part1_data_scrape_initial_analyze.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Finding The Optimal Neighborhood of Toronto (Part 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PART I -- scrape data from Wiki page, then create a dataframe contains the neighborhoods of Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` step 1: scrape Wiki page using pd.read.html ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M2A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postcode           Borough      Neighborhood\n",
       "0      M1A      Not assigned      Not assigned\n",
       "1      M2A      Not assigned      Not assigned\n",
       "2      M3A        North York         Parkwoods\n",
       "3      M4A        North York  Victoria Village\n",
       "4      M5A  Downtown Toronto      Harbourfront"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l = pd.read_html('https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M')\n",
    "df = l[0]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` step 2: drop rows where 'borough'='Not assigned' ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\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>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Manor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postcode           Borough      Neighborhood\n",
       "2      M3A        North York         Parkwoods\n",
       "3      M4A        North York  Victoria Village\n",
       "4      M5A  Downtown Toronto      Harbourfront\n",
       "5      M6A        North York  Lawrence Heights\n",
       "6      M6A        North York    Lawrence Manor"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df['Borough'] != 'Not assigned']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` step 3: merge neighborhoods which has the same postal code ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "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>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Heights,Lawrence Manor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M9A</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge,Malvern</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M3B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M4B</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Gardens,Parkview Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Ryerson,Garden District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>M6B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Glencairn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M9B</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Cloverdale,Islington,Martin Grove,Princess Gar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Highland Creek,Rouge Hill,Port Union</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>M3C</td>\n",
       "      <td>North York</td>\n",
       "      <td>Flemingdon Park,Don Mills South</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>M4C</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>M5C</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>M6C</td>\n",
       "      <td>York</td>\n",
       "      <td>Humewood-Cedarvale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M9C</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Bloordale Gardens,Eringate,Markland Wood,Old B...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood,Morningside,West Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Postcode           Borough  \\\n",
       "0       M3A        North York   \n",
       "1       M4A        North York   \n",
       "2       M5A  Downtown Toronto   \n",
       "3       M6A        North York   \n",
       "4       M7A  Downtown Toronto   \n",
       "5       M9A      Queen's Park   \n",
       "6       M1B       Scarborough   \n",
       "7       M3B        North York   \n",
       "8       M4B         East York   \n",
       "9       M5B  Downtown Toronto   \n",
       "10      M6B        North York   \n",
       "11      M9B         Etobicoke   \n",
       "12      M1C       Scarborough   \n",
       "13      M3C        North York   \n",
       "14      M4C         East York   \n",
       "15      M5C  Downtown Toronto   \n",
       "16      M6C              York   \n",
       "17      M9C         Etobicoke   \n",
       "18      M1E       Scarborough   \n",
       "19      M4E      East Toronto   \n",
       "\n",
       "                                         Neighborhood  \n",
       "0                                           Parkwoods  \n",
       "1                                    Victoria Village  \n",
       "2                                        Harbourfront  \n",
       "3                     Lawrence Heights,Lawrence Manor  \n",
       "4                                        Queen's Park  \n",
       "5                                        Not assigned  \n",
       "6                                       Rouge,Malvern  \n",
       "7                                     Don Mills North  \n",
       "8                      Woodbine Gardens,Parkview Hill  \n",
       "9                             Ryerson,Garden District  \n",
       "10                                          Glencairn  \n",
       "11  Cloverdale,Islington,Martin Grove,Princess Gar...  \n",
       "12               Highland Creek,Rouge Hill,Port Union  \n",
       "13                    Flemingdon Park,Don Mills South  \n",
       "14                                   Woodbine Heights  \n",
       "15                                     St. James Town  \n",
       "16                                 Humewood-Cedarvale  \n",
       "17  Bloordale Gardens,Eringate,Markland Wood,Old B...  \n",
       "18                    Guildwood,Morningside,West Hill  \n",
       "19                                        The Beaches  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.groupby(['Postcode','Borough'], sort = False).agg(lambda x: \",\".join(x)).reset_index()\n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` display the number of rows of this dataframe ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103, 3)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PART II -- get the latitude and the longitude coordinates of each neighborhood"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` step 1: read geocoder data from csv file ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1B</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M1C</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M1E</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M1G</td>\n",
       "      <td>43.770992</td>\n",
       "      <td>-79.216917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M1H</td>\n",
       "      <td>43.773136</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M1J</td>\n",
       "      <td>43.744734</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M1K</td>\n",
       "      <td>43.727929</td>\n",
       "      <td>-79.262029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M1L</td>\n",
       "      <td>43.711112</td>\n",
       "      <td>-79.284577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M1M</td>\n",
       "      <td>43.716316</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M1N</td>\n",
       "      <td>43.692657</td>\n",
       "      <td>-79.264848</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code   Latitude  Longitude\n",
       "0         M1B  43.806686 -79.194353\n",
       "1         M1C  43.784535 -79.160497\n",
       "2         M1E  43.763573 -79.188711\n",
       "3         M1G  43.770992 -79.216917\n",
       "4         M1H  43.773136 -79.239476\n",
       "5         M1J  43.744734 -79.239476\n",
       "6         M1K  43.727929 -79.262029\n",
       "7         M1L  43.711112 -79.284577\n",
       "8         M1M  43.716316 -79.239476\n",
       "9         M1N  43.692657 -79.264848"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_csv('http://cocl.us/Geospatial_data')\n",
    "df1.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` step 2: sort df (neighborhoods) and df1 (locations) in same order, and append 'Latitude' and 'Longitude' in df1 to df ```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "      <td>M3A</td>\n",
       "      <td>43.753259</td>\n",
       "      <td>-79.329656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "      <td>M4A</td>\n",
       "      <td>43.725882</td>\n",
       "      <td>-79.315572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>M5A</td>\n",
       "      <td>43.654260</td>\n",
       "      <td>-79.360636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Heights,Lawrence Manor</td>\n",
       "      <td>M6A</td>\n",
       "      <td>43.718518</td>\n",
       "      <td>-79.464763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>M7A</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M9A</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>M9A</td>\n",
       "      <td>43.667856</td>\n",
       "      <td>-79.532242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge,Malvern</td>\n",
       "      <td>M1B</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M3B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills North</td>\n",
       "      <td>M3B</td>\n",
       "      <td>43.745906</td>\n",
       "      <td>-79.352188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M4B</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Gardens,Parkview Hill</td>\n",
       "      <td>M4B</td>\n",
       "      <td>43.706397</td>\n",
       "      <td>-79.309937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Ryerson,Garden District</td>\n",
       "      <td>M5B</td>\n",
       "      <td>43.657162</td>\n",
       "      <td>-79.378937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>M6B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Glencairn</td>\n",
       "      <td>M6B</td>\n",
       "      <td>43.709577</td>\n",
       "      <td>-79.445073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M9B</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Cloverdale,Islington,Martin Grove,Princess Gar...</td>\n",
       "      <td>M9B</td>\n",
       "      <td>43.650943</td>\n",
       "      <td>-79.554724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Highland Creek,Rouge Hill,Port Union</td>\n",
       "      <td>M1C</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>M3C</td>\n",
       "      <td>North York</td>\n",
       "      <td>Flemingdon Park,Don Mills South</td>\n",
       "      <td>M3C</td>\n",
       "      <td>43.725900</td>\n",
       "      <td>-79.340923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>M4C</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Heights</td>\n",
       "      <td>M4C</td>\n",
       "      <td>43.695344</td>\n",
       "      <td>-79.318389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>M5C</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "      <td>M5C</td>\n",
       "      <td>43.651494</td>\n",
       "      <td>-79.375418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>M6C</td>\n",
       "      <td>York</td>\n",
       "      <td>Humewood-Cedarvale</td>\n",
       "      <td>M6C</td>\n",
       "      <td>43.693781</td>\n",
       "      <td>-79.428191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M9C</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Bloordale Gardens,Eringate,Markland Wood,Old B...</td>\n",
       "      <td>M9C</td>\n",
       "      <td>43.643515</td>\n",
       "      <td>-79.577201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood,Morningside,West Hill</td>\n",
       "      <td>M1E</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>M4E</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Postcode           Borough  \\\n",
       "0       M3A        North York   \n",
       "1       M4A        North York   \n",
       "2       M5A  Downtown Toronto   \n",
       "3       M6A        North York   \n",
       "4       M7A  Downtown Toronto   \n",
       "5       M9A      Queen's Park   \n",
       "6       M1B       Scarborough   \n",
       "7       M3B        North York   \n",
       "8       M4B         East York   \n",
       "9       M5B  Downtown Toronto   \n",
       "10      M6B        North York   \n",
       "11      M9B         Etobicoke   \n",
       "12      M1C       Scarborough   \n",
       "13      M3C        North York   \n",
       "14      M4C         East York   \n",
       "15      M5C  Downtown Toronto   \n",
       "16      M6C              York   \n",
       "17      M9C         Etobicoke   \n",
       "18      M1E       Scarborough   \n",
       "19      M4E      East Toronto   \n",
       "\n",
       "                                         Neighborhood Postal Code   Latitude  \\\n",
       "0                                           Parkwoods         M3A  43.753259   \n",
       "1                                    Victoria Village         M4A  43.725882   \n",
       "2                                        Harbourfront         M5A  43.654260   \n",
       "3                     Lawrence Heights,Lawrence Manor         M6A  43.718518   \n",
       "4                                        Queen's Park         M7A  43.662301   \n",
       "5                                        Not assigned         M9A  43.667856   \n",
       "6                                       Rouge,Malvern         M1B  43.806686   \n",
       "7                                     Don Mills North         M3B  43.745906   \n",
       "8                      Woodbine Gardens,Parkview Hill         M4B  43.706397   \n",
       "9                             Ryerson,Garden District         M5B  43.657162   \n",
       "10                                          Glencairn         M6B  43.709577   \n",
       "11  Cloverdale,Islington,Martin Grove,Princess Gar...         M9B  43.650943   \n",
       "12               Highland Creek,Rouge Hill,Port Union         M1C  43.784535   \n",
       "13                    Flemingdon Park,Don Mills South         M3C  43.725900   \n",
       "14                                   Woodbine Heights         M4C  43.695344   \n",
       "15                                     St. James Town         M5C  43.651494   \n",
       "16                                 Humewood-Cedarvale         M6C  43.693781   \n",
       "17  Bloordale Gardens,Eringate,Markland Wood,Old B...         M9C  43.643515   \n",
       "18                    Guildwood,Morningside,West Hill         M1E  43.763573   \n",
       "19                                        The Beaches         M4E  43.676357   \n",
       "\n",
       "    Longitude  \n",
       "0  -79.329656  \n",
       "1  -79.315572  \n",
       "2  -79.360636  \n",
       "3  -79.464763  \n",
       "4  -79.389494  \n",
       "5  -79.532242  \n",
       "6  -79.194353  \n",
       "7  -79.352188  \n",
       "8  -79.309937  \n",
       "9  -79.378937  \n",
       "10 -79.445073  \n",
       "11 -79.554724  \n",
       "12 -79.160497  \n",
       "13 -79.340923  \n",
       "14 -79.318389  \n",
       "15 -79.375418  \n",
       "16 -79.428191  \n",
       "17 -79.577201  \n",
       "18 -79.188711  \n",
       "19 -79.293031  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.merge(left=df,right=df1, left_on='Postcode', right_on='Postal Code')\n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103, 6)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PART III -- Toronto neighborhoods and boroughs\n",
    "note: for this part, I'm going to replicate the NYC analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving environment: done\n",
      "\n",
      "# All requested packages already installed.\n",
      "\n",
      "Solving environment: done\n",
      "\n",
      "# All requested packages already installed.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import matplotlib as mpl\n",
    "from sklearn.cluster import KMeans\n",
    "import json\n",
    "from pandas.io.json import json_normalize\n",
    "\n",
    "!conda install -c conda-forge geopy --yes\n",
    "from geopy.geocoders import Nominatim\n",
    "\n",
    "import requests\n",
    "\n",
    "!conda install -c conda-forge folium=0.5.0 --yes\n",
    "import folium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 1: create a new dataframe with only boroughs that contain the word Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df['Borough'].str.contains('Toronto')].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The dataframe has 4 boroughs and 39 neighborhoods.\n"
     ]
    }
   ],
   "source": [
    "print('The dataframe has {} boroughs and {} neighborhoods.'.format(len(df2['Borough'].unique()),df2.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 2: use geopy library to get the latitude and longitude values of Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Toronto are 43.653963, -79.387207.\n"
     ]
    }
   ],
   "source": [
    "address = 'Toronto, ON'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"on_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 3: create a map of Toronto with neighborhoods superimposed on top"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
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</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f493da282b0>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Toronto using latitude and longitude values\n",
    "map_Toronto = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, borough, neighborhood in zip(df2['Latitude'], df2['Longitude'], df2['Borough'], df2['Neighborhood']):\n",
    "    label = '{}, {}'.format(neighborhood, borough)\n",
    "    label = folium.Popup(label, parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lng],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color='blue',\n",
    "        fill=True,\n",
    "        fill_color='#3186cc',\n",
    "        fill_opacity=0.7,\n",
    "        parse_html=False).add_to(map_Toronto)  \n",
    "    \n",
    "map_Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 4: for illustration purposes, simply the above map and segment and cluster only the neighborhoods in Downtown Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "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>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>M5A</td>\n",
       "      <td>43.654260</td>\n",
       "      <td>-79.360636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>M7A</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Ryerson,Garden District</td>\n",
       "      <td>M5B</td>\n",
       "      <td>43.657162</td>\n",
       "      <td>-79.378937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M5C</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "      <td>M5C</td>\n",
       "      <td>43.651494</td>\n",
       "      <td>-79.375418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M5E</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Berczy Park</td>\n",
       "      <td>M5E</td>\n",
       "      <td>43.644771</td>\n",
       "      <td>-79.373306</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postcode           Borough             Neighborhood Postal Code   Latitude  \\\n",
       "0      M5A  Downtown Toronto             Harbourfront         M5A  43.654260   \n",
       "1      M7A  Downtown Toronto             Queen's Park         M7A  43.662301   \n",
       "2      M5B  Downtown Toronto  Ryerson,Garden District         M5B  43.657162   \n",
       "3      M5C  Downtown Toronto           St. James Town         M5C  43.651494   \n",
       "4      M5E  Downtown Toronto              Berczy Park         M5E  43.644771   \n",
       "\n",
       "   Longitude  \n",
       "0 -79.360636  \n",
       "1 -79.389494  \n",
       "2 -79.378937  \n",
       "3 -79.375418  \n",
       "4 -79.373306  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtt = df2[df2['Borough'] == 'Downtown Toronto'].reset_index(drop=True)\n",
    "dtt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Downtown Toronto are 43.6563221, -79.3809161.\n"
     ]
    }
   ],
   "source": [
    "# Get the geograpical coordinate of Downtown Toronto\n",
    "\n",
    "address = 'Downtown Toronto, ON'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"ny_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Downtown Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
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</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f493d8d02e8>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Downtown Toronto using latitude and longitude values\n",
    "map_dtt = folium.Map(location=[latitude, longitude], zoom_start=13)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, label in zip(dtt['Latitude'], dtt['Longitude'], dtt['Neighborhood']):\n",
    "    label = folium.Popup(label, parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lng],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color='blue',\n",
    "        fill=True,\n",
    "        fill_color='#3186cc',\n",
    "        fill_opacity=0.7,\n",
    "        parse_html=False).add_to(map_dtt)  \n",
    "    \n",
    "map_dtt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 5: utilizing Foursquare API and explore the neighborhoods and segment them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your credentails:\n",
      "CLIENT_ID: ZNSID3JACAT4524JYYIWEF3UYOAGQ1CJFGKOQVFGWTXPK1L3\n",
      "CLIENT_SECRET:5E0LASVEW5N50XVEP4MKU0FN4YZ5LYKFVPITQDJBIYG1H4S1\n"
     ]
    }
   ],
   "source": [
    "CLIENT_ID = 'ZNSID3JACAT4524JYYIWEF3UYOAGQ1CJFGKOQVFGWTXPK1L3'\n",
    "CLIENT_SECRET = '5E0LASVEW5N50XVEP4MKU0FN4YZ5LYKFVPITQDJBIYG1H4S1'\n",
    "VERSION = '20180605'\n",
    "\n",
    "print('Your credentails:')\n",
    "print('CLIENT_ID: ' + CLIENT_ID)\n",
    "print('CLIENT_SECRET:' + CLIENT_SECRET)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.1 -- explore the first neighborhood in downtown Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Harbourfront'"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtt.loc[0, 'Neighborhood']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Latitude and longitude values of Harbourfront are 43.6542599, -79.3606359.\n"
     ]
    }
   ],
   "source": [
    "# get Harbourfront's latitude and longitude values\n",
    "\n",
    "neighbor_latitude = dtt.loc[0, 'Latitude']\n",
    "neighbor_longitude = dtt.loc[0, 'Longitude']\n",
    "\n",
    "neighbor_name = dtt.loc[0, 'Neighborhood'] # neighborhood name\n",
    "\n",
    "print('Latitude and longitude values of {} are {}, {}.'.format(neighbor_name, neighbor_latitude, neighbor_longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.2 -- get the top 100 venues in the neighborhood within 500 meters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "limit = 100\n",
    "radius = 500\n",
    "\n",
    "url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(\n",
    "    CLIENT_ID, \n",
    "    CLIENT_SECRET, \n",
    "    VERSION, \n",
    "    neighbor_latitude, \n",
    "    neighbor_longitude, \n",
    "    radius, \n",
    "    limit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = requests.get(url).json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function that extracts the category of the venue\n",
    "def get_category_type(row):\n",
    "    try:\n",
    "        categories_list = row['categories']\n",
    "    except:\n",
    "        categories_list = row['venue.categories']\n",
    "        \n",
    "    if len(categories_list) == 0:\n",
    "        return None\n",
    "    else:\n",
    "        return categories_list[0]['name']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.3 -- clean JSON and structure it into a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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>name</th>\n",
       "      <th>categories</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Roselle Desserts</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>43.653447</td>\n",
       "      <td>-79.362017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tandem Coffee</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.653559</td>\n",
       "      <td>-79.361809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cooper Koo Family YMCA</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>43.653191</td>\n",
       "      <td>-79.357947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Body Blitz Spa East</td>\n",
       "      <td>Spa</td>\n",
       "      <td>43.654735</td>\n",
       "      <td>-79.359874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Impact Kitchen</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>43.656369</td>\n",
       "      <td>-79.356980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Morning Glory Cafe</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>43.653947</td>\n",
       "      <td>-79.361149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Dominion Pub and Kitchen</td>\n",
       "      <td>Pub</td>\n",
       "      <td>43.656919</td>\n",
       "      <td>-79.358967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>The Distillery Historic District</td>\n",
       "      <td>Historic Site</td>\n",
       "      <td>43.650244</td>\n",
       "      <td>-79.359323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Corktown Common</td>\n",
       "      <td>Park</td>\n",
       "      <td>43.655618</td>\n",
       "      <td>-79.356211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Figs Breakfast &amp; Lunch</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>43.655675</td>\n",
       "      <td>-79.364503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SOMA chocolatemaker</td>\n",
       "      <td>Chocolate Shop</td>\n",
       "      <td>43.650622</td>\n",
       "      <td>-79.358127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Distillery Sunday Market</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>43.650075</td>\n",
       "      <td>-79.361832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Young Centre for the Performing Arts</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "      <td>43.650825</td>\n",
       "      <td>-79.357593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Cacao 70</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>43.650067</td>\n",
       "      <td>-79.360723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Arvo</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.649963</td>\n",
       "      <td>-79.361442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Rooster Coffee</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.651900</td>\n",
       "      <td>-79.365609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Brick Street Bakery</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>43.650574</td>\n",
       "      <td>-79.359539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.651613</td>\n",
       "      <td>-79.364917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Sumach Espresso</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.658135</td>\n",
       "      <td>-79.359515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Cluny Bistro &amp; Boulangerie</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>43.650565</td>\n",
       "      <td>-79.357843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Underpass Park</td>\n",
       "      <td>Park</td>\n",
       "      <td>43.655764</td>\n",
       "      <td>-79.354806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ODIN Cafe + Bar</td>\n",
       "      <td>Café</td>\n",
       "      <td>43.656739</td>\n",
       "      <td>-79.356503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>El Catrin</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>43.650601</td>\n",
       "      <td>-79.358920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Cocina Economica</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>43.654959</td>\n",
       "      <td>-79.365657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>The Sweet Escape Patisserie</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>43.650632</td>\n",
       "      <td>-79.358709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Dark Horse Espresso Bar</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.653081</td>\n",
       "      <td>-79.357078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Berkeley Church</td>\n",
       "      <td>Event Space</td>\n",
       "      <td>43.655123</td>\n",
       "      <td>-79.365873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Parliament Square Park</td>\n",
       "      <td>Park</td>\n",
       "      <td>43.650264</td>\n",
       "      <td>-79.362195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Caffe Furbo</td>\n",
       "      <td>Café</td>\n",
       "      <td>43.649970</td>\n",
       "      <td>-79.358849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Mill St. Brew Pub</td>\n",
       "      <td>Pub</td>\n",
       "      <td>43.650353</td>\n",
       "      <td>-79.358489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>John Fluevog Shoes</td>\n",
       "      <td>Shoe Store</td>\n",
       "      <td>43.649896</td>\n",
       "      <td>-79.359436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Greg's Ice Cream</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>43.650102</td>\n",
       "      <td>-79.360440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Izumi</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>43.649970</td>\n",
       "      <td>-79.360153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>The Aviary</td>\n",
       "      <td>Pub</td>\n",
       "      <td>43.653634</td>\n",
       "      <td>-79.354662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>The Abnormal Beauty Company</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>43.649892</td>\n",
       "      <td>-79.361005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Soulpepper Theatre</td>\n",
       "      <td>Theater</td>\n",
       "      <td>43.650780</td>\n",
       "      <td>-79.357615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Arta Gallery</td>\n",
       "      <td>Art Gallery</td>\n",
       "      <td>43.650022</td>\n",
       "      <td>-79.361222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Ontario Spring Water Sake Company</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>43.649922</td>\n",
       "      <td>-79.360073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Vistek</td>\n",
       "      <td>Electronics Store</td>\n",
       "      <td>43.657046</td>\n",
       "      <td>-79.359667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>TD Canada Trust</td>\n",
       "      <td>Bank</td>\n",
       "      <td>43.652780</td>\n",
       "      <td>-79.356336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>The Beer Store</td>\n",
       "      <td>Beer Store</td>\n",
       "      <td>43.657773</td>\n",
       "      <td>-79.357463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Savoury Grounds</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>43.656821</td>\n",
       "      <td>-79.358970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Residence &amp; Conference Centre</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>43.653040</td>\n",
       "      <td>-79.357040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>The Healthy Road</td>\n",
       "      <td>Health Food Store</td>\n",
       "      <td>43.656265</td>\n",
       "      <td>-79.357119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>GW General</td>\n",
       "      <td>Antique Shop</td>\n",
       "      <td>43.650495</td>\n",
       "      <td>-79.357538</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    name             categories        lat  \\\n",
       "0                       Roselle Desserts                 Bakery  43.653447   \n",
       "1                          Tandem Coffee            Coffee Shop  43.653559   \n",
       "2                 Cooper Koo Family YMCA   Gym / Fitness Center  43.653191   \n",
       "3                    Body Blitz Spa East                    Spa  43.654735   \n",
       "4                         Impact Kitchen             Restaurant  43.656369   \n",
       "5                     Morning Glory Cafe         Breakfast Spot  43.653947   \n",
       "6               Dominion Pub and Kitchen                    Pub  43.656919   \n",
       "7       The Distillery Historic District          Historic Site  43.650244   \n",
       "8                        Corktown Common                   Park  43.655618   \n",
       "9                 Figs Breakfast & Lunch         Breakfast Spot  43.655675   \n",
       "10                   SOMA chocolatemaker         Chocolate Shop  43.650622   \n",
       "11              Distillery Sunday Market         Farmers Market  43.650075   \n",
       "12  Young Centre for the Performing Arts  Performing Arts Venue  43.650825   \n",
       "13                              Cacao 70           Dessert Shop  43.650067   \n",
       "14                                  Arvo            Coffee Shop  43.649963   \n",
       "15                        Rooster Coffee            Coffee Shop  43.651900   \n",
       "16                   Brick Street Bakery                 Bakery  43.650574   \n",
       "17                             Starbucks            Coffee Shop  43.651613   \n",
       "18                       Sumach Espresso            Coffee Shop  43.658135   \n",
       "19            Cluny Bistro & Boulangerie      French Restaurant  43.650565   \n",
       "20                        Underpass Park                   Park  43.655764   \n",
       "21                       ODIN Cafe + Bar                   Café  43.656739   \n",
       "22                             El Catrin     Mexican Restaurant  43.650601   \n",
       "23                      Cocina Economica     Mexican Restaurant  43.654959   \n",
       "24           The Sweet Escape Patisserie                 Bakery  43.650632   \n",
       "25               Dark Horse Espresso Bar            Coffee Shop  43.653081   \n",
       "26                       Berkeley Church            Event Space  43.655123   \n",
       "27                Parliament Square Park                   Park  43.650264   \n",
       "28                           Caffe Furbo                   Café  43.649970   \n",
       "29                     Mill St. Brew Pub                    Pub  43.650353   \n",
       "30                    John Fluevog Shoes             Shoe Store  43.649896   \n",
       "31                      Greg's Ice Cream         Ice Cream Shop  43.650102   \n",
       "32                                 Izumi       Asian Restaurant  43.649970   \n",
       "33                            The Aviary                    Pub  43.653634   \n",
       "34           The Abnormal Beauty Company         Cosmetics Shop  43.649892   \n",
       "35                    Soulpepper Theatre                Theater  43.650780   \n",
       "36                          Arta Gallery            Art Gallery  43.650022   \n",
       "37     Ontario Spring Water Sake Company                Brewery  43.649922   \n",
       "38                                Vistek      Electronics Store  43.657046   \n",
       "39                       TD Canada Trust                   Bank  43.652780   \n",
       "40                        The Beer Store             Beer Store  43.657773   \n",
       "41                       Savoury Grounds            Coffee Shop  43.656821   \n",
       "42         Residence & Conference Centre                  Hotel  43.653040   \n",
       "43                      The Healthy Road      Health Food Store  43.656265   \n",
       "44                            GW General           Antique Shop  43.650495   \n",
       "\n",
       "          lng  \n",
       "0  -79.362017  \n",
       "1  -79.361809  \n",
       "2  -79.357947  \n",
       "3  -79.359874  \n",
       "4  -79.356980  \n",
       "5  -79.361149  \n",
       "6  -79.358967  \n",
       "7  -79.359323  \n",
       "8  -79.356211  \n",
       "9  -79.364503  \n",
       "10 -79.358127  \n",
       "11 -79.361832  \n",
       "12 -79.357593  \n",
       "13 -79.360723  \n",
       "14 -79.361442  \n",
       "15 -79.365609  \n",
       "16 -79.359539  \n",
       "17 -79.364917  \n",
       "18 -79.359515  \n",
       "19 -79.357843  \n",
       "20 -79.354806  \n",
       "21 -79.356503  \n",
       "22 -79.358920  \n",
       "23 -79.365657  \n",
       "24 -79.358709  \n",
       "25 -79.357078  \n",
       "26 -79.365873  \n",
       "27 -79.362195  \n",
       "28 -79.358849  \n",
       "29 -79.358489  \n",
       "30 -79.359436  \n",
       "31 -79.360440  \n",
       "32 -79.360153  \n",
       "33 -79.354662  \n",
       "34 -79.361005  \n",
       "35 -79.357615  \n",
       "36 -79.361222  \n",
       "37 -79.360073  \n",
       "38 -79.359667  \n",
       "39 -79.356336  \n",
       "40 -79.357463  \n",
       "41 -79.358970  \n",
       "42 -79.357040  \n",
       "43 -79.357119  \n",
       "44 -79.357538  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "venues = results['response']['groups'][0]['items']\n",
    "    \n",
    "nearby_venues = json_normalize(venues) # flatten JSON\n",
    "\n",
    "# filter columns\n",
    "filtered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']\n",
    "nearby_venues = nearby_venues.loc[:, filtered_columns]\n",
    "\n",
    "# filter the category for each row\n",
    "nearby_venues['venue.categories'] = nearby_venues.apply(get_category_type, axis=1)\n",
    "\n",
    "# clean columns\n",
    "nearby_venues.columns = [col.split(\".\")[-1] for col in nearby_venues.columns]\n",
    "\n",
    "nearby_venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45 venues were returned by Foursquare.\n"
     ]
    }
   ],
   "source": [
    "print('{} venues were returned by Foursquare.'.format(nearby_venues.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.4 -- write a function to repeat the same process to all neighborhoods in Downtown Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getNearbyVenues(names, latitudes, longitudes, radius=500):\n",
    "    \n",
    "    venues_list=[]\n",
    "    for name, lat, lng in zip(names, latitudes, longitudes):\n",
    "        print(name)\n",
    "            \n",
    "        # create the API request URL\n",
    "        url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(\n",
    "            CLIENT_ID, \n",
    "            CLIENT_SECRET, \n",
    "            VERSION, \n",
    "            lat, \n",
    "            lng, \n",
    "            radius, \n",
    "            LIMIT)\n",
    "            \n",
    "        # make the GET request\n",
    "        results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n",
    "        \n",
    "        # return only relevant information for each nearby venue\n",
    "        venues_list.append([(\n",
    "            name, \n",
    "            lat, \n",
    "            lng, \n",
    "            v['venue']['name'], \n",
    "            v['venue']['location']['lat'], \n",
    "            v['venue']['location']['lng'],  \n",
    "            v['venue']['categories'][0]['name']) for v in results])\n",
    "\n",
    "    nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])\n",
    "    nearby_venues.columns = ['Neighborhood', \n",
    "                  'Neighborhood Latitude', \n",
    "                  'Neighborhood Longitude', \n",
    "                  'Venue', \n",
    "                  'Venue Latitude', \n",
    "                  'Venue Longitude', \n",
    "                  'Venue Category']\n",
    "    \n",
    "    return(nearby_venues)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Harbourfront\n",
      "Queen's Park\n",
      "Ryerson,Garden District\n",
      "St. James Town\n",
      "Berczy Park\n",
      "Central Bay Street\n",
      "Christie\n",
      "Adelaide,King,Richmond\n",
      "Harbourfront East,Toronto Islands,Union Station\n",
      "Design Exchange,Toronto Dominion Centre\n",
      "Commerce Court,Victoria Hotel\n",
      "Harbord,University of Toronto\n",
      "Chinatown,Grange Park,Kensington Market\n",
      "CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara\n",
      "Rosedale\n",
      "Stn A PO Boxes 25 The Esplanade\n",
      "Cabbagetown,St. James Town\n",
      "First Canadian Place,Underground city\n",
      "Church and Wellesley\n"
     ]
    }
   ],
   "source": [
    "# run above code on each neighborhood and create a new dataframe called *dtt_venues*.\n",
    "\n",
    "dtt_venues = getNearbyVenues(names=dtt['Neighborhood'],\n",
    "                             latitudes=dtt['Latitude'],\n",
    "                             longitudes=dtt['Longitude'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1308, 7)\n"
     ]
    }
   ],
   "source": [
    "print(dtt_venues.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "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>Neighborhood</th>\n",
       "      <th>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Roselle Desserts</td>\n",
       "      <td>43.653447</td>\n",
       "      <td>-79.362017</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Tandem Coffee</td>\n",
       "      <td>43.653559</td>\n",
       "      <td>-79.361809</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Cooper Koo Family YMCA</td>\n",
       "      <td>43.653191</td>\n",
       "      <td>-79.357947</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Body Blitz Spa East</td>\n",
       "      <td>43.654735</td>\n",
       "      <td>-79.359874</td>\n",
       "      <td>Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Impact Kitchen</td>\n",
       "      <td>43.656369</td>\n",
       "      <td>-79.356980</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Neighborhood  Neighborhood Latitude  Neighborhood Longitude  \\\n",
       "0  Harbourfront               43.65426              -79.360636   \n",
       "1  Harbourfront               43.65426              -79.360636   \n",
       "2  Harbourfront               43.65426              -79.360636   \n",
       "3  Harbourfront               43.65426              -79.360636   \n",
       "4  Harbourfront               43.65426              -79.360636   \n",
       "\n",
       "                    Venue  Venue Latitude  Venue Longitude  \\\n",
       "0        Roselle Desserts       43.653447       -79.362017   \n",
       "1           Tandem Coffee       43.653559       -79.361809   \n",
       "2  Cooper Koo Family YMCA       43.653191       -79.357947   \n",
       "3     Body Blitz Spa East       43.654735       -79.359874   \n",
       "4          Impact Kitchen       43.656369       -79.356980   \n",
       "\n",
       "         Venue Category  \n",
       "0                Bakery  \n",
       "1           Coffee Shop  \n",
       "2  Gym / Fitness Center  \n",
       "3                   Spa  \n",
       "4            Restaurant  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtt_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neighborhood</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Adelaide,King,Richmond</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Berczy Park</th>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabbagetown,St. James Town</th>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central Bay Street</th>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chinatown,Grange Park,Kensington Market</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christie</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Church and Wellesley</th>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Commerce Court,Victoria Hotel</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Design Exchange,Toronto Dominion Centre</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First Canadian Place,Underground city</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harbord,University of Toronto</th>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harbourfront</th>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Harbourfront East,Toronto Islands,Union Station</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Queen's Park</th>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rosedale</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ryerson,Garden District</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St. James Town</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stn A PO Boxes 25 The Esplanade</th>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Neighborhood Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Adelaide,King,Richmond                                                100   \n",
       "Berczy Park                                                            55   \n",
       "CN Tower,Bathurst Quay,Island airport,Harbourfr...                     15   \n",
       "Cabbagetown,St. James Town                                             45   \n",
       "Central Bay Street                                                     84   \n",
       "Chinatown,Grange Park,Kensington Market                                90   \n",
       "Christie                                                               17   \n",
       "Church and Wellesley                                                   84   \n",
       "Commerce Court,Victoria Hotel                                         100   \n",
       "Design Exchange,Toronto Dominion Centre                               100   \n",
       "First Canadian Place,Underground city                                 100   \n",
       "Harbord,University of Toronto                                          35   \n",
       "Harbourfront                                                           45   \n",
       "Harbourfront East,Toronto Islands,Union Station                       100   \n",
       "Queen's Park                                                           39   \n",
       "Rosedale                                                                4   \n",
       "Ryerson,Garden District                                               100   \n",
       "St. James Town                                                        100   \n",
       "Stn A PO Boxes 25 The Esplanade                                        95   \n",
       "\n",
       "                                                    Neighborhood Longitude  \\\n",
       "Neighborhood                                                                 \n",
       "Adelaide,King,Richmond                                                 100   \n",
       "Berczy Park                                                             55   \n",
       "CN Tower,Bathurst Quay,Island airport,Harbourfr...                      15   \n",
       "Cabbagetown,St. James Town                                              45   \n",
       "Central Bay Street                                                      84   \n",
       "Chinatown,Grange Park,Kensington Market                                 90   \n",
       "Christie                                                                17   \n",
       "Church and Wellesley                                                    84   \n",
       "Commerce Court,Victoria Hotel                                          100   \n",
       "Design Exchange,Toronto Dominion Centre                                100   \n",
       "First Canadian Place,Underground city                                  100   \n",
       "Harbord,University of Toronto                                           35   \n",
       "Harbourfront                                                            45   \n",
       "Harbourfront East,Toronto Islands,Union Station                        100   \n",
       "Queen's Park                                                            39   \n",
       "Rosedale                                                                 4   \n",
       "Ryerson,Garden District                                                100   \n",
       "St. James Town                                                         100   \n",
       "Stn A PO Boxes 25 The Esplanade                                         95   \n",
       "\n",
       "                                                    Venue  Venue Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Adelaide,King,Richmond                                100             100   \n",
       "Berczy Park                                            55              55   \n",
       "CN Tower,Bathurst Quay,Island airport,Harbourfr...     15              15   \n",
       "Cabbagetown,St. James Town                             45              45   \n",
       "Central Bay Street                                     84              84   \n",
       "Chinatown,Grange Park,Kensington Market                90              90   \n",
       "Christie                                               17              17   \n",
       "Church and Wellesley                                   84              84   \n",
       "Commerce Court,Victoria Hotel                         100             100   \n",
       "Design Exchange,Toronto Dominion Centre               100             100   \n",
       "First Canadian Place,Underground city                 100             100   \n",
       "Harbord,University of Toronto                          35              35   \n",
       "Harbourfront                                           45              45   \n",
       "Harbourfront East,Toronto Islands,Union Station       100             100   \n",
       "Queen's Park                                           39              39   \n",
       "Rosedale                                                4               4   \n",
       "Ryerson,Garden District                               100             100   \n",
       "St. James Town                                        100             100   \n",
       "Stn A PO Boxes 25 The Esplanade                        95              95   \n",
       "\n",
       "                                                    Venue Longitude  \\\n",
       "Neighborhood                                                          \n",
       "Adelaide,King,Richmond                                          100   \n",
       "Berczy Park                                                      55   \n",
       "CN Tower,Bathurst Quay,Island airport,Harbourfr...               15   \n",
       "Cabbagetown,St. James Town                                       45   \n",
       "Central Bay Street                                               84   \n",
       "Chinatown,Grange Park,Kensington Market                          90   \n",
       "Christie                                                         17   \n",
       "Church and Wellesley                                             84   \n",
       "Commerce Court,Victoria Hotel                                   100   \n",
       "Design Exchange,Toronto Dominion Centre                         100   \n",
       "First Canadian Place,Underground city                           100   \n",
       "Harbord,University of Toronto                                    35   \n",
       "Harbourfront                                                     45   \n",
       "Harbourfront East,Toronto Islands,Union Station                 100   \n",
       "Queen's Park                                                     39   \n",
       "Rosedale                                                          4   \n",
       "Ryerson,Garden District                                         100   \n",
       "St. James Town                                                  100   \n",
       "Stn A PO Boxes 25 The Esplanade                                  95   \n",
       "\n",
       "                                                    Venue Category  \n",
       "Neighborhood                                                        \n",
       "Adelaide,King,Richmond                                         100  \n",
       "Berczy Park                                                     55  \n",
       "CN Tower,Bathurst Quay,Island airport,Harbourfr...              15  \n",
       "Cabbagetown,St. James Town                                      45  \n",
       "Central Bay Street                                              84  \n",
       "Chinatown,Grange Park,Kensington Market                         90  \n",
       "Christie                                                        17  \n",
       "Church and Wellesley                                            84  \n",
       "Commerce Court,Victoria Hotel                                  100  \n",
       "Design Exchange,Toronto Dominion Centre                        100  \n",
       "First Canadian Place,Underground city                          100  \n",
       "Harbord,University of Toronto                                   35  \n",
       "Harbourfront                                                    45  \n",
       "Harbourfront East,Toronto Islands,Union Station                100  \n",
       "Queen's Park                                                    39  \n",
       "Rosedale                                                         4  \n",
       "Ryerson,Garden District                                        100  \n",
       "St. James Town                                                 100  \n",
       "Stn A PO Boxes 25 The Esplanade                                 95  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Venues were returned for each neighborhood\n",
    "dtt_venues.groupby('Neighborhood').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 209 uniques categories.\n"
     ]
    }
   ],
   "source": [
    "# unique categories can be curated from all the returned venues\n",
    "print('There are {} uniques categories.'.format(len(dtt_venues['Venue Category'].unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 6: analyze each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "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>Yoga Studio</th>\n",
       "      <th>Afghan Restaurant</th>\n",
       "      <th>Airport</th>\n",
       "      <th>Airport Food Court</th>\n",
       "      <th>Airport Gate</th>\n",
       "      <th>Airport Lounge</th>\n",
       "      <th>Airport Service</th>\n",
       "      <th>Airport Terminal</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Antique Shop</th>\n",
       "      <th>...</th>\n",
       "      <th>Theme Restaurant</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Trail</th>\n",
       "      <th>Train Station</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Game Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wine Shop</th>\n",
       "      <th>Women's Store</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 209 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Yoga Studio  Afghan Restaurant  Airport  Airport Food Court  Airport Gate  \\\n",
       "0            0                  0        0                   0             0   \n",
       "1            0                  0        0                   0             0   \n",
       "2            0                  0        0                   0             0   \n",
       "3            0                  0        0                   0             0   \n",
       "4            0                  0        0                   0             0   \n",
       "\n",
       "   Airport Lounge  Airport Service  Airport Terminal  American Restaurant  \\\n",
       "0               0                0                 0                    0   \n",
       "1               0                0                 0                    0   \n",
       "2               0                0                 0                    0   \n",
       "3               0                0                 0                    0   \n",
       "4               0                0                 0                    0   \n",
       "\n",
       "   Antique Shop  ...  Theme Restaurant  Toy / Game Store  Trail  \\\n",
       "0             0  ...                 0                 0      0   \n",
       "1             0  ...                 0                 0      0   \n",
       "2             0  ...                 0                 0      0   \n",
       "3             0  ...                 0                 0      0   \n",
       "4             0  ...                 0                 0      0   \n",
       "\n",
       "   Train Station  Vegetarian / Vegan Restaurant  Video Game Store  \\\n",
       "0              0                              0                 0   \n",
       "1              0                              0                 0   \n",
       "2              0                              0                 0   \n",
       "3              0                              0                 0   \n",
       "4              0                              0                 0   \n",
       "\n",
       "   Vietnamese Restaurant  Wine Bar  Wine Shop  Women's Store  \n",
       "0                      0         0          0              0  \n",
       "1                      0         0          0              0  \n",
       "2                      0         0          0              0  \n",
       "3                      0         0          0              0  \n",
       "4                      0         0          0              0  \n",
       "\n",
       "[5 rows x 209 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "dtt_onehot = pd.get_dummies(dtt_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "dtt_onehot['Neighborhood'] = dtt_venues['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [dtt_onehot.columns[-1]] + list(dtt_onehot.columns[:-1])\n",
    "dtt_onehot = dtt_onehot[fixed_columns]\n",
    "\n",
    "dtt_onehot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1308, 209)"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtt_onehot.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.1 -- group rows by neighborhood and by taking the mean of the frequency of occurrence of each category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "dtt_grouped = dtt_onehot.groupby('Neighborhood').mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(19, 209)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtt_grouped.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2 -- print each neighborhood along with the top 5 most common venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----Adelaide,King,Richmond----\n",
      "             venue  freq\n",
      "0      Coffee Shop  0.08\n",
      "1              Bar  0.04\n",
      "2       Steakhouse  0.04\n",
      "3             Café  0.04\n",
      "4  Thai Restaurant  0.03\n",
      "----Berczy Park----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.07\n",
      "1        Cocktail Bar  0.05\n",
      "2          Steakhouse  0.04\n",
      "3                Café  0.04\n",
      "4  Seafood Restaurant  0.04\n",
      "----CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara----\n",
      "              venue  freq\n",
      "0    Airport Lounge  0.13\n",
      "1   Airport Service  0.13\n",
      "2  Airport Terminal  0.13\n",
      "3   Harbor / Marina  0.07\n",
      "4               Bar  0.07\n",
      "----Cabbagetown,St. James Town----\n",
      "         venue  freq\n",
      "0  Coffee Shop  0.07\n",
      "1          Pub  0.04\n",
      "2       Bakery  0.04\n",
      "3         Park  0.04\n",
      "4         Café  0.04\n",
      "----Central Bay Street----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.15\n",
      "1                Café  0.06\n",
      "2  Italian Restaurant  0.05\n",
      "3      Ice Cream Shop  0.04\n",
      "4        Burger Joint  0.04\n",
      "----Chinatown,Grange Park,Kensington Market----\n",
      "                           venue  freq\n",
      "0                           Café  0.07\n",
      "1          Vietnamese Restaurant  0.06\n",
      "2  Vegetarian / Vegan Restaurant  0.06\n",
      "3            Dumpling Restaurant  0.04\n",
      "4             Chinese Restaurant  0.04\n",
      "----Christie----\n",
      "                venue  freq\n",
      "0       Grocery Store  0.18\n",
      "1                Café  0.18\n",
      "2                Park  0.12\n",
      "3         Candy Store  0.06\n",
      "4  Italian Restaurant  0.06\n",
      "----Church and Wellesley----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.10\n",
      "1     Sushi Restaurant  0.05\n",
      "2  Japanese Restaurant  0.05\n",
      "3           Restaurant  0.04\n",
      "4              Gay Bar  0.04\n",
      "----Commerce Court,Victoria Hotel----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.11\n",
      "1                Café  0.07\n",
      "2               Hotel  0.06\n",
      "3          Restaurant  0.05\n",
      "4  Italian Restaurant  0.03\n",
      "----Design Exchange,Toronto Dominion Centre----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.14\n",
      "1               Hotel  0.08\n",
      "2                Café  0.07\n",
      "3  Seafood Restaurant  0.03\n",
      "4          Restaurant  0.03\n",
      "----First Canadian Place,Underground city----\n",
      "         venue  freq\n",
      "0  Coffee Shop  0.12\n",
      "1         Café  0.07\n",
      "2   Restaurant  0.04\n",
      "3        Hotel  0.04\n",
      "4          Gym  0.04\n",
      "----Harbord,University of Toronto----\n",
      "            venue  freq\n",
      "0            Café  0.14\n",
      "1          Bakery  0.06\n",
      "2  Sandwich Place  0.06\n",
      "3       Bookstore  0.06\n",
      "4      Restaurant  0.06\n",
      "----Harbourfront----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.16\n",
      "1              Bakery  0.07\n",
      "2                Park  0.07\n",
      "3                 Pub  0.07\n",
      "4  Mexican Restaurant  0.04\n",
      "----Harbourfront East,Toronto Islands,Union Station----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.12\n",
      "1            Aquarium  0.05\n",
      "2                Café  0.04\n",
      "3               Hotel  0.04\n",
      "4  Italian Restaurant  0.04\n",
      "----Queen's Park----\n",
      "          venue  freq\n",
      "0   Coffee Shop  0.31\n",
      "1          Park  0.05\n",
      "2           Gym  0.05\n",
      "3      Creperie  0.03\n",
      "4  Burger Joint  0.03\n",
      "----Rosedale----\n",
      "               venue  freq\n",
      "0               Park  0.50\n",
      "1         Playground  0.25\n",
      "2              Trail  0.25\n",
      "3      Movie Theater  0.00\n",
      "4  Martial Arts Dojo  0.00\n",
      "----Ryerson,Garden District----\n",
      "                       venue  freq\n",
      "0                Coffee Shop  0.09\n",
      "1             Clothing Store  0.05\n",
      "2                       Café  0.04\n",
      "3             Cosmetics Shop  0.04\n",
      "4  Middle Eastern Restaurant  0.03\n",
      "----St. James Town----\n",
      "            venue  freq\n",
      "0            Café  0.06\n",
      "1     Coffee Shop  0.06\n",
      "2      Restaurant  0.05\n",
      "3  Cosmetics Shop  0.03\n",
      "4           Hotel  0.03\n",
      "----Stn A PO Boxes 25 The Esplanade----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.12\n",
      "1                 Café  0.04\n",
      "2           Restaurant  0.03\n",
      "3  Japanese Restaurant  0.03\n",
      "4   Seafood Restaurant  0.03\n"
     ]
    }
   ],
   "source": [
    "num_top_venues = 5\n",
    "\n",
    "for hood in dtt_grouped['Neighborhood']:\n",
    "    print(\"----\"+hood+\"----\")\n",
    "    temp = dtt_grouped[dtt_grouped['Neighborhood'] == hood].T.reset_index()\n",
    "    temp.columns = ['venue','freq']\n",
    "    temp = temp.iloc[1:]\n",
    "    temp['freq'] = temp['freq'].astype(float)\n",
    "    temp = temp.round({'freq': 2})\n",
    "    print(temp.sort_values('freq', ascending=False).reset_index(drop=True).head(num_top_venues))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.3 -- write a function to sort the venues in descending order, create a dataframe and display the top 10 venues for each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "def return_most_common_venues(row, num_top_venues):\n",
    "    row_categories = row.iloc[1:]\n",
    "    row_categories_sorted = row_categories.sort_values(ascending=False)\n",
    "    \n",
    "    return row_categories_sorted.index.values[0:num_top_venues]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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>Neighborhood</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adelaide,King,Richmond</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Clothing Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Berczy Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Café</td>\n",
       "      <td>Fountain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CN Tower,Bathurst Quay,Island airport,Harbourf...</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Airport</td>\n",
       "      <td>Airport Food Court</td>\n",
       "      <td>Airport Gate</td>\n",
       "      <td>Sculpture Garden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cabbagetown,St. James Town</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Park</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Playground</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                             Adelaide,King,Richmond           Coffee Shop   \n",
       "1                                        Berczy Park           Coffee Shop   \n",
       "2  CN Tower,Bathurst Quay,Island airport,Harbourf...        Airport Lounge   \n",
       "3                         Cabbagetown,St. James Town           Coffee Shop   \n",
       "4                                 Central Bay Street           Coffee Shop   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                   Bar            Steakhouse                  Café   \n",
       "1          Cocktail Bar                Bakery           Cheese Shop   \n",
       "2       Airport Service      Airport Terminal              Boutique   \n",
       "3    Italian Restaurant            Restaurant                Bakery   \n",
       "4                  Café    Italian Restaurant          Burger Joint   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0                 Hotel      Asian Restaurant       Thai Restaurant   \n",
       "1              Beer Bar    Seafood Restaurant        Farmers Market   \n",
       "2   Rental Car Location       Harbor / Marina               Airport   \n",
       "3                   Pub                  Park                  Café   \n",
       "4   Japanese Restaurant        Sandwich Place        Ice Cream Shop   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0          Burger Joint      Sushi Restaurant         Clothing Store  \n",
       "1            Steakhouse                  Café               Fountain  \n",
       "2    Airport Food Court          Airport Gate       Sculpture Garden  \n",
       "3           Pizza Place             Gastropub             Playground  \n",
       "4       Bubble Tea Shop           Salad Place     Chinese Restaurant  "
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_top_venues = 10\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for ind in np.arange(num_top_venues):\n",
    "    try:\n",
    "        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n",
    "    except:\n",
    "        columns.append('{}th Most Common Venue'.format(ind+1))\n",
    "\n",
    "# create a new dataframe\n",
    "dtt_venues_sorted = pd.DataFrame(columns=columns)\n",
    "dtt_venues_sorted['Neighborhood'] = dtt_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(dtt_grouped.shape[0]):\n",
    "    dtt_venues_sorted.iloc[ind, 1:] = return_most_common_venues(dtt_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "dtt_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### step 7: cluster neighborhoods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 7.1 -- run k-means to cluster the neighborhood into 6 clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 2, 1, 1, 1, 0, 1, 1, 1], dtype=int32)"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 6\n",
    "\n",
    "dtt_grouped_clustering = dtt_grouped.drop('Neighborhood', 1)\n",
    "\n",
    "# run k-means clustering\n",
    "kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(dtt_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "kmeans.labels_[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 7.2 -- create a dataframe that includes the cluster as well as the top 10 venues for each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "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>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront</td>\n",
       "      <td>M5A</td>\n",
       "      <td>43.654260</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Park</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Café</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Electronics Store</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>M7A</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Park</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Beer Bar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Ryerson,Garden District</td>\n",
       "      <td>M5B</td>\n",
       "      <td>43.657162</td>\n",
       "      <td>-79.378937</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Ramen Restaurant</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M5C</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "      <td>M5C</td>\n",
       "      <td>43.651494</td>\n",
       "      <td>-79.375418</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>M4E</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postcode           Borough             Neighborhood Postal Code   Latitude  \\\n",
       "0      M5A  Downtown Toronto             Harbourfront         M5A  43.654260   \n",
       "1      M7A  Downtown Toronto             Queen's Park         M7A  43.662301   \n",
       "2      M5B  Downtown Toronto  Ryerson,Garden District         M5B  43.657162   \n",
       "3      M5C  Downtown Toronto           St. James Town         M5C  43.651494   \n",
       "4      M4E      East Toronto              The Beaches         M4E  43.676357   \n",
       "\n",
       "   Longitude  Cluster Labels 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "0 -79.360636             1.0           Coffee Shop                   Pub   \n",
       "1 -79.389494             5.0           Coffee Shop                   Gym   \n",
       "2 -79.378937             1.0           Coffee Shop        Clothing Store   \n",
       "3 -79.375418             1.0           Coffee Shop                  Café   \n",
       "4 -79.293031             NaN                   NaN                   NaN   \n",
       "\n",
       "  3rd Most Common Venue 4th Most Common Venue      5th Most Common Venue  \\\n",
       "0                Bakery                  Park             Breakfast Spot   \n",
       "1                  Park           Yoga Studio           Sushi Restaurant   \n",
       "2        Cosmetics Shop                  Café  Middle Eastern Restaurant   \n",
       "3            Restaurant        Cosmetics Shop               Cocktail Bar   \n",
       "4                   NaN                   NaN                        NaN   \n",
       "\n",
       "  6th Most Common Venue 7th Most Common Venue 8th Most Common Venue  \\\n",
       "0                  Café    Mexican Restaurant     Electronics Store   \n",
       "1        Sandwich Place                 Diner          Burger Joint   \n",
       "2    Italian Restaurant          Burger Joint                Bakery   \n",
       "3        Clothing Store              Beer Bar                 Hotel   \n",
       "4                   NaN                   NaN                   NaN   \n",
       "\n",
       "  9th Most Common Venue 10th Most Common Venue  \n",
       "0               Brewery  Performing Arts Venue  \n",
       "1   Japanese Restaurant               Beer Bar  \n",
       "2      Ramen Restaurant    Japanese Restaurant  \n",
       "3                 Diner                 Bakery  \n",
       "4                   NaN                    NaN  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# add clustering labels\n",
    "#dtt_venues_sorted.insert(0, 'Cluster Labels', kmeans.labels_)\n",
    "\n",
    "dtt_merged = df2\n",
    "\n",
    "# merge toronto_grouped with toronto_data to add latitude/longitude for each neighborhood\n",
    "dtt_merged = dtt_merged.join(dtt_venues_sorted.set_index('Neighborhood'), on='Neighborhood')\n",
    "\n",
    "dtt_merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 7.3 -- visualize the resulting clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
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            var popup_3ad72e3221754ee18b29f3fad9f51038 = L.popup({maxWidth: '300'});

            
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            circle_marker_6bb6f802fe5247cca5bef68484bb8ebb.bindPopup(popup_3ad72e3221754ee18b29f3fad9f51038);

            
        
    
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            var popup_493ff54469464a50b4b79283463ea4ff = L.popup({maxWidth: '300'});

            
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            circle_marker_35c2322a11df4a4a832bac5b520be1a4.bindPopup(popup_493ff54469464a50b4b79283463ea4ff);

            
        
    
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            circle_marker_d92e22081d94447290855adb4391a278.bindPopup(popup_d35281cca4db4ae29fb9c5724febfaf7);

            
        
    
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                ).addTo(map_7a07f6871a5b4cb4a84485e341c4d039);
            
    
            var popup_89b370c68fa0464590e6706b94708fc2 = L.popup({maxWidth: '300'});

            
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            circle_marker_bf151c35fdac41e58f2feefe14ff1a60.bindPopup(popup_89b370c68fa0464590e6706b94708fc2);

            
        
    
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            circle_marker_bc1799a526be4fc9bd7af299e53916c6.bindPopup(popup_43c287f5a03546debd4c5589268e3391);

            
        
    
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  "lineJoin": "round",
  "opacity": 1.0,
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                ).addTo(map_7a07f6871a5b4cb4a84485e341c4d039);
            
    
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                var html_bf150a7285e244c88194d2378046cbb4 = $('<div id="html_bf150a7285e244c88194d2378046cbb4" style="width: 100.0%; height: 100.0%;">North Toronto West Cluster nan</div>')[0];
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            circle_marker_cce3a0330a9c4de99920fbb293799ed4.bindPopup(popup_795474cca08c4ba4af407d63ee587fd0);

            
        
    
            var circle_marker_4ed0f5db2977440b95716a46f81a5ae6 = L.circleMarker(
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  "fillOpacity": 0.7,
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  "lineJoin": "round",
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            var popup_d4b7ae11fc0b4880b372e7b3178aa0f9 = L.popup({maxWidth: '300'});

            
                var html_f709c0eed9f64759b653a330305e95b0 = $('<div id="html_f709c0eed9f64759b653a330305e95b0" style="width: 100.0%; height: 100.0%;">Business Reply Mail Processing Centre 969 Eastern Cluster nan</div>')[0];
                popup_d4b7ae11fc0b4880b372e7b3178aa0f9.setContent(html_f709c0eed9f64759b653a330305e95b0);
            

            circle_marker_39a08aebc51e44c2b7f2e70a2741a09f.bindPopup(popup_d4b7ae11fc0b4880b372e7b3178aa0f9);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f493d8150b8>"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map\n",
    "map_clusters = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
    "\n",
    "# set color scheme for the clusters\n",
    "x = np.arange(kclusters)\n",
    "ys = [i + x + (i*x)**2 for i in range(kclusters)]\n",
    "colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\n",
    "rainbow = [colors.rgb2hex(i) for i in colors_array]\n",
    "\n",
    "# add markers to the map\n",
    "markers_colors = []\n",
    "for lat, lon, poi, cluster in zip(dtt_merged['Latitude'], dtt_merged['Longitude'], dtt_merged['Neighborhood'], dtt_merged['Cluster Labels']):\n",
    "    label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lon],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color=rainbow,\n",
    "        fill=True,\n",
    "        fill_color=rainbow,\n",
    "        fill_opacity=0.7).add_to(map_clusters)\n",
    "       \n",
    "map_clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 8: examine the clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "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>Borough</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.422564</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Park</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Nightclub</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Candy Store</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Athletics &amp; Sports</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Borough  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "7  Downtown Toronto -79.422564             0.0                  Café   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "7         Grocery Store                  Park            Restaurant   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "7             Nightclub     Convenience Store           Candy Store   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "7                 Diner    Italian Restaurant     Athletics & Sports  "
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# examine cluster 1\n",
    "dtt_merged.loc[dtt_merged['Cluster Labels'] == 0, dtt_merged.columns[[1] + list(range(5, dtt_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "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>Borough</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Park</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Café</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Electronics Store</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.378937</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Ramen Restaurant</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.375418</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.373306</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Café</td>\n",
       "      <td>Fountain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.387383</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.384568</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Clothing Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.381752</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Aquarium</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Scenic Lookout</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.381576</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Café</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gastropub</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.379817</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.400049</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.374846</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Gym</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.367675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Park</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Playground</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.382280</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.383160</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gay Bar</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Burger Joint</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "0   Downtown Toronto -79.360636             1.0           Coffee Shop   \n",
       "2   Downtown Toronto -79.378937             1.0           Coffee Shop   \n",
       "3   Downtown Toronto -79.375418             1.0           Coffee Shop   \n",
       "5   Downtown Toronto -79.373306             1.0           Coffee Shop   \n",
       "6   Downtown Toronto -79.387383             1.0           Coffee Shop   \n",
       "8   Downtown Toronto -79.384568             1.0           Coffee Shop   \n",
       "10  Downtown Toronto -79.381752             1.0           Coffee Shop   \n",
       "13  Downtown Toronto -79.381576             1.0           Coffee Shop   \n",
       "16  Downtown Toronto -79.379817             1.0           Coffee Shop   \n",
       "30  Downtown Toronto -79.400049             1.0                  Café   \n",
       "34  Downtown Toronto -79.374846             1.0           Coffee Shop   \n",
       "35  Downtown Toronto -79.367675             1.0           Coffee Shop   \n",
       "36  Downtown Toronto -79.382280             1.0           Coffee Shop   \n",
       "37  Downtown Toronto -79.383160             1.0           Coffee Shop   \n",
       "\n",
       "    2nd Most Common Venue          3rd Most Common Venue  \\\n",
       "0                     Pub                         Bakery   \n",
       "2          Clothing Store                 Cosmetics Shop   \n",
       "3                    Café                     Restaurant   \n",
       "5            Cocktail Bar                         Bakery   \n",
       "6                    Café             Italian Restaurant   \n",
       "8                     Bar                     Steakhouse   \n",
       "10               Aquarium             Italian Restaurant   \n",
       "13                  Hotel                           Café   \n",
       "16                   Café                          Hotel   \n",
       "30  Vietnamese Restaurant  Vegetarian / Vegan Restaurant   \n",
       "34                   Café                       Beer Bar   \n",
       "35     Italian Restaurant                     Restaurant   \n",
       "36                   Café                     Restaurant   \n",
       "37    Japanese Restaurant               Sushi Restaurant   \n",
       "\n",
       "   4th Most Common Venue      5th Most Common Venue 6th Most Common Venue  \\\n",
       "0                   Park             Breakfast Spot                  Café   \n",
       "2                   Café  Middle Eastern Restaurant    Italian Restaurant   \n",
       "3         Cosmetics Shop               Cocktail Bar        Clothing Store   \n",
       "5            Cheese Shop                   Beer Bar    Seafood Restaurant   \n",
       "6           Burger Joint        Japanese Restaurant        Sandwich Place   \n",
       "8                   Café                      Hotel      Asian Restaurant   \n",
       "10                  Café                      Hotel        Scenic Lookout   \n",
       "13                   Bar         Seafood Restaurant            Steakhouse   \n",
       "16            Restaurant        American Restaurant    Seafood Restaurant   \n",
       "30           Coffee Shop         Chinese Restaurant   Dumpling Restaurant   \n",
       "34    Seafood Restaurant               Cocktail Bar   Japanese Restaurant   \n",
       "35                Bakery                        Pub                  Park   \n",
       "36                   Gym                      Hotel            Steakhouse   \n",
       "37            Restaurant                    Gay Bar           Yoga Studio   \n",
       "\n",
       "   7th Most Common Venue 8th Most Common Venue 9th Most Common Venue  \\\n",
       "0     Mexican Restaurant     Electronics Store               Brewery   \n",
       "2           Burger Joint                Bakery      Ramen Restaurant   \n",
       "3               Beer Bar                 Hotel                 Diner   \n",
       "5         Farmers Market            Steakhouse                  Café   \n",
       "6         Ice Cream Shop       Bubble Tea Shop           Salad Place   \n",
       "8        Thai Restaurant          Burger Joint      Sushi Restaurant   \n",
       "10               Brewery            Restaurant   Fried Chicken Joint   \n",
       "13   American Restaurant    Italian Restaurant            Restaurant   \n",
       "16            Steakhouse             Gastropub    Italian Restaurant   \n",
       "30                Bakery                   Bar    Mexican Restaurant   \n",
       "34            Restaurant                 Hotel        Farmers Market   \n",
       "35                  Café           Pizza Place             Gastropub   \n",
       "36             Gastropub                   Bar      Asian Restaurant   \n",
       "37                 Hotel           Pizza Place       Bubble Tea Shop   \n",
       "\n",
       "   10th Most Common Venue  \n",
       "0   Performing Arts Venue  \n",
       "2     Japanese Restaurant  \n",
       "3                  Bakery  \n",
       "5                Fountain  \n",
       "6      Chinese Restaurant  \n",
       "8          Clothing Store  \n",
       "10                 Bakery  \n",
       "13              Gastropub  \n",
       "16                    Gym  \n",
       "30             Donut Shop  \n",
       "34                    Gym  \n",
       "35             Playground  \n",
       "36     Seafood Restaurant  \n",
       "37           Burger Joint  "
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# examine cluster 2\n",
    "dtt_merged.loc[dtt_merged['Cluster Labels'] == 1, dtt_merged.columns[[1] + list(range(5, dtt_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "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>Borough</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.39442</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Airport</td>\n",
       "      <td>Airport Food Court</td>\n",
       "      <td>Airport Gate</td>\n",
       "      <td>Sculpture Garden</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "32  Downtown Toronto  -79.39442             2.0        Airport Lounge   \n",
       "\n",
       "   2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "32       Airport Service      Airport Terminal              Boutique   \n",
       "\n",
       "   5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "32   Rental Car Location       Harbor / Marina               Airport   \n",
       "\n",
       "   8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "32    Airport Food Court          Airport Gate       Sculpture Garden  "
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# examine cluster 3\n",
    "dtt_merged.loc[dtt_merged['Cluster Labels'] == 2, dtt_merged.columns[[1] + list(range(5, dtt_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "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>Borough</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.377529</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Park</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "33  Downtown Toronto -79.377529             3.0                  Park   \n",
       "\n",
       "   2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "33            Playground                 Trail          Dance Studio   \n",
       "\n",
       "   5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "33   Dumpling Restaurant            Donut Shop      Doner Restaurant   \n",
       "\n",
       "   8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "33               Dog Run        Discount Store                  Diner  "
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# examine cluster 4\n",
    "dtt_merged.loc[dtt_merged['Cluster Labels'] == 3, dtt_merged.columns[[1] + list(range(5, dtt_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "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>Borough</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>-79.400049</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Dessert Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "27  Downtown Toronto -79.400049             4.0                  Café   \n",
       "\n",
       "   2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "27    Italian Restaurant                   Bar                Bakery   \n",
       "\n",
       "   5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "27            Restaurant             Bookstore        Sandwich Place   \n",
       "\n",
       "   8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "27   Japanese Restaurant                   Pub           Dessert Shop  "
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# examine cluster 5\n",
    "dtt_merged.loc[dtt_merged['Cluster Labels'] == 4, dtt_merged.columns[[1] + list(range(5, dtt_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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