Toronto_neighborhood.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Applied Data Science Capstone Week 3 Segmenting and Clustering Neighborhoods in Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting package metadata (current_repodata.json): done\n",
      "Solving environment: done\n",
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: /home/amos/anaconda3\n",
      "\n",
      "  added / updated specs:\n",
      "    - geopy\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    graphviz-2.40.1            |       h21bd128_1         6.5 MB  https://repo.anaconda.com/pkgs/main/linux-64\n",
      "    ------------------------------------------------------------\n",
      "                                           Total:         6.5 MB\n",
      "\n",
      "The following packages will be DOWNGRADED:\n",
      "\n",
      "  _ipyw_jlab_nb_ext~                                        --> \n",
      "  _libgcc_mutex                                             --> \n",
      "  anaconda                                                  --> \n",
      "  backports.os                                              --> \n",
      "  backports.shutil_~                                        --> \n",
      "  binutils_impl_lin~                                        --> \n",
      "  boto                                                      --> \n",
      "  chardet                                                   --> \n",
      "  colorama                                                  --> \n",
      "  contextlib2                                               --> \n",
      "  get_terminal_size                                         --> \n",
      "  gmp                                                       --> \n",
      "  graphviz                                2.40.1-h21bd128_2 --> 2.40.1-h21bd128_1\n",
      "  gstreamer                                                 --> \n",
      "  html5lib                                                  --> \n",
      "  idna                                                      --> \n",
      "  intel-openmp                                              --> \n",
      "  itsdangerous                                              --> \n",
      "  jbig                                                      --> \n",
      "  jeepney                                                   --> \n",
      "  jinja2                                                    --> \n",
      "  jupyterlab                                                --> \n",
      "  libedit                                                   --> \n",
      "  libgcc-ng                                                 --> \n",
      "  libpng                                                    --> \n",
      "  libxcb                                                    --> \n",
      "  lz4-c                                                     --> \n",
      "  lzo                                                       --> \n",
      "  make                                                      --> \n",
      "  mccabe                                                    --> \n",
      "  mock                                                      --> \n",
      "  multipledispatch                                          --> \n",
      "  nbformat                                                  --> \n",
      "  pandocfilters                                             --> \n",
      "  pep8                                                      --> \n",
      "  pkginfo                                                   --> \n",
      "  py                                                        --> \n",
      "  pycosat                                                   --> \n",
      "  pycparser                                                 --> \n",
      "  pycrypto                                                  --> \n",
      "  pytest-openfiles                                          --> \n",
      "  python-libarchive~                                        --> \n",
      "  send2trash                                                --> \n",
      "  snappy                                                    --> \n",
      "  sortedcollections                                         --> \n",
      "  tk                                                        --> \n",
      "  tktable                                                   --> \n",
      "  unixodbc                                                  --> \n",
      "  wrapt                                                     --> \n",
      "  xz                                                        --> \n",
      "  zstd                                                      --> \n",
      "\n",
      "\n",
      "\n",
      "Downloading and Extracting Packages\n",
      "graphviz-2.40.1      | 6.5 MB    | ##################################### | 100% \n",
      "Preparing transaction: done\n",
      "Verifying transaction: done\n",
      "Executing transaction: done\n",
      "Libraries imported.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np # library to handle data in a vectorized manner\n",
    "\n",
    "import pandas as pd # library for data analsysis\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)\n",
    "\n",
    "import json # library to handle JSON files\n",
    "\n",
    "!conda install -c conda-forge geopy --yes # uncomment this line if you haven't completed the Foursquare API lab\n",
    "from geopy.geocoders import Nominatim # convert an address into latitude and longitude values\n",
    "\n",
    "import requests # library to handle requests\n",
    "from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe\n",
    "\n",
    "import urllib # library to read webpage using url\n",
    "\n",
    "# Matplotlib and associated plotting modules\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors\n",
    "\n",
    "# import k-means from clustering stage\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "#!conda install -c conda-forge folium=0.5.0 --yes # uncomment this line if you haven't completed the Foursquare API lab\n",
    "import folium # map rendering library\n",
    "\n",
    "print('Libraries imported.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Install additional packages for web Scraping"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Now usually the package manager for python-3.x is pip3. So you probably should install it with !pip3 and restart the notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: lxml in /home/jupyterlab/conda/lib/python3.8/site-packages (4.5.2)\n",
      "Requirement already satisfied: html5lib in /home/jupyterlab/conda/lib/python3.8/site-packages (1.1)\n",
      "Requirement already satisfied: beautifulsoup4 in /home/jupyterlab/conda/lib/python3.8/site-packages (4.9.1)\n",
      "Requirement already satisfied: webencodings in /home/jupyterlab/conda/lib/python3.8/site-packages (from html5lib) (0.5.1)\n",
      "Requirement already satisfied: six>=1.9 in /home/jupyterlab/conda/lib/python3.8/site-packages (from html5lib) (1.15.0)\n",
      "Requirement already satisfied: soupsieve>1.2 in /home/jupyterlab/conda/lib/python3.8/site-packages (from beautifulsoup4) (2.0.1)\n"
     ]
    }
   ],
   "source": [
    "!pip3 install lxml html5lib beautifulsoup4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Or, if the error persists use !conda install"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting package metadata (current_repodata.json): done\n",
      "Solving environment: - "
     ]
    }
   ],
   "source": [
    "!conda install -c conda-forge lxml --yes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get data from web: Wikipedia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data downloaded!\n"
     ]
    }
   ],
   "source": [
    "url = \"https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M\"\n",
    "toronto_data = pd.read_html(url)\n",
    "print('Data downloaded!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Print the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[    Postal Code           Borough  \\\n",
       " 0           M1A      Not assigned   \n",
       " 1           M2A      Not assigned   \n",
       " 2           M3A        North York   \n",
       " 3           M4A        North York   \n",
       " 4           M5A  Downtown Toronto   \n",
       " 5           M6A        North York   \n",
       " 6           M7A  Downtown Toronto   \n",
       " 7           M8A      Not assigned   \n",
       " 8           M9A         Etobicoke   \n",
       " 9           M1B       Scarborough   \n",
       " 10          M2B      Not assigned   \n",
       " 11          M3B        North York   \n",
       " 12          M4B         East York   \n",
       " 13          M5B  Downtown Toronto   \n",
       " 14          M6B        North York   \n",
       " 15          M7B      Not assigned   \n",
       " 16          M8B      Not assigned   \n",
       " 17          M9B         Etobicoke   \n",
       " 18          M1C       Scarborough   \n",
       " 19          M2C      Not assigned   \n",
       " 20          M3C        North York   \n",
       " 21          M4C         East York   \n",
       " 22          M5C  Downtown Toronto   \n",
       " 23          M6C              York   \n",
       " 24          M7C      Not assigned   \n",
       " 25          M8C      Not assigned   \n",
       " 26          M9C         Etobicoke   \n",
       " 27          M1E       Scarborough   \n",
       " 28          M2E      Not assigned   \n",
       " 29          M3E      Not assigned   \n",
       " 30          M4E      East Toronto   \n",
       " 31          M5E  Downtown Toronto   \n",
       " 32          M6E              York   \n",
       " 33          M7E      Not assigned   \n",
       " 34          M8E      Not assigned   \n",
       " 35          M9E      Not assigned   \n",
       " 36          M1G       Scarborough   \n",
       " 37          M2G      Not assigned   \n",
       " 38          M3G      Not assigned   \n",
       " 39          M4G         East York   \n",
       " 40          M5G  Downtown Toronto   \n",
       " 41          M6G  Downtown Toronto   \n",
       " 42          M7G      Not assigned   \n",
       " 43          M8G      Not assigned   \n",
       " 44          M9G      Not assigned   \n",
       " 45          M1H       Scarborough   \n",
       " 46          M2H        North York   \n",
       " 47          M3H        North York   \n",
       " 48          M4H         East York   \n",
       " 49          M5H  Downtown Toronto   \n",
       " 50          M6H      West Toronto   \n",
       " 51          M7H      Not assigned   \n",
       " 52          M8H      Not assigned   \n",
       " 53          M9H      Not assigned   \n",
       " 54          M1J       Scarborough   \n",
       " 55          M2J        North York   \n",
       " 56          M3J        North York   \n",
       " 57          M4J         East York   \n",
       " 58          M5J  Downtown Toronto   \n",
       " 59          M6J      West Toronto   \n",
       " 60          M7J      Not assigned   \n",
       " 61          M8J      Not assigned   \n",
       " 62          M9J      Not assigned   \n",
       " 63          M1K       Scarborough   \n",
       " 64          M2K        North York   \n",
       " 65          M3K        North York   \n",
       " 66          M4K      East Toronto   \n",
       " 67          M5K  Downtown Toronto   \n",
       " 68          M6K      West Toronto   \n",
       " 69          M7K      Not assigned   \n",
       " 70          M8K      Not assigned   \n",
       " 71          M9K      Not assigned   \n",
       " 72          M1L       Scarborough   \n",
       " 73          M2L        North York   \n",
       " 74          M3L        North York   \n",
       " 75          M4L      East Toronto   \n",
       " 76          M5L  Downtown Toronto   \n",
       " 77          M6L        North York   \n",
       " 78          M7L      Not assigned   \n",
       " 79          M8L      Not assigned   \n",
       " 80          M9L        North York   \n",
       " 81          M1M       Scarborough   \n",
       " 82          M2M        North York   \n",
       " 83          M3M        North York   \n",
       " 84          M4M      East Toronto   \n",
       " 85          M5M        North York   \n",
       " 86          M6M              York   \n",
       " 87          M7M      Not assigned   \n",
       " 88          M8M      Not assigned   \n",
       " 89          M9M        North York   \n",
       " 90          M1N       Scarborough   \n",
       " 91          M2N        North York   \n",
       " 92          M3N        North York   \n",
       " 93          M4N   Central Toronto   \n",
       " 94          M5N   Central Toronto   \n",
       " 95          M6N              York   \n",
       " 96          M7N      Not assigned   \n",
       " 97          M8N      Not assigned   \n",
       " 98          M9N              York   \n",
       " 99          M1P       Scarborough   \n",
       " 100         M2P        North York   \n",
       " 101         M3P      Not assigned   \n",
       " 102         M4P   Central Toronto   \n",
       " 103         M5P   Central Toronto   \n",
       " 104         M6P      West Toronto   \n",
       " 105         M7P      Not assigned   \n",
       " 106         M8P      Not assigned   \n",
       " 107         M9P         Etobicoke   \n",
       " 108         M1R       Scarborough   \n",
       " 109         M2R        North York   \n",
       " 110         M3R      Not assigned   \n",
       " 111         M4R   Central Toronto   \n",
       " 112         M5R   Central Toronto   \n",
       " 113         M6R      West Toronto   \n",
       " 114         M7R       Mississauga   \n",
       " 115         M8R      Not assigned   \n",
       " 116         M9R         Etobicoke   \n",
       " 117         M1S       Scarborough   \n",
       " 118         M2S      Not assigned   \n",
       " 119         M3S      Not assigned   \n",
       " 120         M4S   Central Toronto   \n",
       " 121         M5S  Downtown Toronto   \n",
       " 122         M6S      West Toronto   \n",
       " 123         M7S      Not assigned   \n",
       " 124         M8S      Not assigned   \n",
       " 125         M9S      Not assigned   \n",
       " 126         M1T       Scarborough   \n",
       " 127         M2T      Not assigned   \n",
       " 128         M3T      Not assigned   \n",
       " 129         M4T   Central Toronto   \n",
       " 130         M5T  Downtown Toronto   \n",
       " 131         M6T      Not assigned   \n",
       " 132         M7T      Not assigned   \n",
       " 133         M8T      Not assigned   \n",
       " 134         M9T      Not assigned   \n",
       " 135         M1V       Scarborough   \n",
       " 136         M2V      Not assigned   \n",
       " 137         M3V      Not assigned   \n",
       " 138         M4V   Central Toronto   \n",
       " 139         M5V  Downtown Toronto   \n",
       " 140         M6V      Not assigned   \n",
       " 141         M7V      Not assigned   \n",
       " 142         M8V         Etobicoke   \n",
       " 143         M9V         Etobicoke   \n",
       " 144         M1W       Scarborough   \n",
       " 145         M2W      Not assigned   \n",
       " 146         M3W      Not assigned   \n",
       " 147         M4W  Downtown Toronto   \n",
       " 148         M5W  Downtown Toronto   \n",
       " 149         M6W      Not assigned   \n",
       " 150         M7W      Not assigned   \n",
       " 151         M8W         Etobicoke   \n",
       " 152         M9W         Etobicoke   \n",
       " 153         M1X       Scarborough   \n",
       " 154         M2X      Not assigned   \n",
       " 155         M3X      Not assigned   \n",
       " 156         M4X  Downtown Toronto   \n",
       " 157         M5X  Downtown Toronto   \n",
       " 158         M6X      Not assigned   \n",
       " 159         M7X      Not assigned   \n",
       " 160         M8X         Etobicoke   \n",
       " 161         M9X      Not assigned   \n",
       " 162         M1Y      Not assigned   \n",
       " 163         M2Y      Not assigned   \n",
       " 164         M3Y      Not assigned   \n",
       " 165         M4Y  Downtown Toronto   \n",
       " 166         M5Y      Not assigned   \n",
       " 167         M6Y      Not assigned   \n",
       " 168         M7Y      East Toronto   \n",
       " 169         M8Y         Etobicoke   \n",
       " 170         M9Y      Not assigned   \n",
       " 171         M1Z      Not assigned   \n",
       " 172         M2Z      Not assigned   \n",
       " 173         M3Z      Not assigned   \n",
       " 174         M4Z      Not assigned   \n",
       " 175         M5Z      Not assigned   \n",
       " 176         M6Z      Not assigned   \n",
       " 177         M7Z      Not assigned   \n",
       " 178         M8Z         Etobicoke   \n",
       " 179         M9Z      Not assigned   \n",
       " \n",
       "                                           Neighborhood  \n",
       " 0                                         Not assigned  \n",
       " 1                                         Not assigned  \n",
       " 2                                            Parkwoods  \n",
       " 3                                     Victoria Village  \n",
       " 4                            Regent Park, Harbourfront  \n",
       " 5                     Lawrence Manor, Lawrence Heights  \n",
       " 6          Queen's Park, Ontario Provincial Government  \n",
       " 7                                         Not assigned  \n",
       " 8              Islington Avenue, Humber Valley Village  \n",
       " 9                                       Malvern, Rouge  \n",
       " 10                                        Not assigned  \n",
       " 11                                           Don Mills  \n",
       " 12                     Parkview Hill, Woodbine Gardens  \n",
       " 13                            Garden District, Ryerson  \n",
       " 14                                           Glencairn  \n",
       " 15                                        Not assigned  \n",
       " 16                                        Not assigned  \n",
       " 17   West Deane Park, Princess Gardens, Martin Grov...  \n",
       " 18              Rouge Hill, Port Union, Highland Creek  \n",
       " 19                                        Not assigned  \n",
       " 20                                           Don Mills  \n",
       " 21                                    Woodbine Heights  \n",
       " 22                                      St. James Town  \n",
       " 23                                  Humewood-Cedarvale  \n",
       " 24                                        Not assigned  \n",
       " 25                                        Not assigned  \n",
       " 26   Eringate, Bloordale Gardens, Old Burnhamthorpe...  \n",
       " 27                   Guildwood, Morningside, West Hill  \n",
       " 28                                        Not assigned  \n",
       " 29                                        Not assigned  \n",
       " 30                                         The Beaches  \n",
       " 31                                         Berczy Park  \n",
       " 32                                 Caledonia-Fairbanks  \n",
       " 33                                        Not assigned  \n",
       " 34                                        Not assigned  \n",
       " 35                                        Not assigned  \n",
       " 36                                              Woburn  \n",
       " 37                                        Not assigned  \n",
       " 38                                        Not assigned  \n",
       " 39                                             Leaside  \n",
       " 40                                  Central Bay Street  \n",
       " 41                                            Christie  \n",
       " 42                                        Not assigned  \n",
       " 43                                        Not assigned  \n",
       " 44                                        Not assigned  \n",
       " 45                                           Cedarbrae  \n",
       " 46                                   Hillcrest Village  \n",
       " 47     Bathurst Manor, Wilson Heights, Downsview North  \n",
       " 48                                    Thorncliffe Park  \n",
       " 49                            Richmond, Adelaide, King  \n",
       " 50                        Dufferin, Dovercourt Village  \n",
       " 51                                        Not assigned  \n",
       " 52                                        Not assigned  \n",
       " 53                                        Not assigned  \n",
       " 54                                 Scarborough Village  \n",
       " 55                        Fairview, Henry Farm, Oriole  \n",
       " 56                     Northwood Park, York University  \n",
       " 57       East Toronto, Broadview North (Old East York)  \n",
       " 58   Harbourfront East, Union Station, Toronto Islands  \n",
       " 59                            Little Portugal, Trinity  \n",
       " 60                                        Not assigned  \n",
       " 61                                        Not assigned  \n",
       " 62                                        Not assigned  \n",
       " 63         Kennedy Park, Ionview, East Birchmount Park  \n",
       " 64                                     Bayview Village  \n",
       " 65                                           Downsview  \n",
       " 66                        The Danforth West, Riverdale  \n",
       " 67            Toronto Dominion Centre, Design Exchange  \n",
       " 68        Brockton, Parkdale Village, Exhibition Place  \n",
       " 69                                        Not assigned  \n",
       " 70                                        Not assigned  \n",
       " 71                                        Not assigned  \n",
       " 72                     Golden Mile, Clairlea, Oakridge  \n",
       " 73                            York Mills, Silver Hills  \n",
       " 74                                           Downsview  \n",
       " 75                      India Bazaar, The Beaches West  \n",
       " 76                      Commerce Court, Victoria Hotel  \n",
       " 77            North Park, Maple Leaf Park, Upwood Park  \n",
       " 78                                        Not assigned  \n",
       " 79                                        Not assigned  \n",
       " 80                                       Humber Summit  \n",
       " 81     Cliffside, Cliffcrest, Scarborough Village West  \n",
       " 82                             Willowdale, Newtonbrook  \n",
       " 83                                           Downsview  \n",
       " 84                                     Studio District  \n",
       " 85                   Bedford Park, Lawrence Manor East  \n",
       " 86    Del Ray, Mount Dennis, Keelsdale and Silverthorn  \n",
       " 87                                        Not assigned  \n",
       " 88                                        Not assigned  \n",
       " 89                                    Humberlea, Emery  \n",
       " 90                         Birch Cliff, Cliffside West  \n",
       " 91                         Willowdale, Willowdale East  \n",
       " 92                                           Downsview  \n",
       " 93                                       Lawrence Park  \n",
       " 94                                            Roselawn  \n",
       " 95                       Runnymede, The Junction North  \n",
       " 96                                        Not assigned  \n",
       " 97                                        Not assigned  \n",
       " 98                                              Weston  \n",
       " 99   Dorset Park, Wexford Heights, Scarborough Town...  \n",
       " 100                                    York Mills West  \n",
       " 101                                       Not assigned  \n",
       " 102                                   Davisville North  \n",
       " 103    Forest Hill North & West, Forest Hill Road Park  \n",
       " 104                      High Park, The Junction South  \n",
       " 105                                       Not assigned  \n",
       " 106                                       Not assigned  \n",
       " 107                                          Westmount  \n",
       " 108                                  Wexford, Maryvale  \n",
       " 109                        Willowdale, Willowdale West  \n",
       " 110                                       Not assigned  \n",
       " 111                  North Toronto West, Lawrence Park  \n",
       " 112                The Annex, North Midtown, Yorkville  \n",
       " 113                             Parkdale, Roncesvalles  \n",
       " 114              Canada Post Gateway Processing Centre  \n",
       " 115                                       Not assigned  \n",
       " 116  Kingsview Village, St. Phillips, Martin Grove ...  \n",
       " 117                                          Agincourt  \n",
       " 118                                       Not assigned  \n",
       " 119                                       Not assigned  \n",
       " 120                                         Davisville  \n",
       " 121                     University of Toronto, Harbord  \n",
       " 122                                 Runnymede, Swansea  \n",
       " 123                                       Not assigned  \n",
       " 124                                       Not assigned  \n",
       " 125                                       Not assigned  \n",
       " 126            Clarks Corners, Tam O'Shanter, Sullivan  \n",
       " 127                                       Not assigned  \n",
       " 128                                       Not assigned  \n",
       " 129                        Moore Park, Summerhill East  \n",
       " 130          Kensington Market, Chinatown, Grange Park  \n",
       " 131                                       Not assigned  \n",
       " 132                                       Not assigned  \n",
       " 133                                       Not assigned  \n",
       " 134                                       Not assigned  \n",
       " 135  Milliken, Agincourt North, Steeles East, L'Amo...  \n",
       " 136                                       Not assigned  \n",
       " 137                                       Not assigned  \n",
       " 138  Summerhill West, Rathnelly, South Hill, Forest...  \n",
       " 139  CN Tower, King and Spadina, Railway Lands, Har...  \n",
       " 140                                       Not assigned  \n",
       " 141                                       Not assigned  \n",
       " 142       New Toronto, Mimico South, Humber Bay Shores  \n",
       " 143  South Steeles, Silverstone, Humbergate, Jamest...  \n",
       " 144                      Steeles West, L'Amoreaux West  \n",
       " 145                                       Not assigned  \n",
       " 146                                       Not assigned  \n",
       " 147                                           Rosedale  \n",
       " 148                                     Stn A PO Boxes  \n",
       " 149                                       Not assigned  \n",
       " 150                                       Not assigned  \n",
       " 151                             Alderwood, Long Branch  \n",
       " 152                Northwest, West Humber - Clairville  \n",
       " 153                                        Upper Rouge  \n",
       " 154                                       Not assigned  \n",
       " 155                                       Not assigned  \n",
       " 156                        St. James Town, Cabbagetown  \n",
       " 157             First Canadian Place, Underground city  \n",
       " 158                                       Not assigned  \n",
       " 159                                       Not assigned  \n",
       " 160      The Kingsway, Montgomery Road, Old Mill North  \n",
       " 161                                       Not assigned  \n",
       " 162                                       Not assigned  \n",
       " 163                                       Not assigned  \n",
       " 164                                       Not assigned  \n",
       " 165                               Church and Wellesley  \n",
       " 166                                       Not assigned  \n",
       " 167                                       Not assigned  \n",
       " 168  Business reply mail Processing Centre, South C...  \n",
       " 169  Old Mill South, King's Mill Park, Sunnylea, Hu...  \n",
       " 170                                       Not assigned  \n",
       " 171                                       Not assigned  \n",
       " 172                                       Not assigned  \n",
       " 173                                       Not assigned  \n",
       " 174                                       Not assigned  \n",
       " 175                                       Not assigned  \n",
       " 176                                       Not assigned  \n",
       " 177                                       Not assigned  \n",
       " 178  Mimico NW, The Queensway West, South of Bloor,...  \n",
       " 179                                       Not assigned  ,\n",
       "                                                   0   \\\n",
       " 0                                                NaN   \n",
       " 1  NL NS PE NB QC ON MB SK AB BC NU/NT YT A B C E...   \n",
       " 2                                                 NL   \n",
       " 3                                                  A   \n",
       " \n",
       "                                                   1   \\\n",
       " 0                              Canadian postal codes   \n",
       " 1  NL NS PE NB QC ON MB SK AB BC NU/NT YT A B C E...   \n",
       " 2                                                 NS   \n",
       " 3                                                  B   \n",
       " \n",
       "                                                   2    3    4    5    6    7   \\\n",
       " 0                                                NaN  NaN  NaN  NaN  NaN  NaN   \n",
       " 1  NL NS PE NB QC ON MB SK AB BC NU/NT YT A B C E...  NaN  NaN  NaN  NaN  NaN   \n",
       " 2                                                 PE   NB   QC   QC   QC   ON   \n",
       " 3                                                  C    E    G    H    J    K   \n",
       " \n",
       "     8    9    10   11   12   13   14   15     16   17  \n",
       " 0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN    NaN  NaN  \n",
       " 1  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN    NaN  NaN  \n",
       " 2   ON   ON   ON   ON   MB   SK   AB   BC  NU/NT   YT  \n",
       " 3    L    M    N    P    R    S    T    V      X    Y  ,\n",
       "    0   1   2   3   4   5   6   7   8   9   10  11  12  13  14  15     16  17\n",
       " 0  NL  NS  PE  NB  QC  QC  QC  ON  ON  ON  ON  ON  MB  SK  AB  BC  NU/NT  YT\n",
       " 1   A   B   C   E   G   H   J   K   L   M   N   P   R   S   T   V      X   Y]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 1: Data processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Let's check the type of data we got"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(toronto_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's check the length of the list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our data is a list of  3  items\n"
     ]
    }
   ],
   "source": [
    "len(toronto_data)\n",
    "print('Our data is a list of ',len(toronto_data),' items')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's check the first item of the list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</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>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Manor, Lawrence Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park, Ontario Provincial Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M8A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M9A</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Islington Avenue, Humber Valley Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Malvern, Rouge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>M2B</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M3B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>M4B</td>\n",
       "      <td>East York</td>\n",
       "      <td>Parkview Hill, Woodbine Gardens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Garden District, Ryerson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>M6B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Glencairn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>M7B</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>M8B</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M9B</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>West Deane Park, Princess Gardens, Martin Grov...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge Hill, Port Union, Highland Creek</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M2C</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>M3C</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>M4C</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>M5C</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>M6C</td>\n",
       "      <td>York</td>\n",
       "      <td>Humewood-Cedarvale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>M7C</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>M8C</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>M9C</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Eringate, Bloordale Gardens, Old Burnhamthorpe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood, Morningside, West Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>M2E</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>M3E</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>M5E</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Berczy Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>M6E</td>\n",
       "      <td>York</td>\n",
       "      <td>Caledonia-Fairbanks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>M7E</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>M8E</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>M9E</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>M1G</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Woburn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>M2G</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>M3G</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>M4G</td>\n",
       "      <td>East York</td>\n",
       "      <td>Leaside</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>M5G</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Central Bay Street</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>M6G</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Christie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>M7G</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>M8G</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>M9G</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>M1H</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cedarbrae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>M2H</td>\n",
       "      <td>North York</td>\n",
       "      <td>Hillcrest Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>M3H</td>\n",
       "      <td>North York</td>\n",
       "      <td>Bathurst Manor, Wilson Heights, Downsview North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>M4H</td>\n",
       "      <td>East York</td>\n",
       "      <td>Thorncliffe Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>M5H</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Richmond, Adelaide, King</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>M6H</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Dufferin, Dovercourt Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>M7H</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>M8H</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>M9H</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>M1J</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Scarborough Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>M2J</td>\n",
       "      <td>North York</td>\n",
       "      <td>Fairview, Henry Farm, Oriole</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>M3J</td>\n",
       "      <td>North York</td>\n",
       "      <td>Northwood Park, York University</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>M4J</td>\n",
       "      <td>East York</td>\n",
       "      <td>East Toronto, Broadview North (Old East York)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>M5J</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront East, Union Station, Toronto Islands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>M6J</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Little Portugal, Trinity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>M7J</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>M8J</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>M9J</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>M1K</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Kennedy Park, Ionview, East Birchmount Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>M2K</td>\n",
       "      <td>North York</td>\n",
       "      <td>Bayview Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>M3K</td>\n",
       "      <td>North York</td>\n",
       "      <td>Downsview</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>M4K</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Danforth West, Riverdale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>M5K</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Toronto Dominion Centre, Design Exchange</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>M6K</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>M7K</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>M8K</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>M9K</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>M1L</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Golden Mile, Clairlea, Oakridge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>M2L</td>\n",
       "      <td>North York</td>\n",
       "      <td>York Mills, Silver Hills</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>M3L</td>\n",
       "      <td>North York</td>\n",
       "      <td>Downsview</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>M4L</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>India Bazaar, The Beaches West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>M5L</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Commerce Court, Victoria Hotel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>M6L</td>\n",
       "      <td>North York</td>\n",
       "      <td>North Park, Maple Leaf Park, Upwood Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>M7L</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>M8L</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>M9L</td>\n",
       "      <td>North York</td>\n",
       "      <td>Humber Summit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>M1M</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cliffside, Cliffcrest, Scarborough Village West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>M2M</td>\n",
       "      <td>North York</td>\n",
       "      <td>Willowdale, Newtonbrook</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>M3M</td>\n",
       "      <td>North York</td>\n",
       "      <td>Downsview</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>M4M</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>Studio District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>M5M</td>\n",
       "      <td>North York</td>\n",
       "      <td>Bedford Park, Lawrence Manor East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>M6M</td>\n",
       "      <td>York</td>\n",
       "      <td>Del Ray, Mount Dennis, Keelsdale and Silverthorn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>M7M</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>M8M</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>M9M</td>\n",
       "      <td>North York</td>\n",
       "      <td>Humberlea, Emery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>M1N</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Birch Cliff, Cliffside West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>M2N</td>\n",
       "      <td>North York</td>\n",
       "      <td>Willowdale, Willowdale East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>M3N</td>\n",
       "      <td>North York</td>\n",
       "      <td>Downsview</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>M4N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>M5N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Roselawn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>M6N</td>\n",
       "      <td>York</td>\n",
       "      <td>Runnymede, The Junction North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>M7N</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>M8N</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>M9N</td>\n",
       "      <td>York</td>\n",
       "      <td>Weston</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>M1P</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Dorset Park, Wexford Heights, Scarborough Town...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>M2P</td>\n",
       "      <td>North York</td>\n",
       "      <td>York Mills West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>M3P</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>M4P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>M5P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Forest Hill North &amp; West, Forest Hill Road Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>M6P</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>High Park, The Junction South</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>M7P</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>M8P</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>M9P</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Westmount</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>M1R</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Wexford, Maryvale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>M2R</td>\n",
       "      <td>North York</td>\n",
       "      <td>Willowdale, Willowdale West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>M3R</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>M4R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>M5R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>M6R</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Parkdale, Roncesvalles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>M7R</td>\n",
       "      <td>Mississauga</td>\n",
       "      <td>Canada Post Gateway Processing Centre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>M8R</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>M9R</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Kingsview Village, St. Phillips, Martin Grove ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>M1S</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Agincourt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>M2S</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>M3S</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>M4S</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>M5S</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>University of Toronto, Harbord</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>M6S</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Runnymede, Swansea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>M7S</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>M8S</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>M9S</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>M1T</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Clarks Corners, Tam O'Shanter, Sullivan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>M2T</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>M3T</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>M4T</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>M5T</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Kensington Market, Chinatown, Grange Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>M6T</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>M7T</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>M8T</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>M9T</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>M1V</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Milliken, Agincourt North, Steeles East, L'Amo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>M2V</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>M3V</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>M4V</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Summerhill West, Rathnelly, South Hill, Forest...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>M5V</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>M6V</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>M7V</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>M8V</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>New Toronto, Mimico South, Humber Bay Shores</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>M9V</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>South Steeles, Silverstone, Humbergate, Jamest...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>M1W</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Steeles West, L'Amoreaux West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>M2W</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>M3W</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>M4W</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Rosedale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>M5W</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Stn A PO Boxes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>M6W</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>M7W</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>M8W</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Alderwood, Long Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>M9W</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Northwest, West Humber - Clairville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>M1X</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Upper Rouge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>M2X</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>M3X</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>M4X</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town, Cabbagetown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>M5X</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>First Canadian Place, Underground city</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>M6X</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>M7X</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>M8X</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>The Kingsway, Montgomery Road, Old Mill North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>M9X</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>M1Y</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>M2Y</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>M3Y</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>M4Y</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Church and Wellesley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>M5Y</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>M6Y</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>M8Y</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Old Mill South, King's Mill Park, Sunnylea, Hu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>M9Y</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>M1Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>M2Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>M3Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>M4Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>M5Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>M6Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>M7Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>M8Z</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Mimico NW, The Queensway West, South of Bloor,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>M9Z</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Postal Code           Borough  \\\n",
       "0           M1A      Not assigned   \n",
       "1           M2A      Not assigned   \n",
       "2           M3A        North York   \n",
       "3           M4A        North York   \n",
       "4           M5A  Downtown Toronto   \n",
       "5           M6A        North York   \n",
       "6           M7A  Downtown Toronto   \n",
       "7           M8A      Not assigned   \n",
       "8           M9A         Etobicoke   \n",
       "9           M1B       Scarborough   \n",
       "10          M2B      Not assigned   \n",
       "11          M3B        North York   \n",
       "12          M4B         East York   \n",
       "13          M5B  Downtown Toronto   \n",
       "14          M6B        North York   \n",
       "15          M7B      Not assigned   \n",
       "16          M8B      Not assigned   \n",
       "17          M9B         Etobicoke   \n",
       "18          M1C       Scarborough   \n",
       "19          M2C      Not assigned   \n",
       "20          M3C        North York   \n",
       "21          M4C         East York   \n",
       "22          M5C  Downtown Toronto   \n",
       "23          M6C              York   \n",
       "24          M7C      Not assigned   \n",
       "25          M8C      Not assigned   \n",
       "26          M9C         Etobicoke   \n",
       "27          M1E       Scarborough   \n",
       "28          M2E      Not assigned   \n",
       "29          M3E      Not assigned   \n",
       "30          M4E      East Toronto   \n",
       "31          M5E  Downtown Toronto   \n",
       "32          M6E              York   \n",
       "33          M7E      Not assigned   \n",
       "34          M8E      Not assigned   \n",
       "35          M9E      Not assigned   \n",
       "36          M1G       Scarborough   \n",
       "37          M2G      Not assigned   \n",
       "38          M3G      Not assigned   \n",
       "39          M4G         East York   \n",
       "40          M5G  Downtown Toronto   \n",
       "41          M6G  Downtown Toronto   \n",
       "42          M7G      Not assigned   \n",
       "43          M8G      Not assigned   \n",
       "44          M9G      Not assigned   \n",
       "45          M1H       Scarborough   \n",
       "46          M2H        North York   \n",
       "47          M3H        North York   \n",
       "48          M4H         East York   \n",
       "49          M5H  Downtown Toronto   \n",
       "50          M6H      West Toronto   \n",
       "51          M7H      Not assigned   \n",
       "52          M8H      Not assigned   \n",
       "53          M9H      Not assigned   \n",
       "54          M1J       Scarborough   \n",
       "55          M2J        North York   \n",
       "56          M3J        North York   \n",
       "57          M4J         East York   \n",
       "58          M5J  Downtown Toronto   \n",
       "59          M6J      West Toronto   \n",
       "60          M7J      Not assigned   \n",
       "61          M8J      Not assigned   \n",
       "62          M9J      Not assigned   \n",
       "63          M1K       Scarborough   \n",
       "64          M2K        North York   \n",
       "65          M3K        North York   \n",
       "66          M4K      East Toronto   \n",
       "67          M5K  Downtown Toronto   \n",
       "68          M6K      West Toronto   \n",
       "69          M7K      Not assigned   \n",
       "70          M8K      Not assigned   \n",
       "71          M9K      Not assigned   \n",
       "72          M1L       Scarborough   \n",
       "73          M2L        North York   \n",
       "74          M3L        North York   \n",
       "75          M4L      East Toronto   \n",
       "76          M5L  Downtown Toronto   \n",
       "77          M6L        North York   \n",
       "78          M7L      Not assigned   \n",
       "79          M8L      Not assigned   \n",
       "80          M9L        North York   \n",
       "81          M1M       Scarborough   \n",
       "82          M2M        North York   \n",
       "83          M3M        North York   \n",
       "84          M4M      East Toronto   \n",
       "85          M5M        North York   \n",
       "86          M6M              York   \n",
       "87          M7M      Not assigned   \n",
       "88          M8M      Not assigned   \n",
       "89          M9M        North York   \n",
       "90          M1N       Scarborough   \n",
       "91          M2N        North York   \n",
       "92          M3N        North York   \n",
       "93          M4N   Central Toronto   \n",
       "94          M5N   Central Toronto   \n",
       "95          M6N              York   \n",
       "96          M7N      Not assigned   \n",
       "97          M8N      Not assigned   \n",
       "98          M9N              York   \n",
       "99          M1P       Scarborough   \n",
       "100         M2P        North York   \n",
       "101         M3P      Not assigned   \n",
       "102         M4P   Central Toronto   \n",
       "103         M5P   Central Toronto   \n",
       "104         M6P      West Toronto   \n",
       "105         M7P      Not assigned   \n",
       "106         M8P      Not assigned   \n",
       "107         M9P         Etobicoke   \n",
       "108         M1R       Scarborough   \n",
       "109         M2R        North York   \n",
       "110         M3R      Not assigned   \n",
       "111         M4R   Central Toronto   \n",
       "112         M5R   Central Toronto   \n",
       "113         M6R      West Toronto   \n",
       "114         M7R       Mississauga   \n",
       "115         M8R      Not assigned   \n",
       "116         M9R         Etobicoke   \n",
       "117         M1S       Scarborough   \n",
       "118         M2S      Not assigned   \n",
       "119         M3S      Not assigned   \n",
       "120         M4S   Central Toronto   \n",
       "121         M5S  Downtown Toronto   \n",
       "122         M6S      West Toronto   \n",
       "123         M7S      Not assigned   \n",
       "124         M8S      Not assigned   \n",
       "125         M9S      Not assigned   \n",
       "126         M1T       Scarborough   \n",
       "127         M2T      Not assigned   \n",
       "128         M3T      Not assigned   \n",
       "129         M4T   Central Toronto   \n",
       "130         M5T  Downtown Toronto   \n",
       "131         M6T      Not assigned   \n",
       "132         M7T      Not assigned   \n",
       "133         M8T      Not assigned   \n",
       "134         M9T      Not assigned   \n",
       "135         M1V       Scarborough   \n",
       "136         M2V      Not assigned   \n",
       "137         M3V      Not assigned   \n",
       "138         M4V   Central Toronto   \n",
       "139         M5V  Downtown Toronto   \n",
       "140         M6V      Not assigned   \n",
       "141         M7V      Not assigned   \n",
       "142         M8V         Etobicoke   \n",
       "143         M9V         Etobicoke   \n",
       "144         M1W       Scarborough   \n",
       "145         M2W      Not assigned   \n",
       "146         M3W      Not assigned   \n",
       "147         M4W  Downtown Toronto   \n",
       "148         M5W  Downtown Toronto   \n",
       "149         M6W      Not assigned   \n",
       "150         M7W      Not assigned   \n",
       "151         M8W         Etobicoke   \n",
       "152         M9W         Etobicoke   \n",
       "153         M1X       Scarborough   \n",
       "154         M2X      Not assigned   \n",
       "155         M3X      Not assigned   \n",
       "156         M4X  Downtown Toronto   \n",
       "157         M5X  Downtown Toronto   \n",
       "158         M6X      Not assigned   \n",
       "159         M7X      Not assigned   \n",
       "160         M8X         Etobicoke   \n",
       "161         M9X      Not assigned   \n",
       "162         M1Y      Not assigned   \n",
       "163         M2Y      Not assigned   \n",
       "164         M3Y      Not assigned   \n",
       "165         M4Y  Downtown Toronto   \n",
       "166         M5Y      Not assigned   \n",
       "167         M6Y      Not assigned   \n",
       "168         M7Y      East Toronto   \n",
       "169         M8Y         Etobicoke   \n",
       "170         M9Y      Not assigned   \n",
       "171         M1Z      Not assigned   \n",
       "172         M2Z      Not assigned   \n",
       "173         M3Z      Not assigned   \n",
       "174         M4Z      Not assigned   \n",
       "175         M5Z      Not assigned   \n",
       "176         M6Z      Not assigned   \n",
       "177         M7Z      Not assigned   \n",
       "178         M8Z         Etobicoke   \n",
       "179         M9Z      Not assigned   \n",
       "\n",
       "                                          Neighborhood  \n",
       "0                                         Not assigned  \n",
       "1                                         Not assigned  \n",
       "2                                            Parkwoods  \n",
       "3                                     Victoria Village  \n",
       "4                            Regent Park, Harbourfront  \n",
       "5                     Lawrence Manor, Lawrence Heights  \n",
       "6          Queen's Park, Ontario Provincial Government  \n",
       "7                                         Not assigned  \n",
       "8              Islington Avenue, Humber Valley Village  \n",
       "9                                       Malvern, Rouge  \n",
       "10                                        Not assigned  \n",
       "11                                           Don Mills  \n",
       "12                     Parkview Hill, Woodbine Gardens  \n",
       "13                            Garden District, Ryerson  \n",
       "14                                           Glencairn  \n",
       "15                                        Not assigned  \n",
       "16                                        Not assigned  \n",
       "17   West Deane Park, Princess Gardens, Martin Grov...  \n",
       "18              Rouge Hill, Port Union, Highland Creek  \n",
       "19                                        Not assigned  \n",
       "20                                           Don Mills  \n",
       "21                                    Woodbine Heights  \n",
       "22                                      St. James Town  \n",
       "23                                  Humewood-Cedarvale  \n",
       "24                                        Not assigned  \n",
       "25                                        Not assigned  \n",
       "26   Eringate, Bloordale Gardens, Old Burnhamthorpe...  \n",
       "27                   Guildwood, Morningside, West Hill  \n",
       "28                                        Not assigned  \n",
       "29                                        Not assigned  \n",
       "30                                         The Beaches  \n",
       "31                                         Berczy Park  \n",
       "32                                 Caledonia-Fairbanks  \n",
       "33                                        Not assigned  \n",
       "34                                        Not assigned  \n",
       "35                                        Not assigned  \n",
       "36                                              Woburn  \n",
       "37                                        Not assigned  \n",
       "38                                        Not assigned  \n",
       "39                                             Leaside  \n",
       "40                                  Central Bay Street  \n",
       "41                                            Christie  \n",
       "42                                        Not assigned  \n",
       "43                                        Not assigned  \n",
       "44                                        Not assigned  \n",
       "45                                           Cedarbrae  \n",
       "46                                   Hillcrest Village  \n",
       "47     Bathurst Manor, Wilson Heights, Downsview North  \n",
       "48                                    Thorncliffe Park  \n",
       "49                            Richmond, Adelaide, King  \n",
       "50                        Dufferin, Dovercourt Village  \n",
       "51                                        Not assigned  \n",
       "52                                        Not assigned  \n",
       "53                                        Not assigned  \n",
       "54                                 Scarborough Village  \n",
       "55                        Fairview, Henry Farm, Oriole  \n",
       "56                     Northwood Park, York University  \n",
       "57       East Toronto, Broadview North (Old East York)  \n",
       "58   Harbourfront East, Union Station, Toronto Islands  \n",
       "59                            Little Portugal, Trinity  \n",
       "60                                        Not assigned  \n",
       "61                                        Not assigned  \n",
       "62                                        Not assigned  \n",
       "63         Kennedy Park, Ionview, East Birchmount Park  \n",
       "64                                     Bayview Village  \n",
       "65                                           Downsview  \n",
       "66                        The Danforth West, Riverdale  \n",
       "67            Toronto Dominion Centre, Design Exchange  \n",
       "68        Brockton, Parkdale Village, Exhibition Place  \n",
       "69                                        Not assigned  \n",
       "70                                        Not assigned  \n",
       "71                                        Not assigned  \n",
       "72                     Golden Mile, Clairlea, Oakridge  \n",
       "73                            York Mills, Silver Hills  \n",
       "74                                           Downsview  \n",
       "75                      India Bazaar, The Beaches West  \n",
       "76                      Commerce Court, Victoria Hotel  \n",
       "77            North Park, Maple Leaf Park, Upwood Park  \n",
       "78                                        Not assigned  \n",
       "79                                        Not assigned  \n",
       "80                                       Humber Summit  \n",
       "81     Cliffside, Cliffcrest, Scarborough Village West  \n",
       "82                             Willowdale, Newtonbrook  \n",
       "83                                           Downsview  \n",
       "84                                     Studio District  \n",
       "85                   Bedford Park, Lawrence Manor East  \n",
       "86    Del Ray, Mount Dennis, Keelsdale and Silverthorn  \n",
       "87                                        Not assigned  \n",
       "88                                        Not assigned  \n",
       "89                                    Humberlea, Emery  \n",
       "90                         Birch Cliff, Cliffside West  \n",
       "91                         Willowdale, Willowdale East  \n",
       "92                                           Downsview  \n",
       "93                                       Lawrence Park  \n",
       "94                                            Roselawn  \n",
       "95                       Runnymede, The Junction North  \n",
       "96                                        Not assigned  \n",
       "97                                        Not assigned  \n",
       "98                                              Weston  \n",
       "99   Dorset Park, Wexford Heights, Scarborough Town...  \n",
       "100                                    York Mills West  \n",
       "101                                       Not assigned  \n",
       "102                                   Davisville North  \n",
       "103    Forest Hill North & West, Forest Hill Road Park  \n",
       "104                      High Park, The Junction South  \n",
       "105                                       Not assigned  \n",
       "106                                       Not assigned  \n",
       "107                                          Westmount  \n",
       "108                                  Wexford, Maryvale  \n",
       "109                        Willowdale, Willowdale West  \n",
       "110                                       Not assigned  \n",
       "111                  North Toronto West, Lawrence Park  \n",
       "112                The Annex, North Midtown, Yorkville  \n",
       "113                             Parkdale, Roncesvalles  \n",
       "114              Canada Post Gateway Processing Centre  \n",
       "115                                       Not assigned  \n",
       "116  Kingsview Village, St. Phillips, Martin Grove ...  \n",
       "117                                          Agincourt  \n",
       "118                                       Not assigned  \n",
       "119                                       Not assigned  \n",
       "120                                         Davisville  \n",
       "121                     University of Toronto, Harbord  \n",
       "122                                 Runnymede, Swansea  \n",
       "123                                       Not assigned  \n",
       "124                                       Not assigned  \n",
       "125                                       Not assigned  \n",
       "126            Clarks Corners, Tam O'Shanter, Sullivan  \n",
       "127                                       Not assigned  \n",
       "128                                       Not assigned  \n",
       "129                        Moore Park, Summerhill East  \n",
       "130          Kensington Market, Chinatown, Grange Park  \n",
       "131                                       Not assigned  \n",
       "132                                       Not assigned  \n",
       "133                                       Not assigned  \n",
       "134                                       Not assigned  \n",
       "135  Milliken, Agincourt North, Steeles East, L'Amo...  \n",
       "136                                       Not assigned  \n",
       "137                                       Not assigned  \n",
       "138  Summerhill West, Rathnelly, South Hill, Forest...  \n",
       "139  CN Tower, King and Spadina, Railway Lands, Har...  \n",
       "140                                       Not assigned  \n",
       "141                                       Not assigned  \n",
       "142       New Toronto, Mimico South, Humber Bay Shores  \n",
       "143  South Steeles, Silverstone, Humbergate, Jamest...  \n",
       "144                      Steeles West, L'Amoreaux West  \n",
       "145                                       Not assigned  \n",
       "146                                       Not assigned  \n",
       "147                                           Rosedale  \n",
       "148                                     Stn A PO Boxes  \n",
       "149                                       Not assigned  \n",
       "150                                       Not assigned  \n",
       "151                             Alderwood, Long Branch  \n",
       "152                Northwest, West Humber - Clairville  \n",
       "153                                        Upper Rouge  \n",
       "154                                       Not assigned  \n",
       "155                                       Not assigned  \n",
       "156                        St. James Town, Cabbagetown  \n",
       "157             First Canadian Place, Underground city  \n",
       "158                                       Not assigned  \n",
       "159                                       Not assigned  \n",
       "160      The Kingsway, Montgomery Road, Old Mill North  \n",
       "161                                       Not assigned  \n",
       "162                                       Not assigned  \n",
       "163                                       Not assigned  \n",
       "164                                       Not assigned  \n",
       "165                               Church and Wellesley  \n",
       "166                                       Not assigned  \n",
       "167                                       Not assigned  \n",
       "168  Business reply mail Processing Centre, South C...  \n",
       "169  Old Mill South, King's Mill Park, Sunnylea, Hu...  \n",
       "170                                       Not assigned  \n",
       "171                                       Not assigned  \n",
       "172                                       Not assigned  \n",
       "173                                       Not assigned  \n",
       "174                                       Not assigned  \n",
       "175                                       Not assigned  \n",
       "176                                       Not assigned  \n",
       "177                                       Not assigned  \n",
       "178  Mimico NW, The Queensway West, South of Bloor,...  \n",
       "179                                       Not assigned  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_data[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### The data we are inerested in is stored in the first index of the list."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Store the first item of the list as a pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=toronto_data[0]\n",
    "type(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>PostalCode</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>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           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  Regent Park, Harbourfront"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save df as csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"postal_code.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The firstt column has a white in its name (\"Postal Code\"), let's remove the space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PostalCode', 'Borough', 'Neighborhood'], dtype='object')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PostalCode', 'Borough', 'Neighborhood'], dtype='object')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = ['PostalCode', 'Borough', 'Neighborhood']\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\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>PostalCode</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>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           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  Regent Park, Harbourfront"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remove all entries with a \"Not assigned\" Borough"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done. All 'Not assigned' Borough has been removed!\n"
     ]
    }
   ],
   "source": [
    "df = df[df[\"Borough\"] != \"Not assigned\"]\n",
    "print(\"Done. All \\'Not assigned\\' Borough has been removed!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>PostalCode</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>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Manor, Lawrence Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park, Ontario Provincial Government</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                                 Neighborhood\n",
       "0        M3A        North York                                    Parkwoods\n",
       "1        M4A        North York                             Victoria Village\n",
       "2        M5A  Downtown Toronto                    Regent Park, Harbourfront\n",
       "3        M6A        North York             Lawrence Manor, Lawrence Heights\n",
       "4        M7A  Downtown Toronto  Queen's Park, Ontario Provincial Government"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reset_index(drop=True, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lets chek wether there is any duplicated entry in PostalCode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PostalCode</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>M1B</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M5R</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M6G</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M6E</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M6C</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Borough\n",
       "PostalCode         \n",
       "M1B               1\n",
       "M5R               1\n",
       "M6G               1\n",
       "M6E               1\n",
       "M6C               1"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"PostalCode\",\"Borough\"]].groupby(\"PostalCode\").count().sort_values(by=[\"Borough\"], ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### This list is grouped and ordered in descending way. The highest value is on top. Since that highest value is 1, therefore there are no duplicated PostalCode in the table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103, 3)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question 2: Data with latitude and longitude"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Install geocoder package"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting geocoder\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/4f/6b/13166c909ad2f2d76b929a4227c952630ebaf0d729f6317eb09cbceccbab/geocoder-1.38.1-py2.py3-none-any.whl (98kB)\n",
      "\u001b[K     |████████████████████████████████| 102kB 5.4MB/s ta 0:00:011\n",
      "\u001b[?25hCollecting click (from geocoder)\n",
      "  Using cached https://files.pythonhosted.org/packages/d2/3d/fa76db83bf75c4f8d338c2fd15c8d33fdd7ad23a9b5e57eb6c5de26b430e/click-7.1.2-py2.py3-none-any.whl\n",
      "Requirement already satisfied: requests in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (2.24.0)\n",
      "Collecting ratelim (from geocoder)\n",
      "  Downloading https://files.pythonhosted.org/packages/f2/98/7e6d147fd16a10a5f821db6e25f192265d6ecca3d82957a4fdd592cad49c/ratelim-0.1.6-py2.py3-none-any.whl\n",
      "Collecting future (from geocoder)\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/45/0b/38b06fd9b92dc2b68d58b75f900e97884c45bedd2ff83203d933cf5851c9/future-0.18.2.tar.gz (829kB)\n",
      "\u001b[K     |████████████████████████████████| 829kB 8.0MB/s eta 0:00:01\n",
      "\u001b[?25hRequirement already satisfied: six in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (1.15.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (2020.6.20)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (3.0.4)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (1.25.9)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (2.10)\n",
      "Requirement already satisfied: decorator in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from ratelim->geocoder) (4.4.2)\n",
      "Building wheels for collected packages: future\n",
      "  Building wheel for future (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Stored in directory: /home/jupyterlab/.cache/pip/wheels/8b/99/a0/81daf51dcd359a9377b110a8a886b3895921802d2fc1b2397e\n",
      "Successfully built future\n",
      "Installing collected packages: click, ratelim, future, geocoder\n",
      "Successfully installed click-7.1.2 future-0.18.2 geocoder-1.38.1 ratelim-0.1.6\n"
     ]
    }
   ],
   "source": [
    "!pip install geocoder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Click here to see the code for geocoder but it's not working...\n",
    "<!--\n",
    "import geocoder # import geocoder\n",
    "\n",
    "latlng = []\n",
    "pp = 100/len(df[\"PostalCode\"])\n",
    "p=0\n",
    "for pstl_cd in df[\"PostalCode\"]:\n",
    "    p=int(round(p+pp))\n",
    "    if p>100:\n",
    "        p=100\n",
    "    print('working ',p,'%', '.'*p, end =\"\\r\")\n",
    "    # initialize your variable to None\n",
    "    lat_lng_coords = None\n",
    "    # loop until you get the coordinates\n",
    "    while(lat_lng_coords is None):\n",
    "      g = geocoder.google('{}, Toronto, Ontario'.format(pstl_cd))\n",
    "      lat_lng_coords = g.latlng\n",
    "\n",
    "    latlng.append(lat_lng_coords)\n",
    "\n",
    "latlng -->"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load location data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\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>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",
       "  </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"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latlng = pd.read_csv(\"http://cocl.us/Geospatial_data\")\n",
    "latlng.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remove space from the column name \"Postal Code\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>PostalCode</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode   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"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latlng.columns = [\"PostalCode\",\"Latitude\",\"Longitude\"]\n",
    "latlng.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "latlng.to_csv(\"latlng.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "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>PostalCode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</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>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>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>Regent Park, Harbourfront</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 Manor, Lawrence Heights</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, Ontario Provincial Government</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                                 Neighborhood  \\\n",
       "0        M3A        North York                                    Parkwoods   \n",
       "1        M4A        North York                             Victoria Village   \n",
       "2        M5A  Downtown Toronto                    Regent Park, Harbourfront   \n",
       "3        M6A        North York             Lawrence Manor, Lawrence Heights   \n",
       "4        M7A  Downtown Toronto  Queen's Park, Ontario Provincial Government   \n",
       "\n",
       "    Latitude  Longitude  \n",
       "0  43.753259 -79.329656  \n",
       "1  43.725882 -79.315572  \n",
       "2  43.654260 -79.360636  \n",
       "3  43.718518 -79.464763  \n",
       "4  43.662301 -79.389494  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postal_code = pd.merge(df, latlng, left_on='PostalCode', right_on='PostalCode')\n",
    "postal_code.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "postal_code.to_csv(\"postal_code_latlng.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Question 3: Explore and cluster the neighborhoods in Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>PostalCode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</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>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>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>Regent Park, Harbourfront</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 Manor, Lawrence Heights</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, Ontario Provincial Government</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                                 Neighborhood  \\\n",
       "0        M3A        North York                                    Parkwoods   \n",
       "1        M4A        North York                             Victoria Village   \n",
       "2        M5A  Downtown Toronto                    Regent Park, Harbourfront   \n",
       "3        M6A        North York             Lawrence Manor, Lawrence Heights   \n",
       "4        M7A  Downtown Toronto  Queen's Park, Ontario Provincial Government   \n",
       "\n",
       "    Latitude  Longitude  \n",
       "0  43.753259 -79.329656  \n",
       "1  43.725882 -79.315572  \n",
       "2  43.654260 -79.360636  \n",
       "3  43.718518 -79.464763  \n",
       "4  43.662301 -79.389494  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postal_code = pd.read_csv(\"postal_code_latlng.csv\")\n",
    "postal_code.drop([\"Unnamed: 0\"], axis=1, inplace=True)\n",
    "postal_code.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Check if the DataFrame contains any NaN value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No NaN values found :)\n"
     ]
    }
   ],
   "source": [
    "if postal_code.isnull().values.any():\n",
    "    print('Dataframe contains NaN values :(')\n",
    "else:\n",
    "    print('No NaN values found :)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  3.1 - Let's extract only entries (Borough) related to Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PostalCode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</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>Regent Park, Harbourfront</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, Ontario Provincial Government</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>Garden District, Ryerson</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>43.651494</td>\n",
       "      <td>-79.375418</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>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                                 Neighborhood  \\\n",
       "0        M5A  Downtown Toronto                    Regent Park, Harbourfront   \n",
       "1        M7A  Downtown Toronto  Queen's Park, Ontario Provincial Government   \n",
       "2        M5B  Downtown Toronto                     Garden District, Ryerson   \n",
       "3        M5C  Downtown Toronto                               St. James Town   \n",
       "4        M4E      East Toronto                                  The Beaches   \n",
       "\n",
       "    Latitude  Longitude  \n",
       "0  43.654260 -79.360636  \n",
       "1  43.662301 -79.389494  \n",
       "2  43.657162 -79.378937  \n",
       "3  43.651494 -79.375418  \n",
       "4  43.676357 -79.293031  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = postal_code[\"Borough\"].str.contains('Toronto', case=False) # Borough lines containing the word \"Toronto\"\n",
    "toronto_postal_code = postal_code[mask]\n",
    "toronto_postal_code.reset_index(drop=True, inplace=True)\n",
    "toronto_postal_code.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Number of neighborhoods in Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Toronto has 39 neighborhood(s)\n"
     ]
    }
   ],
   "source": [
    "print('Toronto has {} neighborhood(s)'.format(toronto_postal_code.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  3.2 - Visualize Toronto neighborhoods on a map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Geographical coordinates of Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinates of Toronto are 43.6534817, -79.3839347.\n"
     ]
    }
   ],
   "source": [
    "address = 'Toronto, CA'\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 coordinates of Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Toronto nieghborhoods on map using ___folium___"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Boroughs of Toronto - zoom start level  11\n",
      "Click on a circle to see the postal code and the associated neighborhood\n"
     ]
    },
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</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7faf1c010278>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Manhattan using latitude and longitude values\n",
    "zoom_start=11\n",
    "map_toronto = folium.Map(location=[latitude, longitude], zoom_start=zoom_start)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, neigh, postal in zip(toronto_postal_code['Latitude'], toronto_postal_code['Longitude'], toronto_postal_code['Neighborhood'], toronto_postal_code['PostalCode']):\n",
    "    label = folium.Popup(neigh+' - '+postal, 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",
    "print('Boroughs of Toronto - zoom start level ',zoom_start)\n",
    "print('Click on a circle to see the postal code and the associated neighborhood')\n",
    "map_toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 - Explore Toronto neighborhoods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Define Foursquare Credentials and Version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# @hidden_cell\n",
    "CLIENT_ID = '' # your Foursquare ID\n",
    "CLIENT_SECRET = '' # your Foursquare Secret\n",
    "VERSION = '20180605' # Foursquare API version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3.1 - Explore the first neighborhood in our dataframe."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Get the name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Regent Park, Harbourfront'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_postal_code.loc[0, 'Neighborhood']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Get the neighborhood's latitude and longitude values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " First neighborhood \"Regent Park, Harbourfront\". Latitude \"43.6542599\", longitude \"-79.3606359\".\n"
     ]
    }
   ],
   "source": [
    "first_neigh_name = toronto_postal_code.loc[0, 'Neighborhood']\n",
    "first_neigh_latitude = toronto_postal_code.loc[0, 'Latitude']\n",
    "first_neigh_longitude = toronto_postal_code.loc[0, 'Longitude']\n",
    "\n",
    "print(' First neighborhood \"{}\". Latitude \"{}\", longitude \"{}\".'.format(first_neigh_name, \n",
    "                                                               first_neigh_latitude, \n",
    "                                                               first_neigh_longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Now, let's get the top 100 venues that are in Regent Park and Harbourfront within a radius of 500 meters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "radius = 500\n",
    "LIMIT = 100\n",
    "url = 'https://api.foursquare.com/v2/venues/explore?client_id={}&client_secret={}&ll={},{}&v={}&radius={}&limit={}'.format(CLIENT_ID, CLIENT_SECRET, latitude, longitude, VERSION, radius, LIMIT)\n",
    "\n",
    "results = requests.get(url).json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's check available info about venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['id', 'name', 'location', 'categories', 'photos'])"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results['response']['groups'][0]['items'][0]['venue'].keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### What we need from this data about venues are: name, location(latitude and longitude) and the venue category"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's see the columns's name of the transformed 'items' to pandas DataFrame using json_normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: pandas.io.json.json_normalize is deprecated, use pandas.json_normalize instead\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['referralId', 'reasons.count', 'reasons.items', 'venue.id',\n",
       "       'venue.name', 'venue.location.lat', 'venue.location.lng',\n",
       "       'venue.location.labeledLatLngs', 'venue.location.distance',\n",
       "       'venue.location.cc', 'venue.location.city', 'venue.location.state',\n",
       "       'venue.location.country', 'venue.location.formattedAddress',\n",
       "       'venue.categories', 'venue.photos.count', 'venue.photos.groups',\n",
       "       'venue.location.address', 'venue.location.crossStreet',\n",
       "       'venue.location.postalCode', 'venue.location.neighborhood',\n",
       "       'venue.venuePage.id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_normalize(results['response']['groups'][0]['items']).columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Then, we will access to the info we need through the following colums name\n",
    "* 'venue.name'\n",
    "* 'venue.categories'\n",
    "* 'venue.location.lat'\n",
    "* 'venue.location.lng'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's create a function to get categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now we clean the json and structure it into a *pandas* dataframe."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### We use 'items' keywords because information about venues are stored there"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:3: FutureWarning: pandas.io.json.json_normalize is deprecated, use pandas.json_normalize instead\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "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>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>Downtown Toronto</td>\n",
       "      <td>Neighborhood</td>\n",
       "      <td>43.653232</td>\n",
       "      <td>-79.385296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Nathan Phillips Square</td>\n",
       "      <td>Plaza</td>\n",
       "      <td>43.652270</td>\n",
       "      <td>-79.383516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Poke Guys</td>\n",
       "      <td>Poke Place</td>\n",
       "      <td>43.654895</td>\n",
       "      <td>-79.385052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Japango</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>43.655268</td>\n",
       "      <td>-79.385165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Indigo</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>43.653515</td>\n",
       "      <td>-79.380696</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     name        categories        lat        lng\n",
       "0        Downtown Toronto      Neighborhood  43.653232 -79.385296\n",
       "1  Nathan Phillips Square             Plaza  43.652270 -79.383516\n",
       "2               Poke Guys        Poke Place  43.654895 -79.385052\n",
       "3                 Japango  Sushi Restaurant  43.655268 -79.385165\n",
       "4                  Indigo         Bookstore  43.653515 -79.380696"
      ]
     },
     "execution_count": 73,
     "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.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Number of venues returned by Foursqure for the first neighborhood in our dataset\n",
    "\n",
    "'Regent Park, Harbourfront'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "81 venues were returned by Foursquare for the neighborhood 'Regent Park, Harbourfront'.\n"
     ]
    }
   ],
   "source": [
    "print('{} venues were returned by Foursquare for the neighborhood \\'Regent Park, Harbourfront\\'.'.format(nearby_venues.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3.2 - Explore all neighborhoods in Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's create a function to repeat the same process to all the neighborhoods in 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",
    "    #End of for loop\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": "markdown",
   "metadata": {},
   "source": [
    "### Now, we create a DataFrame venues within 500 meters of all neighborhoods of Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Regent Park, Harbourfront\n",
      "Queen's Park, Ontario Provincial Government\n",
      "Garden District, Ryerson\n",
      "St. James Town\n",
      "The Beaches\n",
      "Berczy Park\n",
      "Central Bay Street\n",
      "Christie\n",
      "Richmond, Adelaide, King\n",
      "Dufferin, Dovercourt Village\n",
      "Harbourfront East, Union Station, Toronto Islands\n",
      "Little Portugal, Trinity\n",
      "The Danforth West, Riverdale\n",
      "Toronto Dominion Centre, Design Exchange\n",
      "Brockton, Parkdale Village, Exhibition Place\n",
      "India Bazaar, The Beaches West\n",
      "Commerce Court, Victoria Hotel\n",
      "Studio District\n",
      "Lawrence Park\n",
      "Roselawn\n",
      "Davisville North\n",
      "Forest Hill North & West, Forest Hill Road Park\n",
      "High Park, The Junction South\n",
      "North Toronto West, Lawrence Park\n",
      "The Annex, North Midtown, Yorkville\n",
      "Parkdale, Roncesvalles\n",
      "Davisville\n",
      "University of Toronto, Harbord\n",
      "Runnymede, Swansea\n",
      "Moore Park, Summerhill East\n",
      "Kensington Market, Chinatown, Grange Park\n",
      "Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park\n",
      "CN Tower, King and Spadina, Railway Lands, Harbourfront West, Bathurst Quay, South Niagara, Island airport\n",
      "Rosedale\n",
      "Stn A PO Boxes\n",
      "St. James Town, Cabbagetown\n",
      "First Canadian Place, Underground city\n",
      "Church and Wellesley\n",
      "Business reply mail Processing Centre, South Central Letter Processing Plant Toronto\n"
     ]
    }
   ],
   "source": [
    "toronto_venues = getNearbyVenues(names=toronto_postal_code['Neighborhood'],\n",
    "                                   latitudes=toronto_postal_code['Latitude'],\n",
    "                                   longitudes=toronto_postal_code['Longitude']\n",
    "                                  )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Number of venues returned by Foursqure within 500 meters of all Toronto's neighborhoods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1634 venues in total\n"
     ]
    }
   ],
   "source": [
    "print('There are {} venue(s) in total'.format(len(toronto_venues)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "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>Regent Park, 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>Regent Park, 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>Regent Park, Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Cooper Koo Family YMCA</td>\n",
       "      <td>43.653249</td>\n",
       "      <td>-79.358008</td>\n",
       "      <td>Distribution Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Regent Park, 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>Regent Park, 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  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "1  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "2  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "3  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "4  Regent Park, 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       43.653249       -79.358008   \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  Distribution Center  \n",
       "3                  Spa  \n",
       "4           Restaurant  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_venues.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Save DataFrame 'toronto_venues' into a csv format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "toronto_venues.to_csv('toronto_venues.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Regent Park, 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>Regent Park, 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>Regent Park, Harbourfront</td>\n",
       "      <td>43.65426</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Cooper Koo Family YMCA</td>\n",
       "      <td>43.653249</td>\n",
       "      <td>-79.358008</td>\n",
       "      <td>Distribution Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Regent Park, 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>Regent Park, 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  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "1  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "2  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "3  Regent Park, Harbourfront               43.65426              -79.360636   \n",
       "4  Regent Park, 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       43.653249       -79.358008   \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  Distribution Center  \n",
       "3                  Spa  \n",
       "4           Restaurant  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_venues = pd.read_csv('toronto_venues.csv')\n",
    "toronto_venues.drop(['Unnamed: 0'], axis=1, inplace=True)\n",
    "toronto_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1634, 7)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_venues.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### How many venues per neighborhood?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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 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>Berczy Park</th>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brockton, Parkdale Village, Exhibition Place</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Business reply mail Processing Centre, South Central Letter Processing Plant Toronto</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CN Tower, King and Spadina, Railway Lands, Harbourfront West, Bathurst Quay, South Niagara, Island airport</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central Bay Street</th>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Neighborhood Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Berczy Park                                                            57   \n",
       "Brockton, Parkdale Village, Exhibition Place                           22   \n",
       "Business reply mail Processing Centre, South Ce...                     16   \n",
       "CN Tower, King and Spadina, Railway Lands, Harb...                     16   \n",
       "Central Bay Street                                                     66   \n",
       "\n",
       "                                                    Neighborhood Longitude  \\\n",
       "Neighborhood                                                                 \n",
       "Berczy Park                                                             57   \n",
       "Brockton, Parkdale Village, Exhibition Place                            22   \n",
       "Business reply mail Processing Centre, South Ce...                      16   \n",
       "CN Tower, King and Spadina, Railway Lands, Harb...                      16   \n",
       "Central Bay Street                                                      66   \n",
       "\n",
       "                                                    Venue  Venue Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Berczy Park                                            57              57   \n",
       "Brockton, Parkdale Village, Exhibition Place           22              22   \n",
       "Business reply mail Processing Centre, South Ce...     16              16   \n",
       "CN Tower, King and Spadina, Railway Lands, Harb...     16              16   \n",
       "Central Bay Street                                     66              66   \n",
       "\n",
       "                                                    Venue Longitude  \\\n",
       "Neighborhood                                                          \n",
       "Berczy Park                                                      57   \n",
       "Brockton, Parkdale Village, Exhibition Place                     22   \n",
       "Business reply mail Processing Centre, South Ce...               16   \n",
       "CN Tower, King and Spadina, Railway Lands, Harb...               16   \n",
       "Central Bay Street                                               66   \n",
       "\n",
       "                                                    Venue Category  \n",
       "Neighborhood                                                        \n",
       "Berczy Park                                                     57  \n",
       "Brockton, Parkdale Village, Exhibition Place                    22  \n",
       "Business reply mail Processing Centre, South Ce...              16  \n",
       "CN Tower, King and Spadina, Railway Lands, Harb...              16  \n",
       "Central Bay Street                                              66  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_venues_neigh_grouped = toronto_venues.groupby('Neighborhood').count()\n",
    "toronto_venues_neigh_grouped.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Highest and lowest number of venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max: 100, min: 1\n"
     ]
    }
   ],
   "source": [
    "print('max: {}, min: {}'.format(toronto_venues_neigh_grouped['Venue'].max(),toronto_venues_neigh_grouped['Venue'].min()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Neighborhoods with the highest number of venues (100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Commerce Court, Victoria Hotel',\n",
       "       'First Canadian Place, Underground city', 'Garden District, Ryerson',\n",
       "       'Harbourfront East, Union Station, Toronto Islands',\n",
       "       'Toronto Dominion Centre, Design Exchange'],\n",
       "      dtype='object', name='Neighborhood')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_venues_neigh_grouped[toronto_venues_neigh_grouped['Venue']==100].index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Neighborhoods with the lowest number of venues (1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Roselawn'], dtype='object', name='Neighborhood')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_venues_neigh_grouped[toronto_venues_neigh_grouped['Venue']==1].index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How many unique categories of venues have been returned?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 234 unique categories\n"
     ]
    }
   ],
   "source": [
    "print('There are {} unique categories'.format(len(toronto_venues['Venue Category'].unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.4 - Analyze Each Neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# one hot encoding\n",
    "toronto_onehot = pd.get_dummies(toronto_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Yoga Studio</th>\n",
       "      <th>Airport</th>\n",
       "      <th>Airport Food Court</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>Aquarium</th>\n",
       "      <th>Art Gallery</th>\n",
       "      <th>Art Museum</th>\n",
       "      <th>Arts &amp; Crafts Store</th>\n",
       "      <th>Asian Restaurant</th>\n",
       "      <th>Auto Workshop</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Baby Store</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bakery</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Bar</th>\n",
       "      <th>Baseball Stadium</th>\n",
       "      <th>Basketball Stadium</th>\n",
       "      <th>Beach</th>\n",
       "      <th>Bed &amp; Breakfast</th>\n",
       "      <th>Beer Bar</th>\n",
       "      <th>Beer Store</th>\n",
       "      <th>Belgian Restaurant</th>\n",
       "      <th>Bistro</th>\n",
       "      <th>Boat or Ferry</th>\n",
       "      <th>Bookstore</th>\n",
       "      <th>Boutique</th>\n",
       "      <th>Brazilian Restaurant</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Bubble Tea Shop</th>\n",
       "      <th>Building</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Burrito Place</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Butcher</th>\n",
       "      <th>Cable Car</th>\n",
       "      <th>Café</th>\n",
       "      <th>Cajun / Creole Restaurant</th>\n",
       "      <th>Candy Store</th>\n",
       "      <th>Caribbean Restaurant</th>\n",
       "      <th>Cheese Shop</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Chocolate Shop</th>\n",
       "      <th>Church</th>\n",
       "      <th>Climbing Gym</th>\n",
       "      <th>Clothing Store</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Arts Building</th>\n",
       "      <th>College Auditorium</th>\n",
       "      <th>College Cafeteria</th>\n",
       "      <th>College Gym</th>\n",
       "      <th>College Rec Center</th>\n",
       "      <th>Colombian Restaurant</th>\n",
       "      <th>Comfort Food Restaurant</th>\n",
       "      <th>Comic Shop</th>\n",
       "      <th>Concert Hall</th>\n",
       "      <th>Convenience Store</th>\n",
       "      <th>Convention Center</th>\n",
       "      <th>Cosmetics Shop</th>\n",
       "      <th>Coworking Space</th>\n",
       "      <th>Creperie</th>\n",
       "      <th>Cuban Restaurant</th>\n",
       "      <th>Cupcake Shop</th>\n",
       "      <th>Dance Studio</th>\n",
       "      <th>Deli / Bodega</th>\n",
       "      <th>Department Store</th>\n",
       "      <th>Dessert Shop</th>\n",
       "      <th>Diner</th>\n",
       "      <th>Discount Store</th>\n",
       "      <th>Distribution Center</th>\n",
       "      <th>Dog Run</th>\n",
       "      <th>Doner Restaurant</th>\n",
       "      <th>Donut Shop</th>\n",
       "      <th>Dumpling Restaurant</th>\n",
       "      <th>Eastern European Restaurant</th>\n",
       "      <th>Electronics Store</th>\n",
       "      <th>Ethiopian Restaurant</th>\n",
       "      <th>Event Space</th>\n",
       "      <th>Falafel Restaurant</th>\n",
       "      <th>Farmers Market</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Filipino Restaurant</th>\n",
       "      <th>Fish &amp; Chips Shop</th>\n",
       "      <th>Fish Market</th>\n",
       "      <th>Flea Market</th>\n",
       "      <th>Flower Shop</th>\n",
       "      <th>Food</th>\n",
       "      <th>Food &amp; Drink Shop</th>\n",
       "      <th>Food Court</th>\n",
       "      <th>Food Truck</th>\n",
       "      <th>Fountain</th>\n",
       "      <th>French Restaurant</th>\n",
       "      <th>Fried Chicken Joint</th>\n",
       "      <th>Frozen Yogurt Shop</th>\n",
       "      <th>Fruit &amp; Vegetable Store</th>\n",
       "      <th>Furniture / Home Store</th>\n",
       "      <th>Gaming Cafe</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Garden Center</th>\n",
       "      <th>Gas Station</th>\n",
       "      <th>Gastropub</th>\n",
       "      <th>Gay Bar</th>\n",
       "      <th>General Entertainment</th>\n",
       "      <th>General Travel</th>\n",
       "      <th>German Restaurant</th>\n",
       "      <th>Gift Shop</th>\n",
       "      <th>Gluten-free Restaurant</th>\n",
       "      <th>Gourmet Shop</th>\n",
       "      <th>Greek Restaurant</th>\n",
       "      <th>Grocery Store</th>\n",
       "      <th>Gym</th>\n",
       "      <th>Gym / Fitness Center</th>\n",
       "      <th>Harbor / Marina</th>\n",
       "      <th>Health &amp; Beauty Service</th>\n",
       "      <th>Health Food Store</th>\n",
       "      <th>Historic Site</th>\n",
       "      <th>History Museum</th>\n",
       "      <th>Hobby Shop</th>\n",
       "      <th>Hospital</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>IT Services</th>\n",
       "      <th>Ice Cream Shop</th>\n",
       "      <th>Indian Restaurant</th>\n",
       "      <th>Indie Movie Theater</th>\n",
       "      <th>Indoor Play Area</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>Irish Pub</th>\n",
       "      <th>Italian Restaurant</th>\n",
       "      <th>Japanese Restaurant</th>\n",
       "      <th>Jazz Club</th>\n",
       "      <th>Jewelry Store</th>\n",
       "      <th>Juice Bar</th>\n",
       "      <th>Knitting Store</th>\n",
       "      <th>Korean Restaurant</th>\n",
       "      <th>Lake</th>\n",
       "      <th>Latin American Restaurant</th>\n",
       "      <th>Light Rail Station</th>\n",
       "      <th>Lingerie Store</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Lounge</th>\n",
       "      <th>Mac &amp; Cheese Joint</th>\n",
       "      <th>Market</th>\n",
       "      <th>Martial Arts Dojo</th>\n",
       "      <th>Mediterranean Restaurant</th>\n",
       "      <th>Men's Store</th>\n",
       "      <th>Metro Station</th>\n",
       "      <th>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Modern European Restaurant</th>\n",
       "      <th>Molecular Gastronomy Restaurant</th>\n",
       "      <th>Monument / Landmark</th>\n",
       "      <th>Moroccan Restaurant</th>\n",
       "      <th>Movie Theater</th>\n",
       "      <th>Museum</th>\n",
       "      <th>Music Store</th>\n",
       "      <th>Music Venue</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>New American Restaurant</th>\n",
       "      <th>Nightclub</th>\n",
       "      <th>Noodle House</th>\n",
       "      <th>Office</th>\n",
       "      <th>Opera House</th>\n",
       "      <th>Optical Shop</th>\n",
       "      <th>Organic Grocery</th>\n",
       "      <th>Other Great Outdoors</th>\n",
       "      <th>Park</th>\n",
       "      <th>Performing Arts Venue</th>\n",
       "      <th>Pet Store</th>\n",
       "      <th>Pharmacy</th>\n",
       "      <th>Pizza Place</th>\n",
       "      <th>Plane</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Poke Place</th>\n",
       "      <th>Poutine Place</th>\n",
       "      <th>Pub</th>\n",
       "      <th>Ramen Restaurant</th>\n",
       "      <th>Record Shop</th>\n",
       "      <th>Recording Studio</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Roof Deck</th>\n",
       "      <th>Sake Bar</th>\n",
       "      <th>Salad Place</th>\n",
       "      <th>Salon / Barbershop</th>\n",
       "      <th>Sandwich Place</th>\n",
       "      <th>Scenic Lookout</th>\n",
       "      <th>Sculpture Garden</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shoe Store</th>\n",
       "      <th>Shopping Mall</th>\n",
       "      <th>Skate Park</th>\n",
       "      <th>Skating Rink</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>Smoothie Shop</th>\n",
       "      <th>Snack Place</th>\n",
       "      <th>Soup Place</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Speakeasy</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Sports Bar</th>\n",
       "      <th>Stadium</th>\n",
       "      <th>Stationery Store</th>\n",
       "      <th>Steakhouse</th>\n",
       "      <th>Strip Club</th>\n",
       "      <th>Summer Camp</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Supplement Shop</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Taco Place</th>\n",
       "      <th>Tailor Shop</th>\n",
       "      <th>Taiwanese Restaurant</th>\n",
       "      <th>Tanning Salon</th>\n",
       "      <th>Tea Room</th>\n",
       "      <th>Tennis Court</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</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>Women's Store</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</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>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>1</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",
       "      <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",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</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",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</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",
       "      <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>0</td>\n",
       "      <td>0</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",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</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>Regent Park, Harbourfront</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",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>Regent Park, Harbourfront</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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",
       "      <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>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>1</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",
       "      <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>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>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>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>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>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>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>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>Regent Park, Harbourfront</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",
       "      <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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Regent Park, Harbourfront</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",
       "      <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",
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       "      <td>0</td>\n",
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       "      <td>0</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>1</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",
       "      <td>0</td>\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>0</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",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</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",
       "      <td>Regent Park, Harbourfront</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",
       "      <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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "      <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>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>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>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",
       "</div>"
      ],
      "text/plain": [
       "   Yoga Studio  Airport  Airport Food Court  Airport Lounge  Airport Service  \\\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 Terminal  American Restaurant  Antique Shop  Aquarium  Art Gallery  \\\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",
       "   Art Museum  Arts & Crafts Store  Asian Restaurant  Auto Workshop  \\\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",
       "   BBQ Joint  Baby Store  Bagel Shop  Bakery  Bank  Bar  Baseball Stadium  \\\n",
       "0          0           0           0       1     0    0                 0   \n",
       "1          0           0           0       0     0    0                 0   \n",
       "2          0           0           0       0     0    0                 0   \n",
       "3          0           0           0       0     0    0                 0   \n",
       "4          0           0           0       0     0    0                 0   \n",
       "\n",
       "   Basketball Stadium  Beach  Bed & Breakfast  Beer Bar  Beer Store  \\\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",
       "   Belgian Restaurant  Bistro  Boat or Ferry  Bookstore  Boutique  \\\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",
       "   Brazilian Restaurant  Breakfast Spot  Brewery  Bubble Tea Shop  Building  \\\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",
       "   Burger Joint  Burrito Place  Bus Line  Butcher  Cable Car  Café  \\\n",
       "0             0              0         0        0          0     0   \n",
       "1             0              0         0        0          0     0   \n",
       "2             0              0         0        0          0     0   \n",
       "3             0              0         0        0          0     0   \n",
       "4             0              0         0        0          0     0   \n",
       "\n",
       "   Cajun / Creole Restaurant  Candy Store  Caribbean Restaurant  Cheese Shop  \\\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",
       "   Chinese Restaurant  Chocolate Shop  Church  Climbing Gym  Clothing Store  \\\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",
       "   Cocktail Bar  Coffee Shop  College Arts Building  College Auditorium  \\\n",
       "0             0            0                      0                   0   \n",
       "1             0            1                      0                   0   \n",
       "2             0            0                      0                   0   \n",
       "3             0            0                      0                   0   \n",
       "4             0            0                      0                   0   \n",
       "\n",
       "   College Cafeteria  College Gym  College Rec Center  Colombian 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",
       "   Comfort Food Restaurant  Comic Shop  Concert Hall  Convenience 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",
       "   Convention Center  Cosmetics Shop  Coworking Space  Creperie  \\\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",
       "   Cuban Restaurant  Cupcake Shop  Dance Studio  Deli / Bodega  \\\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",
       "   Department Store  Dessert Shop  Diner  Discount Store  Distribution Center  \\\n",
       "0                 0             0      0               0                    0   \n",
       "1                 0             0      0               0                    0   \n",
       "2                 0             0      0               0                    1   \n",
       "3                 0             0      0               0                    0   \n",
       "4                 0             0      0               0                    0   \n",
       "\n",
       "   Dog Run  Doner Restaurant  Donut Shop  Dumpling 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",
       "   Eastern European Restaurant  Electronics Store  Ethiopian Restaurant  \\\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",
       "   Event Space  Falafel Restaurant  Farmers Market  Fast Food 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",
       "   Filipino Restaurant  Fish & Chips Shop  Fish Market  Flea Market  \\\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",
       "   Flower Shop  Food  Food & Drink Shop  Food Court  Food Truck  Fountain  \\\n",
       "0            0     0                  0           0           0         0   \n",
       "1            0     0                  0           0           0         0   \n",
       "2            0     0                  0           0           0         0   \n",
       "3            0     0                  0           0           0         0   \n",
       "4            0     0                  0           0           0         0   \n",
       "\n",
       "   French Restaurant  Fried Chicken Joint  Frozen Yogurt Shop  \\\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",
       "   Fruit & Vegetable Store  Furniture / Home Store  Gaming Cafe  Garden  \\\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",
       "   Garden Center  Gas Station  Gastropub  Gay Bar  General Entertainment  \\\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",
       "   General Travel  German Restaurant  Gift Shop  Gluten-free 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",
       "   Gourmet Shop  Greek Restaurant  Grocery Store  Gym  Gym / Fitness Center  \\\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",
       "   Harbor / Marina  Health & Beauty Service  Health Food Store  Historic Site  \\\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",
       "   History Museum  Hobby Shop  Hospital  Hotel  IT Services  Ice Cream Shop  \\\n",
       "0               0           0         0      0            0               0   \n",
       "1               0           0         0      0            0               0   \n",
       "2               0           0         0      0            0               0   \n",
       "3               0           0         0      0            0               0   \n",
       "4               0           0         0      0            0               0   \n",
       "\n",
       "   Indian Restaurant  Indie Movie Theater  Indoor Play Area  Intersection  \\\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",
       "   Irish Pub  Italian Restaurant  Japanese Restaurant  Jazz Club  \\\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",
       "   Jewelry Store  Juice Bar  Knitting Store  Korean Restaurant  Lake  \\\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",
       "   Latin American Restaurant  Light Rail Station  Lingerie 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",
       "   Liquor Store  Lounge  Mac & Cheese Joint  Market  Martial Arts Dojo  \\\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",
       "   Mediterranean Restaurant  Men's Store  Metro Station  Mexican 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",
       "   Middle Eastern Restaurant  Miscellaneous Shop  Modern European Restaurant  \\\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",
       "   Molecular Gastronomy Restaurant  Monument / Landmark  Moroccan Restaurant  \\\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",
       "   Movie Theater  Museum  Music Store  Music Venue               Neighborhood  \\\n",
       "0              0       0            0            0  Regent Park, Harbourfront   \n",
       "1              0       0            0            0  Regent Park, Harbourfront   \n",
       "2              0       0            0            0  Regent Park, Harbourfront   \n",
       "3              0       0            0            0  Regent Park, Harbourfront   \n",
       "4              0       0            0            0  Regent Park, Harbourfront   \n",
       "\n",
       "   New American Restaurant  Nightclub  Noodle House  Office  Opera House  \\\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",
       "   Optical Shop  Organic Grocery  Other Great Outdoors  Park  \\\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",
       "   Performing Arts Venue  Pet Store  Pharmacy  Pizza Place  Plane  Playground  \\\n",
       "0                      0          0         0            0      0           0   \n",
       "1                      0          0         0            0      0           0   \n",
       "2                      0          0         0            0      0           0   \n",
       "3                      0          0         0            0      0           0   \n",
       "4                      0          0         0            0      0           0   \n",
       "\n",
       "   Plaza  Poke Place  Poutine Place  Pub  Ramen Restaurant  Record Shop  \\\n",
       "0      0           0              0    0                 0            0   \n",
       "1      0           0              0    0                 0            0   \n",
       "2      0           0              0    0                 0            0   \n",
       "3      0           0              0    0                 0            0   \n",
       "4      0           0              0    0                 0            0   \n",
       "\n",
       "   Recording Studio  Rental Car Location  Restaurant  Roof Deck  Sake Bar  \\\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           1          0         0   \n",
       "\n",
       "   Salad Place  Salon / Barbershop  Sandwich Place  Scenic Lookout  \\\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",
       "   Sculpture Garden  Seafood Restaurant  Shoe Store  Shopping Mall  \\\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",
       "   Skate Park  Skating Rink  Smoke Shop  Smoothie Shop  Snack Place  \\\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",
       "   Soup Place  Spa  Speakeasy  Sporting Goods Shop  Sports Bar  Stadium  \\\n",
       "0           0    0          0                    0           0        0   \n",
       "1           0    0          0                    0           0        0   \n",
       "2           0    0          0                    0           0        0   \n",
       "3           0    1          0                    0           0        0   \n",
       "4           0    0          0                    0           0        0   \n",
       "\n",
       "   Stationery Store  Steakhouse  Strip Club  Summer Camp  Supermarket  \\\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",
       "   Supplement Shop  Sushi Restaurant  Swim School  Taco Place  Tailor Shop  \\\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",
       "   Taiwanese Restaurant  Tanning Salon  Tea Room  Tennis Court  \\\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",
       "   Thai Restaurant  Theater  Theme Restaurant  Toy / Game Store  Trail  \\\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",
       "   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  Women's 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  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "toronto_onehot = pd.get_dummies(toronto_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "toronto_onehot['Neighborhood'] = toronto_venues['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [toronto_onehot.columns[-1]] + list(toronto_onehot.columns[:-1])\n",
    "toronto_onehot = toronto_onehot[fixed_columns]\n",
    "\n",
    "toronto_onehot.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "new dataframe size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1634, 234)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_onehot.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>Yoga Studio</th>\n",
       "      <th>Airport</th>\n",
       "      <th>Airport Food Court</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>Aquarium</th>\n",
       "      <th>Art Gallery</th>\n",
       "      <th>Art Museum</th>\n",
       "      <th>Arts &amp; Crafts Store</th>\n",
       "      <th>Asian Restaurant</th>\n",
       "      <th>Auto Workshop</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Baby Store</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bakery</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Bar</th>\n",
       "      <th>Baseball Stadium</th>\n",
       "      <th>Basketball Stadium</th>\n",
       "      <th>Beach</th>\n",
       "      <th>Bed &amp; Breakfast</th>\n",
       "      <th>Beer Bar</th>\n",
       "      <th>Beer Store</th>\n",
       "      <th>Belgian Restaurant</th>\n",
       "      <th>Bistro</th>\n",
       "      <th>Boat or Ferry</th>\n",
       "      <th>Bookstore</th>\n",
       "      <th>Boutique</th>\n",
       "      <th>Brazilian Restaurant</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Bubble Tea Shop</th>\n",
       "      <th>Building</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Burrito Place</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Butcher</th>\n",
       "      <th>Cable Car</th>\n",
       "      <th>Café</th>\n",
       "      <th>Cajun / Creole Restaurant</th>\n",
       "      <th>Candy Store</th>\n",
       "      <th>Caribbean Restaurant</th>\n",
       "      <th>Cheese Shop</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Chocolate Shop</th>\n",
       "      <th>Church</th>\n",
       "      <th>Climbing Gym</th>\n",
       "      <th>Clothing Store</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Arts Building</th>\n",
       "      <th>College Auditorium</th>\n",
       "      <th>College Cafeteria</th>\n",
       "      <th>College Gym</th>\n",
       "      <th>College Rec Center</th>\n",
       "      <th>Colombian Restaurant</th>\n",
       "      <th>Comfort Food Restaurant</th>\n",
       "      <th>Comic Shop</th>\n",
       "      <th>Concert Hall</th>\n",
       "      <th>Convenience Store</th>\n",
       "      <th>Convention Center</th>\n",
       "      <th>Cosmetics Shop</th>\n",
       "      <th>Coworking Space</th>\n",
       "      <th>Creperie</th>\n",
       "      <th>Cuban Restaurant</th>\n",
       "      <th>Cupcake Shop</th>\n",
       "      <th>Dance Studio</th>\n",
       "      <th>Deli / Bodega</th>\n",
       "      <th>Department Store</th>\n",
       "      <th>Dessert Shop</th>\n",
       "      <th>Diner</th>\n",
       "      <th>Discount Store</th>\n",
       "      <th>Distribution Center</th>\n",
       "      <th>Dog Run</th>\n",
       "      <th>Doner Restaurant</th>\n",
       "      <th>Donut Shop</th>\n",
       "      <th>Dumpling Restaurant</th>\n",
       "      <th>Eastern European Restaurant</th>\n",
       "      <th>Electronics Store</th>\n",
       "      <th>Ethiopian Restaurant</th>\n",
       "      <th>Event Space</th>\n",
       "      <th>Falafel Restaurant</th>\n",
       "      <th>Farmers Market</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Filipino Restaurant</th>\n",
       "      <th>Fish &amp; Chips Shop</th>\n",
       "      <th>Fish Market</th>\n",
       "      <th>Flea Market</th>\n",
       "      <th>Flower Shop</th>\n",
       "      <th>Food</th>\n",
       "      <th>Food &amp; Drink Shop</th>\n",
       "      <th>Food Court</th>\n",
       "      <th>Food Truck</th>\n",
       "      <th>Fountain</th>\n",
       "      <th>French Restaurant</th>\n",
       "      <th>Fried Chicken Joint</th>\n",
       "      <th>Frozen Yogurt Shop</th>\n",
       "      <th>Fruit &amp; Vegetable Store</th>\n",
       "      <th>Furniture / Home Store</th>\n",
       "      <th>Gaming Cafe</th>\n",
       "      <th>Garden</th>\n",
       "      <th>Garden Center</th>\n",
       "      <th>Gas Station</th>\n",
       "      <th>Gastropub</th>\n",
       "      <th>Gay Bar</th>\n",
       "      <th>General Entertainment</th>\n",
       "      <th>General Travel</th>\n",
       "      <th>German Restaurant</th>\n",
       "      <th>Gift Shop</th>\n",
       "      <th>Gluten-free Restaurant</th>\n",
       "      <th>Gourmet Shop</th>\n",
       "      <th>Greek Restaurant</th>\n",
       "      <th>Grocery Store</th>\n",
       "      <th>Gym</th>\n",
       "      <th>Gym / Fitness Center</th>\n",
       "      <th>Harbor / Marina</th>\n",
       "      <th>Health &amp; Beauty Service</th>\n",
       "      <th>Health Food Store</th>\n",
       "      <th>Historic Site</th>\n",
       "      <th>History Museum</th>\n",
       "      <th>Hobby Shop</th>\n",
       "      <th>Hospital</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>IT Services</th>\n",
       "      <th>Ice Cream Shop</th>\n",
       "      <th>Indian Restaurant</th>\n",
       "      <th>Indie Movie Theater</th>\n",
       "      <th>Indoor Play Area</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>Irish Pub</th>\n",
       "      <th>Italian Restaurant</th>\n",
       "      <th>Japanese Restaurant</th>\n",
       "      <th>Jazz Club</th>\n",
       "      <th>Jewelry Store</th>\n",
       "      <th>Juice Bar</th>\n",
       "      <th>Knitting Store</th>\n",
       "      <th>Korean Restaurant</th>\n",
       "      <th>Lake</th>\n",
       "      <th>Latin American Restaurant</th>\n",
       "      <th>Light Rail Station</th>\n",
       "      <th>Lingerie Store</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Lounge</th>\n",
       "      <th>Mac &amp; Cheese Joint</th>\n",
       "      <th>Market</th>\n",
       "      <th>Martial Arts Dojo</th>\n",
       "      <th>Mediterranean Restaurant</th>\n",
       "      <th>Men's Store</th>\n",
       "      <th>Metro Station</th>\n",
       "      <th>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Modern European Restaurant</th>\n",
       "      <th>Molecular Gastronomy Restaurant</th>\n",
       "      <th>Monument / Landmark</th>\n",
       "      <th>Moroccan Restaurant</th>\n",
       "      <th>Movie Theater</th>\n",
       "      <th>Museum</th>\n",
       "      <th>Music Store</th>\n",
       "      <th>Music Venue</th>\n",
       "      <th>New American Restaurant</th>\n",
       "      <th>Nightclub</th>\n",
       "      <th>Noodle House</th>\n",
       "      <th>Office</th>\n",
       "      <th>Opera House</th>\n",
       "      <th>Optical Shop</th>\n",
       "      <th>Organic Grocery</th>\n",
       "      <th>Other Great Outdoors</th>\n",
       "      <th>Park</th>\n",
       "      <th>Performing Arts Venue</th>\n",
       "      <th>Pet Store</th>\n",
       "      <th>Pharmacy</th>\n",
       "      <th>Pizza Place</th>\n",
       "      <th>Plane</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Poke Place</th>\n",
       "      <th>Poutine Place</th>\n",
       "      <th>Pub</th>\n",
       "      <th>Ramen Restaurant</th>\n",
       "      <th>Record Shop</th>\n",
       "      <th>Recording Studio</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Roof Deck</th>\n",
       "      <th>Sake Bar</th>\n",
       "      <th>Salad Place</th>\n",
       "      <th>Salon / Barbershop</th>\n",
       "      <th>Sandwich Place</th>\n",
       "      <th>Scenic Lookout</th>\n",
       "      <th>Sculpture Garden</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shoe Store</th>\n",
       "      <th>Shopping Mall</th>\n",
       "      <th>Skate Park</th>\n",
       "      <th>Skating Rink</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>Smoothie Shop</th>\n",
       "      <th>Snack Place</th>\n",
       "      <th>Soup Place</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Speakeasy</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Sports Bar</th>\n",
       "      <th>Stadium</th>\n",
       "      <th>Stationery Store</th>\n",
       "      <th>Steakhouse</th>\n",
       "      <th>Strip Club</th>\n",
       "      <th>Summer Camp</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Supplement Shop</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Taco Place</th>\n",
       "      <th>Tailor Shop</th>\n",
       "      <th>Taiwanese Restaurant</th>\n",
       "      <th>Tanning Salon</th>\n",
       "      <th>Tea Room</th>\n",
       "      <th>Tennis Court</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</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>Women's Store</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>0.045455</td>\n",
       "      <td>0.045455</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.045455</td>\n",
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       "      <td>0.045455</td>\n",
       "      <td>0.045455</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.045455</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.045455</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>0.000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.125</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.060606</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.015152</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood  Yoga Studio  Airport  \\\n",
       "0                                        Berczy Park     0.000000   0.0000   \n",
       "1       Brockton, Parkdale Village, Exhibition Place     0.000000   0.0000   \n",
       "2  Business reply mail Processing Centre, South C...     0.000000   0.0000   \n",
       "3  CN Tower, King and Spadina, Railway Lands, Har...     0.000000   0.0625   \n",
       "4                                 Central Bay Street     0.015152   0.0000   \n",
       "\n",
       "   Airport Food Court  Airport Lounge  Airport Service  Airport Terminal  \\\n",
       "0              0.0000           0.000            0.000             0.000   \n",
       "1              0.0000           0.000            0.000             0.000   \n",
       "2              0.0000           0.000            0.000             0.000   \n",
       "3              0.0625           0.125            0.125             0.125   \n",
       "4              0.0000           0.000            0.000             0.000   \n",
       "\n",
       "   American Restaurant  Antique Shop  Aquarium  Art Gallery  Art Museum  \\\n",
       "0                  0.0           0.0       0.0     0.017544    0.000000   \n",
       "1                  0.0           0.0       0.0     0.000000    0.000000   \n",
       "2                  0.0           0.0       0.0     0.000000    0.000000   \n",
       "3                  0.0           0.0       0.0     0.000000    0.000000   \n",
       "4                  0.0           0.0       0.0     0.000000    0.015152   \n",
       "\n",
       "   Arts & Crafts Store  Asian Restaurant  Auto Workshop  BBQ Joint  \\\n",
       "0                  0.0               0.0         0.0000   0.017544   \n",
       "1                  0.0               0.0         0.0000   0.000000   \n",
       "2                  0.0               0.0         0.0625   0.000000   \n",
       "3                  0.0               0.0         0.0000   0.000000   \n",
       "4                  0.0               0.0         0.0000   0.000000   \n",
       "\n",
       "   Baby Store  Bagel Shop    Bakery  Bank       Bar  Baseball Stadium  \\\n",
       "0         0.0    0.017544  0.035088   0.0  0.000000               0.0   \n",
       "1         0.0    0.000000  0.045455   0.0  0.045455               0.0   \n",
       "2         0.0    0.000000  0.000000   0.0  0.000000               0.0   \n",
       "3         0.0    0.000000  0.000000   0.0  0.062500               0.0   \n",
       "4         0.0    0.000000  0.000000   0.0  0.030303               0.0   \n",
       "\n",
       "   Basketball Stadium     Beach  Bed & Breakfast  Beer Bar  Beer Store  \\\n",
       "0            0.017544  0.017544              0.0  0.035088         0.0   \n",
       "1            0.000000  0.000000              0.0  0.000000         0.0   \n",
       "2            0.000000  0.000000              0.0  0.000000         0.0   \n",
       "3            0.000000  0.000000              0.0  0.000000         0.0   \n",
       "4            0.000000  0.000000              0.0  0.000000         0.0   \n",
       "\n",
       "   Belgian Restaurant    Bistro  Boat or Ferry  Bookstore  Boutique  \\\n",
       "0                 0.0  0.017544         0.0000        0.0    0.0000   \n",
       "1                 0.0  0.000000         0.0000        0.0    0.0000   \n",
       "2                 0.0  0.000000         0.0000        0.0    0.0000   \n",
       "3                 0.0  0.000000         0.0625        0.0    0.0625   \n",
       "4                 0.0  0.000000         0.0000        0.0    0.0000   \n",
       "\n",
       "   Brazilian Restaurant  Breakfast Spot  Brewery  Bubble Tea Shop  Building  \\\n",
       "0                   0.0        0.017544   0.0000         0.000000       0.0   \n",
       "1                   0.0        0.090909   0.0000         0.000000       0.0   \n",
       "2                   0.0        0.000000   0.0625         0.000000       0.0   \n",
       "3                   0.0        0.000000   0.0000         0.000000       0.0   \n",
       "4                   0.0        0.000000   0.0000         0.030303       0.0   \n",
       "\n",
       "   Burger Joint  Burrito Place  Bus Line  Butcher  Cable Car      Café  \\\n",
       "0      0.000000       0.000000       0.0      0.0        0.0  0.035088   \n",
       "1      0.000000       0.045455       0.0      0.0        0.0  0.136364   \n",
       "2      0.000000       0.062500       0.0      0.0        0.0  0.000000   \n",
       "3      0.000000       0.000000       0.0      0.0        0.0  0.000000   \n",
       "4      0.030303       0.000000       0.0      0.0        0.0  0.045455   \n",
       "\n",
       "   Cajun / Creole Restaurant  Candy Store  Caribbean Restaurant  Cheese Shop  \\\n",
       "0                        0.0          0.0                   0.0     0.035088   \n",
       "1                        0.0          0.0                   0.0     0.000000   \n",
       "2                        0.0          0.0                   0.0     0.000000   \n",
       "3                        0.0          0.0                   0.0     0.000000   \n",
       "4                        0.0          0.0                   0.0     0.000000   \n",
       "\n",
       "   Chinese Restaurant  Chocolate Shop  Church  Climbing Gym  Clothing Store  \\\n",
       "0                 0.0             0.0     0.0      0.000000             0.0   \n",
       "1                 0.0             0.0     0.0      0.045455             0.0   \n",
       "2                 0.0             0.0     0.0      0.000000             0.0   \n",
       "3                 0.0             0.0     0.0      0.000000             0.0   \n",
       "4                 0.0             0.0     0.0      0.000000             0.0   \n",
       "\n",
       "   Cocktail Bar  Coffee Shop  College Arts Building  College Auditorium  \\\n",
       "0      0.052632     0.070175                    0.0                 0.0   \n",
       "1      0.000000     0.090909                    0.0                 0.0   \n",
       "2      0.000000     0.000000                    0.0                 0.0   \n",
       "3      0.000000     0.062500                    0.0                 0.0   \n",
       "4      0.000000     0.166667                    0.0                 0.0   \n",
       "\n",
       "   College Cafeteria  College Gym  College Rec Center  Colombian Restaurant  \\\n",
       "0                0.0          0.0                 0.0                   0.0   \n",
       "1                0.0          0.0                 0.0                   0.0   \n",
       "2                0.0          0.0                 0.0                   0.0   \n",
       "3                0.0          0.0                 0.0                   0.0   \n",
       "4                0.0          0.0                 0.0                   0.0   \n",
       "\n",
       "   Comfort Food Restaurant  Comic Shop  Concert Hall  Convenience Store  \\\n",
       "0                 0.017544    0.000000      0.017544           0.000000   \n",
       "1                 0.000000    0.000000      0.000000           0.045455   \n",
       "2                 0.000000    0.062500      0.000000           0.000000   \n",
       "3                 0.000000    0.000000      0.000000           0.000000   \n",
       "4                 0.000000    0.015152      0.000000           0.000000   \n",
       "\n",
       "   Convention Center  Cosmetics Shop  Coworking Space  Creperie  \\\n",
       "0                0.0             0.0              0.0  0.017544   \n",
       "1                0.0             0.0              0.0  0.000000   \n",
       "2                0.0             0.0              0.0  0.000000   \n",
       "3                0.0             0.0              0.0  0.000000   \n",
       "4                0.0             0.0              0.0  0.000000   \n",
       "\n",
       "   Cuban Restaurant  Cupcake Shop  Dance Studio  Deli / Bodega  \\\n",
       "0               0.0           0.0           0.0            0.0   \n",
       "1               0.0           0.0           0.0            0.0   \n",
       "2               0.0           0.0           0.0            0.0   \n",
       "3               0.0           0.0           0.0            0.0   \n",
       "4               0.0           0.0           0.0            0.0   \n",
       "\n",
       "   Department Store  Dessert Shop     Diner  Discount Store  \\\n",
       "0          0.017544      0.000000  0.017544        0.000000   \n",
       "1          0.000000      0.000000  0.000000        0.000000   \n",
       "2          0.000000      0.000000  0.000000        0.000000   \n",
       "3          0.000000      0.000000  0.000000        0.000000   \n",
       "4          0.030303      0.015152  0.015152        0.015152   \n",
       "\n",
       "   Distribution Center  Dog Run  Doner Restaurant  Donut Shop  \\\n",
       "0                  0.0      0.0               0.0    0.000000   \n",
       "1                  0.0      0.0               0.0    0.000000   \n",
       "2                  0.0      0.0               0.0    0.000000   \n",
       "3                  0.0      0.0               0.0    0.000000   \n",
       "4                  0.0      0.0               0.0    0.015152   \n",
       "\n",
       "   Dumpling Restaurant  Eastern European Restaurant  Electronics Store  \\\n",
       "0                  0.0                     0.017544                0.0   \n",
       "1                  0.0                     0.000000                0.0   \n",
       "2                  0.0                     0.000000                0.0   \n",
       "3                  0.0                     0.000000                0.0   \n",
       "4                  0.0                     0.000000                0.0   \n",
       "\n",
       "   Ethiopian Restaurant  Event Space  Falafel Restaurant  Farmers Market  \\\n",
       "0                   0.0          0.0            0.000000        0.035088   \n",
       "1                   0.0          0.0            0.000000        0.000000   \n",
       "2                   0.0          0.0            0.000000        0.062500   \n",
       "3                   0.0          0.0            0.000000        0.000000   \n",
       "4                   0.0          0.0            0.015152        0.000000   \n",
       "\n",
       "   Fast Food Restaurant  Filipino Restaurant  Fish & Chips Shop  Fish Market  \\\n",
       "0                0.0000                  0.0                0.0     0.017544   \n",
       "1                0.0000                  0.0                0.0     0.000000   \n",
       "2                0.0625                  0.0                0.0     0.000000   \n",
       "3                0.0000                  0.0                0.0     0.000000   \n",
       "4                0.0000                  0.0                0.0     0.000000   \n",
       "\n",
       "   Flea Market  Flower Shop  Food  Food & Drink Shop  Food Court  Food Truck  \\\n",
       "0          0.0          0.0   0.0                0.0         0.0         0.0   \n",
       "1          0.0          0.0   0.0                0.0         0.0         0.0   \n",
       "2          0.0          0.0   0.0                0.0         0.0         0.0   \n",
       "3          0.0          0.0   0.0                0.0         0.0         0.0   \n",
       "4          0.0          0.0   0.0                0.0         0.0         0.0   \n",
       "\n",
       "   Fountain  French Restaurant  Fried Chicken Joint  Frozen Yogurt Shop  \\\n",
       "0  0.017544           0.017544                  0.0                 0.0   \n",
       "1  0.000000           0.000000                  0.0                 0.0   \n",
       "2  0.000000           0.000000                  0.0                 0.0   \n",
       "3  0.000000           0.000000                  0.0                 0.0   \n",
       "4  0.000000           0.015152                  0.0                 0.0   \n",
       "\n",
       "   Fruit & Vegetable Store  Furniture / Home Store  Gaming Cafe  Garden  \\\n",
       "0                      0.0                0.000000          0.0  0.0000   \n",
       "1                      0.0                0.045455          0.0  0.0000   \n",
       "2                      0.0                0.000000          0.0  0.0625   \n",
       "3                      0.0                0.000000          0.0  0.0000   \n",
       "4                      0.0                0.015152          0.0  0.0000   \n",
       "\n",
       "   Garden Center  Gas Station  Gastropub  Gay Bar  General Entertainment  \\\n",
       "0         0.0000          0.0   0.000000      0.0                    0.0   \n",
       "1         0.0000          0.0   0.000000      0.0                    0.0   \n",
       "2         0.0625          0.0   0.000000      0.0                    0.0   \n",
       "3         0.0000          0.0   0.000000      0.0                    0.0   \n",
       "4         0.0000          0.0   0.015152      0.0                    0.0   \n",
       "\n",
       "   General Travel  German Restaurant  Gift Shop  Gluten-free Restaurant  \\\n",
       "0             0.0                0.0        0.0                     0.0   \n",
       "1             0.0                0.0        0.0                     0.0   \n",
       "2             0.0                0.0        0.0                     0.0   \n",
       "3             0.0                0.0        0.0                     0.0   \n",
       "4             0.0                0.0        0.0                     0.0   \n",
       "\n",
       "   Gourmet Shop  Greek Restaurant  Grocery Store       Gym  \\\n",
       "0      0.017544          0.017544       0.017544  0.000000   \n",
       "1      0.000000          0.000000       0.045455  0.045455   \n",
       "2      0.000000          0.000000       0.000000  0.000000   \n",
       "3      0.000000          0.000000       0.000000  0.000000   \n",
       "4      0.000000          0.000000       0.000000  0.000000   \n",
       "\n",
       "   Gym / Fitness Center  Harbor / Marina  Health & Beauty Service  \\\n",
       "0              0.000000           0.0000                      0.0   \n",
       "1              0.000000           0.0000                      0.0   \n",
       "2              0.000000           0.0000                      0.0   \n",
       "3              0.000000           0.0625                      0.0   \n",
       "4              0.015152           0.0000                      0.0   \n",
       "\n",
       "   Health Food Store  Historic Site  History Museum  Hobby Shop  Hospital  \\\n",
       "0                0.0            0.0             0.0         0.0       0.0   \n",
       "1                0.0            0.0             0.0         0.0       0.0   \n",
       "2                0.0            0.0             0.0         0.0       0.0   \n",
       "3                0.0            0.0             0.0         0.0       0.0   \n",
       "4                0.0            0.0             0.0         0.0       0.0   \n",
       "\n",
       "      Hotel  IT Services  Ice Cream Shop  Indian Restaurant  \\\n",
       "0  0.017544          0.0        0.000000           0.017544   \n",
       "1  0.000000          0.0        0.000000           0.000000   \n",
       "2  0.000000          0.0        0.000000           0.000000   \n",
       "3  0.000000          0.0        0.000000           0.000000   \n",
       "4  0.015152          0.0        0.015152           0.015152   \n",
       "\n",
       "   Indie Movie Theater  Indoor Play Area  Intersection  Irish Pub  \\\n",
       "0                  0.0               0.0      0.000000   0.017544   \n",
       "1                  0.0               0.0      0.045455   0.000000   \n",
       "2                  0.0               0.0      0.000000   0.000000   \n",
       "3                  0.0               0.0      0.000000   0.000000   \n",
       "4                  0.0               0.0      0.000000   0.000000   \n",
       "\n",
       "   Italian Restaurant  Japanese Restaurant  Jazz Club  Jewelry Store  \\\n",
       "0            0.000000             0.017544   0.017544            0.0   \n",
       "1            0.045455             0.000000   0.000000            0.0   \n",
       "2            0.000000             0.000000   0.000000            0.0   \n",
       "3            0.000000             0.000000   0.000000            0.0   \n",
       "4            0.060606             0.045455   0.000000            0.0   \n",
       "\n",
       "   Juice Bar  Knitting Store  Korean Restaurant  Lake  \\\n",
       "0        0.0             0.0           0.000000   0.0   \n",
       "1        0.0             0.0           0.000000   0.0   \n",
       "2        0.0             0.0           0.000000   0.0   \n",
       "3        0.0             0.0           0.000000   0.0   \n",
       "4        0.0             0.0           0.015152   0.0   \n",
       "\n",
       "   Latin American Restaurant  Light Rail Station  Lingerie Store  \\\n",
       "0                        0.0               0.000             0.0   \n",
       "1                        0.0               0.000             0.0   \n",
       "2                        0.0               0.125             0.0   \n",
       "3                        0.0               0.000             0.0   \n",
       "4                        0.0               0.000             0.0   \n",
       "\n",
       "   Liquor Store  Lounge  Mac & Cheese Joint  Market  Martial Arts Dojo  \\\n",
       "0      0.017544     0.0                 0.0     0.0                0.0   \n",
       "1      0.000000     0.0                 0.0     0.0                0.0   \n",
       "2      0.000000     0.0                 0.0     0.0                0.0   \n",
       "3      0.000000     0.0                 0.0     0.0                0.0   \n",
       "4      0.000000     0.0                 0.0     0.0                0.0   \n",
       "\n",
       "   Mediterranean Restaurant  Men's Store  Metro Station  Mexican Restaurant  \\\n",
       "0                       0.0          0.0            0.0                 0.0   \n",
       "1                       0.0          0.0            0.0                 0.0   \n",
       "2                       0.0          0.0            0.0                 0.0   \n",
       "3                       0.0          0.0            0.0                 0.0   \n",
       "4                       0.0          0.0            0.0                 0.0   \n",
       "\n",
       "   Middle Eastern Restaurant  Miscellaneous Shop  Modern European Restaurant  \\\n",
       "0                   0.000000            0.000000                    0.000000   \n",
       "1                   0.000000            0.000000                    0.000000   \n",
       "2                   0.000000            0.000000                    0.000000   \n",
       "3                   0.000000            0.000000                    0.000000   \n",
       "4                   0.015152            0.015152                    0.015152   \n",
       "\n",
       "   Molecular Gastronomy Restaurant  Monument / Landmark  Moroccan Restaurant  \\\n",
       "0                              0.0                  0.0                  0.0   \n",
       "1                              0.0                  0.0                  0.0   \n",
       "2                              0.0                  0.0                  0.0   \n",
       "3                              0.0                  0.0                  0.0   \n",
       "4                              0.0                  0.0                  0.0   \n",
       "\n",
       "   Movie Theater    Museum  Music Store  Music Venue  New American Restaurant  \\\n",
       "0            0.0  0.017544          0.0          0.0                 0.000000   \n",
       "1            0.0  0.000000          0.0          0.0                 0.000000   \n",
       "2            0.0  0.000000          0.0          0.0                 0.000000   \n",
       "3            0.0  0.000000          0.0          0.0                 0.000000   \n",
       "4            0.0  0.000000          0.0          0.0                 0.015152   \n",
       "\n",
       "   Nightclub  Noodle House    Office  Opera House  Optical Shop  \\\n",
       "0   0.017544           0.0  0.000000          0.0           0.0   \n",
       "1   0.045455           0.0  0.000000          0.0           0.0   \n",
       "2   0.000000           0.0  0.000000          0.0           0.0   \n",
       "3   0.000000           0.0  0.000000          0.0           0.0   \n",
       "4   0.000000           0.0  0.015152          0.0           0.0   \n",
       "\n",
       "   Organic Grocery  Other Great Outdoors      Park  Performing Arts Venue  \\\n",
       "0              0.0                   0.0  0.017544               0.000000   \n",
       "1              0.0                   0.0  0.000000               0.045455   \n",
       "2              0.0                   0.0  0.062500               0.000000   \n",
       "3              0.0                   0.0  0.000000               0.000000   \n",
       "4              0.0                   0.0  0.015152               0.000000   \n",
       "\n",
       "   Pet Store  Pharmacy  Pizza Place   Plane  Playground  Plaza  Poke Place  \\\n",
       "0   0.000000  0.035088     0.000000  0.0000         0.0    0.0    0.000000   \n",
       "1   0.045455  0.000000     0.000000  0.0000         0.0    0.0    0.000000   \n",
       "2   0.000000  0.000000     0.062500  0.0000         0.0    0.0    0.000000   \n",
       "3   0.000000  0.000000     0.000000  0.0625         0.0    0.0    0.000000   \n",
       "4   0.000000  0.000000     0.015152  0.0000         0.0    0.0    0.015152   \n",
       "\n",
       "   Poutine Place  Pub  Ramen Restaurant  Record Shop  Recording Studio  \\\n",
       "0            0.0  0.0          0.000000          0.0            0.0000   \n",
       "1            0.0  0.0          0.000000          0.0            0.0000   \n",
       "2            0.0  0.0          0.000000          0.0            0.0625   \n",
       "3            0.0  0.0          0.000000          0.0            0.0000   \n",
       "4            0.0  0.0          0.015152          0.0            0.0000   \n",
       "\n",
       "   Rental Car Location  Restaurant  Roof Deck  Sake Bar  Salad Place  \\\n",
       "0               0.0000    0.035088        0.0       0.0     0.000000   \n",
       "1               0.0000    0.045455        0.0       0.0     0.000000   \n",
       "2               0.0000    0.062500        0.0       0.0     0.000000   \n",
       "3               0.0625    0.000000        0.0       0.0     0.000000   \n",
       "4               0.0000    0.000000        0.0       0.0     0.030303   \n",
       "\n",
       "   Salon / Barbershop  Sandwich Place  Scenic Lookout  Sculpture Garden  \\\n",
       "0                 0.0        0.000000             0.0            0.0000   \n",
       "1                 0.0        0.000000             0.0            0.0000   \n",
       "2                 0.0        0.000000             0.0            0.0000   \n",
       "3                 0.0        0.000000             0.0            0.0625   \n",
       "4                 0.0        0.045455             0.0            0.0000   \n",
       "\n",
       "   Seafood Restaurant  Shoe Store  Shopping Mall  Skate Park  Skating Rink  \\\n",
       "0            0.035088         0.0       0.017544      0.0000           0.0   \n",
       "1            0.000000         0.0       0.000000      0.0000           0.0   \n",
       "2            0.000000         0.0       0.000000      0.0625           0.0   \n",
       "3            0.000000         0.0       0.000000      0.0000           0.0   \n",
       "4            0.015152         0.0       0.000000      0.0000           0.0   \n",
       "\n",
       "   Smoke Shop  Smoothie Shop  Snack Place  Soup Place       Spa  Speakeasy  \\\n",
       "0         0.0            0.0          0.0         0.0  0.000000        0.0   \n",
       "1         0.0            0.0          0.0         0.0  0.000000        0.0   \n",
       "2         0.0            0.0          0.0         0.0  0.062500        0.0   \n",
       "3         0.0            0.0          0.0         0.0  0.000000        0.0   \n",
       "4         0.0            0.0          0.0         0.0  0.015152        0.0   \n",
       "\n",
       "   Sporting Goods Shop  Sports Bar   Stadium  Stationery Store  Steakhouse  \\\n",
       "0             0.017544         0.0  0.000000               0.0    0.017544   \n",
       "1             0.000000         0.0  0.045455               0.0    0.000000   \n",
       "2             0.000000         0.0  0.000000               0.0    0.000000   \n",
       "3             0.000000         0.0  0.000000               0.0    0.000000   \n",
       "4             0.000000         0.0  0.000000               0.0    0.000000   \n",
       "\n",
       "   Strip Club  Summer Camp  Supermarket  Supplement Shop  Sushi Restaurant  \\\n",
       "0         0.0          0.0          0.0              0.0          0.000000   \n",
       "1         0.0          0.0          0.0              0.0          0.000000   \n",
       "2         0.0          0.0          0.0              0.0          0.000000   \n",
       "3         0.0          0.0          0.0              0.0          0.000000   \n",
       "4         0.0          0.0          0.0              0.0          0.015152   \n",
       "\n",
       "   Swim School  Taco Place  Tailor Shop  Taiwanese Restaurant  Tanning Salon  \\\n",
       "0          0.0         0.0     0.017544                   0.0            0.0   \n",
       "1          0.0         0.0     0.000000                   0.0            0.0   \n",
       "2          0.0         0.0     0.000000                   0.0            0.0   \n",
       "3          0.0         0.0     0.000000                   0.0            0.0   \n",
       "4          0.0         0.0     0.000000                   0.0            0.0   \n",
       "\n",
       "   Tea Room  Tennis Court  Thai Restaurant  Theater  Theme Restaurant  \\\n",
       "0       0.0           0.0         0.017544      0.0               0.0   \n",
       "1       0.0           0.0         0.000000      0.0               0.0   \n",
       "2       0.0           0.0         0.000000      0.0               0.0   \n",
       "3       0.0           0.0         0.000000      0.0               0.0   \n",
       "4       0.0           0.0         0.030303      0.0               0.0   \n",
       "\n",
       "   Toy / Game Store  Trail  Train Station  Vegetarian / Vegan Restaurant  \\\n",
       "0               0.0    0.0            0.0                       0.017544   \n",
       "1               0.0    0.0            0.0                       0.000000   \n",
       "2               0.0    0.0            0.0                       0.000000   \n",
       "3               0.0    0.0            0.0                       0.000000   \n",
       "4               0.0    0.0            0.0                       0.015152   \n",
       "\n",
       "   Video Game Store  Vietnamese Restaurant  Wine Bar  Women's Store  \n",
       "0               0.0                    0.0  0.000000            0.0  \n",
       "1               0.0                    0.0  0.000000            0.0  \n",
       "2               0.0                    0.0  0.000000            0.0  \n",
       "3               0.0                    0.0  0.000000            0.0  \n",
       "4               0.0                    0.0  0.015152            0.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_onehot_grouped = toronto_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "toronto_onehot_grouped.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's confirm the new size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(39, 234)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_onehot_grouped.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Let's print each neighborhood along with the top 5 most common venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----Berczy Park----\n",
      "            venue  freq\n",
      "0     Coffee Shop  0.07\n",
      "1    Cocktail Bar  0.05\n",
      "2        Pharmacy  0.04\n",
      "3        Beer Bar  0.04\n",
      "4  Farmers Market  0.04\n",
      "\n",
      "\n",
      "----Brockton, Parkdale Village, Exhibition Place----\n",
      "            venue  freq\n",
      "0            Café  0.14\n",
      "1  Breakfast Spot  0.09\n",
      "2     Coffee Shop  0.09\n",
      "3          Bakery  0.05\n",
      "4       Pet Store  0.05\n",
      "\n",
      "\n",
      "----Business reply mail Processing Centre, South Central Letter Processing Plant Toronto----\n",
      "                venue  freq\n",
      "0  Light Rail Station  0.12\n",
      "1          Comic Shop  0.06\n",
      "2    Recording Studio  0.06\n",
      "3             Brewery  0.06\n",
      "4       Burrito Place  0.06\n",
      "\n",
      "\n",
      "----CN Tower, King and Spadina, Railway Lands, Harbourfront West, Bathurst Quay, South Niagara, Island airport----\n",
      "              venue  freq\n",
      "0    Airport Lounge  0.12\n",
      "1   Airport Service  0.12\n",
      "2  Airport Terminal  0.12\n",
      "3             Plane  0.06\n",
      "4     Boat or Ferry  0.06\n",
      "\n",
      "\n",
      "----Central Bay Street----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.17\n",
      "1   Italian Restaurant  0.06\n",
      "2       Sandwich Place  0.05\n",
      "3                 Café  0.05\n",
      "4  Japanese Restaurant  0.05\n",
      "\n",
      "\n",
      "----Christie----\n",
      "           venue  freq\n",
      "0  Grocery Store  0.25\n",
      "1           Café  0.19\n",
      "2           Park  0.12\n",
      "3          Diner  0.06\n",
      "4    Coffee Shop  0.06\n",
      "\n",
      "\n",
      "----Church and Wellesley----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.10\n",
      "1  Japanese Restaurant  0.06\n",
      "2     Sushi Restaurant  0.06\n",
      "3           Restaurant  0.04\n",
      "4              Gay Bar  0.04\n",
      "\n",
      "\n",
      "----Commerce Court, Victoria Hotel----\n",
      "         venue  freq\n",
      "0  Coffee Shop  0.13\n",
      "1   Restaurant  0.07\n",
      "2         Café  0.07\n",
      "3        Hotel  0.06\n",
      "4          Gym  0.04\n",
      "\n",
      "\n",
      "----Davisville----\n",
      "                venue  freq\n",
      "0         Pizza Place  0.09\n",
      "1        Dessert Shop  0.09\n",
      "2      Sandwich Place  0.09\n",
      "3                 Gym  0.06\n",
      "4  Italian Restaurant  0.06\n",
      "\n",
      "\n",
      "----Davisville North----\n",
      "                  venue  freq\n",
      "0           Pizza Place  0.11\n",
      "1      Department Store  0.11\n",
      "2  Gym / Fitness Center  0.11\n",
      "3                  Park  0.11\n",
      "4        Breakfast Spot  0.11\n",
      "\n",
      "\n",
      "----Dufferin, Dovercourt Village----\n",
      "         venue  freq\n",
      "0     Pharmacy  0.12\n",
      "1       Bakery  0.12\n",
      "2    Pet Store  0.06\n",
      "3  Music Venue  0.06\n",
      "4      Brewery  0.06\n",
      "\n",
      "\n",
      "----First Canadian Place, Underground city----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.10\n",
      "1                 Café  0.08\n",
      "2                Hotel  0.05\n",
      "3           Restaurant  0.04\n",
      "4  Japanese Restaurant  0.04\n",
      "\n",
      "\n",
      "----Forest Hill North & West, Forest Hill Road Park----\n",
      "              venue  freq\n",
      "0              Park  0.25\n",
      "1             Trail  0.25\n",
      "2     Jewelry Store  0.25\n",
      "3  Sushi Restaurant  0.25\n",
      "4       Yoga Studio  0.00\n",
      "\n",
      "\n",
      "----Garden District, Ryerson----\n",
      "                venue  freq\n",
      "0      Clothing Store  0.10\n",
      "1         Coffee Shop  0.09\n",
      "2      Cosmetics Shop  0.03\n",
      "3               Hotel  0.03\n",
      "4  Italian Restaurant  0.03\n",
      "\n",
      "\n",
      "----Harbourfront East, Union Station, Toronto Islands----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.13\n",
      "1             Aquarium  0.05\n",
      "2                 Café  0.04\n",
      "3                Hotel  0.04\n",
      "4  Fried Chicken Joint  0.03\n",
      "\n",
      "\n",
      "----High Park, The Junction South----\n",
      "                       venue  freq\n",
      "0         Mexican Restaurant  0.08\n",
      "1            Thai Restaurant  0.08\n",
      "2                       Café  0.08\n",
      "3  Cajun / Creole Restaurant  0.04\n",
      "4                Flea Market  0.04\n",
      "\n",
      "\n",
      "----India Bazaar, The Beaches West----\n",
      "              venue  freq\n",
      "0       Pizza Place  0.09\n",
      "1    Sandwich Place  0.09\n",
      "2              Park  0.09\n",
      "3               Gym  0.05\n",
      "4  Sushi Restaurant  0.05\n",
      "\n",
      "\n",
      "----Kensington Market, Chinatown, Grange Park----\n",
      "                   venue  freq\n",
      "0                   Café  0.08\n",
      "1            Coffee Shop  0.06\n",
      "2  Vietnamese Restaurant  0.05\n",
      "3                    Bar  0.05\n",
      "4           Dessert Shop  0.05\n",
      "\n",
      "\n",
      "----Lawrence Park----\n",
      "                 venue  freq\n",
      "0                 Park  0.50\n",
      "1             Bus Line  0.25\n",
      "2          Swim School  0.25\n",
      "3          Yoga Studio  0.00\n",
      "4  Moroccan Restaurant  0.00\n",
      "\n",
      "\n",
      "----Little Portugal, Trinity----\n",
      "                           venue  freq\n",
      "0                            Bar  0.09\n",
      "1                     Restaurant  0.05\n",
      "2          Vietnamese Restaurant  0.05\n",
      "3  Vegetarian / Vegan Restaurant  0.05\n",
      "4                    Men's Store  0.05\n",
      "\n",
      "\n",
      "----Moore Park, Summerhill East----\n",
      "           venue  freq\n",
      "0     Playground  0.33\n",
      "1    Summer Camp  0.33\n",
      "2   Tennis Court  0.33\n",
      "3    Yoga Studio  0.00\n",
      "4  Movie Theater  0.00\n",
      "\n",
      "\n",
      "----North Toronto West, Lawrence Park----\n",
      "                 venue  freq\n",
      "0       Clothing Store  0.15\n",
      "1          Coffee Shop  0.10\n",
      "2          Yoga Studio  0.05\n",
      "3  Rental Car Location  0.05\n",
      "4        Metro Station  0.05\n",
      "\n",
      "\n",
      "----Parkdale, Roncesvalles----\n",
      "                         venue  freq\n",
      "0                    Gift Shop  0.14\n",
      "1               Breakfast Spot  0.14\n",
      "2                 Dessert Shop  0.07\n",
      "3  Eastern European Restaurant  0.07\n",
      "4                Movie Theater  0.07\n",
      "\n",
      "\n",
      "----Queen's Park, Ontario Provincial Government----\n",
      "               venue  freq\n",
      "0        Coffee Shop  0.29\n",
      "1  College Cafeteria  0.06\n",
      "2              Diner  0.06\n",
      "3        Yoga Studio  0.03\n",
      "4           Beer Bar  0.03\n",
      "\n",
      "\n",
      "----Regent Park, Harbourfront----\n",
      "         venue  freq\n",
      "0  Coffee Shop  0.16\n",
      "1         Park  0.07\n",
      "2       Bakery  0.07\n",
      "3          Pub  0.05\n",
      "4         Café  0.05\n",
      "\n",
      "\n",
      "----Richmond, Adelaide, King----\n",
      "            venue  freq\n",
      "0     Coffee Shop  0.09\n",
      "1            Café  0.05\n",
      "2      Restaurant  0.04\n",
      "3           Hotel  0.04\n",
      "4  Clothing Store  0.04\n",
      "\n",
      "\n",
      "----Rosedale----\n",
      "           venue  freq\n",
      "0           Park  0.50\n",
      "1     Playground  0.25\n",
      "2          Trail  0.25\n",
      "3    Yoga Studio  0.00\n",
      "4  Movie Theater  0.00\n",
      "\n",
      "\n",
      "----Roselawn----\n",
      "                      venue  freq\n",
      "0                    Garden   1.0\n",
      "1                    Museum   0.0\n",
      "2         Martial Arts Dojo   0.0\n",
      "3  Mediterranean Restaurant   0.0\n",
      "4               Men's Store   0.0\n",
      "\n",
      "\n",
      "----Runnymede, Swansea----\n",
      "                venue  freq\n",
      "0                Café  0.08\n",
      "1         Coffee Shop  0.08\n",
      "2  Italian Restaurant  0.05\n",
      "3            Tea Room  0.05\n",
      "4    Sushi Restaurant  0.05\n",
      "\n",
      "\n",
      "----St. James Town----\n",
      "            venue  freq\n",
      "0            Café  0.06\n",
      "1     Coffee Shop  0.06\n",
      "2      Restaurant  0.06\n",
      "3  Clothing Store  0.05\n",
      "4  Cosmetics Shop  0.03\n",
      "\n",
      "\n",
      "----St. James Town, Cabbagetown----\n",
      "         venue  freq\n",
      "0  Coffee Shop  0.07\n",
      "1       Market  0.04\n",
      "2    Pet Store  0.04\n",
      "3  Pizza Place  0.04\n",
      "4          Pub  0.04\n",
      "\n",
      "\n",
      "----Stn A PO Boxes----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.10\n",
      "1                 Café  0.04\n",
      "2  Japanese Restaurant  0.03\n",
      "3   Seafood Restaurant  0.03\n",
      "4                Hotel  0.03\n",
      "\n",
      "\n",
      "----Studio District----\n",
      "                 venue  freq\n",
      "0                 Café  0.10\n",
      "1          Coffee Shop  0.07\n",
      "2              Brewery  0.05\n",
      "3  American Restaurant  0.05\n",
      "4            Gastropub  0.05\n",
      "\n",
      "\n",
      "----Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park----\n",
      "                venue  freq\n",
      "0                 Pub  0.12\n",
      "1         Coffee Shop  0.12\n",
      "2        Liquor Store  0.06\n",
      "3  Light Rail Station  0.06\n",
      "4          Sports Bar  0.06\n",
      "\n",
      "\n",
      "----The Annex, North Midtown, Yorkville----\n",
      "               venue  freq\n",
      "0               Café  0.15\n",
      "1     Sandwich Place  0.15\n",
      "2        Coffee Shop  0.10\n",
      "3           Pharmacy  0.05\n",
      "4  Indian Restaurant  0.05\n",
      "\n",
      "\n",
      "----The Beaches----\n",
      "               venue  freq\n",
      "0  Health Food Store  0.25\n",
      "1              Trail  0.25\n",
      "2                Pub  0.25\n",
      "3        Yoga Studio  0.00\n",
      "4             Museum  0.00\n",
      "\n",
      "\n",
      "----The Danforth West, Riverdale----\n",
      "                    venue  freq\n",
      "0        Greek Restaurant  0.19\n",
      "1             Coffee Shop  0.07\n",
      "2      Italian Restaurant  0.07\n",
      "3  Furniture / Home Store  0.05\n",
      "4          Ice Cream Shop  0.05\n",
      "\n",
      "\n",
      "----Toronto Dominion Centre, Design Exchange----\n",
      "                venue  freq\n",
      "0         Coffee Shop  0.13\n",
      "1               Hotel  0.08\n",
      "2                Café  0.06\n",
      "3          Restaurant  0.04\n",
      "4  Seafood Restaurant  0.03\n",
      "\n",
      "\n",
      "----University of Toronto, Harbord----\n",
      "            venue  freq\n",
      "0            Café  0.17\n",
      "1  Sandwich Place  0.06\n",
      "2      Restaurant  0.06\n",
      "3          Bakery  0.06\n",
      "4       Bookstore  0.06\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "num_top_venues = 5\n",
    "\n",
    "for hood in toronto_onehot_grouped['Neighborhood']:\n",
    "    print(\"----\"+hood+\"----\")\n",
    "    temp = toronto_onehot_grouped[toronto_onehot_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))\n",
    "    print('\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Let's put that into a pandas dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Function to sort the venues in descending order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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": "markdown",
   "metadata": {},
   "source": [
    "Now let's create the new dataframe and display the top 10 venues for each neighborhood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Berczy Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Stadium</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Climbing Gym</td>\n",
       "      <td>Pet Store</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Auto Workshop</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Recording Studio</td>\n",
       "      <td>Skate Park</td>\n",
       "      <td>Brewery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Plane</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Department Store</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                                        Berczy Park           Coffee Shop   \n",
       "1       Brockton, Parkdale Village, Exhibition Place                  Café   \n",
       "2  Business reply mail Processing Centre, South C...    Light Rail Station   \n",
       "3  CN Tower, King and Spadina, Railway Lands, Har...        Airport Lounge   \n",
       "4                                 Central Bay Street           Coffee Shop   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0          Cocktail Bar                Bakery              Pharmacy   \n",
       "1           Coffee Shop        Breakfast Spot                   Gym   \n",
       "2         Auto Workshop         Burrito Place                   Spa   \n",
       "3       Airport Service      Airport Terminal   Rental Car Location   \n",
       "4    Italian Restaurant        Sandwich Place                  Café   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0           Cheese Shop                  Café            Restaurant   \n",
       "1               Stadium         Burrito Place            Restaurant   \n",
       "2        Farmers Market  Fast Food Restaurant            Restaurant   \n",
       "3       Harbor / Marina                 Plane         Boat or Ferry   \n",
       "4   Japanese Restaurant       Thai Restaurant           Salad Place   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0        Farmers Market              Beer Bar     Seafood Restaurant  \n",
       "1          Climbing Gym             Pet Store                 Bakery  \n",
       "2      Recording Studio            Skate Park                Brewery  \n",
       "3              Boutique                   Bar            Coffee Shop  \n",
       "4          Burger Joint                   Bar       Department Store  "
      ]
     },
     "execution_count": 24,
     "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",
    "neighborhoods_venues_sorted = pd.DataFrame(columns=columns)\n",
    "neighborhoods_venues_sorted['Neighborhood'] = toronto_onehot_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(toronto_onehot_grouped.shape[0]):\n",
    "    neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(toronto_onehot_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "neighborhoods_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cluster Neighborhoods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run *k*-means to cluster the neighborhood into clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 3, 3, 0, 0, 3, 0, 0, 3, 3], dtype=int32)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 5\n",
    "\n",
    "toronto_onehot_grouped_clustering = toronto_onehot_grouped.drop('Neighborhood', 1)\n",
    "\n",
    "# run k-means clustering\n",
    "kmeans = KMeans(init=\"k-means++\", n_clusters=kclusters, random_state=0).fit(toronto_onehot_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "kmeans.labels_[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "check cluster labels generated for each row in the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "<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>Berczy Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Stadium</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Climbing Gym</td>\n",
       "      <td>Pet Store</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Auto Workshop</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Recording Studio</td>\n",
       "      <td>Skate Park</td>\n",
       "      <td>Brewery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Plane</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Department Store</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                                        Berczy Park           Coffee Shop   \n",
       "1       Brockton, Parkdale Village, Exhibition Place                  Café   \n",
       "2  Business reply mail Processing Centre, South C...    Light Rail Station   \n",
       "3  CN Tower, King and Spadina, Railway Lands, Har...        Airport Lounge   \n",
       "4                                 Central Bay Street           Coffee Shop   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0          Cocktail Bar                Bakery              Pharmacy   \n",
       "1           Coffee Shop        Breakfast Spot                   Gym   \n",
       "2         Auto Workshop         Burrito Place                   Spa   \n",
       "3       Airport Service      Airport Terminal   Rental Car Location   \n",
       "4    Italian Restaurant        Sandwich Place                  Café   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0           Cheese Shop                  Café            Restaurant   \n",
       "1               Stadium         Burrito Place            Restaurant   \n",
       "2        Farmers Market  Fast Food Restaurant            Restaurant   \n",
       "3       Harbor / Marina                 Plane         Boat or Ferry   \n",
       "4   Japanese Restaurant       Thai Restaurant           Salad Place   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0        Farmers Market              Beer Bar     Seafood Restaurant  \n",
       "1          Climbing Gym             Pet Store                 Bakery  \n",
       "2      Recording Studio            Skate Park                Brewery  \n",
       "3              Boutique                   Bar            Coffee Shop  \n",
       "4          Burger Joint                   Bar       Department Store  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neighborhoods_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(39, 11)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neighborhoods_venues_sorted.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add clustering labels\n",
    "neighborhoods_venues_sorted.insert(0, 'Cluster Labels', kmeans.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PostalCode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</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>Regent Park, Harbourfront</td>\n",
       "      <td>43.654260</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Park</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Theater</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Shoe Store</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park, Ontario Provincial Government</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>College Cafeteria</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Creperie</td>\n",
       "      <td>Park</td>\n",
       "      <td>Music Venue</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Hobby Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Garden District, Ryerson</td>\n",
       "      <td>43.657162</td>\n",
       "      <td>-79.378937</td>\n",
       "      <td>0</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Fast Food 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>43.651494</td>\n",
       "      <td>-79.375418</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Creperie</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Moroccan Restaurant</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>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>3</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Health Food Store</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Women's Store</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                                 Neighborhood  \\\n",
       "0        M5A  Downtown Toronto                    Regent Park, Harbourfront   \n",
       "1        M7A  Downtown Toronto  Queen's Park, Ontario Provincial Government   \n",
       "2        M5B  Downtown Toronto                     Garden District, Ryerson   \n",
       "3        M5C  Downtown Toronto                               St. James Town   \n",
       "4        M4E      East Toronto                                  The Beaches   \n",
       "\n",
       "    Latitude  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "0  43.654260 -79.360636               0           Coffee Shop   \n",
       "1  43.662301 -79.389494               0           Coffee Shop   \n",
       "2  43.657162 -79.378937               0        Clothing Store   \n",
       "3  43.651494 -79.375418               0           Coffee Shop   \n",
       "4  43.676357 -79.293031               3                 Trail   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                  Park                Bakery        Breakfast Spot   \n",
       "1     College Cafeteria                 Diner              Creperie   \n",
       "2           Coffee Shop   Japanese Restaurant    Italian Restaurant   \n",
       "3            Restaurant                  Café        Clothing Store   \n",
       "4     Health Food Store                   Pub         Women's Store   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0                  Café                   Pub               Theater   \n",
       "1                  Park           Music Venue    Mexican Restaurant   \n",
       "2        Cosmetics Shop                  Café       Bubble Tea Shop   \n",
       "3          Cocktail Bar   American Restaurant        Cosmetics Shop   \n",
       "4      Doner Restaurant                 Diner        Discount Store   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0    Mexican Restaurant            Shoe Store             Restaurant  \n",
       "1    Italian Restaurant            Hobby Shop    Fried Chicken Joint  \n",
       "2                 Hotel             Bookstore   Fast Food Restaurant  \n",
       "3              Creperie        Breakfast Spot    Moroccan Restaurant  \n",
       "4   Distribution Center               Dog Run    Dumpling Restaurant  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged = toronto_postal_code\n",
    "\n",
    "# merge neighborhoods_venues_sorted with toronto_postal_code to add latitude/longitude for each neighborhood\n",
    "toronto_merged = toronto_merged.join(neighborhoods_venues_sorted.set_index('Neighborhood'), on='Neighborhood')\n",
    "\n",
    "toronto_merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize the resulting clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "latitude = 43.6534817\n",
    "longitude = -79.3839347"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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            var popup_80c33c9b4f5c4430aa92e0f9a83c3f38 = L.popup({maxWidth: '300'});

            
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                ).addTo(map_fdc39ac64ab14174a8accfa0ca0c9fd7);
            
    
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                ).addTo(map_fdc39ac64ab14174a8accfa0ca0c9fd7);
            
    
            var popup_28a0d77beef74ebd9668813591072bd2 = L.popup({maxWidth: '300'});

            
                var html_a9582469d41842339f8693757efa5814 = $('<div id="html_a9582469d41842339f8693757efa5814" style="width: 100.0%; height: 100.0%;">Business reply mail Processing Centre, South Central Letter Processing Plant Toronto Cluster 3</div>')[0];
                popup_28a0d77beef74ebd9668813591072bd2.setContent(html_a9582469d41842339f8693757efa5814);
            

            circle_marker_8dbc28911dec4304ae7445a1180e770b.bindPopup(popup_28a0d77beef74ebd9668813591072bd2);

            
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7faf1b7b2588>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map\n",
    "map_clusters = folium.Map(location=[latitude, longitude], zoom_start=11)\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(toronto_merged['Latitude'], toronto_merged['Longitude'], toronto_merged['Neighborhood'], toronto_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[cluster-1],\n",
    "        fill=True,\n",
    "        fill_color=rainbow[cluster-1],\n",
    "        fill_opacity=0.7).add_to(map_clusters)\n",
    "       \n",
    "map_clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examine Clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's examine each cluster and determine the discriminating venue categories that distinguish each cluster. Based on the defining categories, we can then assign a name to each cluster."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>Cluster Labels</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",
       "    <tr>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Coffee Shop</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing Store</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Airport Lounge</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bar</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Borough  Cluster Labels  2nd Most Common Venue  \\\n",
       "1st Most Common Venue                                                   \n",
       "Coffee Shop                 12              12                     12   \n",
       "Clothing Store               2               2                      2   \n",
       "Airport Lounge               1               1                      1   \n",
       "Bar                          1               1                      1   \n",
       "\n",
       "                       3rd Most Common Venue  4th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Coffee Shop                               12                     12   \n",
       "Clothing Store                             2                      2   \n",
       "Airport Lounge                             1                      1   \n",
       "Bar                                        1                      1   \n",
       "\n",
       "                       5th Most Common Venue  6th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Coffee Shop                               12                     12   \n",
       "Clothing Store                             2                      2   \n",
       "Airport Lounge                             1                      1   \n",
       "Bar                                        1                      1   \n",
       "\n",
       "                       7th Most Common Venue  8th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Coffee Shop                               12                     12   \n",
       "Clothing Store                             2                      2   \n",
       "Airport Lounge                             1                      1   \n",
       "Bar                                        1                      1   \n",
       "\n",
       "                       9th Most Common Venue  10th Most Common Venue  \n",
       "1st Most Common Venue                                                 \n",
       "Coffee Shop                               12                      12  \n",
       "Clothing Store                             2                       2  \n",
       "Airport Lounge                             1                       1  \n",
       "Bar                                        1                       1  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbb = toronto_merged.loc[toronto_merged['Cluster Labels'] == 0, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]\n",
    "bbb.groupby(['1st Most Common Venue']).count().sort_values(by=[\"Borough\"], ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>Cluster Labels</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",
       "    <tr>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Park</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Borough  Cluster Labels  2nd Most Common Venue  \\\n",
       "1st Most Common Venue                                                   \n",
       "Park                         3               3                      3   \n",
       "\n",
       "                       3rd Most Common Venue  4th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Park                                       3                      3   \n",
       "\n",
       "                       5th Most Common Venue  6th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Park                                       3                      3   \n",
       "\n",
       "                       7th Most Common Venue  8th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Park                                       3                      3   \n",
       "\n",
       "                       9th Most Common Venue  10th Most Common Venue  \n",
       "1st Most Common Venue                                                 \n",
       "Park                                       3                       3  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbb = toronto_merged.loc[toronto_merged['Cluster Labels'] == 1, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]\n",
    "bbb.groupby(['1st Most Common Venue']).count().sort_values(by=[\"Borough\"], ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>Cluster Labels</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",
       "    <tr>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Garden</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Borough  Cluster Labels  2nd Most Common Venue  \\\n",
       "1st Most Common Venue                                                   \n",
       "Garden                       1               1                      1   \n",
       "\n",
       "                       3rd Most Common Venue  4th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Garden                                     1                      1   \n",
       "\n",
       "                       5th Most Common Venue  6th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Garden                                     1                      1   \n",
       "\n",
       "                       7th Most Common Venue  8th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Garden                                     1                      1   \n",
       "\n",
       "                       9th Most Common Venue  10th Most Common Venue  \n",
       "1st Most Common Venue                                                 \n",
       "Garden                                     1                       1  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbb = toronto_merged.loc[toronto_merged['Cluster Labels'] == 2, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]\n",
    "bbb.groupby(['1st Most Common Venue']).count().sort_values(by=[\"Borough\"], ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</th>\n",
       "      <th>Cluster Labels</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",
       "    <tr>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Café</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bakery</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coffee Shop</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dessert Shop</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Borough  Cluster Labels  2nd Most Common Venue  \\\n",
       "1st Most Common Venue                                                   \n",
       "Café                         6               6                      6   \n",
       "Bakery                       1               1                      1   \n",
       "Breakfast Spot               1               1                      1   \n",
       "Coffee Shop                  1               1                      1   \n",
       "Dessert Shop                 1               1                      1   \n",
       "\n",
       "                       3rd Most Common Venue  4th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Café                                       6                      6   \n",
       "Bakery                                     1                      1   \n",
       "Breakfast Spot                             1                      1   \n",
       "Coffee Shop                                1                      1   \n",
       "Dessert Shop                               1                      1   \n",
       "\n",
       "                       5th Most Common Venue  6th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Café                                       6                      6   \n",
       "Bakery                                     1                      1   \n",
       "Breakfast Spot                             1                      1   \n",
       "Coffee Shop                                1                      1   \n",
       "Dessert Shop                               1                      1   \n",
       "\n",
       "                       7th Most Common Venue  8th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Café                                       6                      6   \n",
       "Bakery                                     1                      1   \n",
       "Breakfast Spot                             1                      1   \n",
       "Coffee Shop                                1                      1   \n",
       "Dessert Shop                               1                      1   \n",
       "\n",
       "                       9th Most Common Venue  10th Most Common Venue  \n",
       "1st Most Common Venue                                                 \n",
       "Café                                       6                       6  \n",
       "Bakery                                     1                       1  \n",
       "Breakfast Spot                             1                       1  \n",
       "Coffee Shop                                1                       1  \n",
       "Dessert Shop                               1                       1  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbb = toronto_merged.loc[toronto_merged['Cluster Labels'] == 3, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]\n",
    "bbb.groupby(['1st Most Common Venue']).count().sort_values(by=[\"Borough\"], ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>Borough</th>\n",
       "      <th>Cluster Labels</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",
       "    <tr>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Playground</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Borough  Cluster Labels  2nd Most Common Venue  \\\n",
       "1st Most Common Venue                                                   \n",
       "Playground                   1               1                      1   \n",
       "\n",
       "                       3rd Most Common Venue  4th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Playground                                 1                      1   \n",
       "\n",
       "                       5th Most Common Venue  6th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Playground                                 1                      1   \n",
       "\n",
       "                       7th Most Common Venue  8th Most Common Venue  \\\n",
       "1st Most Common Venue                                                 \n",
       "Playground                                 1                      1   \n",
       "\n",
       "                       9th Most Common Venue  10th Most Common Venue  \n",
       "1st Most Common Venue                                                 \n",
       "Playground                                 1                       1  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbb = toronto_merged.loc[toronto_merged['Cluster Labels'] == 4, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]\n",
    "bbb.groupby(['1st Most Common Venue']).count().sort_values(by=[\"Borough\"], ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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