Week3 Question3 Segmenting_and Clustering Neighborhoods in Toronto clusters.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "JupyterNotebook_Week3_Question3_Segmenting and Clustering Neighborhoods in Toronto_clusters.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.5"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yqQJicRedbiP",
        "colab_type": "text"
      },
      "source": [
        "#### Load the dataframe of Toronto postalcode and coordinates"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PddRxRcodbiR",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import folium\n",
        "import requests\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.cm as cm\n",
        "import matplotlib.colors as colors\n",
        "\n",
        "from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe\n",
        "from geopy.geocoders import Nominatim # convert an address into latitude and longitude values\n",
        "from sklearn.cluster import KMeans"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t6wto4OYdbiX",
        "colab_type": "code",
        "colab": {},
        "outputId": "897911b2-c73c-4d2f-8393-06701595f0c5"
      },
      "source": [
        "df = pd.read_csv(\"https://ibm.box.com/shared/static/9afzr83pps4pwf2smjjcf1y5mvgb18rr.csv\")\n",
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Postcode</th>\n",
              "      <th>Borough</th>\n",
              "      <th>Neighbourhood</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>Scarborough</td>\n",
              "      <td>Rouge,Malvern</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>Scarborough</td>\n",
              "      <td>Highland Creek,Rouge Hill,Port Union</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>Scarborough</td>\n",
              "      <td>Guildwood,Morningside,West Hill</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>Scarborough</td>\n",
              "      <td>Woburn</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>Scarborough</td>\n",
              "      <td>Cedarbrae</td>\n",
              "      <td>43.773136</td>\n",
              "      <td>-79.239476</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Postcode      Borough                         Neighbourhood   Latitude  \\\n",
              "0      M1B  Scarborough                         Rouge,Malvern  43.806686   \n",
              "1      M1C  Scarborough  Highland Creek,Rouge Hill,Port Union  43.784535   \n",
              "2      M1E  Scarborough       Guildwood,Morningside,West Hill  43.763573   \n",
              "3      M1G  Scarborough                                Woburn  43.770992   \n",
              "4      M1H  Scarborough                             Cedarbrae  43.773136   \n",
              "\n",
              "   Longitude  \n",
              "0 -79.194353  \n",
              "1 -79.160497  \n",
              "2 -79.188711  \n",
              "3 -79.216917  \n",
              "4 -79.239476  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": false,
        "id": "Kzep3CD6dbif",
        "colab_type": "code",
        "colab": {},
        "outputId": "76a240c8-fbd3-4892-ed59-2cbcf8bb8097"
      },
      "source": [
        "# get the number and the name of distinct borough\n",
        "print(len(df['Borough'].unique()), df['Borough'].unique().tolist())"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "11 ['Scarborough', 'North York', 'East York', 'East Toronto', 'Central Toronto', 'Downtown Toronto', 'York', 'West Toronto', \"Queen's Park\", 'Mississauga', 'Etobicoke']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TeMfakpPdbik",
        "colab_type": "text"
      },
      "source": [
        "#### We will work with only boroughs that contain the word Toronto"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YAw7V2Jvdbil",
        "colab_type": "code",
        "colab": {},
        "outputId": "d669bebc-3fd3-42c4-d4c8-e466b6293446"
      },
      "source": [
        "toronto_data = df[df['Borough'].str.contains('Toronto')].reset_index(drop=True)\n",
        "toronto_data.shape"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(38, 5)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l2UO4avodbio",
        "colab_type": "text"
      },
      "source": [
        "#### Create a map of Toronto with neighborhoods"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3KPWQBXddbip",
        "colab_type": "code",
        "colab": {},
        "outputId": "b4f964bc-aaae-43e0-cb7c-9f85b2a73e3a"
      },
      "source": [
        "address = 'Toronto, CA'\n",
        "\n",
        "geolocator = Nominatim(user_agent=\"ny_explorer\")\n",
        "location = geolocator.geocode(address)\n",
        "latitude = location.latitude\n",
        "longitude = location.longitude\n",
        "print('The geograpical coordinate of Toronto are {}, {}.'.format(latitude, longitude))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The geograpical coordinate of Toronto are 43.653963, -79.387207.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bp_BeVXWdbis",
        "colab_type": "code",
        "colab": {},
        "outputId": "69b4ad8f-b0ac-4274-fd4e-d2dc112e3d02"
      },
      "source": [
        "# create map of Toronto using latitude and longitude values\n",
        "map_Toronto = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
        "\n",
        "# add markers to map\n",
        "for lat, lng, label in zip(toronto_data['Latitude'], toronto_data['Longitude'], toronto_data['Neighbourhood']):\n",
        "    label = folium.Popup(label, parse_html=True)\n",
        "    folium.CircleMarker(\n",
        "        [lat, lng],\n",
        "        radius=5,\n",
        "        popup=label,\n",
        "        color='blue',\n",
        "        fill=True,\n",
        "        fill_color='#3186cc',\n",
        "        fill_opacity=0.7,\n",
        "        parse_html=False).add_to(map_Toronto)  \n",
        "    \n",
        "map_Toronto"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    
        <script>
            L_NO_TOUCH = false;
            L_DISABLE_3D = false;
        </script>
    
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.js"></script>
    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
    <link rel="stylesheet" href="https://rawcdn.githack.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css"/>
    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
    
            <meta name="viewport" content="width=device-width,
                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
            <style>
                #map_d5c6e8fb4e2c4da6bf837209cfc71adc {
                    position: relative;
                    width: 100.0%;
                    height: 100.0%;
                    left: 0.0%;
                    top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_d5c6e8fb4e2c4da6bf837209cfc71adc" ></div>
        
</body>
<script>    
    
            var map_d5c6e8fb4e2c4da6bf837209cfc71adc = L.map(
                "map_d5c6e8fb4e2c4da6bf837209cfc71adc",
                {
                    center: [43.653963, -79.387207],
                    crs: L.CRS.EPSG3857,
                    zoom: 12,
                    zoomControl: true,
                    preferCanvas: false,
                }
            );

            

        
    
            var tile_layer_ffa328104f0f459f978ce1419d1b3b4c = L.tileLayer(
                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
                {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
            var circle_marker_eff5943918e4441bb9d50b194c98e404 = L.circleMarker(
                [43.67635739999999, -79.2930312],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b4c37f91f16940b292c416b8426f8965 = L.popup({"maxWidth": "100%"});

        
            var html_7df70b901a4042fd9025e068eac1b647 = $(`<div id="html_7df70b901a4042fd9025e068eac1b647" style="width: 100.0%; height: 100.0%;">The Beaches</div>`)[0];
            popup_b4c37f91f16940b292c416b8426f8965.setContent(html_7df70b901a4042fd9025e068eac1b647);
        

        circle_marker_eff5943918e4441bb9d50b194c98e404.bindPopup(popup_b4c37f91f16940b292c416b8426f8965)
        ;

        
    
    
            var circle_marker_44f3f54f573b4d848e42f50568bcedf5 = L.circleMarker(
                [43.6795571, -79.352188],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_cf4caf67431a4ea39264cfbd1612f29c = L.popup({"maxWidth": "100%"});

        
            var html_fe65eeb5207244919aeab4567dc2e069 = $(`<div id="html_fe65eeb5207244919aeab4567dc2e069" style="width: 100.0%; height: 100.0%;">The Danforth West,Riverdale</div>`)[0];
            popup_cf4caf67431a4ea39264cfbd1612f29c.setContent(html_fe65eeb5207244919aeab4567dc2e069);
        

        circle_marker_44f3f54f573b4d848e42f50568bcedf5.bindPopup(popup_cf4caf67431a4ea39264cfbd1612f29c)
        ;

        
    
    
            var circle_marker_422b5df04933453387168918a5736c45 = L.circleMarker(
                [43.6689985, -79.31557159999998],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_f5a0b3aae1714db68bf5c6c353e8d84b = L.popup({"maxWidth": "100%"});

        
            var html_bf04f9ae26f343b589976b8b7cd5fbaf = $(`<div id="html_bf04f9ae26f343b589976b8b7cd5fbaf" style="width: 100.0%; height: 100.0%;">The Beaches West,India Bazaar</div>`)[0];
            popup_f5a0b3aae1714db68bf5c6c353e8d84b.setContent(html_bf04f9ae26f343b589976b8b7cd5fbaf);
        

        circle_marker_422b5df04933453387168918a5736c45.bindPopup(popup_f5a0b3aae1714db68bf5c6c353e8d84b)
        ;

        
    
    
            var circle_marker_1bf950130082466ca5e4619940bb6bbe = L.circleMarker(
                [43.6595255, -79.340923],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_17cc55b6d76e4bce8c64578e3abc602e = L.popup({"maxWidth": "100%"});

        
            var html_093c5529688841efb8ec350f1727690d = $(`<div id="html_093c5529688841efb8ec350f1727690d" style="width: 100.0%; height: 100.0%;">Studio District</div>`)[0];
            popup_17cc55b6d76e4bce8c64578e3abc602e.setContent(html_093c5529688841efb8ec350f1727690d);
        

        circle_marker_1bf950130082466ca5e4619940bb6bbe.bindPopup(popup_17cc55b6d76e4bce8c64578e3abc602e)
        ;

        
    
    
            var circle_marker_95927dd46f52407eb160f331571702ce = L.circleMarker(
                [43.7280205, -79.3887901],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b68f6a2fdf074d99a586117885f215a1 = L.popup({"maxWidth": "100%"});

        
            var html_49402621f0c345be859dacfbd0dcf46a = $(`<div id="html_49402621f0c345be859dacfbd0dcf46a" style="width: 100.0%; height: 100.0%;">Lawrence Park</div>`)[0];
            popup_b68f6a2fdf074d99a586117885f215a1.setContent(html_49402621f0c345be859dacfbd0dcf46a);
        

        circle_marker_95927dd46f52407eb160f331571702ce.bindPopup(popup_b68f6a2fdf074d99a586117885f215a1)
        ;

        
    
    
            var circle_marker_9e185ef0c93e4ccf9d05cebb4b6bd311 = L.circleMarker(
                [43.7127511, -79.3901975],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_54be3751f48448099dd284224284c2be = L.popup({"maxWidth": "100%"});

        
            var html_b2fe01088e33424bbade8403a02a5376 = $(`<div id="html_b2fe01088e33424bbade8403a02a5376" style="width: 100.0%; height: 100.0%;">Davisville North</div>`)[0];
            popup_54be3751f48448099dd284224284c2be.setContent(html_b2fe01088e33424bbade8403a02a5376);
        

        circle_marker_9e185ef0c93e4ccf9d05cebb4b6bd311.bindPopup(popup_54be3751f48448099dd284224284c2be)
        ;

        
    
    
            var circle_marker_f3d4492b2d5747d19f1e44a7d3f72af6 = L.circleMarker(
                [43.7153834, -79.40567840000001],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_56db53a630834d9f92d8ea46b33daaa1 = L.popup({"maxWidth": "100%"});

        
            var html_214b7662b8c54d619c7001324e1e8393 = $(`<div id="html_214b7662b8c54d619c7001324e1e8393" style="width: 100.0%; height: 100.0%;">North Toronto West</div>`)[0];
            popup_56db53a630834d9f92d8ea46b33daaa1.setContent(html_214b7662b8c54d619c7001324e1e8393);
        

        circle_marker_f3d4492b2d5747d19f1e44a7d3f72af6.bindPopup(popup_56db53a630834d9f92d8ea46b33daaa1)
        ;

        
    
    
            var circle_marker_6a4c545b865e4c29a21f80f454700290 = L.circleMarker(
                [43.7043244, -79.3887901],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_fe199efd96254792865544dde912f165 = L.popup({"maxWidth": "100%"});

        
            var html_6b4f5946b6d94782b01f8e08cffa2cdd = $(`<div id="html_6b4f5946b6d94782b01f8e08cffa2cdd" style="width: 100.0%; height: 100.0%;">Davisville</div>`)[0];
            popup_fe199efd96254792865544dde912f165.setContent(html_6b4f5946b6d94782b01f8e08cffa2cdd);
        

        circle_marker_6a4c545b865e4c29a21f80f454700290.bindPopup(popup_fe199efd96254792865544dde912f165)
        ;

        
    
    
            var circle_marker_9a0c618551b040a3852e35e8fb78568a = L.circleMarker(
                [43.6895743, -79.38315990000002],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_7c7cb5fc7fe24082a2f7c6a014140f9d = L.popup({"maxWidth": "100%"});

        
            var html_c7f714f92e354fab9ada13ce822c74d6 = $(`<div id="html_c7f714f92e354fab9ada13ce822c74d6" style="width: 100.0%; height: 100.0%;">Moore Park,Summerhill East</div>`)[0];
            popup_7c7cb5fc7fe24082a2f7c6a014140f9d.setContent(html_c7f714f92e354fab9ada13ce822c74d6);
        

        circle_marker_9a0c618551b040a3852e35e8fb78568a.bindPopup(popup_7c7cb5fc7fe24082a2f7c6a014140f9d)
        ;

        
    
    
            var circle_marker_48d90eee3b664d1b8d8fc04ea048c0bd = L.circleMarker(
                [43.68641229999999, -79.4000493],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_ff4a4712f83649a49758a21e4afe9fd1 = L.popup({"maxWidth": "100%"});

        
            var html_c7df5100ffa54fb2bf9bbbe35ee26a99 = $(`<div id="html_c7df5100ffa54fb2bf9bbbe35ee26a99" style="width: 100.0%; height: 100.0%;">Deer Park,Forest Hill SE,Rathnelly,South Hill,Summerhill West</div>`)[0];
            popup_ff4a4712f83649a49758a21e4afe9fd1.setContent(html_c7df5100ffa54fb2bf9bbbe35ee26a99);
        

        circle_marker_48d90eee3b664d1b8d8fc04ea048c0bd.bindPopup(popup_ff4a4712f83649a49758a21e4afe9fd1)
        ;

        
    
    
            var circle_marker_86a690a8f40c4ef2a40d0ded0628b607 = L.circleMarker(
                [43.6795626, -79.37752940000001],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_8a478a301a2d4838ac4561586406b810 = L.popup({"maxWidth": "100%"});

        
            var html_5c68f8f3eb6c4866ad5d95d0c68088b0 = $(`<div id="html_5c68f8f3eb6c4866ad5d95d0c68088b0" style="width: 100.0%; height: 100.0%;">Rosedale</div>`)[0];
            popup_8a478a301a2d4838ac4561586406b810.setContent(html_5c68f8f3eb6c4866ad5d95d0c68088b0);
        

        circle_marker_86a690a8f40c4ef2a40d0ded0628b607.bindPopup(popup_8a478a301a2d4838ac4561586406b810)
        ;

        
    
    
            var circle_marker_1e21798a69894e5e990a3cf5847ac2db = L.circleMarker(
                [43.667967, -79.3676753],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_23bd868a867048aab48941c654fd2e79 = L.popup({"maxWidth": "100%"});

        
            var html_f651aba617884161bf65975f5b3c2573 = $(`<div id="html_f651aba617884161bf65975f5b3c2573" style="width: 100.0%; height: 100.0%;">Cabbagetown,St. James Town</div>`)[0];
            popup_23bd868a867048aab48941c654fd2e79.setContent(html_f651aba617884161bf65975f5b3c2573);
        

        circle_marker_1e21798a69894e5e990a3cf5847ac2db.bindPopup(popup_23bd868a867048aab48941c654fd2e79)
        ;

        
    
    
            var circle_marker_f0fb27be526345489e3ac7b575c4aed3 = L.circleMarker(
                [43.6658599, -79.38315990000002],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_9f6d14379ad143cba39d0bb3504fc741 = L.popup({"maxWidth": "100%"});

        
            var html_ca2a3d48f53b4220950cd7f86ab98869 = $(`<div id="html_ca2a3d48f53b4220950cd7f86ab98869" style="width: 100.0%; height: 100.0%;">Church and Wellesley</div>`)[0];
            popup_9f6d14379ad143cba39d0bb3504fc741.setContent(html_ca2a3d48f53b4220950cd7f86ab98869);
        

        circle_marker_f0fb27be526345489e3ac7b575c4aed3.bindPopup(popup_9f6d14379ad143cba39d0bb3504fc741)
        ;

        
    
    
            var circle_marker_7a598c2c95fe43118086c97ea8823114 = L.circleMarker(
                [43.6542599, -79.3606359],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b4dedf31885e4294acdda118ebee8f44 = L.popup({"maxWidth": "100%"});

        
            var html_fd28f571e5a448b7a4af2612c1533a57 = $(`<div id="html_fd28f571e5a448b7a4af2612c1533a57" style="width: 100.0%; height: 100.0%;">Harbourfront,Regent Park</div>`)[0];
            popup_b4dedf31885e4294acdda118ebee8f44.setContent(html_fd28f571e5a448b7a4af2612c1533a57);
        

        circle_marker_7a598c2c95fe43118086c97ea8823114.bindPopup(popup_b4dedf31885e4294acdda118ebee8f44)
        ;

        
    
    
            var circle_marker_3325afe4424847a59c3bd8db59ea1cdf = L.circleMarker(
                [43.6571618, -79.37893709999999],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_95b9ef9eba224bf0a3a2ff60fe604054 = L.popup({"maxWidth": "100%"});

        
            var html_5518041cc77543c89b43abce1e51812d = $(`<div id="html_5518041cc77543c89b43abce1e51812d" style="width: 100.0%; height: 100.0%;">Ryerson,Garden District</div>`)[0];
            popup_95b9ef9eba224bf0a3a2ff60fe604054.setContent(html_5518041cc77543c89b43abce1e51812d);
        

        circle_marker_3325afe4424847a59c3bd8db59ea1cdf.bindPopup(popup_95b9ef9eba224bf0a3a2ff60fe604054)
        ;

        
    
    
            var circle_marker_37ce366af4ff4beab8dc16b47e71add8 = L.circleMarker(
                [43.6514939, -79.3754179],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_d1c4ca638496479eab9e41faf595c0e4 = L.popup({"maxWidth": "100%"});

        
            var html_e0e76e60c2d049a18d3944a4c1e69ad7 = $(`<div id="html_e0e76e60c2d049a18d3944a4c1e69ad7" style="width: 100.0%; height: 100.0%;">St. James Town</div>`)[0];
            popup_d1c4ca638496479eab9e41faf595c0e4.setContent(html_e0e76e60c2d049a18d3944a4c1e69ad7);
        

        circle_marker_37ce366af4ff4beab8dc16b47e71add8.bindPopup(popup_d1c4ca638496479eab9e41faf595c0e4)
        ;

        
    
    
            var circle_marker_e20d2850981b41d1b8224519b4ddbad2 = L.circleMarker(
                [43.6447708, -79.3733064],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_5558f77beb5e40769d57361000c1d330 = L.popup({"maxWidth": "100%"});

        
            var html_1ad6ff5fcbc34f0d9c6ca0b28fc5ad4f = $(`<div id="html_1ad6ff5fcbc34f0d9c6ca0b28fc5ad4f" style="width: 100.0%; height: 100.0%;">Berczy Park</div>`)[0];
            popup_5558f77beb5e40769d57361000c1d330.setContent(html_1ad6ff5fcbc34f0d9c6ca0b28fc5ad4f);
        

        circle_marker_e20d2850981b41d1b8224519b4ddbad2.bindPopup(popup_5558f77beb5e40769d57361000c1d330)
        ;

        
    
    
            var circle_marker_de075bff9c1849a6985a66fa5e038de4 = L.circleMarker(
                [43.6579524, -79.3873826],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_e14a7d6563e8406885fd053e5dc25269 = L.popup({"maxWidth": "100%"});

        
            var html_269728f0ee724f2295782f510a96c27a = $(`<div id="html_269728f0ee724f2295782f510a96c27a" style="width: 100.0%; height: 100.0%;">Central Bay Street</div>`)[0];
            popup_e14a7d6563e8406885fd053e5dc25269.setContent(html_269728f0ee724f2295782f510a96c27a);
        

        circle_marker_de075bff9c1849a6985a66fa5e038de4.bindPopup(popup_e14a7d6563e8406885fd053e5dc25269)
        ;

        
    
    
            var circle_marker_1d0d4cdbc60c440d9e2c61d8907350f6 = L.circleMarker(
                [43.65057120000001, -79.3845675],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_e70f2d5cd8b94be98ee6801216b6d6bc = L.popup({"maxWidth": "100%"});

        
            var html_d0c67618bdba4f5a8b1bb62882f233f9 = $(`<div id="html_d0c67618bdba4f5a8b1bb62882f233f9" style="width: 100.0%; height: 100.0%;">Adelaide,King,Richmond</div>`)[0];
            popup_e70f2d5cd8b94be98ee6801216b6d6bc.setContent(html_d0c67618bdba4f5a8b1bb62882f233f9);
        

        circle_marker_1d0d4cdbc60c440d9e2c61d8907350f6.bindPopup(popup_e70f2d5cd8b94be98ee6801216b6d6bc)
        ;

        
    
    
            var circle_marker_709cbc8812b44142bcaeb09583c64cff = L.circleMarker(
                [43.6408157, -79.38175229999997],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b3d7c24467c344dc8fd0babff4ffff41 = L.popup({"maxWidth": "100%"});

        
            var html_30a3761c4ea44bb0a612876f5a145ce5 = $(`<div id="html_30a3761c4ea44bb0a612876f5a145ce5" style="width: 100.0%; height: 100.0%;">Harbourfront East,Toronto Islands,Union Station</div>`)[0];
            popup_b3d7c24467c344dc8fd0babff4ffff41.setContent(html_30a3761c4ea44bb0a612876f5a145ce5);
        

        circle_marker_709cbc8812b44142bcaeb09583c64cff.bindPopup(popup_b3d7c24467c344dc8fd0babff4ffff41)
        ;

        
    
    
            var circle_marker_b63a5ce0054d4cb1beb93a12ed47a935 = L.circleMarker(
                [43.6471768, -79.38157640000001],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_5a35dc3cff2c4c84b4d2451412a0f9c5 = L.popup({"maxWidth": "100%"});

        
            var html_d606304125d64d67a5b5f1da8d2006a9 = $(`<div id="html_d606304125d64d67a5b5f1da8d2006a9" style="width: 100.0%; height: 100.0%;">Design Exchange,Toronto Dominion Centre</div>`)[0];
            popup_5a35dc3cff2c4c84b4d2451412a0f9c5.setContent(html_d606304125d64d67a5b5f1da8d2006a9);
        

        circle_marker_b63a5ce0054d4cb1beb93a12ed47a935.bindPopup(popup_5a35dc3cff2c4c84b4d2451412a0f9c5)
        ;

        
    
    
            var circle_marker_9cb70ef953904978acc71bebb1724c72 = L.circleMarker(
                [43.6481985, -79.37981690000002],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_80db32e338544065ad6a1b3bf15d1621 = L.popup({"maxWidth": "100%"});

        
            var html_c318ebc7f7144e25bee3a1176695311c = $(`<div id="html_c318ebc7f7144e25bee3a1176695311c" style="width: 100.0%; height: 100.0%;">Commerce Court,Victoria Hotel</div>`)[0];
            popup_80db32e338544065ad6a1b3bf15d1621.setContent(html_c318ebc7f7144e25bee3a1176695311c);
        

        circle_marker_9cb70ef953904978acc71bebb1724c72.bindPopup(popup_80db32e338544065ad6a1b3bf15d1621)
        ;

        
    
    
            var circle_marker_ce5eda85cf694322996b9095e5b5e045 = L.circleMarker(
                [43.7116948, -79.41693559999999],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_38baa1cfb6154d99a38041e3a80f627f = L.popup({"maxWidth": "100%"});

        
            var html_6cc9c8169432483ea4e323703361557c = $(`<div id="html_6cc9c8169432483ea4e323703361557c" style="width: 100.0%; height: 100.0%;">Roselawn</div>`)[0];
            popup_38baa1cfb6154d99a38041e3a80f627f.setContent(html_6cc9c8169432483ea4e323703361557c);
        

        circle_marker_ce5eda85cf694322996b9095e5b5e045.bindPopup(popup_38baa1cfb6154d99a38041e3a80f627f)
        ;

        
    
    
            var circle_marker_0804233079e3432390fbc55504c5fb9b = L.circleMarker(
                [43.6969476, -79.41130720000002],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_3c791ae7ff594f3581ecf92e73948f1a = L.popup({"maxWidth": "100%"});

        
            var html_a9b34c93b1f04a3c9b2fe6b9eda2e02f = $(`<div id="html_a9b34c93b1f04a3c9b2fe6b9eda2e02f" style="width: 100.0%; height: 100.0%;">Forest Hill North,Forest Hill West</div>`)[0];
            popup_3c791ae7ff594f3581ecf92e73948f1a.setContent(html_a9b34c93b1f04a3c9b2fe6b9eda2e02f);
        

        circle_marker_0804233079e3432390fbc55504c5fb9b.bindPopup(popup_3c791ae7ff594f3581ecf92e73948f1a)
        ;

        
    
    
            var circle_marker_8f7b09ad0a804b849aabf38723e0ae7d = L.circleMarker(
                [43.6727097, -79.40567840000001],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_c6c1d77fa18a403c95d8e4638c493432 = L.popup({"maxWidth": "100%"});

        
            var html_e7c9a12e4f104ca3a9cedc5884b427a2 = $(`<div id="html_e7c9a12e4f104ca3a9cedc5884b427a2" style="width: 100.0%; height: 100.0%;">The Annex,North Midtown,Yorkville</div>`)[0];
            popup_c6c1d77fa18a403c95d8e4638c493432.setContent(html_e7c9a12e4f104ca3a9cedc5884b427a2);
        

        circle_marker_8f7b09ad0a804b849aabf38723e0ae7d.bindPopup(popup_c6c1d77fa18a403c95d8e4638c493432)
        ;

        
    
    
            var circle_marker_0165c198a6804030817263b4feaad949 = L.circleMarker(
                [43.6626956, -79.4000493],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b09b57d1bd484812b1de7737e7bc1983 = L.popup({"maxWidth": "100%"});

        
            var html_8258fa7e2911463e8a38d986b11d0237 = $(`<div id="html_8258fa7e2911463e8a38d986b11d0237" style="width: 100.0%; height: 100.0%;">Harbord,University of Toronto</div>`)[0];
            popup_b09b57d1bd484812b1de7737e7bc1983.setContent(html_8258fa7e2911463e8a38d986b11d0237);
        

        circle_marker_0165c198a6804030817263b4feaad949.bindPopup(popup_b09b57d1bd484812b1de7737e7bc1983)
        ;

        
    
    
            var circle_marker_96a74f4292084fd989ef745b32d66c32 = L.circleMarker(
                [43.6532057, -79.4000493],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b79a2716584146fda60b237b6ec92f8a = L.popup({"maxWidth": "100%"});

        
            var html_8bba885b2567406789b96c7f17488f6c = $(`<div id="html_8bba885b2567406789b96c7f17488f6c" style="width: 100.0%; height: 100.0%;">Chinatown,Grange Park,Kensington Market</div>`)[0];
            popup_b79a2716584146fda60b237b6ec92f8a.setContent(html_8bba885b2567406789b96c7f17488f6c);
        

        circle_marker_96a74f4292084fd989ef745b32d66c32.bindPopup(popup_b79a2716584146fda60b237b6ec92f8a)
        ;

        
    
    
            var circle_marker_fbf5db3aceb64287a67fb830220a1cba = L.circleMarker(
                [43.6289467, -79.3944199],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_2df16038f35a40fe8b3c039696ab83fb = L.popup({"maxWidth": "100%"});

        
            var html_3cbefbe7e841494fae7efc593144e3c1 = $(`<div id="html_3cbefbe7e841494fae7efc593144e3c1" style="width: 100.0%; height: 100.0%;">CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara</div>`)[0];
            popup_2df16038f35a40fe8b3c039696ab83fb.setContent(html_3cbefbe7e841494fae7efc593144e3c1);
        

        circle_marker_fbf5db3aceb64287a67fb830220a1cba.bindPopup(popup_2df16038f35a40fe8b3c039696ab83fb)
        ;

        
    
    
            var circle_marker_dc4308b31dd84829a3390fcecc9ce3ab = L.circleMarker(
                [43.6464352, -79.37484599999998],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_835beeced18a45ad9050aa95e2684341 = L.popup({"maxWidth": "100%"});

        
            var html_7099e143425e4d869fc3654c9cf9ba53 = $(`<div id="html_7099e143425e4d869fc3654c9cf9ba53" style="width: 100.0%; height: 100.0%;">Stn A PO Boxes 25 The Esplanade</div>`)[0];
            popup_835beeced18a45ad9050aa95e2684341.setContent(html_7099e143425e4d869fc3654c9cf9ba53);
        

        circle_marker_dc4308b31dd84829a3390fcecc9ce3ab.bindPopup(popup_835beeced18a45ad9050aa95e2684341)
        ;

        
    
    
            var circle_marker_30ec07bf3c49415d97514426ae7f9b01 = L.circleMarker(
                [43.6484292, -79.3822802],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_3b7eb47b0c50460b9ac27be7d51ff957 = L.popup({"maxWidth": "100%"});

        
            var html_6b1f701fb1a64b5fbc0c3d4934750a41 = $(`<div id="html_6b1f701fb1a64b5fbc0c3d4934750a41" style="width: 100.0%; height: 100.0%;">First Canadian Place,Underground city</div>`)[0];
            popup_3b7eb47b0c50460b9ac27be7d51ff957.setContent(html_6b1f701fb1a64b5fbc0c3d4934750a41);
        

        circle_marker_30ec07bf3c49415d97514426ae7f9b01.bindPopup(popup_3b7eb47b0c50460b9ac27be7d51ff957)
        ;

        
    
    
            var circle_marker_a9b1c0c38f3c48ca9026a99b24c31160 = L.circleMarker(
                [43.669542, -79.4225637],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_a0400b4d496a46a28916fa9708dc0a9f = L.popup({"maxWidth": "100%"});

        
            var html_1219b4c71425429e9f9248c75a1ef52f = $(`<div id="html_1219b4c71425429e9f9248c75a1ef52f" style="width: 100.0%; height: 100.0%;">Christie</div>`)[0];
            popup_a0400b4d496a46a28916fa9708dc0a9f.setContent(html_1219b4c71425429e9f9248c75a1ef52f);
        

        circle_marker_a9b1c0c38f3c48ca9026a99b24c31160.bindPopup(popup_a0400b4d496a46a28916fa9708dc0a9f)
        ;

        
    
    
            var circle_marker_379e0887912b4705b9afd53cde51aa31 = L.circleMarker(
                [43.66900510000001, -79.4422593],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_85ae3c47e89f4a30a1d76264c76b78f0 = L.popup({"maxWidth": "100%"});

        
            var html_01db5bc2cd8740ff879c46c339ef446d = $(`<div id="html_01db5bc2cd8740ff879c46c339ef446d" style="width: 100.0%; height: 100.0%;">Dovercourt Village,Dufferin</div>`)[0];
            popup_85ae3c47e89f4a30a1d76264c76b78f0.setContent(html_01db5bc2cd8740ff879c46c339ef446d);
        

        circle_marker_379e0887912b4705b9afd53cde51aa31.bindPopup(popup_85ae3c47e89f4a30a1d76264c76b78f0)
        ;

        
    
    
            var circle_marker_07a56c7c860c4f459a2dd59ff33f08ac = L.circleMarker(
                [43.647926700000006, -79.4197497],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_0e17416ae5a74b3cb37ec4cbc30101e5 = L.popup({"maxWidth": "100%"});

        
            var html_e961c4e33bcf4713ab6125de6a3bf319 = $(`<div id="html_e961c4e33bcf4713ab6125de6a3bf319" style="width: 100.0%; height: 100.0%;">Little Portugal,Trinity</div>`)[0];
            popup_0e17416ae5a74b3cb37ec4cbc30101e5.setContent(html_e961c4e33bcf4713ab6125de6a3bf319);
        

        circle_marker_07a56c7c860c4f459a2dd59ff33f08ac.bindPopup(popup_0e17416ae5a74b3cb37ec4cbc30101e5)
        ;

        
    
    
            var circle_marker_106a5e87949c472b9a14c4720f2a818b = L.circleMarker(
                [43.6368472, -79.42819140000002],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_af048f83176743f78e3d127b01d0d243 = L.popup({"maxWidth": "100%"});

        
            var html_bc55b502b05b411aa896054c0a72ebc5 = $(`<div id="html_bc55b502b05b411aa896054c0a72ebc5" style="width: 100.0%; height: 100.0%;">Brockton,Exhibition Place,Parkdale Village</div>`)[0];
            popup_af048f83176743f78e3d127b01d0d243.setContent(html_bc55b502b05b411aa896054c0a72ebc5);
        

        circle_marker_106a5e87949c472b9a14c4720f2a818b.bindPopup(popup_af048f83176743f78e3d127b01d0d243)
        ;

        
    
    
            var circle_marker_069016adbf7b48ccaf7365c8c610701c = L.circleMarker(
                [43.6616083, -79.46476329999999],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_b6baf16b4b6e49d899d357431c615111 = L.popup({"maxWidth": "100%"});

        
            var html_7fc822fb3a5c4d559bdff5d91477d037 = $(`<div id="html_7fc822fb3a5c4d559bdff5d91477d037" style="width: 100.0%; height: 100.0%;">High Park,The Junction South</div>`)[0];
            popup_b6baf16b4b6e49d899d357431c615111.setContent(html_7fc822fb3a5c4d559bdff5d91477d037);
        

        circle_marker_069016adbf7b48ccaf7365c8c610701c.bindPopup(popup_b6baf16b4b6e49d899d357431c615111)
        ;

        
    
    
            var circle_marker_6ada515cde1d45ff9f8cbafbfd3294db = L.circleMarker(
                [43.6489597, -79.456325],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_c83d4b7390304c418df2afcd3d8f635f = L.popup({"maxWidth": "100%"});

        
            var html_e718a1edb69542a38f307565bf8ce35e = $(`<div id="html_e718a1edb69542a38f307565bf8ce35e" style="width: 100.0%; height: 100.0%;">Parkdale,Roncesvalles</div>`)[0];
            popup_c83d4b7390304c418df2afcd3d8f635f.setContent(html_e718a1edb69542a38f307565bf8ce35e);
        

        circle_marker_6ada515cde1d45ff9f8cbafbfd3294db.bindPopup(popup_c83d4b7390304c418df2afcd3d8f635f)
        ;

        
    
    
            var circle_marker_5a7a8e813120471c8d17b444ac55099d = L.circleMarker(
                [43.6515706, -79.4844499],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_a5d35901bf4543eb8f9c20a105549d2a = L.popup({"maxWidth": "100%"});

        
            var html_883da67e2b4a472b8af3987c2ac8bac6 = $(`<div id="html_883da67e2b4a472b8af3987c2ac8bac6" style="width: 100.0%; height: 100.0%;">Runnymede,Swansea</div>`)[0];
            popup_a5d35901bf4543eb8f9c20a105549d2a.setContent(html_883da67e2b4a472b8af3987c2ac8bac6);
        

        circle_marker_5a7a8e813120471c8d17b444ac55099d.bindPopup(popup_a5d35901bf4543eb8f9c20a105549d2a)
        ;

        
    
    
            var circle_marker_ed3fcb474d7b42bfb4356116d44586ab = L.circleMarker(
                [43.6627439, -79.321558],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#3186cc", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_d5c6e8fb4e2c4da6bf837209cfc71adc);
        
    
        var popup_af06b998859d419eacc7fe6f726524f3 = L.popup({"maxWidth": "100%"});

        
            var html_60b7a503e0064f958e07fab6d7d68de4 = $(`<div id="html_60b7a503e0064f958e07fab6d7d68de4" style="width: 100.0%; height: 100.0%;">Business Reply Mail Processing Centre 969 Eastern</div>`)[0];
            popup_af06b998859d419eacc7fe6f726524f3.setContent(html_60b7a503e0064f958e07fab6d7d68de4);
        

        circle_marker_ed3fcb474d7b42bfb4356116d44586ab.bindPopup(popup_af06b998859d419eacc7fe6f726524f3)
        ;

        
    
</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 0xb3a47f0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MuJgfZNidbiv",
        "colab_type": "text"
      },
      "source": [
        "### Define Foursquare credentials"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yp2W1DfCdbiw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# @hidden_cell\n",
        "CLIENT_ID = 'OIHC3A3EBAA5JMV1KF3RIPITTLI3H1WVSMUVAVV4LFWFPJRW' # your Foursquare ID\n",
        "CLIENT_SECRET = 'LGO455ZN0W3KS3KDI5CVWRHSTKHNMZ03ZH0B05QXIFCMIKNW' # your Foursquare Secret\n",
        "VERSION = '20180605' # Foursquare API version\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7PZcocGIdbi0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CcyXv8zadbi4",
        "colab_type": "code",
        "colab": {},
        "outputId": "1f065872-37a4-4277-92f2-4267781c5dd4"
      },
      "source": [
        "LIMIT, radius = 100, 500\n",
        "\n",
        "url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(\n",
        "    CLIENT_ID, \n",
        "    CLIENT_SECRET, \n",
        "    VERSION, \n",
        "    toronto_data.loc[0,'Latitude'], \n",
        "    toronto_data.loc[0,'Longitude'], \n",
        "    radius, \n",
        "    LIMIT)\n",
        "\n",
        "url"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'https://api.foursquare.com/v2/venues/explore?&client_id=OIHC3A3EBAA5JMV1KF3RIPITTLI3H1WVSMUVAVV4LFWFPJRW&client_secret=LGO455ZN0W3KS3KDI5CVWRHSTKHNMZ03ZH0B05QXIFCMIKNW&v=20180605&ll=43.67635739999999,-79.2930312&radius=500&limit=100'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OULPey4qdbi6",
        "colab_type": "code",
        "colab": {},
        "outputId": "bc4b4bfc-f29a-464f-a4b3-081c63b94e1a"
      },
      "source": [
        "results = requests.get(url).json()\n",
        "results"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'meta': {'code': 200, 'requestId': '5ce2dc71f594df57ef2a03ac'},\n",
              " 'response': {'headerLocation': 'The Beaches',\n",
              "  'headerFullLocation': 'The Beaches, Toronto',\n",
              "  'headerLocationGranularity': 'neighborhood',\n",
              "  'totalResults': 5,\n",
              "  'suggestedBounds': {'ne': {'lat': 43.680857404499996,\n",
              "    'lng': -79.28682091449052},\n",
              "   'sw': {'lat': 43.67185739549999, 'lng': -79.29924148550948}},\n",
              "  'groups': [{'type': 'Recommended Places',\n",
              "    'name': 'recommended',\n",
              "    'items': [{'reasons': {'count': 0,\n",
              "       'items': [{'summary': 'This spot is popular',\n",
              "         'type': 'general',\n",
              "         'reasonName': 'globalInteractionReason'}]},\n",
              "      'venue': {'id': '4ad4c062f964a52011f820e3',\n",
              "       'name': 'The Big Carrot Natural Food Market',\n",
              "       'location': {'address': '125 Southwood Dr',\n",
              "        'lat': 43.678879,\n",
              "        'lng': -79.297734,\n",
              "        'labeledLatLngs': [{'label': 'display',\n",
              "          'lat': 43.678879,\n",
              "          'lng': -79.297734}],\n",
              "        'distance': 471,\n",
              "        'postalCode': 'M4E 0B8',\n",
              "        'cc': 'CA',\n",
              "        'city': 'Toronto',\n",
              "        'state': 'ON',\n",
              "        'country': 'Canada',\n",
              "        'formattedAddress': ['125 Southwood Dr',\n",
              "         'Toronto ON M4E 0B8',\n",
              "         'Canada']},\n",
              "       'categories': [{'id': '50aa9e744b90af0d42d5de0e',\n",
              "         'name': 'Health Food Store',\n",
              "         'pluralName': 'Health Food Stores',\n",
              "         'shortName': 'Health Food Store',\n",
              "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/food_grocery_',\n",
              "          'suffix': '.png'},\n",
              "         'primary': True}],\n",
              "       'photos': {'count': 0, 'groups': []},\n",
              "       'venuePage': {'id': '75150878'}},\n",
              "      'referralId': 'e-0-4ad4c062f964a52011f820e3-0'},\n",
              "     {'reasons': {'count': 0,\n",
              "       'items': [{'summary': 'This spot is popular',\n",
              "         'type': 'general',\n",
              "         'reasonName': 'globalInteractionReason'}]},\n",
              "      'venue': {'id': '4b8daea1f964a520480833e3',\n",
              "       'name': 'Grover Pub and Grub',\n",
              "       'location': {'address': '676 Kingston Rd.',\n",
              "        'crossStreet': 'at Main St.',\n",
              "        'lat': 43.679181434941015,\n",
              "        'lng': -79.29721535878515,\n",
              "        'labeledLatLngs': [{'label': 'display',\n",
              "          'lat': 43.679181434941015,\n",
              "          'lng': -79.29721535878515}],\n",
              "        'distance': 460,\n",
              "        'postalCode': 'M4E 1R4',\n",
              "        'cc': 'CA',\n",
              "        'city': 'Toronto',\n",
              "        'state': 'ON',\n",
              "        'country': 'Canada',\n",
              "        'formattedAddress': ['676 Kingston Rd. (at Main St.)',\n",
              "         'Toronto ON M4E 1R4',\n",
              "         'Canada']},\n",
              "       'categories': [{'id': '4bf58dd8d48988d11b941735',\n",
              "         'name': 'Pub',\n",
              "         'pluralName': 'Pubs',\n",
              "         'shortName': 'Pub',\n",
              "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/nightlife/pub_',\n",
              "          'suffix': '.png'},\n",
              "         'primary': True}],\n",
              "       'photos': {'count': 0, 'groups': []}},\n",
              "      'referralId': 'e-0-4b8daea1f964a520480833e3-1'},\n",
              "     {'reasons': {'count': 0,\n",
              "       'items': [{'summary': 'This spot is popular',\n",
              "         'type': 'general',\n",
              "         'reasonName': 'globalInteractionReason'}]},\n",
              "      'venue': {'id': '5c125491ad1789002d4eda71',\n",
              "       'name': 'Guru Raghavendra Ji',\n",
              "       'location': {'address': 'Above RIDA Fashions, Behind PIZZA PIZZA (ALBION & ISLINGTON), Toronto, Canada',\n",
              "        'lat': 43.680186658703796,\n",
              "        'lng': -79.29233729839325,\n",
              "        'labeledLatLngs': [{'label': 'display',\n",
              "          'lat': 43.680186658703796,\n",
              "          'lng': -79.29233729839325}],\n",
              "        'distance': 429,\n",
              "        'postalCode': 'M9V 1A6',\n",
              "        'cc': 'CA',\n",
              "        'city': 'Toronto',\n",
              "        'state': 'ON',\n",
              "        'country': 'Canada',\n",
              "        'formattedAddress': ['Above RIDA Fashions, Behind PIZZA PIZZA (ALBION & ISLINGTON), Toronto, Canada',\n",
              "         'Toronto ON M9V 1A6',\n",
              "         'Canada']},\n",
              "       'categories': [{'id': '52f2ab2ebcbc57f1066b8b43',\n",
              "         'name': 'Astrologer',\n",
              "         'pluralName': 'Astrologers',\n",
              "         'shortName': 'Astrologer',\n",
              "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/default_',\n",
              "          'suffix': '.png'},\n",
              "         'primary': True}],\n",
              "       'photos': {'count': 0, 'groups': []}},\n",
              "      'referralId': 'e-0-5c125491ad1789002d4eda71-2'},\n",
              "     {'reasons': {'count': 0,\n",
              "       'items': [{'summary': 'This spot is popular',\n",
              "         'type': 'general',\n",
              "         'reasonName': 'globalInteractionReason'}]},\n",
              "      'venue': {'id': '4df91c4bae60f95f82229ad5',\n",
              "       'name': 'Upper Beaches',\n",
              "       'location': {'lat': 43.68056321147582,\n",
              "        'lng': -79.2928688743688,\n",
              "        'labeledLatLngs': [{'label': 'display',\n",
              "          'lat': 43.68056321147582,\n",
              "          'lng': -79.2928688743688}],\n",
              "        'distance': 468,\n",
              "        'cc': 'CA',\n",
              "        'city': 'Toronto',\n",
              "        'state': 'ON',\n",
              "        'country': 'Canada',\n",
              "        'formattedAddress': ['Toronto ON', 'Canada']},\n",
              "       'categories': [{'id': '4f2a25ac4b909258e854f55f',\n",
              "         'name': 'Neighborhood',\n",
              "         'pluralName': 'Neighborhoods',\n",
              "         'shortName': 'Neighborhood',\n",
              "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/parks_outdoors/neighborhood_',\n",
              "          'suffix': '.png'},\n",
              "         'primary': True}],\n",
              "       'photos': {'count': 0, 'groups': []}},\n",
              "      'referralId': 'e-0-4df91c4bae60f95f82229ad5-3'},\n",
              "     {'reasons': {'count': 0,\n",
              "       'items': [{'summary': 'This spot is popular',\n",
              "         'type': 'general',\n",
              "         'reasonName': 'globalInteractionReason'}]},\n",
              "      'venue': {'id': '50b53e5ee4b0305cc3ebdfdb',\n",
              "       'name': 'Crazy Sexy Cool',\n",
              "       'location': {'address': '870 Kingston',\n",
              "        'lat': 43.68039105585308,\n",
              "        'lng': -79.29065636468626,\n",
              "        'labeledLatLngs': [{'label': 'display',\n",
              "          'lat': 43.68039105585308,\n",
              "          'lng': -79.29065636468626}],\n",
              "        'distance': 488,\n",
              "        'cc': 'CA',\n",
              "        'city': 'Toronto',\n",
              "        'state': 'ON',\n",
              "        'country': 'Canada',\n",
              "        'formattedAddress': ['870 Kingston', 'Toronto ON', 'Canada']},\n",
              "       'categories': [{'id': '4bf58dd8d48988d104951735',\n",
              "         'name': 'Boutique',\n",
              "         'pluralName': 'Boutiques',\n",
              "         'shortName': 'Boutique',\n",
              "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/apparel_boutique_',\n",
              "          'suffix': '.png'},\n",
              "         'primary': True}],\n",
              "       'photos': {'count': 0, 'groups': []}},\n",
              "      'referralId': 'e-0-50b53e5ee4b0305cc3ebdfdb-4'}]}]}}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K0AcIGCKdbi9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# function that extracts the category of the venue\n",
        "def get_category_type(row):\n",
        "    try:\n",
        "        categories_list = row['categories']\n",
        "    except:\n",
        "        categories_list = row['venue.categories']\n",
        "        \n",
        "    if len(categories_list) == 0:\n",
        "        return None\n",
        "    else:\n",
        "        return categories_list[0]['name']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f-u71ividbi_",
        "colab_type": "code",
        "colab": {},
        "outputId": "7b080481-8f41-407a-b227-72f271c0e8dc"
      },
      "source": [
        "venues = results['response']['groups'][0]['items']\n",
        "    \n",
        "nearby_venues = json_normalize(venues) # flatten JSON\n",
        "\n",
        "# filter columns\n",
        "filtered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']\n",
        "nearby_venues =nearby_venues.loc[:, filtered_columns]\n",
        "\n",
        "# filter the category for each row\n",
        "nearby_venues['venue.categories'] = nearby_venues.apply(get_category_type, axis=1)\n",
        "\n",
        "# clean columns\n",
        "nearby_venues.columns = [col.split(\".\")[-1] for col in nearby_venues.columns]\n",
        "\n",
        "nearby_venues"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>categories</th>\n",
              "      <th>lat</th>\n",
              "      <th>lng</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Big Carrot Natural Food Market</td>\n",
              "      <td>Health Food Store</td>\n",
              "      <td>43.678879</td>\n",
              "      <td>-79.297734</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Grover Pub and Grub</td>\n",
              "      <td>Pub</td>\n",
              "      <td>43.679181</td>\n",
              "      <td>-79.297215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Guru Raghavendra Ji</td>\n",
              "      <td>Astrologer</td>\n",
              "      <td>43.680187</td>\n",
              "      <td>-79.292337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Upper Beaches</td>\n",
              "      <td>Neighborhood</td>\n",
              "      <td>43.680563</td>\n",
              "      <td>-79.292869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Crazy Sexy Cool</td>\n",
              "      <td>Boutique</td>\n",
              "      <td>43.680391</td>\n",
              "      <td>-79.290656</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                 name         categories        lat        lng\n",
              "0  The Big Carrot Natural Food Market  Health Food Store  43.678879 -79.297734\n",
              "1                 Grover Pub and Grub                Pub  43.679181 -79.297215\n",
              "2                 Guru Raghavendra Ji         Astrologer  43.680187 -79.292337\n",
              "3                       Upper Beaches       Neighborhood  43.680563 -79.292869\n",
              "4                     Crazy Sexy Cool           Boutique  43.680391 -79.290656"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NYVbwxcfdbjD",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def getNearbyVenues(names, latitudes, longitudes, radius=500):\n",
        "    \n",
        "    venues_list=[]\n",
        "    for name, lat, lng in zip(names, latitudes, longitudes):\n",
        "        print(name)\n",
        "            \n",
        "        # create the API request URL\n",
        "        url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(\n",
        "            CLIENT_ID, \n",
        "            CLIENT_SECRET, \n",
        "            VERSION, \n",
        "            lat, \n",
        "            lng, \n",
        "            radius, \n",
        "            LIMIT)\n",
        "            \n",
        "        # make the GET request\n",
        "        results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n",
        "        \n",
        "        # return only relevant information for each nearby venue\n",
        "        venues_list.append([(\n",
        "            name, \n",
        "            lat, \n",
        "            lng, \n",
        "            v['venue']['name'], \n",
        "            v['venue']['location']['lat'], \n",
        "            v['venue']['location']['lng'],  \n",
        "            v['venue']['categories'][0]['name']) for v in results])\n",
        "\n",
        "    nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])\n",
        "    nearby_venues.columns = ['Neighbourhood', \n",
        "                  'Neighbourhood Latitude', \n",
        "                  'Neighbourhood Longitude', \n",
        "                  'Venue', \n",
        "                  'Venue Latitude', \n",
        "                  'Venue Longitude', \n",
        "                  'Venue Category']\n",
        "    \n",
        "    return(nearby_venues)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vd1J0qHAdbjI",
        "colab_type": "code",
        "colab": {},
        "outputId": "a8afb108-b1dc-4642-e2c1-7e6484902c74"
      },
      "source": [
        "toronto_venues = getNearbyVenues(toronto_data['Neighbourhood'],toronto_data['Latitude'],toronto_data['Longitude'])\n",
        "toronto_venues.shape"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The Beaches\n",
            "The Danforth West,Riverdale\n",
            "The Beaches West,India Bazaar\n",
            "Studio District\n",
            "Lawrence Park\n",
            "Davisville North\n",
            "North Toronto West\n",
            "Davisville\n",
            "Moore Park,Summerhill East\n",
            "Deer Park,Forest Hill SE,Rathnelly,South Hill,Summerhill West\n",
            "Rosedale\n",
            "Cabbagetown,St. James Town\n",
            "Church and Wellesley\n",
            "Harbourfront,Regent Park\n",
            "Ryerson,Garden District\n",
            "St. James Town\n",
            "Berczy Park\n",
            "Central Bay Street\n",
            "Adelaide,King,Richmond\n",
            "Harbourfront East,Toronto Islands,Union Station\n",
            "Design Exchange,Toronto Dominion Centre\n",
            "Commerce Court,Victoria Hotel\n",
            "Roselawn\n",
            "Forest Hill North,Forest Hill West\n",
            "The Annex,North Midtown,Yorkville\n",
            "Harbord,University of Toronto\n",
            "Chinatown,Grange Park,Kensington Market\n",
            "CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara\n",
            "Stn A PO Boxes 25 The Esplanade\n",
            "First Canadian Place,Underground city\n",
            "Christie\n",
            "Dovercourt Village,Dufferin\n",
            "Little Portugal,Trinity\n",
            "Brockton,Exhibition Place,Parkdale Village\n",
            "High Park,The Junction South\n",
            "Parkdale,Roncesvalles\n",
            "Runnymede,Swansea\n",
            "Business Reply Mail Processing Centre 969 Eastern\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1698, 7)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vBqGe2j0dbjP",
        "colab_type": "code",
        "colab": {},
        "outputId": "31180be6-9e07-4f4d-f1ef-9feff5c8c934"
      },
      "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['Neighbourhood'] = toronto_venues['Neighbourhood'] \n",
        "# move neighborhood column to the first column\n",
        "fixed_columns = [toronto_onehot.columns[-1]] + list(toronto_onehot.columns[:-1])\n",
        "toronto_onehot = toronto_onehot[fixed_columns]\n",
        "\n",
        "toronto_onehot.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Neighbourhood</th>\n",
              "      <th>Adult Boutique</th>\n",
              "      <th>Afghan Restaurant</th>\n",
              "      <th>Airport</th>\n",
              "      <th>Airport Food Court</th>\n",
              "      <th>Airport Gate</th>\n",
              "      <th>Airport Lounge</th>\n",
              "      <th>Airport Service</th>\n",
              "      <th>Airport Terminal</th>\n",
              "      <th>American Restaurant</th>\n",
              "      <th>...</th>\n",
              "      <th>Toy / Game Store</th>\n",
              "      <th>Trail</th>\n",
              "      <th>Train Station</th>\n",
              "      <th>Vegetarian / Vegan Restaurant</th>\n",
              "      <th>Video Game Store</th>\n",
              "      <th>Vietnamese Restaurant</th>\n",
              "      <th>Wine Bar</th>\n",
              "      <th>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>The Beaches</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>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>1</th>\n",
              "      <td>The Beaches</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>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>2</th>\n",
              "      <td>The Beaches</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>The Beaches</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>The Beaches</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 240 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "  Neighbourhood  Adult Boutique  Afghan Restaurant  Airport  \\\n",
              "0   The Beaches               0                  0        0   \n",
              "1   The Beaches               0                  0        0   \n",
              "2   The Beaches               0                  0        0   \n",
              "3   The Beaches               0                  0        0   \n",
              "4   The Beaches               0                  0        0   \n",
              "\n",
              "   Airport Food Court  Airport Gate  Airport Lounge  Airport Service  \\\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 Terminal  American Restaurant     ...       Toy / Game Store  \\\n",
              "0                 0                    0     ...                      0   \n",
              "1                 0                    0     ...                      0   \n",
              "2                 0                    0     ...                      0   \n",
              "3                 0                    0     ...                      0   \n",
              "4                 0                    0     ...                      0   \n",
              "\n",
              "   Trail  Train Station  Vegetarian / Vegan Restaurant  Video Game 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",
              "   Vietnamese Restaurant  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 240 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "667MhxoNdbjU",
        "colab_type": "code",
        "colab": {},
        "outputId": "9a3870c6-16d1-4e96-87fe-69a9b439e522"
      },
      "source": [
        "toronto_grouped = toronto_onehot.groupby('Neighbourhood').mean().reset_index()\n",
        "toronto_grouped"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Neighbourhood</th>\n",
              "      <th>Adult Boutique</th>\n",
              "      <th>Afghan Restaurant</th>\n",
              "      <th>Airport</th>\n",
              "      <th>Airport Food Court</th>\n",
              "      <th>Airport Gate</th>\n",
              "      <th>Airport Lounge</th>\n",
              "      <th>Airport Service</th>\n",
              "      <th>Airport Terminal</th>\n",
              "      <th>American Restaurant</th>\n",
              "      <th>...</th>\n",
              "      <th>Toy / Game Store</th>\n",
              "      <th>Trail</th>\n",
              "      <th>Train Station</th>\n",
              "      <th>Vegetarian / Vegan Restaurant</th>\n",
              "      <th>Video Game Store</th>\n",
              "      <th>Vietnamese Restaurant</th>\n",
              "      <th>Wine Bar</th>\n",
              "      <th>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>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.040000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Berczy Park</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.018182</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Brockton,Exhibition Place,Parkdale Village</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Business Reply Mail Processing Centre 969 Eastern</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.058824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CN Tower,Bathurst Quay,Island airport,Harbourf...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.133333</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.133333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Cabbagetown,St. James Town</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Central Bay Street</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011494</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.011494</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011494</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.011494</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Chinatown,Grange Park,Kensington Market</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.060000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.030000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Christie</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Church and Wellesley</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.011364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Commerce Court,Victoria Hotel</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.040000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Davisville</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.028571</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Davisville North</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Deer Park,Forest Hill SE,Rathnelly,South Hill,...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.062500</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.062500</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Design Exchange,Toronto Dominion Centre</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.030000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Dovercourt Village,Dufferin</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>First Canadian Place,Underground city</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.030000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Forest Hill North,Forest Hill West</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.20000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Harbord,University of Toronto</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.027778</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.027778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Harbourfront East,Toronto Islands,Union Station</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Harbourfront,Regent Park</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.021277</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>High Park,The Junction South</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Lawrence Park</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Little Portugal,Trinity</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.016129</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.032258</td>\n",
              "      <td>0.016129</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.016129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Moore Park,Summerhill East</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>North Toronto West</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.055556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Parkdale,Roncesvalles</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Rosedale</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.25000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Roselawn</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Runnymede,Swansea</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.027778</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Ryerson,Garden District</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>St. James Town</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.020000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Stn A PO Boxes 25 The Esplanade</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.010638</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Studio District</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.054054</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.027027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>The Annex,North Midtown,Yorkville</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.041667</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.041667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>The Beaches</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>The Beaches West,India Bazaar</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>The Danforth West,Riverdale</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.023810</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.02381</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.023810</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>38 rows × 240 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                        Neighbourhood  Adult Boutique  \\\n",
              "0                              Adelaide,King,Richmond        0.000000   \n",
              "1                                         Berczy Park        0.000000   \n",
              "2          Brockton,Exhibition Place,Parkdale Village        0.000000   \n",
              "3   Business Reply Mail Processing Centre 969 Eastern        0.000000   \n",
              "4   CN Tower,Bathurst Quay,Island airport,Harbourf...        0.000000   \n",
              "5                          Cabbagetown,St. James Town        0.000000   \n",
              "6                                  Central Bay Street        0.000000   \n",
              "7             Chinatown,Grange Park,Kensington Market        0.000000   \n",
              "8                                            Christie        0.000000   \n",
              "9                                Church and Wellesley        0.011364   \n",
              "10                      Commerce Court,Victoria Hotel        0.000000   \n",
              "11                                         Davisville        0.000000   \n",
              "12                                   Davisville North        0.000000   \n",
              "13  Deer Park,Forest Hill SE,Rathnelly,South Hill,...        0.000000   \n",
              "14            Design Exchange,Toronto Dominion Centre        0.000000   \n",
              "15                        Dovercourt Village,Dufferin        0.000000   \n",
              "16              First Canadian Place,Underground city        0.000000   \n",
              "17                 Forest Hill North,Forest Hill West        0.000000   \n",
              "18                      Harbord,University of Toronto        0.000000   \n",
              "19    Harbourfront East,Toronto Islands,Union Station        0.000000   \n",
              "20                           Harbourfront,Regent Park        0.000000   \n",
              "21                       High Park,The Junction South        0.000000   \n",
              "22                                      Lawrence Park        0.000000   \n",
              "23                            Little Portugal,Trinity        0.000000   \n",
              "24                         Moore Park,Summerhill East        0.000000   \n",
              "25                                 North Toronto West        0.000000   \n",
              "26                              Parkdale,Roncesvalles        0.000000   \n",
              "27                                           Rosedale        0.000000   \n",
              "28                                           Roselawn        0.000000   \n",
              "29                                  Runnymede,Swansea        0.000000   \n",
              "30                            Ryerson,Garden District        0.000000   \n",
              "31                                     St. James Town        0.000000   \n",
              "32                    Stn A PO Boxes 25 The Esplanade        0.000000   \n",
              "33                                    Studio District        0.000000   \n",
              "34                  The Annex,North Midtown,Yorkville        0.000000   \n",
              "35                                        The Beaches        0.000000   \n",
              "36                      The Beaches West,India Bazaar        0.000000   \n",
              "37                        The Danforth West,Riverdale        0.000000   \n",
              "\n",
              "    Afghan Restaurant   Airport  Airport Food Court  Airport Gate  \\\n",
              "0            0.000000  0.000000            0.000000      0.000000   \n",
              "1            0.000000  0.000000            0.000000      0.000000   \n",
              "2            0.000000  0.000000            0.000000      0.000000   \n",
              "3            0.000000  0.000000            0.000000      0.000000   \n",
              "4            0.000000  0.066667            0.066667      0.066667   \n",
              "5            0.000000  0.000000            0.000000      0.000000   \n",
              "6            0.000000  0.000000            0.000000      0.000000   \n",
              "7            0.000000  0.000000            0.000000      0.000000   \n",
              "8            0.000000  0.000000            0.000000      0.000000   \n",
              "9            0.011364  0.000000            0.000000      0.000000   \n",
              "10           0.000000  0.000000            0.000000      0.000000   \n",
              "11           0.000000  0.000000            0.000000      0.000000   \n",
              "12           0.000000  0.000000            0.000000      0.000000   \n",
              "13           0.000000  0.000000            0.000000      0.000000   \n",
              "14           0.000000  0.000000            0.000000      0.000000   \n",
              "15           0.000000  0.000000            0.000000      0.000000   \n",
              "16           0.000000  0.000000            0.000000      0.000000   \n",
              "17           0.000000  0.000000            0.000000      0.000000   \n",
              "18           0.000000  0.000000            0.000000      0.000000   \n",
              "19           0.000000  0.000000            0.000000      0.000000   \n",
              "20           0.000000  0.000000            0.000000      0.000000   \n",
              "21           0.000000  0.000000            0.000000      0.000000   \n",
              "22           0.000000  0.000000            0.000000      0.000000   \n",
              "23           0.000000  0.000000            0.000000      0.000000   \n",
              "24           0.000000  0.000000            0.000000      0.000000   \n",
              "25           0.000000  0.000000            0.000000      0.000000   \n",
              "26           0.000000  0.000000            0.000000      0.000000   \n",
              "27           0.000000  0.000000            0.000000      0.000000   \n",
              "28           0.000000  0.000000            0.000000      0.000000   \n",
              "29           0.000000  0.000000            0.000000      0.000000   \n",
              "30           0.000000  0.000000            0.000000      0.000000   \n",
              "31           0.000000  0.000000            0.000000      0.000000   \n",
              "32           0.000000  0.000000            0.000000      0.000000   \n",
              "33           0.000000  0.000000            0.000000      0.000000   \n",
              "34           0.000000  0.000000            0.000000      0.000000   \n",
              "35           0.000000  0.000000            0.000000      0.000000   \n",
              "36           0.000000  0.000000            0.000000      0.000000   \n",
              "37           0.000000  0.000000            0.000000      0.000000   \n",
              "\n",
              "    Airport Lounge  Airport Service  Airport Terminal  American Restaurant  \\\n",
              "0         0.000000              0.0          0.000000             0.040000   \n",
              "1         0.000000              0.0          0.000000             0.000000   \n",
              "2         0.000000              0.0          0.000000             0.000000   \n",
              "3         0.000000              0.0          0.000000             0.000000   \n",
              "4         0.133333              0.2          0.133333             0.000000   \n",
              "5         0.000000              0.0          0.000000             0.000000   \n",
              "6         0.000000              0.0          0.000000             0.011494   \n",
              "7         0.000000              0.0          0.000000             0.000000   \n",
              "8         0.000000              0.0          0.000000             0.000000   \n",
              "9         0.000000              0.0          0.000000             0.011364   \n",
              "10        0.000000              0.0          0.000000             0.040000   \n",
              "11        0.000000              0.0          0.000000             0.000000   \n",
              "12        0.000000              0.0          0.000000             0.000000   \n",
              "13        0.000000              0.0          0.000000             0.062500   \n",
              "14        0.000000              0.0          0.000000             0.030000   \n",
              "15        0.000000              0.0          0.000000             0.000000   \n",
              "16        0.000000              0.0          0.000000             0.030000   \n",
              "17        0.000000              0.0          0.000000             0.000000   \n",
              "18        0.000000              0.0          0.000000             0.000000   \n",
              "19        0.000000              0.0          0.000000             0.000000   \n",
              "20        0.000000              0.0          0.000000             0.000000   \n",
              "21        0.000000              0.0          0.000000             0.000000   \n",
              "22        0.000000              0.0          0.000000             0.000000   \n",
              "23        0.000000              0.0          0.000000             0.000000   \n",
              "24        0.000000              0.0          0.000000             0.000000   \n",
              "25        0.000000              0.0          0.000000             0.000000   \n",
              "26        0.000000              0.0          0.000000             0.000000   \n",
              "27        0.000000              0.0          0.000000             0.000000   \n",
              "28        0.000000              0.0          0.000000             0.000000   \n",
              "29        0.000000              0.0          0.000000             0.000000   \n",
              "30        0.000000              0.0          0.000000             0.010000   \n",
              "31        0.000000              0.0          0.000000             0.020000   \n",
              "32        0.000000              0.0          0.000000             0.000000   \n",
              "33        0.000000              0.0          0.000000             0.054054   \n",
              "34        0.000000              0.0          0.000000             0.041667   \n",
              "35        0.000000              0.0          0.000000             0.000000   \n",
              "36        0.000000              0.0          0.000000             0.000000   \n",
              "37        0.000000              0.0          0.000000             0.023810   \n",
              "\n",
              "       ...       Toy / Game Store    Trail  Train Station  \\\n",
              "0      ...               0.000000  0.00000           0.00   \n",
              "1      ...               0.000000  0.00000           0.00   \n",
              "2      ...               0.000000  0.00000           0.00   \n",
              "3      ...               0.000000  0.00000           0.00   \n",
              "4      ...               0.000000  0.00000           0.00   \n",
              "5      ...               0.000000  0.00000           0.00   \n",
              "6      ...               0.000000  0.00000           0.00   \n",
              "7      ...               0.010000  0.00000           0.00   \n",
              "8      ...               0.000000  0.00000           0.00   \n",
              "9      ...               0.000000  0.00000           0.00   \n",
              "10     ...               0.000000  0.00000           0.00   \n",
              "11     ...               0.028571  0.00000           0.00   \n",
              "12     ...               0.000000  0.00000           0.00   \n",
              "13     ...               0.000000  0.00000           0.00   \n",
              "14     ...               0.000000  0.00000           0.01   \n",
              "15     ...               0.000000  0.00000           0.00   \n",
              "16     ...               0.000000  0.00000           0.01   \n",
              "17     ...               0.000000  0.20000           0.00   \n",
              "18     ...               0.000000  0.00000           0.00   \n",
              "19     ...               0.000000  0.00000           0.01   \n",
              "20     ...               0.000000  0.00000           0.00   \n",
              "21     ...               0.000000  0.00000           0.00   \n",
              "22     ...               0.000000  0.00000           0.00   \n",
              "23     ...               0.000000  0.00000           0.00   \n",
              "24     ...               0.000000  0.00000           0.00   \n",
              "25     ...               0.000000  0.00000           0.00   \n",
              "26     ...               0.000000  0.00000           0.00   \n",
              "27     ...               0.000000  0.25000           0.00   \n",
              "28     ...               0.000000  0.00000           0.00   \n",
              "29     ...               0.000000  0.00000           0.00   \n",
              "30     ...               0.010000  0.00000           0.00   \n",
              "31     ...               0.000000  0.00000           0.00   \n",
              "32     ...               0.000000  0.00000           0.00   \n",
              "33     ...               0.000000  0.00000           0.00   \n",
              "34     ...               0.000000  0.00000           0.00   \n",
              "35     ...               0.000000  0.00000           0.00   \n",
              "36     ...               0.000000  0.00000           0.00   \n",
              "37     ...               0.000000  0.02381           0.00   \n",
              "\n",
              "    Vegetarian / Vegan Restaurant  Video Game Store  Vietnamese Restaurant  \\\n",
              "0                        0.010000          0.000000               0.000000   \n",
              "1                        0.018182          0.000000               0.000000   \n",
              "2                        0.000000          0.000000               0.000000   \n",
              "3                        0.000000          0.000000               0.000000   \n",
              "4                        0.000000          0.000000               0.000000   \n",
              "5                        0.000000          0.000000               0.000000   \n",
              "6                        0.011494          0.000000               0.000000   \n",
              "7                        0.060000          0.000000               0.030000   \n",
              "8                        0.000000          0.000000               0.000000   \n",
              "9                        0.000000          0.011364               0.011364   \n",
              "10                       0.010000          0.000000               0.000000   \n",
              "11                       0.000000          0.000000               0.000000   \n",
              "12                       0.000000          0.000000               0.000000   \n",
              "13                       0.000000          0.000000               0.062500   \n",
              "14                       0.010000          0.000000               0.000000   \n",
              "15                       0.000000          0.000000               0.000000   \n",
              "16                       0.010000          0.000000               0.000000   \n",
              "17                       0.000000          0.000000               0.000000   \n",
              "18                       0.000000          0.027778               0.000000   \n",
              "19                       0.010000          0.000000               0.000000   \n",
              "20                       0.000000          0.000000               0.000000   \n",
              "21                       0.000000          0.000000               0.000000   \n",
              "22                       0.000000          0.000000               0.000000   \n",
              "23                       0.016129          0.000000               0.032258   \n",
              "24                       0.000000          0.000000               0.000000   \n",
              "25                       0.000000          0.000000               0.000000   \n",
              "26                       0.000000          0.000000               0.000000   \n",
              "27                       0.000000          0.000000               0.000000   \n",
              "28                       0.000000          0.000000               0.000000   \n",
              "29                       0.027778          0.000000               0.000000   \n",
              "30                       0.010000          0.010000               0.010000   \n",
              "31                       0.010000          0.000000               0.000000   \n",
              "32                       0.010638          0.000000               0.000000   \n",
              "33                       0.000000          0.000000               0.000000   \n",
              "34                       0.041667          0.000000               0.000000   \n",
              "35                       0.000000          0.000000               0.000000   \n",
              "36                       0.000000          0.000000               0.000000   \n",
              "37                       0.000000          0.000000               0.000000   \n",
              "\n",
              "    Wine Bar  Wings Joint  Women's Store  Yoga Studio  \n",
              "0   0.010000     0.000000           0.00     0.000000  \n",
              "1   0.000000     0.000000           0.00     0.000000  \n",
              "2   0.000000     0.000000           0.00     0.000000  \n",
              "3   0.000000     0.000000           0.00     0.058824  \n",
              "4   0.000000     0.000000           0.00     0.000000  \n",
              "5   0.000000     0.000000           0.00     0.000000  \n",
              "6   0.011494     0.000000           0.00     0.011494  \n",
              "7   0.010000     0.000000           0.00     0.000000  \n",
              "8   0.000000     0.000000           0.00     0.000000  \n",
              "9   0.000000     0.011364           0.00     0.011364  \n",
              "10  0.010000     0.000000           0.00     0.000000  \n",
              "11  0.000000     0.000000           0.00     0.000000  \n",
              "12  0.000000     0.000000           0.00     0.000000  \n",
              "13  0.000000     0.000000           0.00     0.000000  \n",
              "14  0.010000     0.000000           0.00     0.000000  \n",
              "15  0.000000     0.000000           0.00     0.000000  \n",
              "16  0.010000     0.000000           0.00     0.000000  \n",
              "17  0.000000     0.000000           0.00     0.000000  \n",
              "18  0.000000     0.000000           0.00     0.027778  \n",
              "19  0.010000     0.000000           0.00     0.000000  \n",
              "20  0.000000     0.000000           0.00     0.021277  \n",
              "21  0.000000     0.000000           0.00     0.000000  \n",
              "22  0.000000     0.000000           0.00     0.000000  \n",
              "23  0.016129     0.000000           0.00     0.016129  \n",
              "24  0.000000     0.000000           0.00     0.000000  \n",
              "25  0.000000     0.000000           0.00     0.055556  \n",
              "26  0.000000     0.000000           0.00     0.000000  \n",
              "27  0.000000     0.000000           0.00     0.000000  \n",
              "28  0.000000     0.000000           0.00     0.000000  \n",
              "29  0.000000     0.000000           0.00     0.000000  \n",
              "30  0.010000     0.000000           0.00     0.000000  \n",
              "31  0.000000     0.000000           0.01     0.000000  \n",
              "32  0.000000     0.000000           0.00     0.000000  \n",
              "33  0.000000     0.000000           0.00     0.027027  \n",
              "34  0.000000     0.000000           0.00     0.000000  \n",
              "35  0.000000     0.000000           0.00     0.000000  \n",
              "36  0.000000     0.000000           0.00     0.000000  \n",
              "37  0.000000     0.000000           0.00     0.023810  \n",
              "\n",
              "[38 rows x 240 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VqYvwW-DdbjZ",
        "colab_type": "text"
      },
      "source": [
        "#### Top 5 most common venues"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0SNKsgTadbja",
        "colab_type": "code",
        "colab": {},
        "outputId": "5ed1d3be-3551-4341-cb56-cacbb648aaf7"
      },
      "source": [
        "num_top_venues = 5\n",
        "\n",
        "for hood in toronto_grouped['Neighbourhood']:\n",
        "    print(\"----\"+hood+\"----\")\n",
        "    temp = toronto_grouped[toronto_grouped['Neighbourhood'] == hood].T.reset_index()\n",
        "    temp.columns = ['venue','freq']\n",
        "    temp = temp.iloc[1:]\n",
        "    temp['freq'] = temp['freq'].astype(float)\n",
        "    temp = temp.round({'freq': 2})\n",
        "    print(temp.sort_values('freq', ascending=False).reset_index(drop=True).head(num_top_venues))\n",
        "    print('\\n')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "----Adelaide,King,Richmond----\n",
            "                 venue  freq\n",
            "0          Coffee Shop  0.06\n",
            "1                 Café  0.05\n",
            "2           Steakhouse  0.04\n",
            "3  American Restaurant  0.04\n",
            "4                  Bar  0.04\n",
            "\n",
            "\n",
            "----Berczy Park----\n",
            "                venue  freq\n",
            "0         Coffee Shop  0.07\n",
            "1        Cocktail Bar  0.05\n",
            "2  Italian Restaurant  0.04\n",
            "3      Farmers Market  0.04\n",
            "4         Cheese Shop  0.04\n",
            "\n",
            "\n",
            "----Brockton,Exhibition Place,Parkdale Village----\n",
            "                venue  freq\n",
            "0                Café  0.10\n",
            "1      Breakfast Spot  0.10\n",
            "2         Coffee Shop  0.10\n",
            "3              Office  0.05\n",
            "4  Italian Restaurant  0.05\n",
            "\n",
            "\n",
            "----Business Reply Mail Processing Centre 969 Eastern----\n",
            "                venue  freq\n",
            "0  Light Rail Station  0.12\n",
            "1         Yoga Studio  0.06\n",
            "2       Auto Workshop  0.06\n",
            "3          Comic Shop  0.06\n",
            "4                Park  0.06\n",
            "\n",
            "\n",
            "----CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara----\n",
            "              venue  freq\n",
            "0   Airport Service  0.20\n",
            "1  Airport Terminal  0.13\n",
            "2    Airport Lounge  0.13\n",
            "3     Boat or Ferry  0.07\n",
            "4  Sculpture Garden  0.07\n",
            "\n",
            "\n",
            "----Cabbagetown,St. James Town----\n",
            "                venue  freq\n",
            "0         Coffee Shop  0.09\n",
            "1         Pizza Place  0.07\n",
            "2          Restaurant  0.05\n",
            "3              Bakery  0.05\n",
            "4  Italian Restaurant  0.05\n",
            "\n",
            "\n",
            "----Central Bay Street----\n",
            "                venue  freq\n",
            "0         Coffee Shop  0.16\n",
            "1                Café  0.05\n",
            "2  Italian Restaurant  0.05\n",
            "3        Burger Joint  0.03\n",
            "4      Sandwich Place  0.03\n",
            "\n",
            "\n",
            "----Chinatown,Grange Park,Kensington Market----\n",
            "                           venue  freq\n",
            "0                           Café  0.08\n",
            "1  Vegetarian / Vegan Restaurant  0.06\n",
            "2                    Coffee Shop  0.04\n",
            "3             Mexican Restaurant  0.04\n",
            "4                         Bakery  0.04\n",
            "\n",
            "\n",
            "----Christie----\n",
            "               venue  freq\n",
            "0               Café  0.19\n",
            "1      Grocery Store  0.19\n",
            "2               Park  0.12\n",
            "3         Restaurant  0.06\n",
            "4  Convenience Store  0.06\n",
            "\n",
            "\n",
            "----Church and Wellesley----\n",
            "                 venue  freq\n",
            "0  Japanese Restaurant  0.07\n",
            "1          Coffee Shop  0.07\n",
            "2     Sushi Restaurant  0.06\n",
            "3           Restaurant  0.03\n",
            "4              Gay Bar  0.03\n",
            "\n",
            "\n",
            "----Commerce Court,Victoria Hotel----\n",
            "                 venue  freq\n",
            "0          Coffee Shop  0.11\n",
            "1                 Café  0.07\n",
            "2                Hotel  0.06\n",
            "3           Restaurant  0.05\n",
            "4  American Restaurant  0.04\n",
            "\n",
            "\n",
            "----Davisville----\n",
            "            venue  freq\n",
            "0     Pizza Place  0.09\n",
            "1  Sandwich Place  0.09\n",
            "2    Dessert Shop  0.09\n",
            "3            Café  0.06\n",
            "4      Restaurant  0.06\n",
            "\n",
            "\n",
            "----Davisville North----\n",
            "            venue  freq\n",
            "0  Breakfast Spot  0.14\n",
            "1             Gym  0.14\n",
            "2   Grocery Store  0.14\n",
            "3           Hotel  0.14\n",
            "4            Park  0.14\n",
            "\n",
            "\n",
            "----Deer Park,Forest Hill SE,Rathnelly,South Hill,Summerhill West----\n",
            "                venue  freq\n",
            "0                 Pub  0.12\n",
            "1  Light Rail Station  0.12\n",
            "2         Coffee Shop  0.12\n",
            "3        Liquor Store  0.06\n",
            "4          Bagel Shop  0.06\n",
            "\n",
            "\n",
            "----Design Exchange,Toronto Dominion Centre----\n",
            "           venue  freq\n",
            "0    Coffee Shop  0.12\n",
            "1          Hotel  0.08\n",
            "2           Café  0.07\n",
            "3     Restaurant  0.05\n",
            "4  Deli / Bodega  0.03\n",
            "\n",
            "\n",
            "----Dovercourt Village,Dufferin----\n",
            "            venue  freq\n",
            "0        Pharmacy  0.11\n",
            "1     Supermarket  0.11\n",
            "2          Bakery  0.11\n",
            "3            Pool  0.06\n",
            "4  Discount Store  0.06\n",
            "\n",
            "\n",
            "----First Canadian Place,Underground city----\n",
            "           venue  freq\n",
            "0           Café  0.09\n",
            "1    Coffee Shop  0.09\n",
            "2          Hotel  0.04\n",
            "3     Restaurant  0.03\n",
            "4  Deli / Bodega  0.03\n",
            "\n",
            "\n",
            "----Forest Hill North,Forest Hill West----\n",
            "              venue  freq\n",
            "0     Jewelry Store   0.2\n",
            "1             Trail   0.2\n",
            "2          Bus Line   0.2\n",
            "3              Park   0.2\n",
            "4  Sushi Restaurant   0.2\n",
            "\n",
            "\n",
            "----Harbord,University of Toronto----\n",
            "                venue  freq\n",
            "0                Café  0.14\n",
            "1              Bakery  0.06\n",
            "2          Restaurant  0.06\n",
            "3           Bookstore  0.06\n",
            "4  Italian Restaurant  0.06\n",
            "\n",
            "\n",
            "----Harbourfront East,Toronto Islands,Union Station----\n",
            "                venue  freq\n",
            "0         Coffee Shop  0.12\n",
            "1               Hotel  0.05\n",
            "2            Aquarium  0.05\n",
            "3  Italian Restaurant  0.04\n",
            "4                Café  0.04\n",
            "\n",
            "\n",
            "----Harbourfront,Regent Park----\n",
            "         venue  freq\n",
            "0  Coffee Shop  0.15\n",
            "1       Bakery  0.06\n",
            "2         Park  0.06\n",
            "3          Pub  0.06\n",
            "4         Café  0.04\n",
            "\n",
            "\n",
            "----High Park,The Junction South----\n",
            "                venue  freq\n",
            "0  Mexican Restaurant  0.08\n",
            "1                 Bar  0.08\n",
            "2                Café  0.08\n",
            "3           Bookstore  0.04\n",
            "4       Grocery Store  0.04\n",
            "\n",
            "\n",
            "----Lawrence Park----\n",
            "                venue  freq\n",
            "0                Park  0.25\n",
            "1         Swim School  0.25\n",
            "2  Dim Sum Restaurant  0.25\n",
            "3            Bus Line  0.25\n",
            "4      Adult Boutique  0.00\n",
            "\n",
            "\n",
            "----Little Portugal,Trinity----\n",
            "                     venue  freq\n",
            "0                      Bar  0.13\n",
            "1              Men's Store  0.05\n",
            "2              Coffee Shop  0.05\n",
            "3         Asian Restaurant  0.05\n",
            "4  New American Restaurant  0.03\n",
            "\n",
            "\n",
            "----Moore Park,Summerhill East----\n",
            "                      venue  freq\n",
            "0                Playground  0.33\n",
            "1                       Gym  0.33\n",
            "2                      Park  0.33\n",
            "3              Neighborhood  0.00\n",
            "4  Mediterranean Restaurant  0.00\n",
            "\n",
            "\n",
            "----North Toronto West----\n",
            "                     venue  freq\n",
            "0           Clothing Store  0.17\n",
            "1              Coffee Shop  0.11\n",
            "2  Health & Beauty Service  0.06\n",
            "3       Chinese Restaurant  0.06\n",
            "4      Sporting Goods Shop  0.06\n",
            "\n",
            "\n",
            "----Parkdale,Roncesvalles----\n",
            "            venue  freq\n",
            "0  Breakfast Spot  0.13\n",
            "1       Gift Shop  0.13\n",
            "2         Dog Run  0.07\n",
            "3     Coffee Shop  0.07\n",
            "4   Movie Theater  0.07\n",
            "\n",
            "\n",
            "----Rosedale----\n",
            "                      venue  freq\n",
            "0                      Park  0.50\n",
            "1                Playground  0.25\n",
            "2                     Trail  0.25\n",
            "3              Neighborhood  0.00\n",
            "4  Mediterranean Restaurant  0.00\n",
            "\n",
            "\n",
            "----Roselawn----\n",
            "                      venue  freq\n",
            "0               Music Venue   0.5\n",
            "1                    Garden   0.5\n",
            "2            Adult Boutique   0.0\n",
            "3         Martial Arts Dojo   0.0\n",
            "4  Mediterranean Restaurant   0.0\n",
            "\n",
            "\n",
            "----Runnymede,Swansea----\n",
            "                venue  freq\n",
            "0                Café  0.08\n",
            "1         Pizza Place  0.08\n",
            "2                 Gym  0.06\n",
            "3         Coffee Shop  0.06\n",
            "4  Italian Restaurant  0.06\n",
            "\n",
            "\n",
            "----Ryerson,Garden District----\n",
            "                       venue  freq\n",
            "0                Coffee Shop  0.10\n",
            "1             Clothing Store  0.06\n",
            "2                       Café  0.04\n",
            "3             Cosmetics Shop  0.04\n",
            "4  Middle Eastern Restaurant  0.03\n",
            "\n",
            "\n",
            "----St. James Town----\n",
            "            venue  freq\n",
            "0     Coffee Shop  0.07\n",
            "1            Café  0.06\n",
            "2           Hotel  0.05\n",
            "3      Restaurant  0.05\n",
            "4  Cosmetics Shop  0.04\n",
            "\n",
            "\n",
            "----Stn A PO Boxes 25 The Esplanade----\n",
            "                venue  freq\n",
            "0         Coffee Shop  0.11\n",
            "1          Restaurant  0.04\n",
            "2                Café  0.04\n",
            "3  Italian Restaurant  0.03\n",
            "4  Seafood Restaurant  0.03\n",
            "\n",
            "\n",
            "----Studio District----\n",
            "                venue  freq\n",
            "0                Café  0.11\n",
            "1         Coffee Shop  0.08\n",
            "2  Italian Restaurant  0.05\n",
            "3              Bakery  0.05\n",
            "4           Gastropub  0.05\n",
            "\n",
            "\n",
            "----The Annex,North Midtown,Yorkville----\n",
            "            venue  freq\n",
            "0     Coffee Shop  0.12\n",
            "1  Sandwich Place  0.12\n",
            "2            Café  0.12\n",
            "3     Pizza Place  0.08\n",
            "4  History Museum  0.04\n",
            "\n",
            "\n",
            "----The Beaches----\n",
            "               venue  freq\n",
            "0  Health Food Store   0.2\n",
            "1                Pub   0.2\n",
            "2           Boutique   0.2\n",
            "3       Neighborhood   0.2\n",
            "4         Astrologer   0.2\n",
            "\n",
            "\n",
            "----The Beaches West,India Bazaar----\n",
            "                  venue  freq\n",
            "0                  Park  0.10\n",
            "1        Sandwich Place  0.10\n",
            "2           Pizza Place  0.05\n",
            "3               Brewery  0.05\n",
            "4  Fast Food Restaurant  0.05\n",
            "\n",
            "\n",
            "----The Danforth West,Riverdale----\n",
            "                    venue  freq\n",
            "0        Greek Restaurant  0.21\n",
            "1             Coffee Shop  0.10\n",
            "2          Ice Cream Shop  0.07\n",
            "3      Italian Restaurant  0.07\n",
            "4  Furniture / Home Store  0.05\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ilY9iyf3dbjg",
        "colab_type": "text"
      },
      "source": [
        "#### Run k-means to cluster the neighborhood into 5 clusters"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bc6C80yLdbjg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# set number of clusters\n",
        "kclusters = 5\n",
        "\n",
        "toronto_grouped_clustering = toronto_grouped.drop('Neighbourhood', 1)\n",
        "\n",
        "# run k-means clustering\n",
        "kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(toronto_grouped_clustering)\n",
        "\n",
        "# add clustering labels\n",
        "toronto_grouped.insert(0, 'Cluster Labels', kmeans.labels_)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gD6UhJ6rdbjj",
        "colab_type": "code",
        "colab": {},
        "outputId": "5a2ffcee-f7bb-494e-c960-c138d3577ef7"
      },
      "source": [
        "toronto_grouped = toronto_grouped.join(df.set_index('Neighbourhood'), on='Neighbourhood')\n",
        "toronto_grouped"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Cluster Labels</th>\n",
              "      <th>Neighbourhood</th>\n",
              "      <th>Adult Boutique</th>\n",
              "      <th>Afghan Restaurant</th>\n",
              "      <th>Airport</th>\n",
              "      <th>Airport Food Court</th>\n",
              "      <th>Airport Gate</th>\n",
              "      <th>Airport Lounge</th>\n",
              "      <th>Airport Service</th>\n",
              "      <th>Airport Terminal</th>\n",
              "      <th>...</th>\n",
              "      <th>Video Game Store</th>\n",
              "      <th>Vietnamese Restaurant</th>\n",
              "      <th>Wine Bar</th>\n",
              "      <th>Wings Joint</th>\n",
              "      <th>Women's Store</th>\n",
              "      <th>Yoga Studio</th>\n",
              "      <th>Postcode</th>\n",
              "      <th>Borough</th>\n",
              "      <th>Latitude</th>\n",
              "      <th>Longitude</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Adelaide,King,Richmond</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5H</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.650571</td>\n",
              "      <td>-79.384568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>Berczy Park</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5E</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.644771</td>\n",
              "      <td>-79.373306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>Brockton,Exhibition Place,Parkdale Village</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M6K</td>\n",
              "      <td>West Toronto</td>\n",
              "      <td>43.636847</td>\n",
              "      <td>-79.428191</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>Business Reply Mail Processing Centre 969 Eastern</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.058824</td>\n",
              "      <td>M7Y</td>\n",
              "      <td>East Toronto</td>\n",
              "      <td>43.662744</td>\n",
              "      <td>-79.321558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>CN Tower,Bathurst Quay,Island airport,Harbourf...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.133333</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.133333</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5V</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.628947</td>\n",
              "      <td>-79.394420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0</td>\n",
              "      <td>Cabbagetown,St. James Town</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4X</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.667967</td>\n",
              "      <td>-79.367675</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0</td>\n",
              "      <td>Central Bay Street</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011494</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.011494</td>\n",
              "      <td>M5G</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.657952</td>\n",
              "      <td>-79.387383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0</td>\n",
              "      <td>Chinatown,Grange Park,Kensington Market</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.030000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5T</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.653206</td>\n",
              "      <td>-79.400049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0</td>\n",
              "      <td>Christie</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M6G</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.669542</td>\n",
              "      <td>-79.422564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0</td>\n",
              "      <td>Church and Wellesley</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.011364</td>\n",
              "      <td>M4Y</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.665860</td>\n",
              "      <td>-79.383160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0</td>\n",
              "      <td>Commerce Court,Victoria Hotel</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5L</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.648198</td>\n",
              "      <td>-79.379817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0</td>\n",
              "      <td>Davisville</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4S</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.704324</td>\n",
              "      <td>-79.388790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0</td>\n",
              "      <td>Davisville North</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4P</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.712751</td>\n",
              "      <td>-79.390197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0</td>\n",
              "      <td>Deer Park,Forest Hill SE,Rathnelly,South Hill,...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.062500</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4V</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.686412</td>\n",
              "      <td>-79.400049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0</td>\n",
              "      <td>Design Exchange,Toronto Dominion Centre</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5K</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.647177</td>\n",
              "      <td>-79.381576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0</td>\n",
              "      <td>Dovercourt Village,Dufferin</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M6H</td>\n",
              "      <td>West Toronto</td>\n",
              "      <td>43.669005</td>\n",
              "      <td>-79.442259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0</td>\n",
              "      <td>First Canadian Place,Underground city</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5X</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.648429</td>\n",
              "      <td>-79.382280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>0</td>\n",
              "      <td>Forest Hill North,Forest Hill West</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5P</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.696948</td>\n",
              "      <td>-79.411307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0</td>\n",
              "      <td>Harbord,University of Toronto</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.027778</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.027778</td>\n",
              "      <td>M5S</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.662696</td>\n",
              "      <td>-79.400049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>0</td>\n",
              "      <td>Harbourfront East,Toronto Islands,Union Station</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5J</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.640816</td>\n",
              "      <td>-79.381752</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>0</td>\n",
              "      <td>Harbourfront,Regent Park</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.021277</td>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.654260</td>\n",
              "      <td>-79.360636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>0</td>\n",
              "      <td>High Park,The Junction South</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M6P</td>\n",
              "      <td>West Toronto</td>\n",
              "      <td>43.661608</td>\n",
              "      <td>-79.464763</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2</td>\n",
              "      <td>Lawrence Park</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4N</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.728020</td>\n",
              "      <td>-79.388790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>0</td>\n",
              "      <td>Little Portugal,Trinity</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.032258</td>\n",
              "      <td>0.016129</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.016129</td>\n",
              "      <td>M6J</td>\n",
              "      <td>West Toronto</td>\n",
              "      <td>43.647927</td>\n",
              "      <td>-79.419750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1</td>\n",
              "      <td>Moore Park,Summerhill East</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4T</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.689574</td>\n",
              "      <td>-79.383160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>0</td>\n",
              "      <td>North Toronto West</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.055556</td>\n",
              "      <td>M4R</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.715383</td>\n",
              "      <td>-79.405678</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>0</td>\n",
              "      <td>Parkdale,Roncesvalles</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M6R</td>\n",
              "      <td>West Toronto</td>\n",
              "      <td>43.648960</td>\n",
              "      <td>-79.456325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>1</td>\n",
              "      <td>Rosedale</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4W</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.679563</td>\n",
              "      <td>-79.377529</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>3</td>\n",
              "      <td>Roselawn</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5N</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.711695</td>\n",
              "      <td>-79.416936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>0</td>\n",
              "      <td>Runnymede,Swansea</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M6S</td>\n",
              "      <td>West Toronto</td>\n",
              "      <td>43.651571</td>\n",
              "      <td>-79.484450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>0</td>\n",
              "      <td>Ryerson,Garden District</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5B</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.657162</td>\n",
              "      <td>-79.378937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>0</td>\n",
              "      <td>St. James Town</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5C</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.651494</td>\n",
              "      <td>-79.375418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>0</td>\n",
              "      <td>Stn A PO Boxes 25 The Esplanade</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5W</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>43.646435</td>\n",
              "      <td>-79.374846</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>0</td>\n",
              "      <td>Studio District</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.027027</td>\n",
              "      <td>M4M</td>\n",
              "      <td>East Toronto</td>\n",
              "      <td>43.659526</td>\n",
              "      <td>-79.340923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>0</td>\n",
              "      <td>The Annex,North Midtown,Yorkville</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M5R</td>\n",
              "      <td>Central Toronto</td>\n",
              "      <td>43.672710</td>\n",
              "      <td>-79.405678</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>4</td>\n",
              "      <td>The Beaches</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4E</td>\n",
              "      <td>East Toronto</td>\n",
              "      <td>43.676357</td>\n",
              "      <td>-79.293031</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>0</td>\n",
              "      <td>The Beaches West,India Bazaar</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>M4L</td>\n",
              "      <td>East Toronto</td>\n",
              "      <td>43.668999</td>\n",
              "      <td>-79.315572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>0</td>\n",
              "      <td>The Danforth West,Riverdale</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.023810</td>\n",
              "      <td>M4K</td>\n",
              "      <td>East Toronto</td>\n",
              "      <td>43.679557</td>\n",
              "      <td>-79.352188</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>38 rows × 245 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    Cluster Labels                                      Neighbourhood  \\\n",
              "0                0                             Adelaide,King,Richmond   \n",
              "1                0                                        Berczy Park   \n",
              "2                0         Brockton,Exhibition Place,Parkdale Village   \n",
              "3                0  Business Reply Mail Processing Centre 969 Eastern   \n",
              "4                0  CN Tower,Bathurst Quay,Island airport,Harbourf...   \n",
              "5                0                         Cabbagetown,St. James Town   \n",
              "6                0                                 Central Bay Street   \n",
              "7                0            Chinatown,Grange Park,Kensington Market   \n",
              "8                0                                           Christie   \n",
              "9                0                               Church and Wellesley   \n",
              "10               0                      Commerce Court,Victoria Hotel   \n",
              "11               0                                         Davisville   \n",
              "12               0                                   Davisville North   \n",
              "13               0  Deer Park,Forest Hill SE,Rathnelly,South Hill,...   \n",
              "14               0            Design Exchange,Toronto Dominion Centre   \n",
              "15               0                        Dovercourt Village,Dufferin   \n",
              "16               0              First Canadian Place,Underground city   \n",
              "17               0                 Forest Hill North,Forest Hill West   \n",
              "18               0                      Harbord,University of Toronto   \n",
              "19               0    Harbourfront East,Toronto Islands,Union Station   \n",
              "20               0                           Harbourfront,Regent Park   \n",
              "21               0                       High Park,The Junction South   \n",
              "22               2                                      Lawrence Park   \n",
              "23               0                            Little Portugal,Trinity   \n",
              "24               1                         Moore Park,Summerhill East   \n",
              "25               0                                 North Toronto West   \n",
              "26               0                              Parkdale,Roncesvalles   \n",
              "27               1                                           Rosedale   \n",
              "28               3                                           Roselawn   \n",
              "29               0                                  Runnymede,Swansea   \n",
              "30               0                            Ryerson,Garden District   \n",
              "31               0                                     St. James Town   \n",
              "32               0                    Stn A PO Boxes 25 The Esplanade   \n",
              "33               0                                    Studio District   \n",
              "34               0                  The Annex,North Midtown,Yorkville   \n",
              "35               4                                        The Beaches   \n",
              "36               0                      The Beaches West,India Bazaar   \n",
              "37               0                        The Danforth West,Riverdale   \n",
              "\n",
              "    Adult Boutique  Afghan Restaurant   Airport  Airport Food Court  \\\n",
              "0         0.000000           0.000000  0.000000            0.000000   \n",
              "1         0.000000           0.000000  0.000000            0.000000   \n",
              "2         0.000000           0.000000  0.000000            0.000000   \n",
              "3         0.000000           0.000000  0.000000            0.000000   \n",
              "4         0.000000           0.000000  0.066667            0.066667   \n",
              "5         0.000000           0.000000  0.000000            0.000000   \n",
              "6         0.000000           0.000000  0.000000            0.000000   \n",
              "7         0.000000           0.000000  0.000000            0.000000   \n",
              "8         0.000000           0.000000  0.000000            0.000000   \n",
              "9         0.011364           0.011364  0.000000            0.000000   \n",
              "10        0.000000           0.000000  0.000000            0.000000   \n",
              "11        0.000000           0.000000  0.000000            0.000000   \n",
              "12        0.000000           0.000000  0.000000            0.000000   \n",
              "13        0.000000           0.000000  0.000000            0.000000   \n",
              "14        0.000000           0.000000  0.000000            0.000000   \n",
              "15        0.000000           0.000000  0.000000            0.000000   \n",
              "16        0.000000           0.000000  0.000000            0.000000   \n",
              "17        0.000000           0.000000  0.000000            0.000000   \n",
              "18        0.000000           0.000000  0.000000            0.000000   \n",
              "19        0.000000           0.000000  0.000000            0.000000   \n",
              "20        0.000000           0.000000  0.000000            0.000000   \n",
              "21        0.000000           0.000000  0.000000            0.000000   \n",
              "22        0.000000           0.000000  0.000000            0.000000   \n",
              "23        0.000000           0.000000  0.000000            0.000000   \n",
              "24        0.000000           0.000000  0.000000            0.000000   \n",
              "25        0.000000           0.000000  0.000000            0.000000   \n",
              "26        0.000000           0.000000  0.000000            0.000000   \n",
              "27        0.000000           0.000000  0.000000            0.000000   \n",
              "28        0.000000           0.000000  0.000000            0.000000   \n",
              "29        0.000000           0.000000  0.000000            0.000000   \n",
              "30        0.000000           0.000000  0.000000            0.000000   \n",
              "31        0.000000           0.000000  0.000000            0.000000   \n",
              "32        0.000000           0.000000  0.000000            0.000000   \n",
              "33        0.000000           0.000000  0.000000            0.000000   \n",
              "34        0.000000           0.000000  0.000000            0.000000   \n",
              "35        0.000000           0.000000  0.000000            0.000000   \n",
              "36        0.000000           0.000000  0.000000            0.000000   \n",
              "37        0.000000           0.000000  0.000000            0.000000   \n",
              "\n",
              "    Airport Gate  Airport Lounge  Airport Service  Airport Terminal  \\\n",
              "0       0.000000        0.000000              0.0          0.000000   \n",
              "1       0.000000        0.000000              0.0          0.000000   \n",
              "2       0.000000        0.000000              0.0          0.000000   \n",
              "3       0.000000        0.000000              0.0          0.000000   \n",
              "4       0.066667        0.133333              0.2          0.133333   \n",
              "5       0.000000        0.000000              0.0          0.000000   \n",
              "6       0.000000        0.000000              0.0          0.000000   \n",
              "7       0.000000        0.000000              0.0          0.000000   \n",
              "8       0.000000        0.000000              0.0          0.000000   \n",
              "9       0.000000        0.000000              0.0          0.000000   \n",
              "10      0.000000        0.000000              0.0          0.000000   \n",
              "11      0.000000        0.000000              0.0          0.000000   \n",
              "12      0.000000        0.000000              0.0          0.000000   \n",
              "13      0.000000        0.000000              0.0          0.000000   \n",
              "14      0.000000        0.000000              0.0          0.000000   \n",
              "15      0.000000        0.000000              0.0          0.000000   \n",
              "16      0.000000        0.000000              0.0          0.000000   \n",
              "17      0.000000        0.000000              0.0          0.000000   \n",
              "18      0.000000        0.000000              0.0          0.000000   \n",
              "19      0.000000        0.000000              0.0          0.000000   \n",
              "20      0.000000        0.000000              0.0          0.000000   \n",
              "21      0.000000        0.000000              0.0          0.000000   \n",
              "22      0.000000        0.000000              0.0          0.000000   \n",
              "23      0.000000        0.000000              0.0          0.000000   \n",
              "24      0.000000        0.000000              0.0          0.000000   \n",
              "25      0.000000        0.000000              0.0          0.000000   \n",
              "26      0.000000        0.000000              0.0          0.000000   \n",
              "27      0.000000        0.000000              0.0          0.000000   \n",
              "28      0.000000        0.000000              0.0          0.000000   \n",
              "29      0.000000        0.000000              0.0          0.000000   \n",
              "30      0.000000        0.000000              0.0          0.000000   \n",
              "31      0.000000        0.000000              0.0          0.000000   \n",
              "32      0.000000        0.000000              0.0          0.000000   \n",
              "33      0.000000        0.000000              0.0          0.000000   \n",
              "34      0.000000        0.000000              0.0          0.000000   \n",
              "35      0.000000        0.000000              0.0          0.000000   \n",
              "36      0.000000        0.000000              0.0          0.000000   \n",
              "37      0.000000        0.000000              0.0          0.000000   \n",
              "\n",
              "      ...      Video Game Store  Vietnamese Restaurant  Wine Bar  Wings Joint  \\\n",
              "0     ...              0.000000               0.000000  0.010000     0.000000   \n",
              "1     ...              0.000000               0.000000  0.000000     0.000000   \n",
              "2     ...              0.000000               0.000000  0.000000     0.000000   \n",
              "3     ...              0.000000               0.000000  0.000000     0.000000   \n",
              "4     ...              0.000000               0.000000  0.000000     0.000000   \n",
              "5     ...              0.000000               0.000000  0.000000     0.000000   \n",
              "6     ...              0.000000               0.000000  0.011494     0.000000   \n",
              "7     ...              0.000000               0.030000  0.010000     0.000000   \n",
              "8     ...              0.000000               0.000000  0.000000     0.000000   \n",
              "9     ...              0.011364               0.011364  0.000000     0.011364   \n",
              "10    ...              0.000000               0.000000  0.010000     0.000000   \n",
              "11    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "12    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "13    ...              0.000000               0.062500  0.000000     0.000000   \n",
              "14    ...              0.000000               0.000000  0.010000     0.000000   \n",
              "15    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "16    ...              0.000000               0.000000  0.010000     0.000000   \n",
              "17    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "18    ...              0.027778               0.000000  0.000000     0.000000   \n",
              "19    ...              0.000000               0.000000  0.010000     0.000000   \n",
              "20    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "21    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "22    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "23    ...              0.000000               0.032258  0.016129     0.000000   \n",
              "24    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "25    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "26    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "27    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "28    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "29    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "30    ...              0.010000               0.010000  0.010000     0.000000   \n",
              "31    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "32    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "33    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "34    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "35    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "36    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "37    ...              0.000000               0.000000  0.000000     0.000000   \n",
              "\n",
              "    Women's Store  Yoga Studio  Postcode           Borough   Latitude  \\\n",
              "0            0.00     0.000000       M5H  Downtown Toronto  43.650571   \n",
              "1            0.00     0.000000       M5E  Downtown Toronto  43.644771   \n",
              "2            0.00     0.000000       M6K      West Toronto  43.636847   \n",
              "3            0.00     0.058824       M7Y      East Toronto  43.662744   \n",
              "4            0.00     0.000000       M5V  Downtown Toronto  43.628947   \n",
              "5            0.00     0.000000       M4X  Downtown Toronto  43.667967   \n",
              "6            0.00     0.011494       M5G  Downtown Toronto  43.657952   \n",
              "7            0.00     0.000000       M5T  Downtown Toronto  43.653206   \n",
              "8            0.00     0.000000       M6G  Downtown Toronto  43.669542   \n",
              "9            0.00     0.011364       M4Y  Downtown Toronto  43.665860   \n",
              "10           0.00     0.000000       M5L  Downtown Toronto  43.648198   \n",
              "11           0.00     0.000000       M4S   Central Toronto  43.704324   \n",
              "12           0.00     0.000000       M4P   Central Toronto  43.712751   \n",
              "13           0.00     0.000000       M4V   Central Toronto  43.686412   \n",
              "14           0.00     0.000000       M5K  Downtown Toronto  43.647177   \n",
              "15           0.00     0.000000       M6H      West Toronto  43.669005   \n",
              "16           0.00     0.000000       M5X  Downtown Toronto  43.648429   \n",
              "17           0.00     0.000000       M5P   Central Toronto  43.696948   \n",
              "18           0.00     0.027778       M5S  Downtown Toronto  43.662696   \n",
              "19           0.00     0.000000       M5J  Downtown Toronto  43.640816   \n",
              "20           0.00     0.021277       M5A  Downtown Toronto  43.654260   \n",
              "21           0.00     0.000000       M6P      West Toronto  43.661608   \n",
              "22           0.00     0.000000       M4N   Central Toronto  43.728020   \n",
              "23           0.00     0.016129       M6J      West Toronto  43.647927   \n",
              "24           0.00     0.000000       M4T   Central Toronto  43.689574   \n",
              "25           0.00     0.055556       M4R   Central Toronto  43.715383   \n",
              "26           0.00     0.000000       M6R      West Toronto  43.648960   \n",
              "27           0.00     0.000000       M4W  Downtown Toronto  43.679563   \n",
              "28           0.00     0.000000       M5N   Central Toronto  43.711695   \n",
              "29           0.00     0.000000       M6S      West Toronto  43.651571   \n",
              "30           0.00     0.000000       M5B  Downtown Toronto  43.657162   \n",
              "31           0.01     0.000000       M5C  Downtown Toronto  43.651494   \n",
              "32           0.00     0.000000       M5W  Downtown Toronto  43.646435   \n",
              "33           0.00     0.027027       M4M      East Toronto  43.659526   \n",
              "34           0.00     0.000000       M5R   Central Toronto  43.672710   \n",
              "35           0.00     0.000000       M4E      East Toronto  43.676357   \n",
              "36           0.00     0.000000       M4L      East Toronto  43.668999   \n",
              "37           0.00     0.023810       M4K      East Toronto  43.679557   \n",
              "\n",
              "    Longitude  \n",
              "0  -79.384568  \n",
              "1  -79.373306  \n",
              "2  -79.428191  \n",
              "3  -79.321558  \n",
              "4  -79.394420  \n",
              "5  -79.367675  \n",
              "6  -79.387383  \n",
              "7  -79.400049  \n",
              "8  -79.422564  \n",
              "9  -79.383160  \n",
              "10 -79.379817  \n",
              "11 -79.388790  \n",
              "12 -79.390197  \n",
              "13 -79.400049  \n",
              "14 -79.381576  \n",
              "15 -79.442259  \n",
              "16 -79.382280  \n",
              "17 -79.411307  \n",
              "18 -79.400049  \n",
              "19 -79.381752  \n",
              "20 -79.360636  \n",
              "21 -79.464763  \n",
              "22 -79.388790  \n",
              "23 -79.419750  \n",
              "24 -79.383160  \n",
              "25 -79.405678  \n",
              "26 -79.456325  \n",
              "27 -79.377529  \n",
              "28 -79.416936  \n",
              "29 -79.484450  \n",
              "30 -79.378937  \n",
              "31 -79.375418  \n",
              "32 -79.374846  \n",
              "33 -79.340923  \n",
              "34 -79.405678  \n",
              "35 -79.293031  \n",
              "36 -79.315572  \n",
              "37 -79.352188  \n",
              "\n",
              "[38 rows x 245 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "COVnt-Radbjq",
        "colab_type": "code",
        "colab": {},
        "outputId": "bc715c6c-89a6-4666-91dc-7647e96e6f07"
      },
      "source": [
        "# create map\n",
        "map_clusters = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
        "\n",
        "# set color scheme for the clusters\n",
        "x = np.arange(kclusters)\n",
        "ys = [i + x + (i*x)**2 for i in range(kclusters)]\n",
        "colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\n",
        "rainbow = [colors.rgb2hex(i) for i in colors_array]\n",
        "\n",
        "# add markers to the map\n",
        "markers_colors = []\n",
        "for lat, lon, poi, cluster in zip(toronto_grouped['Latitude'], toronto_grouped['Longitude'], toronto_grouped['Neighbourhood'], toronto_grouped['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"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    
        <script>
            L_NO_TOUCH = false;
            L_DISABLE_3D = false;
        </script>
    
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.js"></script>
    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
    <link rel="stylesheet" href="https://rawcdn.githack.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css"/>
    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
    
            <meta name="viewport" content="width=device-width,
                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
            <style>
                #map_4145cf5421354f49a8542166190dc103 {
                    position: relative;
                    width: 100.0%;
                    height: 100.0%;
                    left: 0.0%;
                    top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_4145cf5421354f49a8542166190dc103" ></div>
        
</body>
<script>    
    
            var map_4145cf5421354f49a8542166190dc103 = L.map(
                "map_4145cf5421354f49a8542166190dc103",
                {
                    center: [43.653963, -79.387207],
                    crs: L.CRS.EPSG3857,
                    zoom: 12,
                    zoomControl: true,
                    preferCanvas: false,
                }
            );

            

        
    
            var tile_layer_4fac1b7c285e42e58de9fde570c82e1f = L.tileLayer(
                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
                {"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
            var circle_marker_027ccf467b434b1a809c20949efe810c = L.circleMarker(
                [43.65057120000001, -79.3845675],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_3f519c7c5abe4744a34fe0db2bef5ac8 = L.popup({"maxWidth": "100%"});

        
            var html_5ab6ecf66fa14b4297d45f4550ec1846 = $(`<div id="html_5ab6ecf66fa14b4297d45f4550ec1846" style="width: 100.0%; height: 100.0%;">Adelaide,King,Richmond Cluster 0</div>`)[0];
            popup_3f519c7c5abe4744a34fe0db2bef5ac8.setContent(html_5ab6ecf66fa14b4297d45f4550ec1846);
        

        circle_marker_027ccf467b434b1a809c20949efe810c.bindPopup(popup_3f519c7c5abe4744a34fe0db2bef5ac8)
        ;

        
    
    
            var circle_marker_f8547ae1da8449c8bfcfcad88ac8de34 = L.circleMarker(
                [43.6447708, -79.3733064],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_9d6f83fb7138492b98974cfeed36220c = L.popup({"maxWidth": "100%"});

        
            var html_de3b93b89c86438d80948283e5229250 = $(`<div id="html_de3b93b89c86438d80948283e5229250" style="width: 100.0%; height: 100.0%;">Berczy Park Cluster 0</div>`)[0];
            popup_9d6f83fb7138492b98974cfeed36220c.setContent(html_de3b93b89c86438d80948283e5229250);
        

        circle_marker_f8547ae1da8449c8bfcfcad88ac8de34.bindPopup(popup_9d6f83fb7138492b98974cfeed36220c)
        ;

        
    
    
            var circle_marker_d0c6e09f8b69492a9e8558c3589d8193 = L.circleMarker(
                [43.6368472, -79.42819140000002],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_b87e9eba2cd44c4283b9fc06c4066b35 = L.popup({"maxWidth": "100%"});

        
            var html_4ef235890db44ec7b09f18eaa0096c94 = $(`<div id="html_4ef235890db44ec7b09f18eaa0096c94" style="width: 100.0%; height: 100.0%;">Brockton,Exhibition Place,Parkdale Village Cluster 0</div>`)[0];
            popup_b87e9eba2cd44c4283b9fc06c4066b35.setContent(html_4ef235890db44ec7b09f18eaa0096c94);
        

        circle_marker_d0c6e09f8b69492a9e8558c3589d8193.bindPopup(popup_b87e9eba2cd44c4283b9fc06c4066b35)
        ;

        
    
    
            var circle_marker_68d0a6c5874a44089a60f67a5037d48a = L.circleMarker(
                [43.6627439, -79.321558],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_9d3930a6c3d140959c9b70c3eee68bfb = L.popup({"maxWidth": "100%"});

        
            var html_d2b43bd083ea4f84b4037923f0895b27 = $(`<div id="html_d2b43bd083ea4f84b4037923f0895b27" style="width: 100.0%; height: 100.0%;">Business Reply Mail Processing Centre 969 Eastern Cluster 0</div>`)[0];
            popup_9d3930a6c3d140959c9b70c3eee68bfb.setContent(html_d2b43bd083ea4f84b4037923f0895b27);
        

        circle_marker_68d0a6c5874a44089a60f67a5037d48a.bindPopup(popup_9d3930a6c3d140959c9b70c3eee68bfb)
        ;

        
    
    
            var circle_marker_624bd3f052204ae384c5cf207f051af8 = L.circleMarker(
                [43.6289467, -79.3944199],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_6a5ee7e5b5f74d67a3ca6d44ccbd048a = L.popup({"maxWidth": "100%"});

        
            var html_847666ff5c464fa584304e3f66eb9515 = $(`<div id="html_847666ff5c464fa584304e3f66eb9515" style="width: 100.0%; height: 100.0%;">CN Tower,Bathurst Quay,Island airport,Harbourfront West,King and Spadina,Railway Lands,South Niagara Cluster 0</div>`)[0];
            popup_6a5ee7e5b5f74d67a3ca6d44ccbd048a.setContent(html_847666ff5c464fa584304e3f66eb9515);
        

        circle_marker_624bd3f052204ae384c5cf207f051af8.bindPopup(popup_6a5ee7e5b5f74d67a3ca6d44ccbd048a)
        ;

        
    
    
            var circle_marker_462eeb03b98248c38f37aa6401810ec5 = L.circleMarker(
                [43.667967, -79.3676753],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_216637e94d5044a8b689cc84aee2bd1e = L.popup({"maxWidth": "100%"});

        
            var html_20413f6a5c9040978fa0451517287a4e = $(`<div id="html_20413f6a5c9040978fa0451517287a4e" style="width: 100.0%; height: 100.0%;">Cabbagetown,St. James Town Cluster 0</div>`)[0];
            popup_216637e94d5044a8b689cc84aee2bd1e.setContent(html_20413f6a5c9040978fa0451517287a4e);
        

        circle_marker_462eeb03b98248c38f37aa6401810ec5.bindPopup(popup_216637e94d5044a8b689cc84aee2bd1e)
        ;

        
    
    
            var circle_marker_300d43d1b57d480f86567027df08b500 = L.circleMarker(
                [43.6579524, -79.3873826],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_212f263d6c7846ebaceb03341e8b58ff = L.popup({"maxWidth": "100%"});

        
            var html_8dd0b2d6898841579a72b991b59c29d1 = $(`<div id="html_8dd0b2d6898841579a72b991b59c29d1" style="width: 100.0%; height: 100.0%;">Central Bay Street Cluster 0</div>`)[0];
            popup_212f263d6c7846ebaceb03341e8b58ff.setContent(html_8dd0b2d6898841579a72b991b59c29d1);
        

        circle_marker_300d43d1b57d480f86567027df08b500.bindPopup(popup_212f263d6c7846ebaceb03341e8b58ff)
        ;

        
    
    
            var circle_marker_3758d250f92e45f8aec09b6553bce4f6 = L.circleMarker(
                [43.6532057, -79.4000493],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_669e478f775f4aa89938675508cd0c90 = L.popup({"maxWidth": "100%"});

        
            var html_577deb4e83074877a3397818b175deb1 = $(`<div id="html_577deb4e83074877a3397818b175deb1" style="width: 100.0%; height: 100.0%;">Chinatown,Grange Park,Kensington Market Cluster 0</div>`)[0];
            popup_669e478f775f4aa89938675508cd0c90.setContent(html_577deb4e83074877a3397818b175deb1);
        

        circle_marker_3758d250f92e45f8aec09b6553bce4f6.bindPopup(popup_669e478f775f4aa89938675508cd0c90)
        ;

        
    
    
            var circle_marker_169b7f7bb7864c4f9116e24835f641e4 = L.circleMarker(
                [43.669542, -79.4225637],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_bb72cf6d67834b299a4de0ed05dec2aa = L.popup({"maxWidth": "100%"});

        
            var html_ed7fd79534e942d4bf0e6e937521fecd = $(`<div id="html_ed7fd79534e942d4bf0e6e937521fecd" style="width: 100.0%; height: 100.0%;">Christie Cluster 0</div>`)[0];
            popup_bb72cf6d67834b299a4de0ed05dec2aa.setContent(html_ed7fd79534e942d4bf0e6e937521fecd);
        

        circle_marker_169b7f7bb7864c4f9116e24835f641e4.bindPopup(popup_bb72cf6d67834b299a4de0ed05dec2aa)
        ;

        
    
    
            var circle_marker_0e509a04d2dd4268bf257acaca0a6b9f = L.circleMarker(
                [43.6658599, -79.38315990000002],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_2d1944a404d547f090957cfae09d3e3a = L.popup({"maxWidth": "100%"});

        
            var html_560c52cf693b40259af59b4cc7c7a36a = $(`<div id="html_560c52cf693b40259af59b4cc7c7a36a" style="width: 100.0%; height: 100.0%;">Church and Wellesley Cluster 0</div>`)[0];
            popup_2d1944a404d547f090957cfae09d3e3a.setContent(html_560c52cf693b40259af59b4cc7c7a36a);
        

        circle_marker_0e509a04d2dd4268bf257acaca0a6b9f.bindPopup(popup_2d1944a404d547f090957cfae09d3e3a)
        ;

        
    
    
            var circle_marker_4953832138db408d8c119fd79e7ed87d = L.circleMarker(
                [43.6481985, -79.37981690000002],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_620d0e06ebd84d6dbed899db8bc30b2b = L.popup({"maxWidth": "100%"});

        
            var html_417490b794d5450a982da07995c64780 = $(`<div id="html_417490b794d5450a982da07995c64780" style="width: 100.0%; height: 100.0%;">Commerce Court,Victoria Hotel Cluster 0</div>`)[0];
            popup_620d0e06ebd84d6dbed899db8bc30b2b.setContent(html_417490b794d5450a982da07995c64780);
        

        circle_marker_4953832138db408d8c119fd79e7ed87d.bindPopup(popup_620d0e06ebd84d6dbed899db8bc30b2b)
        ;

        
    
    
            var circle_marker_fef20ba8bf3c45d6ad174d06b6d21151 = L.circleMarker(
                [43.7043244, -79.3887901],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_4d513dd58baf4536b53020e9c381fdd9 = L.popup({"maxWidth": "100%"});

        
            var html_378afa1877fe4ad78f1f5d6d0f634d65 = $(`<div id="html_378afa1877fe4ad78f1f5d6d0f634d65" style="width: 100.0%; height: 100.0%;">Davisville Cluster 0</div>`)[0];
            popup_4d513dd58baf4536b53020e9c381fdd9.setContent(html_378afa1877fe4ad78f1f5d6d0f634d65);
        

        circle_marker_fef20ba8bf3c45d6ad174d06b6d21151.bindPopup(popup_4d513dd58baf4536b53020e9c381fdd9)
        ;

        
    
    
            var circle_marker_b404202cfafa4ca4af7c99dc80412f0b = L.circleMarker(
                [43.7127511, -79.3901975],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_42d86498a0764a17b0a4c03364af702a = L.popup({"maxWidth": "100%"});

        
            var html_a638af4dedaa4379996d00179ae2776d = $(`<div id="html_a638af4dedaa4379996d00179ae2776d" style="width: 100.0%; height: 100.0%;">Davisville North Cluster 0</div>`)[0];
            popup_42d86498a0764a17b0a4c03364af702a.setContent(html_a638af4dedaa4379996d00179ae2776d);
        

        circle_marker_b404202cfafa4ca4af7c99dc80412f0b.bindPopup(popup_42d86498a0764a17b0a4c03364af702a)
        ;

        
    
    
            var circle_marker_bf1feec258f5475e8b0a16b2eb23b2ec = L.circleMarker(
                [43.68641229999999, -79.4000493],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_119e390ea0ac4c74af3b048c9109620d = L.popup({"maxWidth": "100%"});

        
            var html_85ce6a6f67c64417bfbc2e9f831cf68f = $(`<div id="html_85ce6a6f67c64417bfbc2e9f831cf68f" style="width: 100.0%; height: 100.0%;">Deer Park,Forest Hill SE,Rathnelly,South Hill,Summerhill West Cluster 0</div>`)[0];
            popup_119e390ea0ac4c74af3b048c9109620d.setContent(html_85ce6a6f67c64417bfbc2e9f831cf68f);
        

        circle_marker_bf1feec258f5475e8b0a16b2eb23b2ec.bindPopup(popup_119e390ea0ac4c74af3b048c9109620d)
        ;

        
    
    
            var circle_marker_6149a482955a45ff99e19bca9566b4a5 = L.circleMarker(
                [43.6471768, -79.38157640000001],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_67c4de7e7731421998863b67a9901584 = L.popup({"maxWidth": "100%"});

        
            var html_aca65a3b9c8c4b30ae42283ebc49f594 = $(`<div id="html_aca65a3b9c8c4b30ae42283ebc49f594" style="width: 100.0%; height: 100.0%;">Design Exchange,Toronto Dominion Centre Cluster 0</div>`)[0];
            popup_67c4de7e7731421998863b67a9901584.setContent(html_aca65a3b9c8c4b30ae42283ebc49f594);
        

        circle_marker_6149a482955a45ff99e19bca9566b4a5.bindPopup(popup_67c4de7e7731421998863b67a9901584)
        ;

        
    
    
            var circle_marker_0150c713b88145989b0511ff783ecd27 = L.circleMarker(
                [43.66900510000001, -79.4422593],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_49bb31665b2f430c82362b8bfb63e182 = L.popup({"maxWidth": "100%"});

        
            var html_27353b0e09d84e72910b716f34e5ffdd = $(`<div id="html_27353b0e09d84e72910b716f34e5ffdd" style="width: 100.0%; height: 100.0%;">Dovercourt Village,Dufferin Cluster 0</div>`)[0];
            popup_49bb31665b2f430c82362b8bfb63e182.setContent(html_27353b0e09d84e72910b716f34e5ffdd);
        

        circle_marker_0150c713b88145989b0511ff783ecd27.bindPopup(popup_49bb31665b2f430c82362b8bfb63e182)
        ;

        
    
    
            var circle_marker_0f3abdbe5130478f84a15f2cccf7a00a = L.circleMarker(
                [43.6484292, -79.3822802],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_3e5f16e85dba47d499997c1074fc2c40 = L.popup({"maxWidth": "100%"});

        
            var html_2eced5ee016a4e94bb74d3b0e06b4880 = $(`<div id="html_2eced5ee016a4e94bb74d3b0e06b4880" style="width: 100.0%; height: 100.0%;">First Canadian Place,Underground city Cluster 0</div>`)[0];
            popup_3e5f16e85dba47d499997c1074fc2c40.setContent(html_2eced5ee016a4e94bb74d3b0e06b4880);
        

        circle_marker_0f3abdbe5130478f84a15f2cccf7a00a.bindPopup(popup_3e5f16e85dba47d499997c1074fc2c40)
        ;

        
    
    
            var circle_marker_4abc23ca462341f88c83dbb1674a634e = L.circleMarker(
                [43.6969476, -79.41130720000002],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_9fbf131c2c1e479596f0d042faadfbd0 = L.popup({"maxWidth": "100%"});

        
            var html_50ef28c54dd44485b1a65eee935aac0b = $(`<div id="html_50ef28c54dd44485b1a65eee935aac0b" style="width: 100.0%; height: 100.0%;">Forest Hill North,Forest Hill West Cluster 0</div>`)[0];
            popup_9fbf131c2c1e479596f0d042faadfbd0.setContent(html_50ef28c54dd44485b1a65eee935aac0b);
        

        circle_marker_4abc23ca462341f88c83dbb1674a634e.bindPopup(popup_9fbf131c2c1e479596f0d042faadfbd0)
        ;

        
    
    
            var circle_marker_dfc723d16f2540ba990304f7914f0b73 = L.circleMarker(
                [43.6626956, -79.4000493],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_a3cb066d3a694a8b81d73ff6cc7afa1f = L.popup({"maxWidth": "100%"});

        
            var html_4cc77cf2933b41caa368d23d3d4abc7e = $(`<div id="html_4cc77cf2933b41caa368d23d3d4abc7e" style="width: 100.0%; height: 100.0%;">Harbord,University of Toronto Cluster 0</div>`)[0];
            popup_a3cb066d3a694a8b81d73ff6cc7afa1f.setContent(html_4cc77cf2933b41caa368d23d3d4abc7e);
        

        circle_marker_dfc723d16f2540ba990304f7914f0b73.bindPopup(popup_a3cb066d3a694a8b81d73ff6cc7afa1f)
        ;

        
    
    
            var circle_marker_18f08a2cd9744a7aa606549043c3625f = L.circleMarker(
                [43.6408157, -79.38175229999997],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_bf546977985c4e7e9db9141c4eb00f3e = L.popup({"maxWidth": "100%"});

        
            var html_4c16bad8b7854acca4b878fab854c07d = $(`<div id="html_4c16bad8b7854acca4b878fab854c07d" style="width: 100.0%; height: 100.0%;">Harbourfront East,Toronto Islands,Union Station Cluster 0</div>`)[0];
            popup_bf546977985c4e7e9db9141c4eb00f3e.setContent(html_4c16bad8b7854acca4b878fab854c07d);
        

        circle_marker_18f08a2cd9744a7aa606549043c3625f.bindPopup(popup_bf546977985c4e7e9db9141c4eb00f3e)
        ;

        
    
    
            var circle_marker_41857fa5ea154344a2dd971c0f52ed81 = L.circleMarker(
                [43.6542599, -79.3606359],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_13c71fa273054b05bf293ca8e6eeb5a1 = L.popup({"maxWidth": "100%"});

        
            var html_f74fad429d854ebcb0b022812cf7ec36 = $(`<div id="html_f74fad429d854ebcb0b022812cf7ec36" style="width: 100.0%; height: 100.0%;">Harbourfront,Regent Park Cluster 0</div>`)[0];
            popup_13c71fa273054b05bf293ca8e6eeb5a1.setContent(html_f74fad429d854ebcb0b022812cf7ec36);
        

        circle_marker_41857fa5ea154344a2dd971c0f52ed81.bindPopup(popup_13c71fa273054b05bf293ca8e6eeb5a1)
        ;

        
    
    
            var circle_marker_d09c8165bf4d427fbb91d1c07047dd94 = L.circleMarker(
                [43.6616083, -79.46476329999999],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_ba226d5d09f04f06a70a5148a94ecf33 = L.popup({"maxWidth": "100%"});

        
            var html_a6352525ce6e44eda685820f303cf58c = $(`<div id="html_a6352525ce6e44eda685820f303cf58c" style="width: 100.0%; height: 100.0%;">High Park,The Junction South Cluster 0</div>`)[0];
            popup_ba226d5d09f04f06a70a5148a94ecf33.setContent(html_a6352525ce6e44eda685820f303cf58c);
        

        circle_marker_d09c8165bf4d427fbb91d1c07047dd94.bindPopup(popup_ba226d5d09f04f06a70a5148a94ecf33)
        ;

        
    
    
            var circle_marker_bfd536ae936c44b0981d1043ca74c213 = L.circleMarker(
                [43.7280205, -79.3887901],
                {"bubblingMouseEvents": true, "color": "#00b5eb", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#00b5eb", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_1eaed3d42b244226916c3d3a23853484 = L.popup({"maxWidth": "100%"});

        
            var html_a8726d30a21d4bcb8497fc2da94e590f = $(`<div id="html_a8726d30a21d4bcb8497fc2da94e590f" style="width: 100.0%; height: 100.0%;">Lawrence Park Cluster 2</div>`)[0];
            popup_1eaed3d42b244226916c3d3a23853484.setContent(html_a8726d30a21d4bcb8497fc2da94e590f);
        

        circle_marker_bfd536ae936c44b0981d1043ca74c213.bindPopup(popup_1eaed3d42b244226916c3d3a23853484)
        ;

        
    
    
            var circle_marker_958a536a947d459aaeda4a62e8c7f0eb = L.circleMarker(
                [43.647926700000006, -79.4197497],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_7934f62fa3904d9cbf753468f1db31a3 = L.popup({"maxWidth": "100%"});

        
            var html_0174238198f84f48b06e30ab0b32a7f2 = $(`<div id="html_0174238198f84f48b06e30ab0b32a7f2" style="width: 100.0%; height: 100.0%;">Little Portugal,Trinity Cluster 0</div>`)[0];
            popup_7934f62fa3904d9cbf753468f1db31a3.setContent(html_0174238198f84f48b06e30ab0b32a7f2);
        

        circle_marker_958a536a947d459aaeda4a62e8c7f0eb.bindPopup(popup_7934f62fa3904d9cbf753468f1db31a3)
        ;

        
    
    
            var circle_marker_c2f1c589dfd241eb9754530d561744d6 = L.circleMarker(
                [43.6895743, -79.38315990000002],
                {"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_4145cf5421354f49a8542166190dc103);
        
    
        var popup_3627d8a2ddaf4b02bfd345bf79978b69 = L.popup({"maxWidth": "100%"});

        
            var html_d08b3073644a4e27945858280132317e = $(`<div id="html_d08b3073644a4e27945858280132317e" style="width: 100.0%; height: 100.0%;">Moore Park,Summerhill East Cluster 1</div>`)[0];
            popup_3627d8a2ddaf4b02bfd345bf79978b69.setContent(html_d08b3073644a4e27945858280132317e);
        

        circle_marker_c2f1c589dfd241eb9754530d561744d6.bindPopup(popup_3627d8a2ddaf4b02bfd345bf79978b69)
        ;

        
    
    
            var circle_marker_a75b378fdc6b4b1a8a12074e3b09715c = L.circleMarker(
                [43.7153834, -79.40567840000001],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_2bb5322130b543b7946069fe05a5c493 = L.popup({"maxWidth": "100%"});

        
            var html_eaa5f310dd66425b8082eb263e7d4532 = $(`<div id="html_eaa5f310dd66425b8082eb263e7d4532" style="width: 100.0%; height: 100.0%;">North Toronto West Cluster 0</div>`)[0];
            popup_2bb5322130b543b7946069fe05a5c493.setContent(html_eaa5f310dd66425b8082eb263e7d4532);
        

        circle_marker_a75b378fdc6b4b1a8a12074e3b09715c.bindPopup(popup_2bb5322130b543b7946069fe05a5c493)
        ;

        
    
    
            var circle_marker_818c44ed372148d48d99668fa3d15b6f = L.circleMarker(
                [43.6489597, -79.456325],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_0c5ad0f6c4ae49ba87dbf55cd1915309 = L.popup({"maxWidth": "100%"});

        
            var html_ef725a9813314337b915fad55d0b4230 = $(`<div id="html_ef725a9813314337b915fad55d0b4230" style="width: 100.0%; height: 100.0%;">Parkdale,Roncesvalles Cluster 0</div>`)[0];
            popup_0c5ad0f6c4ae49ba87dbf55cd1915309.setContent(html_ef725a9813314337b915fad55d0b4230);
        

        circle_marker_818c44ed372148d48d99668fa3d15b6f.bindPopup(popup_0c5ad0f6c4ae49ba87dbf55cd1915309)
        ;

        
    
    
            var circle_marker_945fe5b06b0e4b8da14fc999014533ef = L.circleMarker(
                [43.6795626, -79.37752940000001],
                {"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_4145cf5421354f49a8542166190dc103);
        
    
        var popup_a301409c9bc94e7a8bfeff0d92b30b5c = L.popup({"maxWidth": "100%"});

        
            var html_0349d78a4e854d94a55d38f43c9c80fa = $(`<div id="html_0349d78a4e854d94a55d38f43c9c80fa" style="width: 100.0%; height: 100.0%;">Rosedale Cluster 1</div>`)[0];
            popup_a301409c9bc94e7a8bfeff0d92b30b5c.setContent(html_0349d78a4e854d94a55d38f43c9c80fa);
        

        circle_marker_945fe5b06b0e4b8da14fc999014533ef.bindPopup(popup_a301409c9bc94e7a8bfeff0d92b30b5c)
        ;

        
    
    
            var circle_marker_976e6a53ee544b95ae9d0206b6c31f76 = L.circleMarker(
                [43.7116948, -79.41693559999999],
                {"bubblingMouseEvents": true, "color": "#80ffb4", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#80ffb4", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_b0e502f9327541638b972d50540b413f = L.popup({"maxWidth": "100%"});

        
            var html_df8b8005f07947018f45f52ba0e01ddf = $(`<div id="html_df8b8005f07947018f45f52ba0e01ddf" style="width: 100.0%; height: 100.0%;">Roselawn Cluster 3</div>`)[0];
            popup_b0e502f9327541638b972d50540b413f.setContent(html_df8b8005f07947018f45f52ba0e01ddf);
        

        circle_marker_976e6a53ee544b95ae9d0206b6c31f76.bindPopup(popup_b0e502f9327541638b972d50540b413f)
        ;

        
    
    
            var circle_marker_4fd8a69b87364193b9b25c5429f6c200 = L.circleMarker(
                [43.6515706, -79.4844499],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_26aa4caf0cec4cceb30611872aebe7bf = L.popup({"maxWidth": "100%"});

        
            var html_4493e5ac767247838a1396cbc1476310 = $(`<div id="html_4493e5ac767247838a1396cbc1476310" style="width: 100.0%; height: 100.0%;">Runnymede,Swansea Cluster 0</div>`)[0];
            popup_26aa4caf0cec4cceb30611872aebe7bf.setContent(html_4493e5ac767247838a1396cbc1476310);
        

        circle_marker_4fd8a69b87364193b9b25c5429f6c200.bindPopup(popup_26aa4caf0cec4cceb30611872aebe7bf)
        ;

        
    
    
            var circle_marker_92237f98b64042f9bc944497c8bc0213 = L.circleMarker(
                [43.6571618, -79.37893709999999],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_31d979b687634abdae5253b5d1d64ec6 = L.popup({"maxWidth": "100%"});

        
            var html_0a4042a6c87b42c3bbe6cfada13be1cd = $(`<div id="html_0a4042a6c87b42c3bbe6cfada13be1cd" style="width: 100.0%; height: 100.0%;">Ryerson,Garden District Cluster 0</div>`)[0];
            popup_31d979b687634abdae5253b5d1d64ec6.setContent(html_0a4042a6c87b42c3bbe6cfada13be1cd);
        

        circle_marker_92237f98b64042f9bc944497c8bc0213.bindPopup(popup_31d979b687634abdae5253b5d1d64ec6)
        ;

        
    
    
            var circle_marker_3fd234641cff42b6b8b3673557f68494 = L.circleMarker(
                [43.6514939, -79.3754179],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_2e8d0d77c9be46fdb7ec1ac4404f81fa = L.popup({"maxWidth": "100%"});

        
            var html_6076279f13a14046beb95271cc2aeb72 = $(`<div id="html_6076279f13a14046beb95271cc2aeb72" style="width: 100.0%; height: 100.0%;">St. James Town Cluster 0</div>`)[0];
            popup_2e8d0d77c9be46fdb7ec1ac4404f81fa.setContent(html_6076279f13a14046beb95271cc2aeb72);
        

        circle_marker_3fd234641cff42b6b8b3673557f68494.bindPopup(popup_2e8d0d77c9be46fdb7ec1ac4404f81fa)
        ;

        
    
    
            var circle_marker_32de308427364b329e02b917e179ac98 = L.circleMarker(
                [43.6464352, -79.37484599999998],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_119d1600da6148b592af46ef2b8b6f19 = L.popup({"maxWidth": "100%"});

        
            var html_c07d4db61102492ea4ca4874d2378ab0 = $(`<div id="html_c07d4db61102492ea4ca4874d2378ab0" style="width: 100.0%; height: 100.0%;">Stn A PO Boxes 25 The Esplanade Cluster 0</div>`)[0];
            popup_119d1600da6148b592af46ef2b8b6f19.setContent(html_c07d4db61102492ea4ca4874d2378ab0);
        

        circle_marker_32de308427364b329e02b917e179ac98.bindPopup(popup_119d1600da6148b592af46ef2b8b6f19)
        ;

        
    
    
            var circle_marker_f9961ad44b444936831e50fa7081c8cf = L.circleMarker(
                [43.6595255, -79.340923],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_579b588216da4bfaa94fbd9a7c882ab0 = L.popup({"maxWidth": "100%"});

        
            var html_a43ff6d5d0224830b0d0643fb3d9fe30 = $(`<div id="html_a43ff6d5d0224830b0d0643fb3d9fe30" style="width: 100.0%; height: 100.0%;">Studio District Cluster 0</div>`)[0];
            popup_579b588216da4bfaa94fbd9a7c882ab0.setContent(html_a43ff6d5d0224830b0d0643fb3d9fe30);
        

        circle_marker_f9961ad44b444936831e50fa7081c8cf.bindPopup(popup_579b588216da4bfaa94fbd9a7c882ab0)
        ;

        
    
    
            var circle_marker_e99261153aa2437cbd379957d69d57c0 = L.circleMarker(
                [43.6727097, -79.40567840000001],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_ab3ff7ff79224a4eaa347f6871e3b238 = L.popup({"maxWidth": "100%"});

        
            var html_cfef4625c4514d50b4fb8651a7bbb125 = $(`<div id="html_cfef4625c4514d50b4fb8651a7bbb125" style="width: 100.0%; height: 100.0%;">The Annex,North Midtown,Yorkville Cluster 0</div>`)[0];
            popup_ab3ff7ff79224a4eaa347f6871e3b238.setContent(html_cfef4625c4514d50b4fb8651a7bbb125);
        

        circle_marker_e99261153aa2437cbd379957d69d57c0.bindPopup(popup_ab3ff7ff79224a4eaa347f6871e3b238)
        ;

        
    
    
            var circle_marker_2bd8e97477d440e5ab3c6cf868bb3e75 = L.circleMarker(
                [43.67635739999999, -79.2930312],
                {"bubblingMouseEvents": true, "color": "#ffb360", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ffb360", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_f3ece6b49c19406e9f434874bd3501db = L.popup({"maxWidth": "100%"});

        
            var html_b8ac104b9f494831b914b123ee1e016a = $(`<div id="html_b8ac104b9f494831b914b123ee1e016a" style="width: 100.0%; height: 100.0%;">The Beaches Cluster 4</div>`)[0];
            popup_f3ece6b49c19406e9f434874bd3501db.setContent(html_b8ac104b9f494831b914b123ee1e016a);
        

        circle_marker_2bd8e97477d440e5ab3c6cf868bb3e75.bindPopup(popup_f3ece6b49c19406e9f434874bd3501db)
        ;

        
    
    
            var circle_marker_7bf96abb69564963aca9a14a45460f9d = L.circleMarker(
                [43.6689985, -79.31557159999998],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_b163e64d39004670a9ef3c9a32b97ad9 = L.popup({"maxWidth": "100%"});

        
            var html_6e42080d8a424d9a83cc39f8fdcbf405 = $(`<div id="html_6e42080d8a424d9a83cc39f8fdcbf405" style="width: 100.0%; height: 100.0%;">The Beaches West,India Bazaar Cluster 0</div>`)[0];
            popup_b163e64d39004670a9ef3c9a32b97ad9.setContent(html_6e42080d8a424d9a83cc39f8fdcbf405);
        

        circle_marker_7bf96abb69564963aca9a14a45460f9d.bindPopup(popup_b163e64d39004670a9ef3c9a32b97ad9)
        ;

        
    
    
            var circle_marker_1a9a3bab9b2143408e6a2ba60ec05921 = L.circleMarker(
                [43.6795571, -79.352188],
                {"bubblingMouseEvents": true, "color": "#ff0000", "dashArray": null, "dashOffset": null, "fill": true, "fillColor": "#ff0000", "fillOpacity": 0.7, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "opacity": 1.0, "radius": 5, "stroke": true, "weight": 3}
            ).addTo(map_4145cf5421354f49a8542166190dc103);
        
    
        var popup_a39bb5a2e47243f1946eec76433e4046 = L.popup({"maxWidth": "100%"});

        
            var html_e9f1ee87149b4ee69d405bb65ca2014a = $(`<div id="html_e9f1ee87149b4ee69d405bb65ca2014a" style="width: 100.0%; height: 100.0%;">The Danforth West,Riverdale Cluster 0</div>`)[0];
            popup_a39bb5a2e47243f1946eec76433e4046.setContent(html_e9f1ee87149b4ee69d405bb65ca2014a);
        

        circle_marker_1a9a3bab9b2143408e6a2ba60ec05921.bindPopup(popup_a39bb5a2e47243f1946eec76433e4046)
        ;

        
    
</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 0xb9f9a90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D6kkPTgwdbjv",
        "colab_type": "text"
      },
      "source": [
        "#### Results show most of neighbourhood belong to the same cluster"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gGKQIBhNdbjw",
        "colab_type": "text"
      },
      "source": [
        "#### Find out what are the top 10  most common venues for each cluster"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0lE_WiBHdbjx",
        "colab_type": "code",
        "colab": {},
        "outputId": "f9a5e631-fe17-452f-cbab-13c7be4b83ae"
      },
      "source": [
        "toronto_grouped_mean = toronto_grouped.groupby('Cluster Labels').mean()\n",
        "toronto_grouped_mean"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Adult Boutique</th>\n",
              "      <th>Afghan Restaurant</th>\n",
              "      <th>Airport</th>\n",
              "      <th>Airport Food Court</th>\n",
              "      <th>Airport Gate</th>\n",
              "      <th>Airport Lounge</th>\n",
              "      <th>Airport Service</th>\n",
              "      <th>Airport Terminal</th>\n",
              "      <th>American Restaurant</th>\n",
              "      <th>Antique Shop</th>\n",
              "      <th>...</th>\n",
              "      <th>Train Station</th>\n",
              "      <th>Vegetarian / Vegan Restaurant</th>\n",
              "      <th>Video Game Store</th>\n",
              "      <th>Vietnamese Restaurant</th>\n",
              "      <th>Wine Bar</th>\n",
              "      <th>Wings Joint</th>\n",
              "      <th>Women's Store</th>\n",
              "      <th>Yoga Studio</th>\n",
              "      <th>Latitude</th>\n",
              "      <th>Longitude</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cluster Labels</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.000344</td>\n",
              "      <td>0.000344</td>\n",
              "      <td>0.00202</td>\n",
              "      <td>0.00202</td>\n",
              "      <td>0.00202</td>\n",
              "      <td>0.00404</td>\n",
              "      <td>0.006061</td>\n",
              "      <td>0.00404</td>\n",
              "      <td>0.01136</td>\n",
              "      <td>0.002179</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000909</td>\n",
              "      <td>0.007754</td>\n",
              "      <td>0.001489</td>\n",
              "      <td>0.004428</td>\n",
              "      <td>0.002958</td>\n",
              "      <td>0.000344</td>\n",
              "      <td>0.000303</td>\n",
              "      <td>0.007674</td>\n",
              "      <td>43.662750</td>\n",
              "      <td>-79.392610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>43.684568</td>\n",
              "      <td>-79.380345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>43.728020</td>\n",
              "      <td>-79.388790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>43.711695</td>\n",
              "      <td>-79.416936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>43.676357</td>\n",
              "      <td>-79.293031</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 241 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                Adult Boutique  Afghan Restaurant  Airport  \\\n",
              "Cluster Labels                                               \n",
              "0                     0.000344           0.000344  0.00202   \n",
              "1                     0.000000           0.000000  0.00000   \n",
              "2                     0.000000           0.000000  0.00000   \n",
              "3                     0.000000           0.000000  0.00000   \n",
              "4                     0.000000           0.000000  0.00000   \n",
              "\n",
              "                Airport Food Court  Airport Gate  Airport Lounge  \\\n",
              "Cluster Labels                                                     \n",
              "0                          0.00202       0.00202         0.00404   \n",
              "1                          0.00000       0.00000         0.00000   \n",
              "2                          0.00000       0.00000         0.00000   \n",
              "3                          0.00000       0.00000         0.00000   \n",
              "4                          0.00000       0.00000         0.00000   \n",
              "\n",
              "                Airport Service  Airport Terminal  American Restaurant  \\\n",
              "Cluster Labels                                                           \n",
              "0                      0.006061           0.00404              0.01136   \n",
              "1                      0.000000           0.00000              0.00000   \n",
              "2                      0.000000           0.00000              0.00000   \n",
              "3                      0.000000           0.00000              0.00000   \n",
              "4                      0.000000           0.00000              0.00000   \n",
              "\n",
              "                Antique Shop    ...      Train Station  \\\n",
              "Cluster Labels                  ...                      \n",
              "0                   0.002179    ...           0.000909   \n",
              "1                   0.000000    ...           0.000000   \n",
              "2                   0.000000    ...           0.000000   \n",
              "3                   0.000000    ...           0.000000   \n",
              "4                   0.000000    ...           0.000000   \n",
              "\n",
              "                Vegetarian / Vegan Restaurant  Video Game Store  \\\n",
              "Cluster Labels                                                    \n",
              "0                                    0.007754          0.001489   \n",
              "1                                    0.000000          0.000000   \n",
              "2                                    0.000000          0.000000   \n",
              "3                                    0.000000          0.000000   \n",
              "4                                    0.000000          0.000000   \n",
              "\n",
              "                Vietnamese Restaurant  Wine Bar  Wings Joint  Women's Store  \\\n",
              "Cluster Labels                                                                \n",
              "0                            0.004428  0.002958     0.000344       0.000303   \n",
              "1                            0.000000  0.000000     0.000000       0.000000   \n",
              "2                            0.000000  0.000000     0.000000       0.000000   \n",
              "3                            0.000000  0.000000     0.000000       0.000000   \n",
              "4                            0.000000  0.000000     0.000000       0.000000   \n",
              "\n",
              "                Yoga Studio   Latitude  Longitude  \n",
              "Cluster Labels                                     \n",
              "0                  0.007674  43.662750 -79.392610  \n",
              "1                  0.000000  43.684568 -79.380345  \n",
              "2                  0.000000  43.728020 -79.388790  \n",
              "3                  0.000000  43.711695 -79.416936  \n",
              "4                  0.000000  43.676357 -79.293031  \n",
              "\n",
              "[5 rows x 241 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t9_xiujadbj2",
        "colab_type": "code",
        "colab": {},
        "outputId": "b8a2968d-6d01-4ab5-9251-d4728a3d6af4"
      },
      "source": [
        "toronto_grouped_mean = toronto_grouped_mean.drop(columns = ['Latitude','Longitude'])\n",
        "\n",
        "x=pd.DataFrame(toronto_grouped_mean).T\n",
        "rslt = pd.DataFrame(np.zeros((0,5)), columns=['top1','top2','top3','top4','top5'])\n",
        "for i in x.columns:\n",
        "    df1row = pd.DataFrame(x.nlargest(5, i).index.tolist(), index=['top1','top2','top3','top4','top5']).T\n",
        "    rslt = pd.concat([rslt, df1row], axis=0)\n",
        "\n",
        "rslt.index=toronto_grouped_mean.index\n",
        "rslt"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>top1</th>\n",
              "      <th>top2</th>\n",
              "      <th>top3</th>\n",
              "      <th>top4</th>\n",
              "      <th>top5</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cluster Labels</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Coffee Shop</td>\n",
              "      <td>Café</td>\n",
              "      <td>Park</td>\n",
              "      <td>Restaurant</td>\n",
              "      <td>Italian Restaurant</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Park</td>\n",
              "      <td>Playground</td>\n",
              "      <td>Gym</td>\n",
              "      <td>Trail</td>\n",
              "      <td>Adult Boutique</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Bus Line</td>\n",
              "      <td>Dim Sum Restaurant</td>\n",
              "      <td>Park</td>\n",
              "      <td>Swim School</td>\n",
              "      <td>Adult Boutique</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Garden</td>\n",
              "      <td>Music Venue</td>\n",
              "      <td>Adult Boutique</td>\n",
              "      <td>Afghan Restaurant</td>\n",
              "      <td>Airport</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Astrologer</td>\n",
              "      <td>Boutique</td>\n",
              "      <td>Health Food Store</td>\n",
              "      <td>Neighborhood</td>\n",
              "      <td>Pub</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       top1                top2               top3  \\\n",
              "Cluster Labels                                                       \n",
              "0               Coffee Shop                Café               Park   \n",
              "1                      Park          Playground                Gym   \n",
              "2                  Bus Line  Dim Sum Restaurant               Park   \n",
              "3                    Garden         Music Venue     Adult Boutique   \n",
              "4                Astrologer            Boutique  Health Food Store   \n",
              "\n",
              "                             top4                top5  \n",
              "Cluster Labels                                         \n",
              "0                      Restaurant  Italian Restaurant  \n",
              "1                           Trail      Adult Boutique  \n",
              "2                     Swim School      Adult Boutique  \n",
              "3               Afghan Restaurant             Airport  \n",
              "4                    Neighborhood                 Pub  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x6hpft1edbj4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}