Coursera_Capstone_Final.ipynb

{
    "cells": [
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": "Requirement already satisfied: beautifulsoup4 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (4.10.0)\nRequirement already satisfied: soupsieve>1.2 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from beautifulsoup4) (2.3.1)\nRequirement already satisfied: lxml in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (4.7.1)\nCollecting package metadata (current_repodata.json): done\nSolving environment: done\n\n# All requested packages already installed.\n\nFolium installed\nLibraries imported.\n"
                }
            ],
            "source": "!pip install beautifulsoup4\n!pip install lxml\nimport requests # library to handle requests\nimport pandas as pd # library for data analsysis\nimport numpy as np # library to handle data in a vectorized manner\nimport random # library for random number generation\n\n#!conda install -c conda-forge geopy --yes \nfrom geopy.geocoders import Nominatim # module to convert an address into latitude and longitude values\n\n# libraries for displaying images\nfrom IPython.display import Image \nfrom IPython.core.display import HTML \n\n\nfrom IPython.display import display_html\nimport pandas as pd\nimport numpy as np\n    \n# tranforming json file into a pandas dataframe library\nfrom pandas.io.json import json_normalize\n\n!conda install -c conda-forge folium=0.5.0 --yes\nimport folium # plotting library\nfrom bs4 import BeautifulSoup\nfrom sklearn.cluster import KMeans\nimport matplotlib.cm as cm\nimport matplotlib.colors as colors\n\nprint('Folium installed')\nprint('Libraries imported.')"
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>PostalCode</th>\n      <th>Borough</th>\n      <th>Neighborhood</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>M1B</td>\n      <td>Scarborough</td>\n      <td>Malvern / Rouge</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>M1C</td>\n      <td>Scarborough</td>\n      <td>Rouge Hill / Port Union / Highland Creek</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    </tr>\n    <tr>\n      <th>3</th>\n      <td>M1G</td>\n      <td>Scarborough</td>\n      <td>Woburn</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>M1H</td>\n      <td>Scarborough</td>\n      <td>Cedarbrae</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>M1J</td>\n      <td>Scarborough</td>\n      <td>Scarborough Village</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>M1K</td>\n      <td>Scarborough</td>\n      <td>Kennedy Park / Ionview / East Birchmount Park</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>M1L</td>\n      <td>Scarborough</td>\n      <td>Golden Mile / Clairlea / Oakridge</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>M1M</td>\n      <td>Scarborough</td>\n      <td>Cliffside / Cliffcrest / Scarborough Village West</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>M1N</td>\n      <td>Scarborough</td>\n      <td>Birch Cliff / Cliffside West</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
                        "text/plain": "  PostalCode      Borough                                       Neighborhood\n0        M1B  Scarborough                                    Malvern / Rouge\n1        M1C  Scarborough           Rouge Hill / Port Union / Highland Creek\n2        M1E  Scarborough                Guildwood / Morningside / West Hill\n3        M1G  Scarborough                                             Woburn\n4        M1H  Scarborough                                          Cedarbrae\n5        M1J  Scarborough                                Scarborough Village\n6        M1K  Scarborough      Kennedy Park / Ionview / East Birchmount Park\n7        M1L  Scarborough                  Golden Mile / Clairlea / Oakridge\n8        M1M  Scarborough  Cliffside / Cliffcrest / Scarborough Village West\n9        M1N  Scarborough                       Birch Cliff / Cliffside West"
                    },
                    "execution_count": 4,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "url = 'https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M'\nhtml_data = requests.get(url).text \n\nsoup = BeautifulSoup(html_data, 'html5lib')\n\n# creating Toronto Dataframe\ndf= pd.DataFrame(columns = ['PostalCode','Borough','Neighborhood'])\n\n\n# scrapping all rows of the table\ntable_rows = soup.find('table').tbody.find_all('tr')\n\n# filtering rows and inserting data to df_toronto\nfor rows in table_rows :\n    for column in rows.find_all('td') :\n        if column.span.text != 'Not assigned' :\n            span  = column.span.text.split('(')\n            df = df.append({'PostalCode' : column.b.text,\n                              'Borough' : span[0],\n                              'Neighborhood' : span[1][:-1]}, ignore_index=True)\n            \ndf['Borough']=df['Borough'].replace({'Downtown TorontoStn A PO Boxes25 The Esplanade':'Downtown Toronto Stn A',\n                                             'East TorontoBusiness reply mail Processing Centre969 Eastern':'East Toronto Business',\n                                             'EtobicokeNorthwest':'Etobicoke Northwest','East YorkEast Toronto':'East York/East Toronto',\n                                             'MississaugaCanada Post Gateway Processing Centre':'Mississauga'})\n\ndf = df.sort_values('PostalCode').reset_index(drop = True)\ndf.head(10)"
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": "(103, 3)"
                    },
                    "execution_count": 5,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "df.shape"
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": "--2022-06-13 23:35:40--  https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DS0701EN-SkillsNetwork/labs_v1/Geospatial_Coordinates.csv\nResolving cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)... 198.23.119.245\nConnecting to cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)|198.23.119.245|:443... connected.\nHTTP request sent, awaiting response... 200 OK\nLength: 2788 (2.7K) [text/csv]\nSaving to: \u2018GeoSpataial_Data\u2019\n\nGeoSpataial_Data    100%[===================>]   2.72K  --.-KB/s    in 0s      \n\n2022-06-13 23:35:40 (50.8 MB/s) - \u2018GeoSpataial_Data\u2019 saved [2788/2788]\n\n"
                }
            ],
            "source": "!wget -O GeoSpataial_Data https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DS0701EN-SkillsNetwork/labs_v1/Geospatial_Coordinates.csv\n"
        },
        {
            "cell_type": "code",
            "execution_count": 7,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>PostalCode</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>M1B</td>\n      <td>43.806686</td>\n      <td>-79.194353</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>M1C</td>\n      <td>43.784535</td>\n      <td>-79.160497</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>M1E</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>M1G</td>\n      <td>43.770992</td>\n      <td>-79.216917</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>M1H</td>\n      <td>43.773136</td>\n      <td>-79.239476</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
                        "text/plain": "  PostalCode   Latitude  Longitude\n0        M1B  43.806686 -79.194353\n1        M1C  43.784535 -79.160497\n2        M1E  43.763573 -79.188711\n3        M1G  43.770992 -79.216917\n4        M1H  43.773136 -79.239476"
                    },
                    "execution_count": 7,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "geospatial_data = pd.read_csv('GeoSpataial_Data')\ngeospatial_data.columns = ['PostalCode','Latitude', 'Longitude']\ngeospatial_data.head()"
        },
        {
            "cell_type": "code",
            "execution_count": 8,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": "(103, 3)"
                    },
                    "execution_count": 8,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "geospatial_data.shape"
        },
        {
            "cell_type": "code",
            "execution_count": 9,
            "metadata": {},
            "outputs": [],
            "source": "df = df.join(geospatial_data.set_index('PostalCode'), on = 'PostalCode')"
        },
        {
            "cell_type": "code",
            "execution_count": 10,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>PostalCode</th>\n      <th>Borough</th>\n      <th>Neighborhood</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>M1B</td>\n      <td>Scarborough</td>\n      <td>Malvern / Rouge</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>Rouge Hill / Port Union / Highland Creek</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    <tr>\n      <th>5</th>\n      <td>M1J</td>\n      <td>Scarborough</td>\n      <td>Scarborough Village</td>\n      <td>43.744734</td>\n      <td>-79.239476</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>M1K</td>\n      <td>Scarborough</td>\n      <td>Kennedy Park / Ionview / East Birchmount Park</td>\n      <td>43.727929</td>\n      <td>-79.262029</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>M1L</td>\n      <td>Scarborough</td>\n      <td>Golden Mile / Clairlea / Oakridge</td>\n      <td>43.711112</td>\n      <td>-79.284577</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>M1M</td>\n      <td>Scarborough</td>\n      <td>Cliffside / Cliffcrest / Scarborough Village West</td>\n      <td>43.716316</td>\n      <td>-79.239476</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>M1N</td>\n      <td>Scarborough</td>\n      <td>Birch Cliff / Cliffside West</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
                        "text/plain": "  PostalCode      Borough                                       Neighborhood  \\\n0        M1B  Scarborough                                    Malvern / Rouge   \n1        M1C  Scarborough           Rouge Hill / Port Union / Highland Creek   \n2        M1E  Scarborough                Guildwood / Morningside / West Hill   \n3        M1G  Scarborough                                             Woburn   \n4        M1H  Scarborough                                          Cedarbrae   \n5        M1J  Scarborough                                Scarborough Village   \n6        M1K  Scarborough      Kennedy Park / Ionview / East Birchmount Park   \n7        M1L  Scarborough                  Golden Mile / Clairlea / Oakridge   \n8        M1M  Scarborough  Cliffside / Cliffcrest / Scarborough Village West   \n9        M1N  Scarborough                       Birch Cliff / Cliffside West   \n\n    Latitude  Longitude  \n0  43.806686 -79.194353  \n1  43.784535 -79.160497  \n2  43.763573 -79.188711  \n3  43.770992 -79.216917  \n4  43.773136 -79.239476  \n5  43.744734 -79.239476  \n6  43.727929 -79.262029  \n7  43.711112 -79.284577  \n8  43.716316 -79.239476  \n9  43.692657 -79.264848  "
                    },
                    "execution_count": 10,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "df.head(10)"
        },
        {
            "cell_type": "code",
            "execution_count": 11,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": "North York                24\nScarborough               17\nDowntown Toronto          17\nEtobicoke                 11\nCentral Toronto            9\nWest Toronto               6\nYork                       5\nEast York                  4\nEast Toronto               4\nEast York/East Toronto     1\nDowntown Toronto Stn A     1\nQueen's Park               1\nMississauga                1\nEast Toronto Business      1\nEtobicoke Northwest        1\nName: Borough, dtype: int64"
                    },
                    "execution_count": 11,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "df.Borough.value_counts()"
        },
        {
            "cell_type": "code",
            "execution_count": 12,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": "The geograpical coordinate of Toronto City are 43.6534817, -79.3839347.\n"
                }
            ],
            "source": "address = 'Toronto, Ontario'\ngeolocator = Nominatim(user_agent = 'ny_explorer')\nlocation = geolocator.geocode(address)\nlatitude = location.latitude\nlongitude = location.longitude\nprint('The geograpical coordinate of Toronto City are {}, {}.'.format(latitude, longitude))"
        },
        {
            "cell_type": "code",
            "execution_count": 13,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n&lt;head&gt;    \n    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n    &lt;script&gt;L_PREFER_CANVAS = false; L_NO_TOUCH = false; L_DISABLE_3D = false;&lt;/script&gt;\n    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n    &lt;script src=&quot;https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js&quot;&gt;&lt;/script&gt;\n    &lt;script src=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js&quot;&gt;&lt;/script&gt;\n    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.css&quot;/&gt;\n    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css&quot;/&gt;\n    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css&quot;/&gt;\n    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css&quot;/&gt;\n    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://rawgit.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css&quot;/&gt;\n    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n    \n            &lt;style&gt; 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style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Roselawn, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_837f578bb91670f84eaa34466d7703aa.setContent(html_806093074cd9862e98e6f6a134a04792);\n            \n\n            circle_marker_d1bf4be3604f21bd9bb4a01d06005df7.bindPopup(popup_837f578bb91670f84eaa34466d7703aa);\n\n            \n        \n    \n            var circle_marker_733b0ed9c2d34fafb5a7e48e7e29e207 = L.circleMarker(\n                [43.6969476,-79.4113072],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_e6d960b870c4999e2d2130fc5a9da931 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_0ee7edec999790703371ccd37d5cfe0f = $(&#x27;&lt;div id=&quot;html_0ee7edec999790703371ccd37d5cfe0f&quot; 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style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;The Annex / North Midtown / Yorkville, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_aae9cbc3104eab68832ae0be38f59bd0.setContent(html_30428b723d4c7a196d9ff2b4a9bdb1f1);\n            \n\n            circle_marker_6f472c97634d64fb32bea04e65ba4ee8.bindPopup(popup_aae9cbc3104eab68832ae0be38f59bd0);\n\n            \n        \n    \n            var circle_marker_2118f12576e7cce86ff90986edea55c9 = L.circleMarker(\n                [43.6626956,-79.4000493],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_17d010aa9387d651fae1132a55a0f756 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_658c3da6c0977a698ee998b0d7f819aa = $(&#x27;&lt;div id=&quot;html_658c3da6c0977a698ee998b0d7f819aa&quot; 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style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Enclave of M5E, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_2767624b3005459a5f2aec1563aac497.setContent(html_1bddcded3f91877c56667b4a291a6ea2);\n            \n\n            circle_marker_e80753cf0cf000a4cfffe77cef2351b6.bindPopup(popup_2767624b3005459a5f2aec1563aac497);\n\n            \n        \n    \n            var circle_marker_59eaa9fd22e771241625c8e990173912 = L.circleMarker(\n                [43.6484292,-79.3822802],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_7b325d9460ed2f275290584f8848d6d7 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_daabce292217ace1ce4d4597b366a6a3 = $(&#x27;&lt;div id=&quot;html_daabce292217ace1ce4d4597b366a6a3&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;First Canadian Place / Underground city, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_7b325d9460ed2f275290584f8848d6d7.setContent(html_daabce292217ace1ce4d4597b366a6a3);\n            \n\n            circle_marker_59eaa9fd22e771241625c8e990173912.bindPopup(popup_7b325d9460ed2f275290584f8848d6d7);\n\n            \n        \n    \n            var circle_marker_b2965465b4ab0dbce993f551f3b7978a = L.circleMarker(\n                [43.669542,-79.4225637],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_f4ee757dbb9f63500e3e2318bcd2ce5f = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_22b4c2e85029351a9dedbd10f9648873 = $(&#x27;&lt;div id=&quot;html_22b4c2e85029351a9dedbd10f9648873&quot; 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style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Dufferin / Dovercourt Village, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_56cae61af42206a2f0f09b2748898623.setContent(html_dffdc957d601cf4707b6e7428bc99f01);\n            \n\n            circle_marker_4ecb41cf36ba70df7200a903da688cc4.bindPopup(popup_56cae61af42206a2f0f09b2748898623);\n\n            \n        \n    \n            var circle_marker_87f4696361a5c72d17d40b9feb6a0eba = L.circleMarker(\n                [43.6479267,-79.4197497],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_abadc99994fbc93906a16dddd3c6ce96 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_747bc3162ac780923765676555ba5995 = $(&#x27;&lt;div id=&quot;html_747bc3162ac780923765676555ba5995&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Little Portugal / Trinity, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_abadc99994fbc93906a16dddd3c6ce96.setContent(html_747bc3162ac780923765676555ba5995);\n            \n\n            circle_marker_87f4696361a5c72d17d40b9feb6a0eba.bindPopup(popup_abadc99994fbc93906a16dddd3c6ce96);\n\n            \n        \n    \n            var circle_marker_8bfeba936061bab19523a609cb0376af = L.circleMarker(\n                [43.6368472,-79.4281914],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_9d868b46dd156b6efdb69e242c3ffa52 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_1e427851047f9675683fd88d10393f58 = $(&#x27;&lt;div id=&quot;html_1e427851047f9675683fd88d10393f58&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Brockton / Parkdale Village / Exhibition Place, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_9d868b46dd156b6efdb69e242c3ffa52.setContent(html_1e427851047f9675683fd88d10393f58);\n            \n\n            circle_marker_8bfeba936061bab19523a609cb0376af.bindPopup(popup_9d868b46dd156b6efdb69e242c3ffa52);\n\n            \n        \n    \n            var circle_marker_e39fda9426813fc09a7893bc8cfa15e9 = L.circleMarker(\n                [43.6616083,-79.4647633],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_106ad5717d664b749c886fee140aa7af = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_31db31f7926a091dfaebe14b1a979ff3 = $(&#x27;&lt;div id=&quot;html_31db31f7926a091dfaebe14b1a979ff3&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;High Park / The Junction South, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_106ad5717d664b749c886fee140aa7af.setContent(html_31db31f7926a091dfaebe14b1a979ff3);\n            \n\n            circle_marker_e39fda9426813fc09a7893bc8cfa15e9.bindPopup(popup_106ad5717d664b749c886fee140aa7af);\n\n            \n        \n    \n            var circle_marker_28ba2f586fba0fa5bb801b81b59da91b = L.circleMarker(\n                [43.6489597,-79.456325],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;blue&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;blue&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_bc39c40ebac4088887771c01639c5428 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_78eae26a1cbbbe320d44d33f09e5e265 = $(&#x27;&lt;div id=&quot;html_78eae26a1cbbbe320d44d33f09e5e265&quot; 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style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Enclave of M4L, [&amp;#39;Downtown Toronto&amp;#39;, &amp;#39;Central Toronto&amp;#39;, &amp;#39;West Toronto&amp;#39;, &amp;#39;East Toronto&amp;#39;, &amp;#39;Downtown Toronto Stn A&amp;#39;, &amp;#39;East Toronto Business&amp;#39;, &amp;#39;East York/East Toronto&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_df52dcddcab6525562910da1a0403844.setContent(html_5cfe518d2d757afd85ff4b86ce073f7a);\n            \n\n            circle_marker_6df5f36cae43e3574e28141fb9005e0a.bindPopup(popup_df52dcddcab6525562910da1a0403844);\n\n            \n        \n    \n            var circle_marker_677683f15e504aee7c162512588257fd = L.circleMarker(\n                [43.8066863,-79.1943534],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;green&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;green&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_89ebce4539dbd8df3ef2c542703f5919 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_ce99926ffb661d42d01edf3ce88c27b7 = $(&#x27;&lt;div id=&quot;html_ce99926ffb661d42d01edf3ce88c27b7&quot; 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style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Kingsview Village / St. Phillips / Martin Grove Gardens / Richview Gardens, [&amp;#39;Etobicoke&amp;#39;, &amp;#39;Etobicoke Northwest&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_fd765f53e255b493d084c3d7663c3087.setContent(html_bf0dbe95c897b706704ade9118fc7ac3);\n            \n\n            circle_marker_b65f060a442ed98e265e72afa64979f5.bindPopup(popup_fd765f53e255b493d084c3d7663c3087);\n\n            \n        \n    \n            var circle_marker_63d9d704d3c0eb662de6516858c09af8 = L.circleMarker(\n                [43.7394164,-79.5884369],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;purple&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;purple&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_9d3ade2bcbb1002b0396ad2980c82ed3 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_7aa407ffae4ec6ca40573f96db4c075f = $(&#x27;&lt;div id=&quot;html_7aa407ffae4ec6ca40573f96db4c075f&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;South Steeles / Silverstone / Humbergate / Jamestown / Mount Olive / Beaumond Heights / Thistletown / Albion Gardens, [&amp;#39;Etobicoke&amp;#39;, &amp;#39;Etobicoke Northwest&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_9d3ade2bcbb1002b0396ad2980c82ed3.setContent(html_7aa407ffae4ec6ca40573f96db4c075f);\n            \n\n            circle_marker_63d9d704d3c0eb662de6516858c09af8.bindPopup(popup_9d3ade2bcbb1002b0396ad2980c82ed3);\n\n            \n        \n    \n            var circle_marker_192a05d6385270c4bde08f2787fba051 = L.circleMarker(\n                [43.7067483,-79.5940544],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;purple&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;purple&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_fac29f13a7ee0c71449694a6b5c0a953 = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_32b88b780987e177f5daba47c0dba019 = $(&#x27;&lt;div id=&quot;html_32b88b780987e177f5daba47c0dba019&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Clairville / Humberwood / Woodbine Downs / West Humber / Kipling Heights / Rexdale / Elms / Tandridge / Old Rexdale, [&amp;#39;Etobicoke&amp;#39;, &amp;#39;Etobicoke Northwest&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_fac29f13a7ee0c71449694a6b5c0a953.setContent(html_32b88b780987e177f5daba47c0dba019);\n            \n\n            circle_marker_192a05d6385270c4bde08f2787fba051.bindPopup(popup_fac29f13a7ee0c71449694a6b5c0a953);\n\n            \n        \n    \n            var circle_marker_83ed972909972c8cad01a99f2326f7c8 = L.circleMarker(\n                [43.6623015,-79.3894938],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;orange&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;orange&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_419f343e1529354b39a33cc8e99a77bf = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_3beed8f9b07c6a43ea39766b467940d1 = $(&#x27;&lt;div id=&quot;html_3beed8f9b07c6a43ea39766b467940d1&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Ontario Provincial Government, [&amp;#34;Queen&amp;#39;s Park&amp;#34;, &amp;#39;Mississauga&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_419f343e1529354b39a33cc8e99a77bf.setContent(html_3beed8f9b07c6a43ea39766b467940d1);\n            \n\n            circle_marker_83ed972909972c8cad01a99f2326f7c8.bindPopup(popup_419f343e1529354b39a33cc8e99a77bf);\n\n            \n        \n    \n            var circle_marker_729cbf7d034d24c73675e94dd92bbca9 = L.circleMarker(\n                [43.6369656,-79.615819],\n                {\n  &quot;bubblingMouseEvents&quot;: true,\n  &quot;color&quot;: &quot;orange&quot;,\n  &quot;dashArray&quot;: null,\n  &quot;dashOffset&quot;: null,\n  &quot;fill&quot;: true,\n  &quot;fillColor&quot;: &quot;orange&quot;,\n  &quot;fillOpacity&quot;: 0.7,\n  &quot;fillRule&quot;: &quot;evenodd&quot;,\n  &quot;lineCap&quot;: &quot;round&quot;,\n  &quot;lineJoin&quot;: &quot;round&quot;,\n  &quot;opacity&quot;: 1.0,\n  &quot;radius&quot;: 5,\n  &quot;stroke&quot;: true,\n  &quot;weight&quot;: 3\n}\n                ).addTo(map_3a49575c984979e242637f1993e3ef0e);\n            \n    \n            var popup_db4b02dd117dea43dd46b3df49ae2acd = L.popup({maxWidth: &#x27;300&#x27;});\n\n            \n                var html_9a5eab3d4ca3e1ed44d23b0e2f71e211 = $(&#x27;&lt;div id=&quot;html_9a5eab3d4ca3e1ed44d23b0e2f71e211&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Enclave of L4W, [&amp;#34;Queen&amp;#39;s Park&amp;#34;, &amp;#39;Mississauga&amp;#39;]&lt;/div&gt;&#x27;)[0];\n                popup_db4b02dd117dea43dd46b3df49ae2acd.setContent(html_9a5eab3d4ca3e1ed44d23b0e2f71e211);\n            \n\n            circle_marker_729cbf7d034d24c73675e94dd92bbca9.bindPopup(popup_db4b02dd117dea43dd46b3df49ae2acd);\n\n            \n        \n&lt;/script&gt;\" 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 0x7f8cd05faf40>"
                    },
                    "execution_count": 13,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "# segmenting boroughs in 5 categories\nyork = ['North York', 'York ','East York' ]\ntoronto = ['Downtown Toronto', 'Central Toronto', 'West Toronto', 'East Toronto',\n           'Downtown Toronto Stn A' ,'East Toronto Business','East York/East Toronto']\nscarborough = ['Scarborough']\netobicoke = ['Etobicoke','Etobicoke Northwest']\nothers = [\"Queen's Park\", 'Mississauga']\n\nborough_array = [york, toronto, scarborough, etobicoke, others]\n\n# now let's make changes in the dataframe accordingly\ndf1 = df.copy()\nfor boroughs in borough_array :\n    for borough in boroughs :\n        df1.replace(borough, str(boroughs), inplace = True)\n    \ncolors_array = ['red', 'blue', 'green', 'purple', 'orange']\n\n\n# create map of Toronto using latitude and longitude values\nmap_toronto = folium.Map(location=[latitude, longitude], zoom_start=10)\n\n# add markers to map\nfor borough, color in zip(borough_array, colors_array) :\n    df2 = df1[df1.Borough == str(borough)]\n    for lat, lng, borough, neighborhood in zip(df2['Latitude'], df2['Longitude'], df2['Borough'], df2['Neighborhood']):\n        label = '{}, {}'.format(neighborhood, borough)\n        label = folium.Popup(label, parse_html=True)\n        folium.CircleMarker(\n            [lat, lng],\n            radius=5,\n            popup=label,\n            color=color,\n            fill=True,\n            fill_color=color,\n            fill_opacity=0.7,\n            parse_html=False).add_to(map_toronto)  \n    \nmap_toronto"
        },
        {
            "cell_type": "code",
            "execution_count": 14,
            "metadata": {},
            "outputs": [],
            "source": "df_north_york = df[df.Borough == 'North York']\n\nCLIENT_ID = '0RVTYD1VK2FA522PAZNV0O0SLWVRLZBVCHXXG3VCPXKTPM3Y' # your Foursquare ID\nCLIENT_SECRET = 'LDRZ1G3S2XW5GIO45L0L0ONSCZ0WUVKPOKGHKXJH544EKABH' # your Foursquare Secret\nVERSION = '20180605' # Foursquare API version\nLIMIT = 100 # A default Foursquare API limit value"
        },
        {
            "cell_type": "code",
            "execution_count": 15,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>PostalCode</th>\n      <th>Borough</th>\n      <th>Neighborhood</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>17</th>\n      <td>M2H</td>\n      <td>North York</td>\n      <td>Hillcrest Village</td>\n      <td>43.803762</td>\n      <td>-79.363452</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>M2J</td>\n      <td>North York</td>\n      <td>Fairview / Henry Farm / Oriole</td>\n      <td>43.778517</td>\n      <td>-79.346556</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>M2K</td>\n      <td>North York</td>\n      <td>Bayview Village</td>\n      <td>43.786947</td>\n      <td>-79.385975</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>M2L</td>\n      <td>North York</td>\n      <td>York Mills / Silver Hills</td>\n      <td>43.757490</td>\n      <td>-79.374714</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>M2M</td>\n      <td>North York</td>\n      <td>Willowdale / Newtonbrook</td>\n      <td>43.789053</td>\n      <td>-79.408493</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
                        "text/plain": "   PostalCode     Borough                    Neighborhood   Latitude  \\\n17        M2H  North York               Hillcrest Village  43.803762   \n18        M2J  North York  Fairview / Henry Farm / Oriole  43.778517   \n19        M2K  North York                 Bayview Village  43.786947   \n20        M2L  North York       York Mills / Silver Hills  43.757490   \n21        M2M  North York        Willowdale / Newtonbrook  43.789053   \n\n    Longitude  \n17 -79.363452  \n18 -79.346556  \n19 -79.385975  \n20 -79.374714  \n21 -79.408493  "
                    },
                    "execution_count": 15,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "df_north_york = df[df['Borough'] == 'North York']\ndf_north_york.head()"
        },
        {
            "cell_type": "code",
            "execution_count": 16,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": "array(['Scarborough', 'North York', 'East York', 'East Toronto',\n       'East York/East Toronto', 'Central Toronto', 'Downtown Toronto',\n       'Downtown Toronto Stn A', 'York', 'West Toronto', \"Queen's Park\",\n       'Mississauga', 'East Toronto Business', 'Etobicoke',\n       'Etobicoke Northwest'], dtype=object)"
                    },
                    "execution_count": 16,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": "df.Borough.unique()"
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": ""
        }
    ],
    "metadata": {
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            "name": "python",
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