr3/6dnSQTGyecAmipmTdVae/bSAEaND+wOgOccfcvhe8/RhRYjVXa8ELL33jN+r01r98DPB2O377o+JFwfE/MelZwjQXc/QHgAYDBwcHmbwsgIiIiIiIiIgvkF4VT+SXmPzXSpZkCQ6NRW99waO+bzBVj1+7qaqW/L8NAaO27dXeG9pZk0+9xOdLJRKia2rjhVJymBlbuPmpmp83skLsfB14IfC38ehXwjvD48fCSw8BrzexBokHol0Lg9CngN8xsW1j3YuDN7n7BzLJm9jzgS8Argd+vOVfd12jWz0BERERERERErm49qqfmCiUeOztVbesbGplk5FIudm1HS5JDvVE41d/bTX9fhp1drU29v+VKJ+eHobemo7a+xAar7qrXWkz0+nngQ2GHwJPATwAJ4KNm9hrgKeDlYe3fAi8DHgNmwlpCMPU24OGw7t7KAHbgZ4H3A+1Ew9Y/EY6/YznXEBEREREREZG1ky+WyRVLzK1R9VTZndMXZkIwFe3c9/jZ6dhQLGFwYFfXgrlT+7Z3kNhAlUm14VRlKPpmDafiWLMHkV0LBgcH/ejRo+t9GyIiIiIiIiKbUrnsNeFUNBy93OQ84sJ0nqGRyequfcdHs0znS7Fr+7a0LZg7dUtPF23pjdPal07O79RXCag22lyslTCzR9x9MO65jbVnooiIiIiIiIhsenPFaNe+uUJl577mVk/N5ks8Oj5fOTU8kmU8Oxe7NtOWisKpMHfqUG+GbR0tTb2/5UglEvM79YWA6loIp5ZLgZWIiIiIiIiIrFip7AvmTs0Vyk2tniqVnSfPTzM0kq0ORz91bpq4cVfppHFLTxeHdkfh1EBfhhu3tm+YoeOpRE3lVPr6DafiKLASERERERERkbpVqqdyhSicamb1lLtzNjvHUNixb2g0y6NjWXKF+Gvu2dbOQF93qJ7KcGBnFy2pRNPubzmSCavu1FcJqVLJjXFvG5ECKxERERERERGJtdbVU1NzRR4dDZVTI1mGRrNcmM7Hrt3anqa/L1MNqPp7M2Ta0k27t+VIJqzazteqcGpFFFiJiIiIiIiICO5OvlReEE41s3qqWCpz8tz0grlTT12YIS4Oa00luHV3V3XHvv6+bnZnWjdEa1/CjNZ0gpZkgtZ0FFClFU6tmgIrERERERERketQqexRW1+lva9YxptUPeXuPH0pF6qmonDqxHiWQuny6xmwf2dnta2vv7ebm3Z2bojZTgmzmplTSVrC7n3SeAqsRERERERERK5x7h7t2lcsMxfCqWZWT12aLVSrpirzpyZzxdi1O7taFrT1HerN0NGy/nGFmS2YN9WaSiqcWkPr/wkQERERERERkYYqlsrkasKpZlZP5YtlHhufqpk7NcnTF3Oxa9vTSQ7VVE7192bYlWltyn0th9VWTlVDquR639Z1TYGViIiIiIiIyCZWrZ4Ks6dyhTLFcnOqp8runLkwy/DoJEMhnHr87DSl8uVhWMLgwM6uEE5Fc6f2be9Y99a+SjgVzZwKAVUysSHmYck8BVYiIiIiIiIim0ht9VSuWCbfxOqpC9N5hkYmGQ5tfcNjWabnSrFre7vbFsydOri7i7b0+lYpmRnppEW79VUGo6cUTm0GCqxERERERERENqja6qlc2LmvWdVTs4USJ8ayYde+LEMjk4xn52LXdrWmQtVUhoHebg71Ztje2dKU+1qOlpp2vkp7n8KpzUmBlYiIiIiIiMgGUSiVF+za16zqqVLZeerCTLV6amhkkifOTRPT2UcqYdzS01Vt6+vvzbBnWzuJdQ6C0pWWvmSy2tqncOraocBKREREREREZB1Uqqcq4VSuUIqdBdWI65ybyi8Ip46PZckV4iu19mxrDzv2dTPQl+HmXV3rvjteOjm/U1+ltS+xzrOwpLkUWImIiIiIiIisgUJpYThVKHlTqqem54ocH8tWd+wbHslyfjofu3Zre5r+MBR9oK+bQ7szdLenG35Py1EJp2pb+xROXX8UWImIiIiIiIg0WLkcZk+FXfvmis2pniqWypw8N12tnBoezfLU+RnirtSSSnBrTxcDoa2vvy9Db3fburbRpRLzO/W1ppK0pBLrvougbAwKrERERERERERWKb8onMoXGz8Y3d0ZuZRbEE6dGJ+KvZYB+3Z0MBDa+vp7M9y0s5NUcv1a+1KJStVUJaRKKpySJSmwEhEREREREVmGSvVUpb2vWdVTk7MFhkezDI9OVnfuuzRbiF27o6uFgd7u0NqX4dbdGTpb1++v/MmEze/UF2ZOrWdYJpuPAisRERERERGRK8gXy+SKJeYKldlTja+eyhfLPH52qmYwepavX5yNXduWTlSHovf3ZRjo7WZXprXh91SvZMIWzJtqTSmcktVTYCUiIiIiIiISlMs+H06Fx3KDB6OX3TkzMcvwyCRDo1Hl1OPjUxRjqrQSBjft7KzOnRro62bf9o51a6VLmFXb+SrtfWmFU9IECqxERERERETkujVXnN+1b65Qbkr11MRMfkHl1PHRLFNzxdi1u7tb6a+ZO3Vwd4b2dLLh91SPhFnNzKmkwilZUwqsRERERERE5LpQKvuCwejNqJ7KFUqcGJuqzp0aGp1kbHIudm1na5L+3Rn6+yoBVTfbO1saej/1qg2nWmp27BNZLwqsRERERERE5Jq0OJxqdPVUqew8dWGG4ZrqqZPnpoibv55KGDf3dFXb+vp7M+zZ1k7C1r61z2orpxROyQalwEpEREREREQ2vVLZF+za14zqqbPZOYZGJxkeiXbuOz46xWyhFLt2z7b2MBg9Cqhu3tW1LqFQJZxqSSbC7Knoa1uHoExkORRYiYiIiIiIyKbi7iGYKjMXQqpGV0/N5IscD1VTw6NRa9/5qXzs2i3t6erMqf7ebg71ZtjSnm7o/dTDzEgnLdqtLx1CqpTCKdmcFFiJiIiIiIgs05Hhce5/6CSnJ2bYu62Du287wO39Pet9W9esYqk8Pxg9BFXewOqpYqnME+emq219w6OTPHl+hrgrtKQSHOzpqs6cGujL0Nvdti6hUEvNvKlKe5/CKblWKLASERERERFZhiPD49xz+BjppLG1Pc14Nsc9h49xLyi0aoBq9VSYPZUrlCmWG1c95e6MTuYYDgPRh0eynBifYq54+TUM2Lejo1o5NdCX4cDOTlLrsFNeutrSp3BKrg9ND6zM7BSQBUpA0d0HzWw78BFgP3AK+CF3n7Dof233AS8DZoBXu/tXwnleBfzXcNq3u/sHwvFnA+8H2oG/BV7v7r6Sa4iIiIiIiFzN/Q+dJJ00Olqiv051tKSYyRe5/6GTmzKwWu9qsWKpTC609uWKZfINrp7K5goMj2YXBFQXZwuxa7d3tjBQMxT91t4MXa1rX+eRTs4PQ6+09iUSCqfk+rJW/8t7gbufq/n+TcBn3f0dZvam8P0bgZcCB8Ov5wLvAZ4bwqe3AIOAA4+Y2WF3nwhr7gK+SBRYvQT4xHKv0cw3LyIiIiIi147TEzNsXTSfqD2d5MzEzDrd0cqtdbVYs6un8sUyj5+dqrb1DY9mOTMxG7u2LZ3g0O7Mgl37dmVa17xqqTacquzcp3BKZP1aAu8Abg9ffwA4QhQm3QF80KM4/YtmttXM+sLaT7v7BWTKZsQAACAASURBVAAz+zTwEjM7AnS7+z+F4x8Evp8osFrWNdx9pInvV0RERERErhF7t3Uwns1VK6wAZgsl9mzrWMe7WplmV4sVSvOD0RtdPeXunJmYDXOnonDq8bNTFEqXnz9hsH9nJwO93SGgyvCMHZ0k1zgYSicT1VCqElCt9T2IbBZrEVg58Hdm5sD97v4AsLsSELn7iJlV/p/wRuB0zWvPhGNXOn4m5jgruIYCKxERERERuaq7bzvAPYePMZMv0p5OMlsoUSg5d992YL1vbdkaWS1WWz2VK5aYa3D11MWZfLVyamgky/GxLNlcMXZtT6aV/r5MFFD1Zbh1d4b2dLJh91KPVKIyc2p+MLrCKZH6rUVg9e3u/nQIjD5tZsNXWBv3v15fwfErqes1ZnYXUash+/btu8opRURERETkenF7fw/3ElUnnZmYYc8m3iVwNdVihdLCXfsaWT2VK5R4bHyKodEsw6F6auRSLnZtZ0syGore111t79ve2dKQ+6hXKlFTOZVWOCXSCE0PrNz96fA4bmZ/DTwHGKu04YWWv/Gw/Aywt+ble4Cnw/HbFx0/Eo7viVnPCq6x+L4fAB4AGBwcbNzEPxERERER2fRu7+/ZlAHVYvVWi5XLoXqqGAVUuUKJUrkxf00qlZ2nLsyEweiTDI1mOXl2irjTpxLGzbu6qm19/b3d7NneTmIN504lE7Zg3lRrKrEuuwaKXOuaGliZWSeQcPds+PrFwL3AYeBVwDvC48fDSw4DrzWzB4kGoV8KgdOngN8ws21h3YuBN7v7BTPLmtnzgC8BrwR+v+ZcdV+jST8CERERERGRDWuparHn37KTbK5QDafyxca19p2bmlvQ2vfoWJaZfCl27Q1b2+jv7WYgtPfd0tNFS2rtwqFkwqrtfJXWvrTCKZE10ewKq93AX4ddFlLAh939k2b2MPBRM3sN8BTw8rD+b4GXAY8BM8BPAIRg6m3Aw2HdvZUB7MDPAu8H2omGrX8iHH/Hcq4hIiIiIiJyPbrt1l0898CO6q59c8VSw3Y8nMkXeXRsqjoUfWhkknNT+di13W2p6m59/aF6asui+VrNlDCjNZ2gJZmgNR0FVAqnRNaPNarH+Fo2ODjoR48eXe/bEBERERERWbV8aO2rhFONqp4qlZ0nzk1XK6eGR7OcOjcdO2Q4nTQO9sy39Q30Zejb0oatUWtfwqxm5lSSlrB7n4isLTN7xN0H455bi6HrIiIiIiIisg4qs6fmh6M3ZvaUuzM2OVcTTk3y6NgUc0uEX8/Y3lGtmhroy3BgZ+eazX0ys5qd+hLV+VMisrEpsBIREREREblGVIaizxWikKpQakz1VDZXiIaih7a+46NZJmYKsWu3daQZ6OuuVk8d6s3Q1bo2f/W02sqpakiVXJNri0hjKbASERERERHZhEpljwKqQplceCw3YORLvljm5Lmpalvf0MgkZyZmY9e2pRLc2pvh0O5MNaTqybSuSWtfJZyKZk6FgCqZWLO2QhFpLgVWIiIiIiIim0CleipXiMKpRlRPuTtfvzgbgqmote+x8SkKpcuDr4TB/h2dC1r79u/oJJlYm3AqnbRot77KYPSUwimRa5kCKxERERERkQ2mUj1VGYzeqOqpizP5qLUvhFPDo1kmc8XYtbu6WqO2vr5uBnoz3Lo7Q3vL2rTXtdS081Xa+xROiVxfFFiJiIiIiIisI3cnXyovCKcaUT01VyhxYnyq2tY3PJpl5FIudm1nS5JDvVFbX39vhv7eDDu6Wld9D/VIV1r6kslqa5/CKRFRYCUiIiIiIrKGSmWv7tpXefRVVk+V3XnqwgzDI1mGRicZHsly8tx07I6AyYRx867Oaltff2+Gvds7SKxBSJROzu/UV2ntS6xBS6GIbD4KrERERERERJrE3aNd+4pl5kI41YjqqfNTc9WZU0OjWR4dzTKdL8Wu7dvStqBy6mBPF63p5rf2VcKp2tY+hVMiUi8FViIiIiIiIg1SLJUXVE41onpqNl/i0bH5tr6hkSxnp+Zi13a3paJgKgRUA73dbOlIr+r69Ugl5nfqa00laUkl1mQYu4hcuxRYiYiIiIiIrEC1eirMnsoVyhTLq6ueKpWdU+emq219Q6NZnjw/TUxnH+mkcbCnqzoUvb+vmxu2tDV9/lMqUamaqoRUSYVTItJwCqxERERERETqUCyVyYXWvlyxTH6V1VPuzlh2LgqmQvXUibEsuWJ86LV3W3u1tW+gr5sDuzpJJxMrvn49kgmb36kvzJxKNfmaIiKgwEpEREREROQyzaiemsoVGR6db+sbHp1kYqYQu3ZbR3rBUPT+3m662pr717dkwhbMm2pNKZwSkfWjwEpEREREZJM5MjzO/Q+d5PTEDHu3dXD3bQe4vb/nurl+MzS6eqpQKnPy7HTN3KlJTk/Mxq5tSyU4uDtTrZzq78uwO9Pa1Na+hFm1na/S3tfsai0RkeVQYCUiIiIisokcGR7nnsPHSCeNre1pxrM57jl8jHthTUKj9b5+I9RWT+WKJeZWWT3l7jx9KcfwyGS1curE+BSF0uWBlwH7d3aGmVPRUPT9OzubOgMqYVYzcyqpcEpENgUFViIiIiIim8j9D50knTQ6WqI/yne0pJjJF7n/oZNrEhit9/VXorBo577VVk9dmikwPFYJp7IMj0wymSvGrt3V1Up/33z11K27u6o/u2aoDadaanbsExHZbBRYiYiIiIhsIqcnZtjanl5wrD2d5MzEzHVx/aupVE9VwqnVVk/li2VOjGcXzJ16+mIudm1HS5JDvZmoeqo3au3b2dW64mtfjdVWTimcEpFrjAIrEREREZFNZO+2DsazuQVVOrOFEnu2dVwX11+sUKoJp1ZZPVV25/SFmVA1lWVodJLHz05TKl9+vmTCuGlnJwOhra+/L8O+7R0kmjR3yi6rnIp27GvmnCsRkfWkwEpEREREZBO5+7YD3HP4GDP5Iu3pJLOFEoWSc/dtB6756y+unsoVSrFhUr0uTOcXDEU/PpZleq4Uu7ZvS1u0W19fNwO9GQ72dNGaTq742ldiZqSTFu3Wl1Y4JSLXJwVWIiIiIiKbyO39PdxLNEvqzMQMe9Z4l761vH5t9VQuBGMrrZ6azZd4dHy+rW94JMt4di52bXdbKgqnQuVUf2+GrR0tq3krV9RSM2+q0t6ncEpErne2mmGD14vBwUE/evToet+GiIiIiMg1q1wOO/cVS+QK0eNKq6dKZefU+elqW9/waJZT56aJO106adzS00V/b3e1ve+GrW1NC4zSyUSomlI4JSJiZo+4+2Dcc6qwEhERERGRNZdfFE7liysbjO7ujGfnqm19w6NZHh3LkivEn2/PtnYG+rrDrn0ZDuzsatqg8nRyfhh6azpq60skFE6JiNRDgZWIiIiIiDRVI6unpuaKHB+N2vqi9r4sF6bzsWu3tqfprxmK3t+bIdOWjl27WrXhVGUousIpEZGVU2AlIiIiIiIN1ajqqUKpzBPnpmsGo2d56sJM7NrWVIJbd8+39vX3drO7u7Up7Xbp5PxOfZWAKqlwSkSkoRRYiYiIiIjIilWqpyrD0VdaPeXujFzKMVSZOzWS5cR4lkLp8nMZ8IwdHTWtfd3s39FBKtn41r5UIjG/U18IqBROiYg0nwIrERERERGpW75YJlcsMbfK6qlLswWO18ydGh7Ncmm2ELu2uy2FmVEql9mdaeOVz3sG33lo12reRqxUoqZyKq1wSkRkPSmwEhERERGRWI2qnsoXyzw2PrVg7tTXL87Grm1PJzkUBqL393aTy5d4/z+dIpUw2tIJcoUyf/S/T9KaTvKcA9tX/N6SCavu1FcJqZpRoSUiIiuzJoGVmSWBo8DX3f0/mtlNwIPAduArwI+7e97MWoEPAs8GzgOvcPdT4RxvBl4DlIDXufunwvGXAPcBSeC97v6OcHzZ1xARERERuZ7VVk/lCiUKpeVXT5XdOTMxy/DIJEOjWYZHsjx+dopiTNCVMDiwq4uB3gz9ob1v3/aOBVVNb/jIV0kljPZ0EogCrdlCiQcfPl13YJVMWLWdr1XhlIjIprBWFVavB4aA7vD9bwG/5+4PmtkfEQVR7wmPE+5+i5ndGda9wsy+AbgTeCZwA/AZM7s1nOvdwPcAZ4CHzeywu39tuddo9g9ARERERGQjKZd9PpwKj2VffvXUhen8fFvfyCTDY1mm50qxa3u720LlVDR36paeLtpCELWUkclZutsW/rWlLZ1gdDK+QithVm3nq1ROpRVOiYhsOk0PrMxsD/C9wH8D3mDRNh3fDfxIWPIB4K1EYdId4WuAjwF/ENbfATzo7nPAE2b2GPCcsO4xdz8ZrvUgcIeZDS33Gu4r+K+ziIiIiMgmMVcszbf3Fcorqp6aLZQ4MZattvUNjUwynp2LXdvVmgrBVNTa19+XYVtHy7Kv2dfdzvnpuWqFFUCuUKa3u70aTrUkE7SmkwqnRESuIWtRYfVO4FeATPh+B3DR3Yvh+zPAjeHrG4HTAO5eNLNLYf2NwBdrzln7mtOLjj93hdc4V3vTZnYXcBfAvn37lv2mRURERETWS6nszBVL5MJg9JVUT5XKzpPnp0MwlWV4dJInzk0TN8IqnTRu3tVVrZzq782wZ1s70b89r86d37qX+z53glyxRFs6Sb5YxoHXvuBm9u/sXPX5RURkY7pqYGVmzwbOuPtY+P5HgR8AngTudfeLV3jtfwTG3f0RM7u9cjhmqV/luaWOx/3zyZXWX+368wfcHwAeABgcHFT1lYiIiIhsWKutnnJ3zmbnqlVTw6NZjo9lyRXiz7NnWzv9vVHl1EBfhpt3ddGSalxlU8Ks2s73vd/Ux86uFt73j6c4MzHDnm0d3H3bAW7v72nY9UREZOOpp8LqAeDFAGb2HcDvAL8AfFN47oeu8NpvB77PzF4GtBHNsHonsNXMUqECag/wdFh/BtgLnDGzFLAFuFBzvKL2NXHHz63gGiIiIiIiG14jqqem54ocH80uCKjOT+dj125pT1fnTvX3RtVT3e3pRrwVYGE4VRmMvjj8etEze3nRM3sbdk0REdn46gmsUu5+Pnx9J/CAu38E+IiZffVKL3T3NwNvBggVVr/s7j9qZn8J/CDRLn6vAj4eXnI4fP9P4fnPubub2WHgw2b2u0RD1w8CXyaqljoYdgT8eri/Hwmv+fvlXKOOn4OIiIiIyJpbHE4tt3qqWCpz8tx0ta1veCTLUxdmLm8xAFpSCW7t6aK/L8NAmDvV293WkNY+AKsJp1qXCKdERESgvsAqaWZJdy8BLwR+pva5FV73jcCDZvZ24J+B94Xj7wP+LAxVv0AUQOHux8zso8DXgCLwc+F+MLPXAp8K9/In7n5sJdcQEREREVlvpbJHbX3FK1dPffnkBR58+DQjk7P0dbdz57fu5TkHtuPujE7mquHU0EiWE+NT5IuXh1wG7NvRUZ07NdCb4aadnaQaNLR8cThVqZ4SERGph12tuMjM7gFeBJwFbgG+xd3LZnYz8Gfu/vzm3+b6Ghwc9KNHj673bYiIiIhIcGR4nPsfOsnpiRn2btKZRu5OvlRedvXUl09e4L7PnSCVMNJJYzJXJFcos2drO6OTOS7OFmJft6OrJaqa6s3Q35fh0O4Mna2N2YOpEk5Fu/WFgCqZaFhlloiIXJvM7BF3H4x7rp7/Qr0N+BzQB3zS3Sv/FU0Dr2vMLYqIiIiI1OfI8Dj3HD5GOmlsbU8zns1xz+Fj3AsbOrSqrZ6qPC5nMkW+WObxs1P8/t8/xqXZAoVSmUJp/vXDY9nq1+3pJId6u6KZU6G9b1emtSHvQ+GUiIishXoCq0fc/VmLD7r7cBPuR0RERETkiu5/6CTppNHREv1RtqMlxUy+yP0PndwwgZW7h7a+MnMhnFrO7KmyO2cmZhcMRX98fIpiOT7gak0lSBi89gW30N/Xzb7tHSQTqw+QzKIqrtZUkoefOM8HvvAkZy7OsG9756asahMRkc2jnsBK/1QiIiIiIhvG6YkZti7apa49neTMxMw63VE02Ly2cmq51VMTM/lqMDU0kuX4aJapuWLs2pZkgmTC6GxN0p5K0ppOMFcss6OzlZf+X30rfg+14VTt7Ckz48jwOO/45HHSSWNbR8umqWoTEZHNq57AapeZLdn65+7vauD9iIiIiIhc0d5tHYxnc9UKK4DZQok92zrW5PqrrZ7KFUqcGJtiKOzYNzQ6ydjkXOzaztYk/b3dDIS2vkO9GR4bm6rOsGpLJ8gVyhTLzp3fundZ7yNdbelLLgin4myGqjYREbm21LVLILATVVqJiIiIyAZw920HuOfwMWbyRdrTSWYLJQol5+7bDjTlequpniqVnacuzDA8MsnQaJbhkSwnz00R19mXShg393RVd+3r782wZ1s7iUUh0nMObOf1HOTBh08zOjlLb80ugUuphlPJqCKrJZkgsYyWwY1Y1SYiIte2egKrEXe/p+l3IiIiIiJSh9v7e7iXqOrnzMQMexq4S2C1eirs3BdVL9VfPXU2O1etnBoeneT46BSzhVLs2hu2tjFQqZ7q6+bmXV20pBJ1Xec5B7YvGVClk5V2vvnWvuWEU3HWu6pNRESuP5phJSIiIiKbzu39PQ0JqIqlMrnQ2pcrlskvo3pqeq7I8bFsta1veDTL+al87Not7elQOZWhP7T2bVlUsbQS6WSiZt5UFFA1Ytj6Ymtd1SYiIlJPYPU9Zta91JPuPtnA+xERERERaYra6qlcscTcMqqniqUyT5ybrg5FHx6d5MnzM8RFWy2pBAcXtfb1bWlbcj5UvVKJysypSkiVbEo4FaeZVW0iIiJx6gms/hlwFlZaVb53YF8T7ktEREREZFUKi2ZP1Vs95e6MTc7V7No3yYnxKeaKl4dbBuzb3kF/qJwa6MtwYGcnqWR9rX1LSSZsfhh6mDm12nOuVqOq2kREROpx1cDK3Ze33YiIiIiIyBpbTfVUNldgeHS+te/4aJaJmULs2u2dLQzUVE7d2puhq7WefwNeWjJh1Yqpym596x1OiYiIrLer/tfVzO5w94/HHE8B/6+7/2ZT7kxEREREZAkrrZ7KF8s8fnaqWjk1PJrlzMRs7Nq2dIJbd2eqAdVAXzc7u1pW1dqXMAttffMD0dMKp0RERC5Tzz8Hvc7Mfgr4eXc/BWBmLwbeCXyuifcmIiIiIlKtnqqEU7lCiVK5vta+MxOzC8Kpx89OUShd/tqEwU07O6ttff29GZ6xo3NVM6ISZvMD0dNJWsKAdBEREbm6eloCX2hmPw58zsw+AHwjsAf4MXf/SrNvUEREREQ2viPD49z/0ElOT8ywd5UDuQulheFUoeR1VU9NzOQZDgPRh0ayHB/Lks0VY9fu7m6lv7e7unPfwd0Z2tPJFd0vgJnVDEOfr6ASERGRlam34f5DwEHgjcAF4Lvc/fGm3ZWIiIiIbBpHhse55/Ax0klja3ua8WyOew4f4164amhVLofZU8XlVU/lCiUeG5+qGYyeZXQyF7u2szVJ/+4M/X3d1Z37tne2rOStAlE4NR9Mze/YJyIiIo1TzwyrbwP+EDgK7AVeAHzSzD4I/Ja755t7iyIiIiKykd3/0EnSSaOjJfqjZUdLipl8kfsfOnlZYLW4eiofs/PeYqWy89SFGYZrwqmT56aIy7WSCeOWXV3Vyqn+3m72bG8nscK5U2ZGOhl27EuHgCqZWNUcKxEREbm6eiqs/hD4OXf/Qvj+Y2b2CeBe4KvAQLNuTkREREQ2vtMTM2xtTy841p5OcvrCNLP5EnPFErlCVEVVT/XU2ezcgrlTj45lmcmXYtfesLVtYWtfT2bFrXiVcGrxjn0Kp0RERNZePYHVoLsv+BOCu08Dv2Rmf9qc2xIRERGRzWLvtg7Gszna0kncoezOTL7Izq42Ri7F78BXMZMvcnw0W62cGh6d5NxUfAF/d1uK/r5uBnoz9IfqqS2LgrLlSCcT1R37FE6JiIhsLPUEVr8A/HcAM/sBd/+rmudeAfx7M25MRERERDau2tlTP/TsPfz23x0nXyzTlk6QK5Qplp07v3XvgteUys4T56arQ9GHR7OcOjdNXM1VOmkc7ImCqYHebvr7MtywpW3FgVI1nEpGrX0tyQSJVewAKCIiIs1lV9txxcy+4u7PWvx13PfXqsHBQT969Oh634aIiIjIusmHcKrS2rd49tSXT17gwYdPMzo5S293O68Y3MMzdnUyPDIfTp0Yy5JbYmbVvu0dYeZUNBT9pp2dpJMra+1LJ+d36lM4JSIisnGZ2SPuPhj3XD0VVrbE13Hfi4iIiMgmV6meqgxHr2f21Dfc0M2PPHcvQ6NZhkey/PbfHWdiphC7dltHmoG+7upQ9EO9Gbpa6928eqHacKqyc5/CKRERkc2vnj8Z+BJfx30vIiIiIpvM1aqnFiuUyjx+dorhkWwIqCY5PRE/q6otleDW3qhyqr83Cql6Mq0rau2rhFMtNQFVUuGUiIjINamewOqbzOwCUTVVJnxN+L6raXcmIiIiIg233Oopd+frF2cXDEV/bHyKQuny1yQM9u/sjNr6wtyp/Ts6VxQqpRKVgegKp0RERK5H9QRWLfWcyMy63X1ylfcjIiIiIg203OqpizN5hkNb39DoJMOjWbK5YuzankxrVDkV2vtu7cnQ3pJc9j3WhlOV6imFUyIiIte3qwZW7l6q81xHgGt+ALuIiIjIRrXc6qm5QokT41PVtr7h0Swjl3KxaztbkhwKA9H7Q4vfjq7WZd9jKpGozpqKQiqFUyIiInK5lU23jKc/aYiIiIisoeVUT5XdeerCTLWtb3gky8lz07GBVjJhHNjZWTMYPcPe7R0kljl3KpkwvnJqgg99+SmevjTLvm0d/Mx33czt/T3Lfq8iIiJyfWlkYHXZn3bMrA14CGgN1/qYu7/FzG4CHgS2A18Bftzd82bWCnwQeDZwHniFu58K53oz8BqgBLzO3T8Vjr8EuA9IAu9193eE48u+hoiIiMh6OTI8zv0PneT0xAx7t3Vw920HFgQ7y62eOjc1t6Ct7/holpl8fOF835a2aO5UqJ462NNFa3p5rX3JhC3Yqa81leAfTpzj9z57gnTS2N7RwtmpOe45fIx7QaGViIiIXFEjA6s4c8B3u/uUmaWBfzCzTwBvAH7P3R80sz8iCqLeEx4n3P0WM7sT+C3gFWb2DcCdwDOBG4DPmNmt4RrvBr4HOAM8bGaH3f1r4bV1X6PJPwcRERGRJR0ZHueew8dIJ42t7WnGszl+7eP/zq/mBxi8aftVq6dm8yUeHcsyNDIZ2vuynJ2ai13b3Zaqzp2qtPZt7ahrZGlVMmHVWVOVcCqVTFy27v6HTpJOGh0t0R85O1pSzOSL3P/QSQVWIiIickVNbQl0dwemwrfp8MuB7wZ+JBz/APBWojDpjvA1wMeAP7Boz+M7gAfdfQ54wsweA54T1j3m7icBzOxB4A4zG1ruNcK9ioiIiKy5P/r84yQT0JJKUCx7dabT/Q+d5FBfZsHaUtk5dW56wdypU+eniSu2SieNgz1d9PdWWvu6uWFrG7aM1r7acKpSPZWOCafinJ6YYWt7esGx9nSSMxMzdV9fRERErk9XDazM7H8CP+fuT11l6YuXeH0SeAS4haga6nHgortXtps5A9wYvr4ROA3g7kUzuwTsCMe/WHPa2tecXnT8ueE1y73Guau8PxEREZGGyBfL5Iol5sLsqSfOT9PdlqJUmk+d2tIJRi7NMDaZq86dGhrJcmIsS26Jaqu929qrbX0Dfd0c2NVZd7gEkDCjNZ2gJZmgNZ1cVjgVfz8djGdz1QorgNlCiT3bOlZ8ThEREbk+1FNh9RfAZ83svcDvLLVroLufXeJ4CfhmM9sK/DUwELcsPMb9c59f4Xjcn6CutP5K11jAzO4C7gLYt29fzEtERERErq5UduZCOFUJqcqLCrv7uts5Pz1HSzJBLgxRn84XKZacH/7jL8Wed1tHuqZyKqqe6mqrv3g+YVazW1+SlmS0e18j3X3bAe45fIyZfJH2dJLZQolCybn7tgMNvY6IiIhce676pxp3/3CosnorcNTMPgCUa55/Vz0XcveLZnYEeB6w1cxSoQJqD/B0WHYG2AucMbMUsAW4UHO8ovY1ccfPreAai+/3AeABgMHBQbULioiISKzFw9J/8tv389ybd0TD0QtlCqX4aqhCqczJs9MMj06SMHj6Um7JIeptqQQHd2eqbX0DfRl6Mq11t/bVhlO17X3Ndnt/D/cStTaemZhhT8wweREREZE49f4z3CzRjnodwC5qAqsrMbNdQCGEVe3Ai4iGnP898INEu/i9Cvh4eMnh8P0/hec/5+5uZoeBD5vZ7xINXT8IfJmoWupg2BHw60SD2X8kvGZZ16jz5yAiIiJS9bmhMe45fIxUwuhsSfL1izPcc/gYr//ugzznwPbqOnfn6Yu5alvf8OgkJ8anKJSWCKjSCb7xhi3cdusuBnoz7N/ZWZ1rdTVmVhNMrV04tZTb+3sUUImIiMiy1TPD6oXAfcAngWe5+/Qyzt8HfCDMsUoAH3X3vzGzrwEPmtnbgX8G3hfWvw/4szBU/QJRAIW7HzOzjwJfA4pEM7VK4f5eC3wKSAJ/4u7HwrneuJxriIiIiFzNXLHEXLEctfcVSrzrs49hQEsygTu0pZK4l/jzLz5JGWe4ZjD6ZK4Ye85dXa3zbX193RzanaG9JVnX/VhtW19N9ZSIiIjIZmdXKy4ysy8AP+Pu/7o2t7TxDA4O+tGjR9f7NkRERGQNlctenTm11OypH/7jL9LVmiRfdHKFaPZUrlCisERrX0dLkkO9GQbCzKn+vgw7u1rruh+7rK0vGo6+nB3/RERERDYSM3vE3QfjnqtnhtXzr3Dip9xdE8lFRERk06vduS9XKMXOniq7c/rCTGjryzI5W2Rsci72fAmDA7u6onCqL5o7tXdbR12tfZVwKtqtN/AVdwAAIABJREFUT+GUiIiIXH/q30omnv7UJCIiIptOPdVTABem8wyNTDIU2vqOj2aZzsdumEwqYaSTCVJJ40efs4/v++YbaEtfvT3PzEgnjdZUktZ0CKlSCqdERETk+rbawErDykVERGTDq8yeutLOfbOFEo+OZatD0YdHsoxn46unMm2paOZUb4akGQ+fmuD89By93e3c+a17Fwxcr1UbTtXOnlI4JSIiIrJQPUPX37DUU0BXY29HREREZHVKZWeuGM2TmluieqpUdk6dn2Y4tPYNjU5y6tw0caOn0knjlp4u+nujtr5DuzPs2da+IGR65fP3V7/+8skLvOEjX2VkcpYbt7Tzym/bzwsGehROyf9h797j47rPet9/nrXmKml08UW240sShyR2k+bSGJpCCSm9kLbstvAq0LA3FE45yeZyWti0tJzdBkjpPilwgJZrcqCbls1ugXCpD7TQltQn7SZp61ycxLVyU2Jbvsm2biON5rbW7/yx1oxH8kiWZF1G1vf9es1L0po1a62RZ5Lx18/z/ERERGQe5lJhlZvlvk8s1oWIiIjI8tvXN8j9D/dzdLjA9p427r5tJ7fv6l3py5qXC1VPOec4nS9xKF6x79DJPM+dylOsnF9lBbCtJ8vuLZ3s2pxj95YcOzd0kEp4F7yOpO/x2MvD/OFXXyCZMDa0pxgtVvjdrzxHd1ty1f1eRURERFbSXIau/8ZyXIiIiIgsr319g9yz9yBJ3+jOJhnMF7ln70HuhZYNV+ZSPTVeqvJcXDXVdyLPoZN5hibKTY/XnU2ya0uO3fGKfbs258hlkhe8jmRtGLp/bu6U5xm/8uBTpJMebanoI1ZbyqNQrnL/w/0t+ztdLpdCOCoiIiLLZy4tgZ+c7X7n3HsX73JERERkudz/cD9J3xrClUTLhSvTw6np1VOVIOSlMxP1oeiHTuQ5MlRoeqx0wmNLV4aJUkA5CNja1cZP3LqDV1+1ftZrSPq1WVNTw6lmjg4X6M5ODbyySZ+B4ebXtFasxnBUREREVtZcWgIfW/KrEBERkWXXauFKELqorS9u7ytXp1ZPOec4PlqMq6ai6qnnB/NUgvMHTxlw+fo2dm+J5k7t2tzJ6bESf7jvBTJJj+62BPlShU9+9QXeZ1Yfkt4YTtWGos8UTjWzvaeNwXyxHgJCNMx9W0/bwn8xl4DVEI6KiIhIa5lLS+Cnm203swzwHxb9ikRERGRZrGS44pyjVA3jW/PqqdHJSn21vtr8qbFitenxNnSkGuZOdXLNpo4pzwvgj7/6IgnPyCZ9IApNipUqDz4+wNtv3koq4eHPI5xq5u7bdnLP3oMUylWySZ/JSkAlcNx9286LOu5q12rhqIiIiLS+uVRY1ZmZD7wJuBP4AeBrwN8uwXWJiIjIElvOcKUahOcGo8dBlWuonipXQ14YHG+YOzXG8ZFi02Nlkz7Xbs7Vw6ldm3NszKVnPX/C8ziVL9KVTeKbYQZmRtJPcmqsSDblL8rzvH1XL/cSVRQNDBfYpllNgCrPREREZP7mFFiZ2W3AjwNvBb4JfA9wpXNO/ywmIiKySi1VuFKvnopnTxUrIdXwXPVU6BwDQ5P0nRzjUBxOvXh6giA8v7XPM9i5oSNu68uxa0snO9a1zVoJlfC8ejtfOhm19/meccX6dgbzRZJLHJrcvqt3zQdU06nyTEREROZrLkPXB4AjwJ8AH3DO5c3sJYVVIiIiq99ihCvVIKRYDSlVAorVkPK06qmhiXJ9KHrfiTH6TuWZKAVNj7W5M3MunNrcydWbOsgkZ65+8j2bMm8qnfBI+F7TfRWarBxVnomIiMh8zaXC6u+AdwA/BgRm9nng/H8CFRERkUvehaqnipWA507l6yv2HToxxmC+1PRYHekE127OsXtLjt2bO7l2c4517akZz+2Z1SumagFVcoZwqhmFJitLlWciIiIyH9b4L6Az7mRmwOuIZle9BegE3gN8wTk3vqRX2AL27Nnj9u/fv9KXISIisuxmq54KQsfhsxP1cKrv5BgvnZmgSWcfSd+4amPHlLlT23qyRB8xzueZNbT1+fMOp0RERESk9ZnZY865Pc3um9MMKxd9Mn0IeMjMksCbgXcBfwxsWKwLFRERkZXTWD1VjFfuq1VPOec4M36ute/QiTGePZWnWAmbHmtbT7be1rd7S46rNnaQSjQPnMyMdKJh7lRcQSUiIiIia9d8VwncCOCc2wvsNbPsklyViIjIGrevb5D7H+7n6HCB7UvUulaZtnJfY/XURKnKs6fy9RX7+k7kOTtRbnqc7mySXXFb364tOa7dlKMzm2y6rzVWTtVDqsVZoW8tWI7XhYiIiEgrmMvQdQN+DfgFwIs3VYE/cM7du8TXJyIisubs6xvknr0HSfpGdzbJYL7IPXsPci8sOJyoVU/VwqnG6qlqENJ/ZqLe1td3Is+RoULTgZWphMc1vR31tr7dWzrZ1Jlu2tpnZiT9aCh6NHvKI+V7M7YByuyW4nUhIiIi0qrmUmH1i8D3AN/pnHsJwMx2An9iZr/knPu9pbxAERGRteb+h/tJ+kZbKvrfdFsqQaFc5f6H++ccTFSChnCqoXrKOceJ0WK9ra/vZJ7nB8cpV89v7TPg8vVt7Iorp3ZvznHlhvYZV+FLNVRM1SqoFE4tnsV4XYiIiIisFnMJrH4SeKNz7kxtg3Ou38z+E/AlQIGViIjIIjo6XKB7WktdNukzMFxoun8YxrOnqkG9iiqIJ5+PTlZ49mRUORVVUOUZnaw0Pc769lS9tW/3lhzXbMrRnm7+USHpe/UV+xROLY/5vi5EREREVrO5BFbJxrCqxjl3Oh7ALiIiIotoe08bg/livZIGYLISsK2nDYByHE4VK9HXWnVUuRrywuD4lHDq2Mhk03Nkkl59KHotpNqYSzfdN+mfG4aeTkZtfZ6ncGq5Xeh1ISIiInIpmUtg1XzC6oXvExERWTVaaZj13bft5J69BymUq2QSHoVKQLnq+NFbtnH47ARB6AidY2B48lxr34k8L54epxqeP3nKM7hyQ/uUuVM71rXhNwmdauFUY2ufwqnW0Pi6yCZ9JisBlcBx9207V/rSRERERBad1VYDmnEHswCYaHYXkHHOXfJVVnv27HH79+9f6csQEVkVWin4mavGYdaNQcC9b7tu2a+91tb30LcH+fQjL3NidJLNnVl+8IYtZFJeHFDlefZknvFStekxNnWm2RW39e3anOPqTTmyyfNX4kt4Xn0Yejrhk0p4TUMsaR2199fAcIFtq+T9JSIiIjITM3vMOben6X0XCqxEgZWIyFy1UvAzH3c+8Oh5rVaFcpXeXIbP3nXrkp03CN2U1r5SJSR0jmIl4PlT51r7Dp0c49RYqekx2tN+PZy6dlNUPbWuPXXefgmvVjV1bvaUwikRERERWUmzBVZzaQkUERGZk9W6itlyDbOeHk5VgpAgdBwZKtAXr9h36ESe/jPjNOnsI+EZV/V21Nv6dm3Osa0nizdt2LnvWb1iqjYQfaaV/UREREREWpECKxERWTSrdRWzpRhmHYRRpVR99b64eup0vsShk9HMqb6TYzx7cpzJStD0GFu7s3E4FQVUV23sIJWYGjx5ZvWKqVpAlVQ4JSIiIiKrnAIrERFZNKt1FbOLHWbtnKMchOdVT02Uqjx3Kl9fse/QyTHOjjdfr6Qrm6zPnNq9pZNrN+XonBb+eWYNbX0+Kd87L8ASEREREbkULGlgZWbbgc8Am4EQeMA59wkzWwf8NXAF8DLwo865YTMz4BPAW4AC8FPOucfjY70b+HB86N90zn063n4L8BdAFvgC8D7nnFvIOURE5OJcbPCzUgPbb9/Vy70w52HWjdVTta+VasBLZyY4dDJfr546fLZAs0mRqYTH1b0dcUAVzZ/a3JnBGlr7rDGcahiKLiIiIiKyFizp0HUz2wJscc49bmY54DHgHcBPAUPOufvM7ENAj3Pug2b2FuD/IAqTXg18wjn36jh82g/sAVx8nFviAOqbwPuAR4kCq086575oZr81n3PM9jw0dF1EZO4WuopZqw5sd87FbX0hpTicKlcDTo4V6YsHovedyPP84Dilanje4w3Ysa6NXQ3h1M4N7VNmSjWGU6mGgEpERERE5FK2YkPXnXMngBPx93kzOwRsBd4O3B7v9mlgH/DBePtnXJSiPWpm3XHodTvwZefcEICZfRm4w8z2AZ3OuUfi7Z8hCsS+ON9zxNcqIiIX6fZdvQsKmFplYHs1CKdUTpWqIWOTZfriyqlaQDUyWWn6+HXtKXY3DEW/ZnOOjvS5/92aGUk/GoqeTnqk/CigMtOKfSIiIiIiNcs2w8rMrgBuBr4BbKoFRM65E2ZW+5vIVuBow8MG4m2zbR9osp0FnEOBlYjIAi1GK99KDGyvV0/VZk9Vo7lTL54ej+dORSv3DQxPNn18Julx7abclFX7NubS9fCpMZxqbO9TOCUiIiIiMrtlCazMrAP4O+AXnXNjs3xQb3aHW8D2WS9nLo8xs7uAuwB27NhxgUOKiKxdja183dkkg/ki9+w9yL0wr9BqOQa2T6+eKlYCjg4VooHoJ6Jw6sXT41SC8/9X4hlcsaGd3Zs76yv3Xb6+Hd9TOCUiIiIistiWPLAysyRRWPVXzrm/jzefqrXhxS1/g/H2AWB7w8O3Acfj7bdP274v3r6tyf4LOccUzrkHgAcgmmE15ycsIqvWSg38Xu0Wq5XvYge2Tze9eqpYCTkzXqxXTh06kefZU3nyxWrTx/fm0uzakosCqi05rtmUI5uM5kopnBIRERERWVpLvUqgAX8OHHLO/W7DXXuBdwP3xV8/37D9F8zsc0QD0UfjwOlfgf9mZj3xfm8CftU5N2RmeTO7lajV8CeBP1jIORb7uYvI6rJYVUJr0WK18s13pb7pqkFIMR6MXqyGjE1WeP5UPl61L6qeOjFabPrY9rTPrk05dm3prLf3rWtPAQqnRERERERWwlJXWH0P8BPA02b2ZLzt/yQKkf7GzN4DHAF+JL7vC0Sr970AFICfBoiDqY8C34r3u7c2gB34WeAvgCzRsPUvxtvndQ4RWdtaZeD3ajTXVr65VLDNdWD79OqpiVJA/5nxeDD6GIdO5uk/PU7YpD424RlXbeyot/Xt2tzJtnVZPDOFUyIiIiIiLWKpVwn8Os1nRgG8vsn+Dvj5GY71KeBTTbbvB65vsv3sfM8hImvXSgz8vlTMpZXvYivYGqun9vUN8ql/f5mB4QLphE9HOsHJsSKFctD0sZd1Z+ptfbs257i6N0cq4QGQ9D3SSS9asU/hlIiIiIhIy1i2VQJFRFrZcgz8vlTNpZXv/of7KVcDzo5XKQchKd8jl0k0rWCbXj01NFHm2yfGOHRijH9/8SyHTow1VE5VGcyX6o/tzCTqq/Xt3tLJtZtzdMVBZNKvVUz5pJMeKd/D8xROiYiIiIi0IgVWIiIs/sDvteZCrXzPnRpjrFjFw/DNqAaOsxNlqsHYlOqpiXKVZ+MV+6Lh6HlePjPRdPlXA9IJj4RvrG9P87Efup4tXRnMjIRXq5zy6u19vsIpEREREZFVQ4GViAgXP/BbZlcJosip1m1nBmHgKJQDPvPIy/WV+547NU6pGjY9xo51URVcLp0gm/SntO/lS1Wuu6yr3t6ncEpEREREZHVTYCUiEpvrwG+Zu1r1VMI3wqIj9KLgKgzBAYVKyL3/dOi8x/W0Jdm9pbM+FP3azTk60gl++W8OMDRRoi2VwMzwLGrdvGJ9Oz3xqn4iIiIiIrL6KbASEZFF0Th7aqxY4dvHx3jm+Ch9J/NMlAICgCbFU0nfSPkeDujtSPNj37mdN123iYTvnbda3/tefzX37D1IOQjVuikiIiIicglTYCUiIgtSCUJK1ZDJcpUXT0/w1MAoh06M0XdyjBcGx+ttgNOlfCPpR7Onbr96I994eYhUwiOb9ClVQ/7qm0e4elMHb3jF5vMeq9ZNEREREZG1QYGViIhcUK16qlgJODla5MDAKAePjdJ3coy+k3nGitWmj+vKJrlxWxe7NucAeOTFIc6MF9nSneWnv/sK/vLRI7SlfNrT0Up+qYRPoVzlz7/+ctPACtS6KSIiIiKyFiiwEhFZQ/b1DXL/w/0cHS6wfZbqpEoQhVOjkxWeOTbG08dG+PbxKJw6MVpseux0wsM5SCc9OtI+huGAd9y0le+7diPppM8H7vBI+l79MR//12fpzianHCeb9BkYLizq8xYRERERkdVFgZWIyCKZaxi0Uvb1DXLP3oMkfaM7m2QwX+SevQf5ded4zVUbmKxUefZkngMDIxw8PkbfiTz9ZyYIwvNb+3zP2LmhvWEweo7f/8rzjBTK9YHoZlCsBPztYwP88C3bml7T9p5o5b+21Ln/HU1WArb1tC3Z70FERERERFqfAisRaSmtHvrMZKYw6F5Y1Ou/mN/P/Q/3k/SNTNIndGBAoVzlQ3//NFt7sjx3Ms9EOWj62C1dGXZv6WTX5hy7t+S4pjdHLpsknfDioeg+H/n8QbqzScys/rgLVUvdfdtO7tl7kEK5qiHqIiIiIiJSp8BKRFrGcoU+S6EWBtUqhdpSCQrlKvc/3L9o176Q308YRrOnhiZKPHtqDMMoVYsUKyHVhsqpwXyp/n1nJsGuhnBq9+ZOejszDav1RSv3TbeQaikNURcRERERkWYUWInIjJa72mk5Qp+axX5uR4cLSz6LaS6/n3I1ZLxU4dCJPE8eHeHgsVEOncxz+OwETTr74uP43HH9ZnZvzrH7si6uWN9GJulPqZ6ai4VWSy32EPXVWqUnIiIiIiLnKLASkaZWotppOUIfuLjnNlMYshyzmKb/fpxzlCpV9r98lpvu/RJJ36M95XNytEixGjY9hu8Z6US0n2eGZ/Crb97N63b3ziucaqYVqqVWc5WeiIiIiIico8BKRJpazmqnmuUawL3Q5zZbGLIcs5i2dmc5PjIJwGQ5IF+qUoqDqZFCBYDTDft3pBO8cmsXu7fkMOBbh4cYGJqkEoSEYchVmzr5z9931aL+eS52tdR8rcTrVkREREREFp8CKxFparmqnRot1wDuhT632cKQz95164Kqi2aq2ApCR75Y4ZljozxxdIRnBkbpPz3B6fFS0+MY4OKvCQ825tKA8RO37iDheXz0n79NKuFxWXe2/ntd7LCqFazE61ZERERERBafAisRaWq5qp0aLVdL2UKf24XCkPlWF9UqthIe5NI+R4Ym+KW/eZLrLutiaKLE84PjVILmg6cSnhE4R2cmQXc2xamxScIQzIMgdKzvyFAoV/nLR48AkEp4l3zV0b6+QcYmK5wcLZJOeGzoSNOZTS7561ZERERERBafAisRaWq5qp2mW46WsoU+t8UK8apByMnRIh/7wiFGC2UqoaNYCepD0b/+wpkp+2/sSLNrS47dm3Ncv7WLV27rYl1bmv/9M/s5M16kPZ3k+Ogkvmc4IB2v4FcL0xxc8lVHtfCvPe0zWQ4oByHHRycpVQNSCX/JX7ciIiIiIrK4FFiJSFOtMEB7qcz1uTW26+XSCfLFCifGSiR9Y1MuTcL3Lhh0OecYm6xw4OgoTx4d5qljo3z7xBjHR4pN9/csqp565y3buG5rFzdt62ZbT1s8EN3D86y+78/dflU9eEv5HuUgxLC4HXBqmLbc1XLLrdau2ZXNkE74nM6XKFYDCuWA+374hkvidSsiIiIispYosBKRGa30AO2ldKHn1jhg3Td4fnAcgHVtCfLFgIGRSa7e2MFH3vqKKccpVwIOncrzxOEonHrm2Cgvnp4gCJu39kUzsXyyyQTZlEcYOjZ1ZvnoO16J3xBOzTTrqha8jRbKVEPHuvYkHemo5a8xTFvsarmZrmelNLZr5jJJcpkkzjlGJyuX7GtYRERERORSpsBKRKSJxgHr/afHo/DIQaEccvWmHIVyle62FFf1dvCPTxzjyaMjPD0wSt/JMSbKQdNjrmtPceO2Lq67rIsbt3eRL1T52Be/zXipyngpwDmHc9GMqa89d7oetMy2OmFj8FYLkZpVjS1mtdyFrmclrMTMNRERERERWToKrEREmmis2CkHIb5nhGFIsQKnxooUylVeOjPB9/7WV5s+Ppv0CZ0jnfDIZRJ4Fs2X+k+vvpzXv2ITEAU/nhnOUa/A8j0YLpSnBECzrU7YGBDNVjW2mNVyc72e5bRSM9dERERERGRpKLASkTVrtra2rV0ZBkYmCR2EoaMaOGpNfYP50pTjJH3jO3o72L2lkxu2dnHTjh4+8NdPcGRkkslKQBA6NnSkSfjGn339pXpgdf/D/XRmkxTKAWYOz4wwdOSLVTZ3JeoB0IVWJ1xurXY9cGnPXBMRERERWYsUWIlIy1jOuUiNbW1dmQTHhif4L397gJu2dfHy2QIvnZmg+dSpaCh60jfuuH4LP3TzZVy/tZtcJkHS9+rH7h8q4Jvhm1ENHMdHJ7msKzMl1KkFP7UKLgCzqKKrMQBqtXa3Vruemkt55pqIiIiIyFqjwEpEltVModRizUWaS+g1Uijzf32xj7HJCtXQ1augAB569nTT43akfXKZBDjYsb6dn/2+q2a8rvsf7ifpeTjAzDADQjiVL3Hz9p76frXgxwNK1ZBaQpbybUoA1Grtbq12PSIiIiIiculRYCUiCzbfiqjZQqnFmIvU7Pgf+fwzvHvwckLgwMAozwyMcnioeetabU2+jkyCznSCbCpBKmGUqiG9uQyfvevWOV3H0eECmzrTnBgtEeIwA4ejGjAl1Ln7tp28/8EDVMNo2HpNNYxWt/vIW18BtF67W6tdj4iIiIiIXHoUWEnLWs72MJm/T37lOf5o34sEYTRYvBqEF6yImi2UajYXqRqEPH5kmNd+/KE5vQb+9P97EedCShVjeKLMZCVgshLym1/oa7p/wjPaUj7ZlE97KkHoQo4OTRKGjsHxEim/woaONLlMYl7zmWqVU5d1ZzidL0Utf2ZctbH9vCHpGzvSjBerWOgIXTTHKuEZGzvScx6ovhJa7XpEREREROTSsqSBlZl9CvhBYNA5d328bR3w18AVwMvAjzrnhs3MgE8AbwEKwE855x6PH/Nu4MPxYX/TOffpePstwF8AWeALwPucc24h55DWsljtYbI09vUN8kf7XiR0joQXzWg6O1FmfXtqSkXU9NDxuVNjbOnKTjlWbVbT9LlIY5MVjo0USXgzvwaGJ8rsPzzE44dHeGpghG+8PDSlUqnRho4U113WxfVbO7l5Rw+FYpXf/tKzpBJeva1tvBjgeVYPmGqzp9ZXU1y5oWPOv59ay1zSN67c0F5vmfvgHbvO2zdfqvIdvR1E/3mKOBdVWImIiIiIiKxVS11h9RfAHwKfadj2IeDfnHP3mdmH4p8/CLwZuDq+vRr4E+DVcfj0a8Aeogkvj5nZXufccLzPXcCjRIHVHcAX53uOJXv2smCL0R621i1lhdr9D/dTDUOSvodxbkZTvlitVyI1Cx3HSwFnxktszGXqx6rNapo+F+lUvgjA5q4MZkYm6TNZLnHP3oNct/8oTx8bZWB4sun1mUE24ZNJ+fgGW7vb+Puf+248z6bs15lNTmlrS/keSd84O16J5k950fMaLlS4bx7zmebTMteqA8xFRERERERW0pIGVs65h83simmb3w7cHn//aWAfUZj0duAzzjkHPGpm3Wa2Jd73y865IQAz+zJwh5ntAzqdc4/E2z8DvIMosJrXOZxzJxbzecvFa9Ye1rhqmsxuqSvUjg4XSPsegYvCIYi+lqphPWhpFjqua08yNFGhPZ04b1h3Y8hzdGiCIAjpzCQZnaxwcrRIsRrWz3+kYQaVZ3DVxg6u39pFW8rnK4dO0Zb0aE8n68f/xTdcfV5YBee3tb324w+xvj1NOuHXW/mSntGWTsz79zbXlrn5DjBXq6yIiIiIiKwFKzHDalMtIHLOnTCz2t+0tgJHG/YbiLfNtn2gyfaFnEOBVYtR1cnFWeoKte09bQRhyNnxSn2oeOAcvmf1oKVZ6Li+PU0lcPTmMlMqj67b2sW/PHOCx4+MEDrHyGSVSghDhfPb4lK+x23XbODGbd28akcPN27vpiNz7nXyxt2bmlY2zSXoqb3ucpkkuUx07YVyld6GirDFNp9qLLXKioiIiIjIWtFKQ9fPL3+IWgDnu30h5zh/R7O7iNoN2bFjxwUOK4ttvlUnMtVSV6jV/nzWd8BooUIpCEl4Hj9/+1X14GSm0HHnhg5+8Q1Xs//wMAeOjvChv3+ak2PFGc9lnKvicg5+4XVX8d43XDPj/o2VTbWQ6v0PHiBfrNLTlmRDR3rGoGelXndzrcZSq6yIiIiIiKwVKxFYnaq14cUtf4Px9gFge8N+24Dj8fbbp23fF2/f1mT/hZzjPM65B4AHAPbs2XOhIEwW2XyqTtaiC1ULdaR8Xjg9ThA6Ur7Hho40Cd9mrVBrPGYuncA5x3g5mPJ947nqfz5e8z+fu2/byUc+/wylapkgDBkvVilWQl46M8GPPfBo02toS/nsubyHt7xyC5/95hFOjU2SLwaUg5CU79GZTfBI/xDvnePvqFaNVChVCV00GD6d8OnMJpsGPa3+ulOrrIiIiIiIrBUrEVjtBd4N3Bd//XzD9l8ws88RDUIfjQOnfwX+m5n1xPu9CfhV59yQmeXN7FbgG8BPAn+wkHMs4XOVizDXqpO15kJtYfv6Bjk7UaYaODyDYiXgyFABs6idbl/f4Hm/18Zj+gbPD44D0NOW4PjwJA7wPOPMeIn3P3iA33nnjef9+TjnOD4yyRNHhnns8AgHBkY4NRbNgWpmW0+WzZ0ZXhgcpy3lkfCMwfEy/+vFs5zOlxjMF9nSlWVjburqeXMNZxqrkSph1K7oQjgzXqIzm5wx6Gnl151aZUVEREREZK1Y0sDKzD5LVB21wcwGiFb7uw/4GzN7D3AE+JF49y8AbwFeAArATwPEwdRHgW/F+91bG8DZtm1+AAAgAElEQVQO/CzRSoRZomHrX4y3z+scIqvJhdrC7n+4n85skvZ0ghMjkwRxfWDKM8pB2LQVrvGY/afH8T0DB2fi1fIAwtDhzBgpVLjvi4e45YoenhoY5bHDQzxxZISnj41yZrzc9Jq7s0mu39rFDdu6uOXyHm65vIfuthR3PvAo6ztSVAPH8dFJPKLA7KUzEziYcUXBuWisRkr5HtUwmrVVC9BWY9Bz9207ef+DBzg2MkkQh3Ad6QQfeesrVvrSREREREREFtVSrxJ45wx3vb7Jvg74+RmO8yngU0227weub7L97HzPIbJUZmq1297Txmt2ruOR/qF5rfh2obaw2v1mxmm/BDjMgyB0M848ajxmOQijwIqpA94c0WD1IHT0nRrnhl//UtMBcGaQ8Ix17SnefuNl/MRrrmBbTxaz80fI1c770ugEHobnWXSe0LGhIzXjioLzGaDelkqwMZfm+EiRkKhFslCuXnA2VauuxmcALqo2w1nTwXwiIiIiIiKrXSsNXRe55MzUare1O8PLZ8f55stDbOxIzToIfLrpbWFjkxVO5Ys4B3c+8CgdqSjcaUslovDJDOeiKiNoPvOo8ZhJz6iGUTA1XbVhW23lgys2tHPjti7aUwm+cugU7WmftlSCyUrAvxw8xXdftYHt65pXMtXOW7tOoH6tM60oCDRtiXznwMiU8O81O9fx4OPHKJSrdKQTrO9IMjRRIZv06M1lZg2gprddvnRmnLv/x2PkMgmu7s2tWHhVq57b3JWtb9PQdRERERERuRRZVHQks9mzZ4/bv3//Sl+GrEJ3PvBoPQjqPz0eBT4OEn4UztSGie/c2AFE4UNvLsNn77p1xmM2hinVIOTYSLTC3tbuDAnfY2wyauPryiY5ORqFQYZxWXeGXCbJ6XyRQjmgM5tke08b//HVO3jpzAT/z9f6qQQhpWpIk6xqis60z5/+xB5eua2LXCZ53nOtmX6u6UFP7bkM5ouEocPicO2y7gy+Z01/FzOdZ7hQYVtPdko11jtftZVH+ofmPUC98RxjkxWOj04CkPSMLd1ZKoHj3rddt+wh0Ws//lC9eq7GOcfoZIWvffD7l/VaRERERERELpaZPeac29PsPlVYiSyhmVrtanOUvIaZSjC3Fd9qK9nd98VD9J+ZxLnoOEeHJ8kmfXKZBD1tKbrbUowWylRDx7r2JB3pBINjk5weL9Oe9slPVvjW6BCP9J+d9/OarIT8wUMvTAmAprcqjk1WODtRJnSOHevamlaQNT6X50+PkzRjc1ca37MZW/aatUTmi1WqYXjeXK9H+odmDf9m0niOM+MlPAzzoDJLW+Vy0NB1ERERERFZKxRYiSzQbLOpakFOY8BQG/xNQ3teOQjxgP7T4/VA64q4fa52/OcH8xRKAcVKgCOqztqUS1OshhhRa16tIqpUCSgHIdUg5J/f+728dHaCz33zCHufPM6zp/JU4gns+WJw3vO5dnOO3o40zxwfJT9ZoTpDlVUinof1xNFh3vOZ/VzT28EH79h1XphyZrwEQCbhY2YzBj21Vflqz3dguDBry17T0KYcgEHfyTFSvseGjjS5TGLOKwrOdo65tlUuh7tv28k9ew9SKFfPm+slIiIiIiJyKVFL4ByoJXBtazZ8G5i1La/WMvb5Jwf4xwMncC4aRu5cNJB8a3eGchByYrR03vkMSCU8ytWQpB9VGjV7l3pAGO9PfOxao5hn0JZOkC9Wmz6npG9kkz5tKZ9s0qcchPyvD72eOx94lJfOjHNy7PzrqokCqyi8cTg8M3o7M7zzVVt58PFj9WP3ncxjwNaebL1tcDHa1xpbIrNJnzPjJU6OlfA9SHoezkGIY317iis3dCyowqrxHM3aKufSurlUGoO9+bQ5ioiIiIiItBq1BIos0PTh27W2trakR9K3+mwq3zNwcHK0SML3KFVD7v7L/ZQDh+dFFVC1bDh0jpNjJTa2J/Hj8KeRA0rVaGM5mDlQDhv2ryVatb0DRz2s6kgneOW2Lm7e3s2/HRqkWA3ozJxrqSuUq+zoageiVrh8sTpl5bnpVxCE4HtTV/RL+sYj/UPc+7brova+wfH69sZMfDHa12pthLXQplAOWNeWZLwUVaCZB0HVcSpfoho67nzg0XmHOo3nmN5WOZcVBpdSrSJNRERERETkUqbASlpSs6qmpf5LerNz3v9wfz2YgnOzkV44PU464cftd45E1ClGJYQo4nGU4q67MKTeugdRcLWtJ8vA8CRhCEmv9rjFkfCM9e0pPvjmXdy4vZsr17fjxbOzvuuKdbO2lG3vaYtCt3ilwOlSvhE4MBylakAYz8+qBmG9Ra5QCdnWk61Xnh0bmQRcvfJsMYKextCmNoh8vFTldL7EZCWoz/Xa3JmZ8+qLs52jWVUTRMPZl/M1KiIiIiIislaoJXAO1BK4vKa3fNVClaVclW2mcw5NFHHO6qv5behIA47DQ5NTQqi5qj3m8nVtHB5anBlIRtRuaAYb2lOkk4lZf1eztZTt6xvk7v/xGKFzGNTbEVO+sakzg5lxYqQwJWCrPae2pM+Oddn6YHKAfLHCydEiDnjVjp4lCXWmrxpYmwc239UX52MlXqMiIiIiIiKXGrUEyqoyU1XTYq3KNtdKqtP5IhOlkIRv+GZUA8fx0UmCuE3vYqLeI4sUVgF0pKOh5inf2Lkxd8FQaHpL2b6+wSmVQm+5fhNfeOYU1TAkm/ToakuS9H3ufdt1APzcXz1OJTw3tL32e6iGIc+fHmdbd7Z+Xy4TtdGNTlbqYdFiV89NH0ReiofRb8yl6/ss9pD0pX6NioiIiIiIrHUKrKTlHB0u0J1NTtm2WIHDTDOpJkoVtnRlp+ybL1bxDMLQUcXVh5o7ooHnjvmHVm7a14uVSXhcv7V7wZVDzX4fx0Ym+fnbr+KR/qGmVVjrOlJsNDg6PFlvCUzE86ySnsepfInObKp+jsa5VTP9/ufbrtdo+kyrtpRPe9qvD3qffg2LYSlfoyIiIiIiIqLASlrQ9p62KS1esHiBw/TKmGrgGMwXKVVCJsoBm3IZOuMgolQNwUHQ8Pha0LSII6cuSi5zcSHJ/Q/3U64GnB2v1tvocpkEj/QPzRiC1f58fM9ImWFmhM6R9IwNHSkGRoozzsi6mMqk2Sqzps+bmm1O12JYyteoiIiIiIiIRIUiIi3l7tt2UgkchXIV59yCV2Wrtbq99uMPcecDj7Kvb5CjwwWySZ+xyQrPncpzeKhAKR7IVA0cx0YmGZssUyhXATclrGpF+dLFhSTPnRrj7ESZauDqbY9nJ8o8f2psxsfU/nx8LwqqQhdVn23MpUn4Htf0dtCbyzA6WaE3l5ky16n2+280l8qkWgg1mC9Oqcza1zd43r637+rl3rddN+M1LIbFeo2KiIiIiIhIc6qwkpYzvcVrektaM/v6Bvn4v/TRf2YCgI0dKYrVkK5sckrA0ZHyOTNeqoc0cK5qKggdZnB4aBLfM4JFKqPKJj1ed20vP3jjZfzZ1/o5PlLg1Fg5utOiVQMXIuFx0SFJJf4d1FYRtLgFshzMfFG1P5/7vniI50+PkzRjc1ca3zMqgeMjb90145/VQiuT5luZNX1O12JbyGtURERERERE5k6BlbSU6W1fH3379VNave5/uJ/nTo1RCRyphMfVvTles3Mdf/a1fsZK5+qhBkaKALSnEljK6q1/QeCohq7pDCnHufAoCC9uypQBSd/YuaGdf/ml76tvb0v63LP3IO2pKuPlcMHDrAxIeB4bOlLc/3A/H/78MwsaYJ5KeEyWg2hVwFp45qLts6kFQo0rDvbmMhc8//QB6XNt12vFmVFLHYqJiIiIiIisZQqspGXs6xvk/Q8eYLxUJQgdZ8ZLvP/BA/zOO2/kqYER/uCrL9QrgmqGJ87yaP/ZGXOfw0MF0gkvmke1xKKMx0gnojlQqYTPh968e8o+t+/q5Z0DI/zRvhfxDUI3NbOqDXWvSXpGJXT4HoQhJPyoEmp9e4pq6ChVw/Pa5OYzwPzq3hwvnx1nbPLcDKvO9iRXrO+Y0+PnG9ostDJJM6NERERERETWFgVWsuxqVTnPD+YpV0OSvnHNpk6Onh1npFAB56i6qF2tWCnzU3/xrRmPNUvnWt1yhFUQzXAaLVQoVgOqBcfP376jaRDzSP8Q23qy9fCl//Q4xWpAEBdc1UIrs+iW8qPB5qlk/NU3rtzQwUihTDkIZ2yTm21IeU2t4mlzV2LJBpRPt5DKpIVWZomIiIiIiMjqpMBKlsRs7XsPPn6MShAwWqiAwWQFXjozzsmx0kpf9oKta0uyoSPDho4MAIVylUf6h3hvk32nt7dtzKU5NjwJ5vDMwCB0Dg8InOPqjR186M27zwt5Xvvxh2Zsk6sNKU/6Nmv11WqZxbRarlNEREREREQWhwIrWXS1sKRcDRgrVgGYLAe8fHacx48M09OWJF+M2v5qtU+rLayy+GsuE72FLuvOTrl/tvlK23vaeOnMOPniuTa8joxPEEazo8rVkJRvbOhIY2bkS1HVFEwNm6a3yY1NVjiVL+IcvPdzT9CW8unKRgHabEPKV8ssptVynSIiIiIiInLxZp+sLLIA933xEIP5IqfGStFKfC5ahW5ovEypGnJqrMREOWB5GvWWxn//qe/kpfveyiffdTMAfSfz9J8eZ2yyAsw+X+k1O9dxejxq5/MMykHIWDHgZ157Jfs//Eae+vUf4Hd+5CYKlZByEE6pkNrXN1g/zt237aQSOArlKmOTZY6NTFINHJs700yUq5ydKNevB1Z+SLmIiIiIiIjIXKnCSi5a40yqQjmgUA6m3F8JXTRdPHZx6++tPM+oVzzds/cg7WmfyXJAOQg5PjpJqRqQSvgzzld6pH+I3lxq6qDzbGJKC+H9D/eT9KPVDV8anaAchPiecd8XD9WrjBrb5B4/MkzCMzZ3ZchlkmTiQOzMeInOuG1QQ8pFRERERERktVBgJRflk195jj/a9yLVIDxvxbvVwjdwDkLOX6WvGTNjYLhQD5W6shnSCZ/T+RLFahTY3ffDN8zYvnZ0uMD69nR93hWAc25K9dPR4QK+wfHRIh6Gb0YYOp4/Pc6+vsEpodXtu3rr86zMombF2lysUjXEOach5SIiIiIiIrKqKLCSBdnXN8gv/82TnC1ULrxzC/M9I4irvzyYtU3R4v0Nx+hkheOjQ2QSHhs60nRmk+QySZyL7ptt1tL02VNwfvXT9p42njg6jIfheVY/f9Ks6Ryq6cfMZZJsyAVMlAJGJysaUi4iIiIiIiKrigIrmaLW3nd0uMD2OOQA+Pi/9NF/ZgKAlG/kS8Fsh1k1wtDVg6pahZXnQcr3CUJHOTgXYdVa9DBoT/tUg7DeBgjQmU3Oqe3u7tt2cs/egxTKVbJJv2n109237eQ9n9kfVX8RVYA5B5u70k3nUDU7ZtL3+eS7Zq70EhEREREREWlVCqxkygyqfLFKT1uSDR1pBvNFPvDgAUYKZSoNpUel6spd62Jz8S3pRYFVEEIirmjyPSOFVw+tzIxM0qOrLcGGjqgN8PhIEYfjzHiJhG9zartrnD01MFxoWv10+65erunt4KUzEwShI+V7bMyl8T2jN5dZ0DFbRbNQtBWvU0RERERERFaOObcapw4trz179rj9+/ev9GUsiX19g9yz9yBJ3+g/PbEqZ1A14zVUJs2FGWQTHpOVkIRvJLxzC2hWw5Bs0uepX/+B82ZF5YsVBseKlALHd12xblHDl8Y/m8ZKrHvfdt2qDXguxeckIiIiIiIiC2Nmjznn9jS7b01WWJnZHcAnAB/4M+fcfSt8ScuqsaJqaKLcuIDfqmTx18ansakzTcr3ODw0OadjOAddbUnWex7HR4tUwxDPosUNQwc/89orgeazompVT5+969ZFfFarq2pqrmqD6mu/v7ZUgkK52nQul4iIiIiIiKxday6wMjMf+CPgjcAA8C0z2+uc+/bKXtnSqoVUB4+Pki9VYZWu6NdMbWU/I5oz1ZtLs31dOwPDBdIJj1J1tlHq8dwqg6GJCrlMgsu6MpwZL1EOHO0pn5957ZW89w3XAHObP7WYaqsAXiqODhfozianbMsm/aZzuURERERERGTtWnOBFfBdwAvOuX4AM/sc8Hbgkg2sam1YlSBgrHgJDaCKOaKgCqJqqFI1rFcivfbjD+EbnBkvU6qGBM7V2wR7O1KMFauUqiGeZ6xrT7K+Pc1kJWBjLtO0Te1SrHpaTnNZIVFERERERERkLQZWW4GjDT8PAK9eoWtZFrU2rLPjUVhlNvfZTq0om/SBaIW/chDWB6c3DiavtZjVApKdGzvqjz8zXmSiFJBO+tzcm2OkUKYchHNuU7vUqp6W03JXqImIiIiIiMjq5F14l0uONdl2XnxjZneZ2X4z23/69OlluKylc3S4QDbpUw6iuUzLHVYlPejMJNjQnmTXpg66sjPnpGbRKn21iimAhm+nbLd4sHp7ymfX5k52buwgl0lOaTG7+7adVAJHoVzFuehr0vf55Ltu5msf/H4+e9et5EvVeghWoza1pXH7rl7ufdt19OYyjE5W6J2hkk1ERERERETWtrVYYTUAbG/4eRtwfPpOzrkHgAcgWiVweS5t8Tnn6M2lGRgu4JxbtAHrHjD7ZCjoTPt88s5XnRdG7Osb5COff4ajw9FA9ISBMwjC6PvLujMkfI+xyQrr21NMlANGJyskPGO8FBA6hxkE8ddcZurLuLHFbC4tfGpTW16qUBMREREREZELWYuB1beAq83sSuAY8C7gx1f2khbP6GSFJ48M89jhYQ4MjPL0sVGGJspzemzSg+62FD9x6+U80j/E86fGyJcCDCg2DC5/zZU9fPbu7wamrjhYKAeUqwG+53Hl+jY+9ObdM7bUfW3X99cfWwuSXrNzHY/0DzEwXKA3l+Ejb31F/fG1OVzppMdooUIpCEl4Hu+4cTOPHRmdtcXsQgGJ2tREREREREREWou51TzMaIHM7C3A7wM+8Cnn3Mdm23/Pnj1u//79y3Jt81Guhhw8Pspjh4d58ugIzxwb5eWzzdvYUr5HKuFRDUNwkE16XLu5k+++an09JGpWfTQ9VFrJAeMzXctiXGMrPU8RERERERGRtcDMHnPO7Wl631oMrOarFQIr5xwvnZngscPDPHFkhKeOjfDcyXHKwfmNeZ7BlRvauWl7Nzfv6OFVO3q4ZlMHCX8tjiwTERERERERkVY0W2C1FlsCV4Wz4yX2Hx7miSPDHDg6ysHjo4wVq0337c2luWFbFzft6OaWHT3csK2b9rT+aEVERERERERkdVKq0QImy1WeHBjh8cMjHDg6wjPHRzk+Umy6b1vK5/rLurhxexevujyqntrUmVnmKxYRERERERERWToKrJZZGDr6To6dG4o+MMoLp8cJmizf55vxHb0d3Li9i5u393DLFT1ctbED37MVuHIRERERERERkeWhwGqJHRueZP/hIQ4cHeGpgVEOnRhjohw03fey7gyv3NrFTdt7uOXybl65tZtsyl/mKxYRERERERERWVkKrBbR6GSZJ46M8MSRYZ46NsrBY2MM5ktN981lElx3WSc3buvmVZf3cMvlPWzoSC/zFYuIiIiIiIiItB4FVgtUrAQcPD7Gk0eHOXB0hIPHx3jpzARNOvtI+sY1m3LcsK2LV8Wr9u3c2I6ZWvtERERERERERKZTYDUHzsHzg3meODzCgYERnjk2yrOn8hQrYdP9t69r44atndy4vZtbLu/h+q1dpBNq7RMRERERERERmQsFVnNw6OQYb/zdh5ve192WjFbt29bNzZd3s+fyHrrbUst8hSIiIiIiIiIilw4FVnNQW8EvnfDYtTnHK7dFq/btubyHHevb1NonIiIiIiIiIrKIFFjNwZauDP/wc9/N9Zd1klRrn4iIiIiIiIjIklJgNQcbOtLcvKNnpS9DRERERERERGRN8Fb6AkRERERERERERBopsBIRERERERERkZaiwEpERERERERERFqKAisREREREREREWkpCqxERERERERERKSlKLASEREREREREZGWosBKRERERERERERaigIrERERERERERFpKQqsRERERERERESkpSiwEhERERERERGRlqLASkREREREREREWoo551b6GlqemZ0GDq/0dSySDcCZlb4IkVVI7x2RhdF7R2Th9P4RWRi9d0QWZiXeO5c75zY2u0OB1RpjZvudc3tW+jpEVhu9d0QWRu8dkYXT+0dkYfTeEVmYVnvvqCVQRERERERERERaigIrERERERERERFpKQqs1p4HVvoCRFYpvXdEFkbvHZGF0/tHZGH03hFZmJZ672iGlYiIiIiIiIiItBRVWImIiIiIiIiISEtRYLVGmNkdZvasmb1gZh9a6esRWUpm9ikzGzSzZxq2rTOzL5vZ8/HXnni7mdkn4/fGU2b2qobHvDve/3kze3fD9lvM7On4MZ80M1voOURaiZltN7OvmtkhMztoZu+Lt+v9IzILM8uY2TfN7ED83vmNePuVZvaN+HX912aWiren459fiO+/ouFYvxpvf9bMfqBhe9PPcgs5h0irMTPfzJ4ws3+Kf9Z7R2QOzOzl+HPVk2a2P952yXxuU2C1BpiZD/wR8GbgFcCdZvaKlb0qkSX1F8Ad07Z9CPg359zVwL/FP0P0vrg6vt0F/AlE/xEGfg14NfBdwK/V/kMc73NXw+PuWMg5RFpQFfhl59xu4Fbg5+P/X+j9IzK7EvD9zrkbgZuAO8zsVuDjwO/Fr+th4D3x/u8Bhp1z3wH8Xrwf8fvtXcB1RO+NP47/Ij/bZ7l5nUOkRb0PONTws947InP3OufcTc65PfHPl8znNgVWa8N3AS845/qdc2Xgc8DbV/iaRJaMc+5hYGja5rcDn46//zTwjobtn3GRR4FuM9sC/ADwZefckHNuGPgy0V9AtgCdzrlHXDQE8DPTjjWfc4i0FOfcCefc4/H3eaK/PGxF7x+RWcWvz/H4x2R8c8D3Aw/G26e/rmuv9weB18f/av124HPOuZJz7iXgBaLPcU0/y8WPme85RFqKmW0D3gr8WfzzQl7Xeu+InHPJfG5TYLU2bAWONvw8EG8TWUs2OedOQPSXcqA33j7T+2O27QNNti/kHCItK26BuBn4Bnr/iFxQXM3xJDBI9GH/RWDEOVeNd2l87dZf1/H9o8B65v+eWr+Ac4i0mt8HfgUI458X8rrWe0fWKgd8ycweM7O74m2XzOe2xEIfKKtKs38R0PKQIpGZ3h/z3b6Qc4i0JDPrAP4O+EXn3Ngs/7Cs949IzDkXADeZWTfwD8DuZrvFX+f7Hmn2j8wXek/pvSMtz8x+EBh0zj1mZrfXNjfZVe8dkea+xzl33Mx6gS+bWd8s+666z22qsFobBoDtDT9vA46v0LWIrJRTtXLU+OtgvH2m98ds27c12b6Qc4i0HDNLEoVVf+Wc+/t4s94/InPknBsB9hHNges2s9o/EDe+duuv6/j+LqJW9vm+p84s4BwireR7gLeZ2ctE7XrfT1RxpfeOyBw4547HXweJ/rHku7iEPrcpsFobvgVcHa+EkSIaSLh3ha9JZLntBWorXrwb+HzD9p+MV7S4FRiNy1r/FXiTmfXEQwffBPxrfF/ezG6N5xn85LRjzeccIi0lfk3/OXDIOfe7DXfp/SMyCzPbGFdWYWZZ4A1EM+C+Crwz3m3667r2en8n8FA8H2Qv8C6LVim7kmho7TeZ4bNc/Jj5nkOkZTjnftU5t805dwXR6/oh59x/RO8dkQsys3Yzy9W+J/q89QyX0uc255xua+AGvAV4jmiewn9d6evRTbelvAGfBU4AFaKU/z1Eswf+DXg+/rou3teIVo95EXga2NNwnP+NaGjnC8BPN2zfE//P4EXgDwGLt8/7HLrp1ko34LVEZdtPAU/Gt7fo/aObbrPfgBuAJ+L3zjPAPfH2nUR/aX4B+FsgHW/PxD+/EN+/s+FY/zV+vT8LvLlhe9PPcgs5h266teINuB34p/h7vXd00+0Ct/g1fCC+Hay9vi+lz221k4mIiIiIiIiIiLQEtQSKiIiIiIiIiEhLUWAlIiIiIiIiIiItRYGViIiIiIiIiIi0FAVWIiIiIiIiIiLSUhRYiYiIiIiIiIhIS1FgJSIiIiIiIiIiLUWBlYiIiMgCmVlgZk+a2UEzO2Bm/8XMvGn7fMLMjjVuN7OfMrM/jL//dTN7f8N9ZmaPmNkbG7b9uJn98wzXkGi4jtrtA/F9XzezbzTse6uZfcXM3tKw77iZPRt//9/N7A1mNhr/3Gdm9zU8/mfM7Pfj738zfl6N582ZWYeZfc7MnjazZ8zsa2bWdvG/bREREVlLEit9ASIiIiKr2KRz7iYAM+sF/ifQBfxavM0Dfgg4CtwG7LvQAZ1zzsz+M/A/zexmIA3cC7xxlofla9fRxBYze6Nz7ssN5/gC8IX4Gr8O/IJz7sn45zcAX3XOvSMOmg6Y2T84577R5Ni/7Zz7/cYNZvYR4Ihz7l3xz7uAyoWet4iIiEgjVViJiIiILALn3CBwF/ALZmbx5tcBzwB/Atw5j2MdAP4V+ADwG8CfO+deWuCl/Tbw4YU80DlXAA4AW+fxsC3AsYZj9DnnFFiJiIjIvCiwEhEREVkkzrl+os9XvfGmO4HPAv8A/KCZJedxuHuAdwOvB37nAvvmprXmvbPhvq8BmNn3zuPcxI9ZB+wEvj7DLh9oOOdX4m1/DnzYzP7dzD5qZt8x3/OKiIiIKLASERERWVwGYGYp4C3APzrnxoBvAG+a60Gcc+PAg8Cn51ChlHfO3dRwe3Da/R9jflVWrzOzp4CTwD/E1WPN/HbDOd8QX/djRCHX/w1sAPab2TXzOLeIiIiIAisRERGRxWJmO4EAGATuIJpn9bSZvQy8lnm0BcbC+HZRnHNfArqBPXN8yFedczcANwDvNbNXzvN8eefc3znnfhb4HNB/TB8AAAEtSURBVPDmeV2wiIiIrHkKrEREREQWgZltBP4U+EPnnCMKp37GOXeFc+4K4ErgTSu4Yt7HgF+ZzwOcc33Ab83ncWb2WjPrjr9PA7uBw/M5r4iIiIgCKxEREZGFy8bzmw4CXwG+BPxGHEr9APDPtR2dcxNEs6D+Q5PjfNjMBmq3BVzH9BlWH2uyz/8LDC3g2H8MvN7MdjS57wPTzrsduBr4mpk9DTwOPAJ8fgHnFRERkTXMon8AFBERERERERERaQ2qsBIRERERERERkZaSWOkLEBEREZELM7NeopbD6W53zo0s9/WIiIiILCW1BIqIiIiIiIiISEtRS6CIiIiIyP/fjh0LAAAAAAzyt57GjsIIAFgRVgAAAACsCCsAAAAAVoQVAAAAACvCCgAAAICVAEGbN/UBwog0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,5))\n",
    "sns.regplot(data=stations_all, x=\"DAILY_ENTRIES\", y=\"DAILY_EXITS\");\n",
    "plt.title('Daily Entries VS Daily Exits', fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "# Conclusions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the MTA is focusing on reducing the daily traffic of entries and exits, then more turnstiles should be added 34 ST-PENN STA, 34 ST-HERALD SQ, and GRD CNTRL-42 ST.\n",
    "\n",
    "However, if we take a look at the number of turnstiles for each of these stations, we can notice that 34 ST-HERALD SQ has nearly half the amount of turnstiles that 34 ST-PENN STA and GRD CNTRL-42 ST have. In this case, 34 ST-HERALD SQ should be prioritized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "#saved for visualizations in Tableau\n",
    "#stations_all.to_csv(\"stations_all.csv\")\n",
    "#top_stations_daily.to_csv(\"top_stations_daily.csv\")\n",
    "#turnstiles_per_station.to_csv(\"turnstiles_per_station.csv\")"
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "toc": {
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "288px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
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