Part 3 - Segmenting and Clustering Neighborhoods in Toronto (Wei Keat).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Recreating Part 1 Dataframe**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "import pandas as pd\n",
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extracting the html file from the URL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M'\n",
    "r = requests.get(url).text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using BeautifulSoup to find the table rows containing the postcode info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [],
   "source": [
    "soup = BeautifulSoup(r,'lxml')\n",
    "btable = soup.find('table')\n",
    "tab_rows = btable.find_all('tr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating the pandas dataframe and populating it with info from the html \n",
    "### (with processing of _Not assigned_ and duplicate postal code rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "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>Harbourfront, Regent Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Heights, Lawrence Manor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>Queen's Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M9A</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Islington Avenue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge, Malvern</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M3B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M4B</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Gardens, Parkview Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Ryerson, Garden District</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>M6B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Glencairn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M9B</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Cloverdale, Islington, Martin Grove, Princess ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Highland Creek, Rouge Hill, Port Union</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>M3C</td>\n",
       "      <td>North York</td>\n",
       "      <td>Flemingdon Park, Don Mills South</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>M4C</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>M5C</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>M6C</td>\n",
       "      <td>York</td>\n",
       "      <td>Humewood-Cedarvale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M9C</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Bloordale Gardens, Eringate, Markland Wood, Ol...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood, Morningside, West Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>M5E</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Berczy Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>M6E</td>\n",
       "      <td>York</td>\n",
       "      <td>Caledonia-Fairbanks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>M1G</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Woburn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>M4G</td>\n",
       "      <td>East York</td>\n",
       "      <td>Leaside</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>M5G</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Central Bay Street</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>M6G</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Christie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>M1H</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cedarbrae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>M2H</td>\n",
       "      <td>North York</td>\n",
       "      <td>Hillcrest Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>M3H</td>\n",
       "      <td>North York</td>\n",
       "      <td>Bathurst Manor, Downsview North, Wilson Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>M4H</td>\n",
       "      <td>East York</td>\n",
       "      <td>Thorncliffe Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>M4R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>M5R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>M6R</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Parkdale, Roncesvalles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>M7R</td>\n",
       "      <td>Mississauga</td>\n",
       "      <td>Canada Post Gateway Processing Centre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>M9R</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Kingsview Village, Martin Grove Gardens, Richv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>M1S</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Agincourt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>M4S</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>M5S</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbord, University of Toronto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>M6S</td>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Runnymede, Swansea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>M1T</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Clarks Corners, Sullivan, Tam O'Shanter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>M4T</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>M5T</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Chinatown, Grange Park, Kensington Market</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>M1V</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Agincourt North, L'Amoreaux East, Milliken, St...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>M4V</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Deer Park, Forest Hill SE, Rathnelly, South Hi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>M5V</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>CN Tower, Bathurst Quay, Island airport, Harbo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>M8V</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Humber Bay Shores, Mimico South, New Toronto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>M9V</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Albion Gardens, Beaumond Heights, Humbergate, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>M1W</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>L'Amoreaux West, Steeles West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>M4W</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Rosedale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>M5W</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Stn A PO Boxes 25 The Esplanade</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>M8W</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Alderwood, Long Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>M9W</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Northwest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>M1X</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Upper Rouge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>M4X</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Cabbagetown, St. James Town</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>M5X</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>First Canadian Place, Underground city</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</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>99</th>\n",
       "      <td>M4Y</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Church and Wellesley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>Business reply mail Processing Centre969 Eastern</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>M8Y</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Humber Bay, King's Mill Park, Kingsway Park So...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>M8Z</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Kingsway Park South West, Mimico NW, The Queen...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>103 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    PostalCode           Borough  \\\n",
       "0          M3A        North York   \n",
       "1          M4A        North York   \n",
       "2          M5A  Downtown Toronto   \n",
       "3          M6A        North York   \n",
       "4          M7A      Queen's Park   \n",
       "5          M9A         Etobicoke   \n",
       "6          M1B       Scarborough   \n",
       "7          M3B        North York   \n",
       "8          M4B         East York   \n",
       "9          M5B  Downtown Toronto   \n",
       "10         M6B        North York   \n",
       "11         M9B         Etobicoke   \n",
       "12         M1C       Scarborough   \n",
       "13         M3C        North York   \n",
       "14         M4C         East York   \n",
       "15         M5C  Downtown Toronto   \n",
       "16         M6C              York   \n",
       "17         M9C         Etobicoke   \n",
       "18         M1E       Scarborough   \n",
       "19         M4E      East Toronto   \n",
       "20         M5E  Downtown Toronto   \n",
       "21         M6E              York   \n",
       "22         M1G       Scarborough   \n",
       "23         M4G         East York   \n",
       "24         M5G  Downtown Toronto   \n",
       "25         M6G  Downtown Toronto   \n",
       "26         M1H       Scarborough   \n",
       "27         M2H        North York   \n",
       "28         M3H        North York   \n",
       "29         M4H         East York   \n",
       "..         ...               ...   \n",
       "73         M4R   Central Toronto   \n",
       "74         M5R   Central Toronto   \n",
       "75         M6R      West Toronto   \n",
       "76         M7R       Mississauga   \n",
       "77         M9R         Etobicoke   \n",
       "78         M1S       Scarborough   \n",
       "79         M4S   Central Toronto   \n",
       "80         M5S  Downtown Toronto   \n",
       "81         M6S      West Toronto   \n",
       "82         M1T       Scarborough   \n",
       "83         M4T   Central Toronto   \n",
       "84         M5T  Downtown Toronto   \n",
       "85         M1V       Scarborough   \n",
       "86         M4V   Central Toronto   \n",
       "87         M5V  Downtown Toronto   \n",
       "88         M8V         Etobicoke   \n",
       "89         M9V         Etobicoke   \n",
       "90         M1W       Scarborough   \n",
       "91         M4W  Downtown Toronto   \n",
       "92         M5W  Downtown Toronto   \n",
       "93         M8W         Etobicoke   \n",
       "94         M9W         Etobicoke   \n",
       "95         M1X       Scarborough   \n",
       "96         M4X  Downtown Toronto   \n",
       "97         M5X  Downtown Toronto   \n",
       "98         M8X         Etobicoke   \n",
       "99         M4Y  Downtown Toronto   \n",
       "100        M7Y      East Toronto   \n",
       "101        M8Y         Etobicoke   \n",
       "102        M8Z         Etobicoke   \n",
       "\n",
       "                                          Neighborhood  \n",
       "0                                            Parkwoods  \n",
       "1                                     Victoria Village  \n",
       "2                            Harbourfront, Regent Park  \n",
       "3                     Lawrence Heights, Lawrence Manor  \n",
       "4                                         Queen's Park  \n",
       "5                                     Islington Avenue  \n",
       "6                                       Rouge, Malvern  \n",
       "7                                      Don Mills North  \n",
       "8                      Woodbine Gardens, Parkview Hill  \n",
       "9                             Ryerson, Garden District  \n",
       "10                                           Glencairn  \n",
       "11   Cloverdale, Islington, Martin Grove, Princess ...  \n",
       "12              Highland Creek, Rouge Hill, Port Union  \n",
       "13                    Flemingdon Park, Don Mills South  \n",
       "14                                    Woodbine Heights  \n",
       "15                                      St. James Town  \n",
       "16                                  Humewood-Cedarvale  \n",
       "17   Bloordale Gardens, Eringate, Markland Wood, Ol...  \n",
       "18                   Guildwood, Morningside, West Hill  \n",
       "19                                         The Beaches  \n",
       "20                                         Berczy Park  \n",
       "21                                 Caledonia-Fairbanks  \n",
       "22                                              Woburn  \n",
       "23                                             Leaside  \n",
       "24                                  Central Bay Street  \n",
       "25                                            Christie  \n",
       "26                                           Cedarbrae  \n",
       "27                                   Hillcrest Village  \n",
       "28     Bathurst Manor, Downsview North, Wilson Heights  \n",
       "29                                    Thorncliffe Park  \n",
       "..                                                 ...  \n",
       "73                                  North Toronto West  \n",
       "74                 The Annex, North Midtown, Yorkville  \n",
       "75                              Parkdale, Roncesvalles  \n",
       "76               Canada Post Gateway Processing Centre  \n",
       "77   Kingsview Village, Martin Grove Gardens, Richv...  \n",
       "78                                           Agincourt  \n",
       "79                                          Davisville  \n",
       "80                      Harbord, University of Toronto  \n",
       "81                                  Runnymede, Swansea  \n",
       "82             Clarks Corners, Sullivan, Tam O'Shanter  \n",
       "83                         Moore Park, Summerhill East  \n",
       "84           Chinatown, Grange Park, Kensington Market  \n",
       "85   Agincourt North, L'Amoreaux East, Milliken, St...  \n",
       "86   Deer Park, Forest Hill SE, Rathnelly, South Hi...  \n",
       "87   CN Tower, Bathurst Quay, Island airport, Harbo...  \n",
       "88        Humber Bay Shores, Mimico South, New Toronto  \n",
       "89   Albion Gardens, Beaumond Heights, Humbergate, ...  \n",
       "90                       L'Amoreaux West, Steeles West  \n",
       "91                                            Rosedale  \n",
       "92                     Stn A PO Boxes 25 The Esplanade  \n",
       "93                              Alderwood, Long Branch  \n",
       "94                                           Northwest  \n",
       "95                                         Upper Rouge  \n",
       "96                         Cabbagetown, St. James Town  \n",
       "97              First Canadian Place, Underground city  \n",
       "98       The Kingsway, Montgomery Road, Old Mill North  \n",
       "99                                Church and Wellesley  \n",
       "100   Business reply mail Processing Centre969 Eastern  \n",
       "101  Humber Bay, King's Mill Park, Kingsway Park So...  \n",
       "102  Kingsway Park South West, Mimico NW, The Queen...  \n",
       "\n",
       "[103 rows x 3 columns]"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "column_names = ['PostalCode', 'Borough', 'Neighborhood']  # Setting the columns for the new pandas dataframe\n",
    "postcodes = pd.DataFrame(columns=column_names)\n",
    "\n",
    "for n in range(1,len(tab_rows)):\n",
    "    row_t = tab_rows[n].text.split('\\n')\n",
    "    if row_t[2] != 'Not assigned':  # Skip rows with 'Not assigned' Boroughs\n",
    "        if row_t[3] == 'Not assigned':  # Copying Borough name to 'Not assigned' Neighborhoods\n",
    "            row_t[3] = row_t[2]\n",
    "        if row_t[1] in postcodes.loc[:,'PostalCode'].unique():  # Appending the Neighborhood names to duplicate PostalCode areas\n",
    "            postcodes.loc[tag,'Neighborhood'] = postcodes.loc[tag,'Neighborhood'] + ', ' + row_t[3]\n",
    "        else: \n",
    "            postcodes.loc[n,:] = row_t[1:4]\n",
    "            tag = n\n",
    "\n",
    "postcodes.reset_index(drop=True,inplace=True)\n",
    "postcodes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Print the number of rows of the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of the dataframe:  (103, 3)\n"
     ]
    }
   ],
   "source": [
    "print('The shape of the dataframe: ',postcodes.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Recreating Part 2**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading csv file that has the geographical coordinates of each postal code \n",
    "## *(Geocoder package failed to work)*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data downloaded!\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>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": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import csv\n",
    "\n",
    "!wget -q -O Geospatial_Coordinates.csv http://cocl.us/Geospatial_data\n",
    "print('Data downloaded!')\n",
    "\n",
    "# read csv file\n",
    "coord = pd.read_csv('Geospatial_Coordinates.csv')\n",
    "coord.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Match the Postal Codes to the coordinate values to populate the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "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",
       "      <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>Harbourfront, Regent Park</td>\n",
       "      <td>43.654260</td>\n",
       "      <td>-79.360636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Heights, Lawrence Manor</td>\n",
       "      <td>43.718518</td>\n",
       "      <td>-79.464763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                      Neighborhood   Latitude  \\\n",
       "0        M3A        North York                         Parkwoods  43.753259   \n",
       "1        M4A        North York                  Victoria Village  43.725882   \n",
       "2        M5A  Downtown Toronto         Harbourfront, Regent Park  43.654260   \n",
       "3        M6A        North York  Lawrence Heights, Lawrence Manor  43.718518   \n",
       "4        M7A      Queen's Park                      Queen's Park  43.662301   \n",
       "\n",
       "   Longitude  \n",
       "0 -79.329656  \n",
       "1 -79.315572  \n",
       "2 -79.360636  \n",
       "3 -79.464763  \n",
       "4 -79.389494  "
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i,n in enumerate(postcodes['PostalCode']):\n",
    "    res = coord[coord['Postal Code']==n]\n",
    "    postcodes.loc[i,'Latitude'] = res.Latitude.values\n",
    "    postcodes.loc[i,'Longitude'] = res.Longitude.values\n",
    "\n",
    "postcodes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Part 3**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import relevant libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Libraries imported.\n"
     ]
    }
   ],
   "source": [
    "# import k-means from clustering stage\n",
    "from sklearn.cluster import KMeans\n",
    "import numpy as np\n",
    "import folium # map rendering library\n",
    "\n",
    "# Matplotlib and associated plotting modules\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors\n",
    "\n",
    "print('Libraries imported.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define Foursquare credentials and version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your credentails:\n",
      "CLIENT_ID: QSWCVB3IUNTUBZTDNQE00EYS44ZNHES3IDLNPJIQ2PY5FX4U\n",
      "CLIENT_SECRET:MGVRCCQSNGLQUIEAS45KHJVWKOW2TIOK14RBYCP20GHHNC24\n"
     ]
    }
   ],
   "source": [
    "CLIENT_ID = 'QSWCVB3IUNTUBZTDNQE00EYS44ZNHES3IDLNPJIQ2PY5FX4U' # your Foursquare ID\n",
    "CLIENT_SECRET = 'MGVRCCQSNGLQUIEAS45KHJVWKOW2TIOK14RBYCP20GHHNC24' # your Foursquare Secret\n",
    "VERSION = '20180605' # Foursquare API version\n",
    "\n",
    "print('Your credentails:')\n",
    "print('CLIENT_ID: ' + CLIENT_ID)\n",
    "print('CLIENT_SECRET:' + CLIENT_SECRET)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define getNearbyVenues function for extracting venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "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",
    "            100)\n",
    "            \n",
    "        # make the GET request\n",
    "        results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n",
    "        \n",
    "        # return only relevant information for each nearby venue\n",
    "        venues_list.append([(\n",
    "            name, \n",
    "            lat, \n",
    "            lng, \n",
    "            v['venue']['name'], \n",
    "            v['venue']['location']['lat'], \n",
    "            v['venue']['location']['lng'],  \n",
    "            v['venue']['categories'][0]['name']) for v in results])\n",
    "\n",
    "    nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])\n",
    "    nearby_venues.columns = ['Neighborhood', \n",
    "                  'Neighborhood Latitude', \n",
    "                  'Neighborhood Longitude', \n",
    "                  'Venue', \n",
    "                  'Venue Latitude', \n",
    "                  'Venue Longitude', \n",
    "                  'Venue Category']\n",
    "    \n",
    "    return(nearby_venues)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select a subset of neighborhoods and explore the nearby venues for each"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "toronto_data = postcodes[6:91].reset_index(drop=True)\n",
    "toronto_venues = getNearbyVenues(toronto_data['Neighborhood'],toronto_data[\"Latitude\"],toronto_data['Longitude'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a one hot encoding dataframe for the neighborhood's venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .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>Accessories Store</th>\n",
       "      <th>Airport</th>\n",
       "      <th>Airport Food Court</th>\n",
       "      <th>Airport Gate</th>\n",
       "      <th>Airport Lounge</th>\n",
       "      <th>Airport Service</th>\n",
       "      <th>Airport Terminal</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Antique Shop</th>\n",
       "      <th>Aquarium</th>\n",
       "      <th>...</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Game Store</th>\n",
       "      <th>Video Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Warehouse Store</th>\n",
       "      <th>Whisky Bar</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wings Joint</th>\n",
       "      <th>Women's Store</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 261 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Accessories Store  Airport  Airport Food Court  Airport Gate  \\\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",
       "   Airport Lounge  Airport Service  Airport Terminal  American Restaurant  \\\n",
       "0               0                0                 0                    0   \n",
       "1               0                0                 0                    0   \n",
       "2               0                0                 0                    0   \n",
       "3               0                0                 0                    0   \n",
       "4               0                0                 0                    0   \n",
       "\n",
       "   Antique Shop  Aquarium     ...       Vegetarian / Vegan 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",
       "   Video Game Store  Video Store  Vietnamese Restaurant  Warehouse 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",
       "   Whisky Bar  Wine Bar  Wings Joint  Women's Store  Yoga Studio  \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",
       "[5 rows x 261 columns]"
      ]
     },
     "execution_count": 221,
     "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.columns = ['Neighborhood'].extend(toronto_onehot.columns)\n",
    "toronto_onehot['Neighborhood'] = toronto_venues['Neighborhood'] \n",
    "\n",
    "toronto_onehot.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Group the one hot encoded dataframe by Neighborhood to obtain frequencies for each venue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "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>Accessories Store</th>\n",
       "      <th>Airport</th>\n",
       "      <th>Airport Food Court</th>\n",
       "      <th>Airport Gate</th>\n",
       "      <th>Airport Lounge</th>\n",
       "      <th>Airport Service</th>\n",
       "      <th>Airport Terminal</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Antique Shop</th>\n",
       "      <th>...</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Game Store</th>\n",
       "      <th>Video Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Warehouse Store</th>\n",
       "      <th>Whisky Bar</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wings Joint</th>\n",
       "      <th>Women's Store</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adelaide, King, Richmond</td>\n",
       "      <td>0.01</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>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01</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>0.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Agincourt</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Agincourt North, L'Amoreaux East, Milliken, St...</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Albion Gardens, Beaumond Heights, Humbergate, ...</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bathurst Manor, Downsview North, Wilson Heights</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 261 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood  Accessories Store  \\\n",
       "0                           Adelaide, King, Richmond               0.01   \n",
       "1                                          Agincourt               0.00   \n",
       "2  Agincourt North, L'Amoreaux East, Milliken, St...               0.00   \n",
       "3  Albion Gardens, Beaumond Heights, Humbergate, ...               0.00   \n",
       "4    Bathurst Manor, Downsview North, Wilson Heights               0.00   \n",
       "\n",
       "   Airport  Airport Food Court  Airport Gate  Airport Lounge  Airport Service  \\\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",
       "   Airport Terminal  American Restaurant  Antique Shop     ...       \\\n",
       "0               0.0                 0.04           0.0     ...        \n",
       "1               0.0                 0.00           0.0     ...        \n",
       "2               0.0                 0.00           0.0     ...        \n",
       "3               0.0                 0.00           0.0     ...        \n",
       "4               0.0                 0.00           0.0     ...        \n",
       "\n",
       "   Vegetarian / Vegan Restaurant  Video Game Store  Video Store  \\\n",
       "0                           0.01               0.0     0.000000   \n",
       "1                           0.00               0.0     0.000000   \n",
       "2                           0.00               0.0     0.000000   \n",
       "3                           0.00               0.0     0.000000   \n",
       "4                           0.00               0.0     0.055556   \n",
       "\n",
       "   Vietnamese Restaurant  Warehouse Store  Whisky Bar  Wine Bar  Wings Joint  \\\n",
       "0                    0.0              0.0         0.0      0.01          0.0   \n",
       "1                    0.0              0.0         0.0      0.00          0.0   \n",
       "2                    0.0              0.0         0.0      0.00          0.0   \n",
       "3                    0.0              0.0         0.0      0.00          0.0   \n",
       "4                    0.0              0.0         0.0      0.00          0.0   \n",
       "\n",
       "   Women's Store  Yoga Studio  \n",
       "0           0.01          0.0  \n",
       "1           0.00          0.0  \n",
       "2           0.00          0.0  \n",
       "3           0.00          0.0  \n",
       "4           0.00          0.0  \n",
       "\n",
       "[5 rows x 261 columns]"
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_grouped = toronto_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "toronto_grouped.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the function for extracting the most common venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "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": [
    "## Build the top 5 most common venues for each neighborhood dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adelaide, King, Richmond</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>American Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Agincourt</td>\n",
       "      <td>Lounge</td>\n",
       "      <td>Skating Rink</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Agincourt North, L'Amoreaux East, Milliken, St...</td>\n",
       "      <td>Park</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Dim Sum Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Albion Gardens, Beaumond Heights, Humbergate, ...</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bathurst Manor, Downsview North, Wilson Heights</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                           Adelaide, King, Richmond           Coffee Shop   \n",
       "1                                          Agincourt                Lounge   \n",
       "2  Agincourt North, L'Amoreaux East, Milliken, St...                  Park   \n",
       "3  Albion Gardens, Beaumond Heights, Humbergate, ...         Grocery Store   \n",
       "4    Bathurst Manor, Downsview North, Wilson Heights           Coffee Shop   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                  Café       Thai Restaurant            Steakhouse   \n",
       "1          Skating Rink        Breakfast Spot        Sandwich Place   \n",
       "2            Playground           Yoga Studio            Donut Shop   \n",
       "3   Fried Chicken Joint           Coffee Shop              Pharmacy   \n",
       "4         Shopping Mall           Pizza Place      Sushi Restaurant   \n",
       "\n",
       "       5th Most Common Venue  \n",
       "0        American Restaurant  \n",
       "1                Yoga Studio  \n",
       "2         Dim Sum Restaurant  \n",
       "3                Pizza Place  \n",
       "4  Middle Eastern Restaurant  "
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_top_venues = 5\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_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(toronto_grouped.shape[0]):\n",
    "    neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(toronto_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "neighborhoods_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cluster the neighborhoods based on the common venues (_by using k-means clustering where k=5_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 3, 4, 3, 3, 3, 3, 3, 3, 3], dtype=int32)"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 5\n",
    "\n",
    "toronto_grouped_clustering = toronto_grouped.drop('Neighborhood', 1)\n",
    "\n",
    "# run k-means clustering\n",
    "kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(toronto_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "kmeans.labels_[0:10] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the dataframe for displaying the cluster which each neighborhood belongs to"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "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",
       "      <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge, Malvern</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "      <td>3</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>Event Space</td>\n",
       "      <td>Ethiopian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M3B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills North</td>\n",
       "      <td>43.745906</td>\n",
       "      <td>-79.352188</td>\n",
       "      <td>3</td>\n",
       "      <td>Basketball Court</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Café</td>\n",
       "      <td>Caribbean Restaurant</td>\n",
       "      <td>Baseball Field</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M4B</td>\n",
       "      <td>East York</td>\n",
       "      <td>Woodbine Gardens, Parkview Hill</td>\n",
       "      <td>43.706397</td>\n",
       "      <td>-79.309937</td>\n",
       "      <td>4</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Rock Climbing Spot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Ryerson, Garden District</td>\n",
       "      <td>43.657162</td>\n",
       "      <td>-79.378937</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Café</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M6B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Glencairn</td>\n",
       "      <td>43.709577</td>\n",
       "      <td>-79.445073</td>\n",
       "      <td>3</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  PostalCode           Borough                     Neighborhood   Latitude  \\\n",
       "0        M1B       Scarborough                   Rouge, Malvern  43.806686   \n",
       "1        M3B        North York                  Don Mills North  43.745906   \n",
       "2        M4B         East York  Woodbine Gardens, Parkview Hill  43.706397   \n",
       "3        M5B  Downtown Toronto         Ryerson, Garden District  43.657162   \n",
       "4        M6B        North York                        Glencairn  43.709577   \n",
       "\n",
       "   Longitude  Cluster Labels 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "0 -79.194353               3  Fast Food Restaurant           Yoga Studio   \n",
       "1 -79.352188               3      Basketball Court  Gym / Fitness Center   \n",
       "2 -79.309937               4  Fast Food Restaurant           Pizza Place   \n",
       "3 -79.378937               3           Coffee Shop        Clothing Store   \n",
       "4 -79.445073               3    Italian Restaurant   Japanese Restaurant   \n",
       "\n",
       "  3rd Most Common Venue 4th Most Common Venue      5th Most Common Venue  \n",
       "0    Falafel Restaurant           Event Space       Ethiopian Restaurant  \n",
       "1                  Café  Caribbean Restaurant             Baseball Field  \n",
       "2             Gastropub              Pharmacy         Rock Climbing Spot  \n",
       "3                  Café        Cosmetics Shop  Middle Eastern Restaurant  \n",
       "4                   Pub                Bakery           Doner Restaurant  "
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged = toronto_data\n",
    "\n",
    "# add clustering labels\n",
    "toronto_merged['Cluster Labels'] = kmeans.labels_\n",
    "\n",
    "# merge toronto_grouped with toronto_data 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": [
    "## Generate Folium map (assuming Toronto city hall as the centre of Toronto)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
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                var html_660e53bc70d64ceca145adcdcdae1e8c = $('<div id="html_660e53bc70d64ceca145adcdcdae1e8c" style="width: 100.0%; height: 100.0%;">Albion Gardens, Beaumond Heights, Humbergate, Jamestown, Mount Olive, Silverstone, South Steeles, Thistletown Cluster 1</div>')[0];
                popup_4d657d4235494c2e86bd4b24a1c0e509.setContent(html_660e53bc70d64ceca145adcdcdae1e8c);
            

            circle_marker_15c7d993ad3c443d84ce2a7729ab2aa1.bindPopup(popup_4d657d4235494c2e86bd4b24a1c0e509);

            
        
    
            var circle_marker_35b1c8018c654d19a07c9e450b8d7fbe = L.circleMarker(
                [43.799525200000005,-79.3183887],
                {
  "bubblingMouseEvents": true,
  "color": "#8000ff",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#8000ff",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_4e0698092b94467a86bba8b798f35160);
            
    
            var popup_98c00bd3143647b5880609048cc924a6 = L.popup({maxWidth: '300'});

            
                var html_b5cc937400994fe493b70e494646adea = $('<div id="html_b5cc937400994fe493b70e494646adea" style="width: 100.0%; height: 100.0%;">L&#39;Amoreaux West, Steeles West Cluster 1</div>')[0];
                popup_98c00bd3143647b5880609048cc924a6.setContent(html_b5cc937400994fe493b70e494646adea);
            

            circle_marker_35b1c8018c654d19a07c9e450b8d7fbe.bindPopup(popup_98c00bd3143647b5880609048cc924a6);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fcc6c059320>"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Assuming Toronto coordinates as 43.653170, -79.383541\n",
    "tor_latitude = 43.653170\n",
    "tor_longitude = -79.383541\n",
    "\n",
    "# create map\n",
    "map_clusters = folium.Map(location=[tor_latitude, tor_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": [
    "### Cluster 1\n",
    "### There are many restaurants and eateries in this region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "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>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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>North York</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Hardware Store</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Borough  Cluster Labels 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "49  North York               0           Coffee Shop    Italian Restaurant   \n",
       "\n",
       "   3rd Most Common Venue 4th Most Common Venue 5th Most Common Venue  \n",
       "49  Fast Food Restaurant        Hardware Store            Restaurant  "
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged.loc[toronto_merged['Cluster Labels'] == 0, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 2 \n",
    "### These regions are good for exercising (Yoga studios, parks) and grabbing a quick bite (coffee shops, sandwich place, restaurants)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "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>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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>1</td>\n",
       "      <td>Park</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Beer Store</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>1</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Other Great Outdoors</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>North York</td>\n",
       "      <td>1</td>\n",
       "      <td>Bus Stop</td>\n",
       "      <td>Airport</td>\n",
       "      <td>Park</td>\n",
       "      <td>Electronics Store</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>1</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>North York</td>\n",
       "      <td>1</td>\n",
       "      <td>Park</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Bank</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>York</td>\n",
       "      <td>1</td>\n",
       "      <td>Check Cashing Service</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Turkish Restaurant</td>\n",
       "      <td>Department Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>North York</td>\n",
       "      <td>1</td>\n",
       "      <td>Baseball Field</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Dim Sum Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>North York</td>\n",
       "      <td>1</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Ramen Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sandwich Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>1</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Dim Sum Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>York</td>\n",
       "      <td>1</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>Event Space</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>1</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Latin American Restaurant</td>\n",
       "      <td>Pet Store</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>1</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Liquor Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>1</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>1</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Grocery Store</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough  Cluster Labels  1st Most Common Venue  \\\n",
       "11         Etobicoke               1                   Park   \n",
       "13      East Toronto               1            Coffee Shop   \n",
       "34        North York               1               Bus Stop   \n",
       "36  Downtown Toronto               1            Coffee Shop   \n",
       "40        North York               1                   Park   \n",
       "50              York               1  Check Cashing Service   \n",
       "51        North York               1         Baseball Field   \n",
       "53        North York               1            Coffee Shop   \n",
       "56   Central Toronto               1                 Garden   \n",
       "58              York               1      Convenience Store   \n",
       "59       Scarborough               1      Indian Restaurant   \n",
       "68   Central Toronto               1         Sandwich Place   \n",
       "83         Etobicoke               1          Grocery Store   \n",
       "84       Scarborough               1   Fast Food Restaurant   \n",
       "\n",
       "        2nd Most Common Venue 3rd Most Common Venue   4th Most Common Venue  \\\n",
       "11                       Café              Pharmacy              Beer Store   \n",
       "13       Other Great Outdoors                   Pub             Yoga Studio   \n",
       "34                    Airport                  Park       Electronics Store   \n",
       "36                       Café                 Hotel              Restaurant   \n",
       "40              Grocery Store                  Bank           Shopping Mall   \n",
       "50             Discount Store        Sandwich Place      Turkish Restaurant   \n",
       "51                Yoga Studio    Dim Sum Restaurant          Farmers Market   \n",
       "53                 Restaurant      Ramen Restaurant                    Café   \n",
       "56                Yoga Studio            Donut Shop      Dim Sum Restaurant   \n",
       "58                Yoga Studio          Dessert Shop      Falafel Restaurant   \n",
       "59  Latin American Restaurant             Pet Store  Furniture / Home Store   \n",
       "68                Coffee Shop                  Café             Pizza Place   \n",
       "83        Fried Chicken Joint           Coffee Shop                Pharmacy   \n",
       "84         Chinese Restaurant           Coffee Shop          Breakfast Spot   \n",
       "\n",
       "    5th Most Common Venue  \n",
       "11            Pizza Place  \n",
       "13             Donut Shop  \n",
       "34             Donut Shop  \n",
       "36    American Restaurant  \n",
       "40             Donut Shop  \n",
       "50       Department Store  \n",
       "51     Falafel Restaurant  \n",
       "53         Sandwich Place  \n",
       "56                  Diner  \n",
       "58            Event Space  \n",
       "59  Vietnamese Restaurant  \n",
       "68           Liquor Store  \n",
       "83            Pizza Place  \n",
       "84          Grocery Store  "
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged.loc[toronto_merged['Cluster Labels'] == 1, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 3 \n",
    "### Exotic cuisines can be found here (Mexican and Thai food)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "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>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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>2</td>\n",
       "      <td>Café</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Borough  Cluster Labels 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "63  West Toronto               2                  Café    Mexican Restaurant   \n",
       "\n",
       "   3rd Most Common Venue 4th Most Common Venue 5th Most Common Venue  \n",
       "63                   Bar         Grocery Store       Thai Restaurant  "
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged.loc[toronto_merged['Cluster Labels'] == 2, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 4 \n",
    "### Coffee shops and cafes are frequented in this regions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "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>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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>Event Space</td>\n",
       "      <td>Ethiopian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Basketball Court</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Café</td>\n",
       "      <td>Caribbean Restaurant</td>\n",
       "      <td>Baseball Field</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Café</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>3</td>\n",
       "      <td>Golf Course</td>\n",
       "      <td>Bank</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Moving Target</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>Beer Store</td>\n",
       "      <td>Storage Facility</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>East York</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Skating Rink</td>\n",
       "      <td>Beer Store</td>\n",
       "      <td>Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Gastropub</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>York</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Field</td>\n",
       "      <td>Hockey Arena</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Electronics Store</td>\n",
       "      <td>Medical Center</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Steakhouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>York</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Market</td>\n",
       "      <td>Women's Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Korean Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>East York</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sporting Goods Shop</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Smoothie Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Café</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Park</td>\n",
       "      <td>Baby Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Hakka Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Caribbean Restaurant</td>\n",
       "      <td>Bank</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Pool</td>\n",
       "      <td>Mediterranean Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Golf Course</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>East York</td>\n",
       "      <td>3</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>American Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Event Space</td>\n",
       "      <td>Ethiopian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bus Station</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Massage Studio</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>East York</td>\n",
       "      <td>3</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Park</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Aquarium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Train Station</td>\n",
       "      <td>Bus Station</td>\n",
       "      <td>Department Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Basketball Court</td>\n",
       "      <td>Park</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Construction &amp; Landscaping</td>\n",
       "      <td>Eastern European Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Empanada Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>Event Space</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Motel</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>Event Space</td>\n",
       "      <td>Ethiopian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Dim Sum Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Home Service</td>\n",
       "      <td>Food Truck</td>\n",
       "      <td>Baseball Field</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>American Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>College Stadium</td>\n",
       "      <td>Café</td>\n",
       "      <td>Skating Rink</td>\n",
       "      <td>General Entertainment</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Athletics &amp; Sports</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Liquor Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Dim Sum Restaurant</td>\n",
       "      <td>Dessert Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>York</td>\n",
       "      <td>3</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Bank</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Sandwich Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Jewelry Store</td>\n",
       "      <td>Department Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>3</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Intersection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Paper / Office Supplies Store</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Shopping Mall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>North York</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Butcher</td>\n",
       "      <td>Pharmacy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Gift Shop</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Mississauga</td>\n",
       "      <td>3</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Burrito Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Mobile Phone Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Lounge</td>\n",
       "      <td>Skating Rink</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Café</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Noodle House</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Park</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Trail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Café</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Scarborough</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Dim Sum Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Medical Center</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "      <td>Plane</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>3</td>\n",
       "      <td>Café</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>67 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough  Cluster Labels      1st Most Common Venue  \\\n",
       "0        Scarborough               3       Fast Food Restaurant   \n",
       "1         North York               3           Basketball Court   \n",
       "3   Downtown Toronto               3                Coffee Shop   \n",
       "4         North York               3         Italian Restaurant   \n",
       "5          Etobicoke               3                Golf Course   \n",
       "6        Scarborough               3                        Bar   \n",
       "7         North York               3                        Gym   \n",
       "8          East York               3                       Park   \n",
       "9   Downtown Toronto               3                Coffee Shop   \n",
       "10              York               3                       Park   \n",
       "12       Scarborough               3                        Spa   \n",
       "14  Downtown Toronto               3                Coffee Shop   \n",
       "15              York               3                       Park   \n",
       "16       Scarborough               3                Coffee Shop   \n",
       "17         East York               3                Coffee Shop   \n",
       "18  Downtown Toronto               3                Coffee Shop   \n",
       "19  Downtown Toronto               3                       Café   \n",
       "20       Scarborough               3           Hakka Restaurant   \n",
       "21        North York               3                       Pool   \n",
       "22        North York               3                Coffee Shop   \n",
       "23         East York               3          Indian Restaurant   \n",
       "24  Downtown Toronto               3                Coffee Shop   \n",
       "25      West Toronto               3                     Bakery   \n",
       "26       Scarborough               3                 Playground   \n",
       "27        North York               3             Clothing Store   \n",
       "28        North York               3             Massage Studio   \n",
       "29         East York               3          Convenience Store   \n",
       "30  Downtown Toronto               3                Coffee Shop   \n",
       "31      West Toronto               3                        Bar   \n",
       "32       Scarborough               3             Discount Store   \n",
       "..               ...             ...                        ...   \n",
       "43        North York               3           Basketball Court   \n",
       "44        North York               3        Empanada Restaurant   \n",
       "45       Scarborough               3        American Restaurant   \n",
       "46        North York               3                        Gym   \n",
       "47        North York               3               Home Service   \n",
       "48      East Toronto               3                       Café   \n",
       "52       Scarborough               3            College Stadium   \n",
       "54        North York               3         Athletics & Sports   \n",
       "55   Central Toronto               3                       Park   \n",
       "57              York               3                   Bus Line   \n",
       "60        North York               3                       Park   \n",
       "61   Central Toronto               3                       Park   \n",
       "62   Central Toronto               3                       Park   \n",
       "64         Etobicoke               3                Pizza Place   \n",
       "65       Scarborough               3  Middle Eastern Restaurant   \n",
       "66        North York               3                Coffee Shop   \n",
       "69      West Toronto               3             Breakfast Spot   \n",
       "70       Mississauga               3                      Hotel   \n",
       "71         Etobicoke               3                       Park   \n",
       "72       Scarborough               3                     Lounge   \n",
       "73   Central Toronto               3               Dessert Shop   \n",
       "74  Downtown Toronto               3                       Café   \n",
       "75      West Toronto               3                Coffee Shop   \n",
       "76       Scarborough               3                Pizza Place   \n",
       "77   Central Toronto               3                 Restaurant   \n",
       "78  Downtown Toronto               3                       Café   \n",
       "79       Scarborough               3                       Park   \n",
       "80   Central Toronto               3                Coffee Shop   \n",
       "81  Downtown Toronto               3           Airport Terminal   \n",
       "82         Etobicoke               3                       Café   \n",
       "\n",
       "            2nd Most Common Venue   3rd Most Common Venue  \\\n",
       "0                     Yoga Studio      Falafel Restaurant   \n",
       "1            Gym / Fitness Center                    Café   \n",
       "3                  Clothing Store                    Café   \n",
       "4             Japanese Restaurant                     Pub   \n",
       "5                            Bank     Dumpling Restaurant   \n",
       "6                   Moving Target             Yoga Studio   \n",
       "7                     Coffee Shop        Asian Restaurant   \n",
       "8                  Cosmetics Shop            Skating Rink   \n",
       "9                            Café              Restaurant   \n",
       "10                          Field            Hockey Arena   \n",
       "12              Electronics Store          Medical Center   \n",
       "14                   Cocktail Bar              Restaurant   \n",
       "15                       Pharmacy    Fast Food Restaurant   \n",
       "16              Korean Restaurant             Yoga Studio   \n",
       "17            Sporting Goods Shop            Burger Joint   \n",
       "18                           Café      Italian Restaurant   \n",
       "19                  Grocery Store                    Park   \n",
       "20                Thai Restaurant    Caribbean Restaurant   \n",
       "21       Mediterranean Restaurant                 Dog Run   \n",
       "22                  Shopping Mall             Pizza Place   \n",
       "23                    Yoga Studio             Supermarket   \n",
       "24                           Café         Thai Restaurant   \n",
       "25                       Pharmacy             Supermarket   \n",
       "26                    Yoga Studio        Department Store   \n",
       "27           Fast Food Restaurant             Coffee Shop   \n",
       "28                    Coffee Shop  Furniture / Home Store   \n",
       "29                    Coffee Shop                    Park   \n",
       "30                          Hotel             Pizza Place   \n",
       "31                           Café              Restaurant   \n",
       "32             Chinese Restaurant           Train Station   \n",
       "..                            ...                     ...   \n",
       "43                           Park                  Bakery   \n",
       "44                    Yoga Studio    Fast Food Restaurant   \n",
       "45                          Motel      Falafel Restaurant   \n",
       "46                    Yoga Studio     Dumpling Restaurant   \n",
       "47                     Food Truck          Baseball Field   \n",
       "48                    Coffee Shop      Italian Restaurant   \n",
       "52                           Café            Skating Rink   \n",
       "54           Gym / Fitness Center           Grocery Store   \n",
       "55                    Swim School                Bus Line   \n",
       "57                  Grocery Store             Pizza Place   \n",
       "60                           Bank             Yoga Studio   \n",
       "61                    Pizza Place          Breakfast Spot   \n",
       "62               Sushi Restaurant                   Trail   \n",
       "64             Chinese Restaurant          Sandwich Place   \n",
       "65  Paper / Office Supplies Store          Sandwich Place   \n",
       "66                  Grocery Store             Pizza Place   \n",
       "69                      Gift Shop            Dessert Shop   \n",
       "70                    Coffee Shop    Gym / Fitness Center   \n",
       "71                    Pizza Place       Mobile Phone Shop   \n",
       "72                   Skating Rink          Breakfast Spot   \n",
       "73                 Sandwich Place             Pizza Place   \n",
       "74                      Bookstore             Coffee Shop   \n",
       "75                    Pizza Place                    Café   \n",
       "76                   Noodle House     Fried Chicken Joint   \n",
       "77                            Gym                    Park   \n",
       "78                            Bar      Chinese Restaurant   \n",
       "79                     Playground             Yoga Studio   \n",
       "80                            Pub          Medical Center   \n",
       "81                 Airport Lounge         Airport Service   \n",
       "82                            Gym             Flower Shop   \n",
       "\n",
       "            4th Most Common Venue          5th Most Common Venue  \n",
       "0                     Event Space           Ethiopian Restaurant  \n",
       "1            Caribbean Restaurant                 Baseball Field  \n",
       "3                  Cosmetics Shop      Middle Eastern Restaurant  \n",
       "4                          Bakery               Doner Restaurant  \n",
       "5                           Diner                 Discount Store  \n",
       "6                           Diner                 Discount Store  \n",
       "7                      Beer Store               Storage Facility  \n",
       "8                      Beer Store                            Spa  \n",
       "9                           Hotel                      Gastropub  \n",
       "10                          Trail                    Yoga Studio  \n",
       "12                    Pizza Place                 Breakfast Spot  \n",
       "14             Seafood Restaurant                     Steakhouse  \n",
       "15                         Market                  Women's Store  \n",
       "16            Dumpling Restaurant                          Diner  \n",
       "17                  Grocery Store                  Smoothie Shop  \n",
       "18                 Sandwich Place                   Burger Joint  \n",
       "19                     Baby Store                    Coffee Shop  \n",
       "20                           Bank                         Bakery  \n",
       "21                    Golf Course                    Yoga Studio  \n",
       "22               Sushi Restaurant      Middle Eastern Restaurant  \n",
       "23                   Liquor Store                 Discount Store  \n",
       "24                     Steakhouse            American Restaurant  \n",
       "25           Gym / Fitness Center                           Park  \n",
       "26                    Event Space           Ethiopian Restaurant  \n",
       "27                    Bus Station                     Restaurant  \n",
       "28                            Bar                    Yoga Studio  \n",
       "29            Dumpling Restaurant                          Diner  \n",
       "30                           Café                       Aquarium  \n",
       "31                    Coffee Shop  Vegetarian / Vegan Restaurant  \n",
       "32                    Bus Station               Department Store  \n",
       "..                            ...                            ...  \n",
       "43     Construction & Landscaping    Eastern European Restaurant  \n",
       "44             Falafel Restaurant                    Event Space  \n",
       "45                    Event Space           Ethiopian Restaurant  \n",
       "46             Dim Sum Restaurant                          Diner  \n",
       "47                    Yoga Studio            Dumpling Restaurant  \n",
       "48                         Bakery            American Restaurant  \n",
       "52          General Entertainment                    Yoga Studio  \n",
       "54                 Discount Store                   Liquor Store  \n",
       "55             Dim Sum Restaurant                   Dessert Shop  \n",
       "57                         Bakery                    Yoga Studio  \n",
       "60            Dumpling Restaurant                          Diner  \n",
       "61                   Burger Joint                 Sandwich Place  \n",
       "62                  Jewelry Store               Department Store  \n",
       "64      Middle Eastern Restaurant                   Intersection  \n",
       "65                 Breakfast Spot                  Shopping Mall  \n",
       "66                        Butcher                       Pharmacy  \n",
       "69                     Restaurant                      Bookstore  \n",
       "70            American Restaurant                  Burrito Place  \n",
       "71                    Yoga Studio               Doner Restaurant  \n",
       "72                 Sandwich Place                    Yoga Studio  \n",
       "73                    Coffee Shop                           Café  \n",
       "74                            Bar            Japanese Restaurant  \n",
       "75               Sushi Restaurant             Italian Restaurant  \n",
       "76                       Pharmacy                Thai Restaurant  \n",
       "77                     Playground                          Trail  \n",
       "78  Vegetarian / Vegan Restaurant                         Bakery  \n",
       "79                     Donut Shop             Dim Sum Restaurant  \n",
       "80            American Restaurant               Sushi Restaurant  \n",
       "81                  Boat or Ferry                          Plane  \n",
       "82                     Restaurant            Fried Chicken Joint  \n",
       "\n",
       "[67 rows x 7 columns]"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged.loc[toronto_merged['Cluster Labels'] == 3, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 5\n",
    "### Sporting needs can be met here (Sporting goods shop, rock climbing spot, yoga studio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>East York</td>\n",
       "      <td>4</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Rock Climbing Spot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Sporting Goods Shop</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Grocery Store</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "            Borough  Cluster Labels 1st Most Common Venue  \\\n",
       "2         East York               4  Fast Food Restaurant   \n",
       "67  Central Toronto               4        Clothing Store   \n",
       "\n",
       "   2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "2            Pizza Place             Gastropub              Pharmacy   \n",
       "67   Sporting Goods Shop           Coffee Shop           Yoga Studio   \n",
       "\n",
       "   5th Most Common Venue  \n",
       "2     Rock Climbing Spot  \n",
       "67         Grocery Store  "
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toronto_merged.loc[toronto_merged['Cluster Labels'] == 4, toronto_merged.columns[[1] + list(range(5, toronto_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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