Segmenting and Clustering Neighbourhoods in Toronto_part3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Segmenting and Clustering Neighbourhoods in Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.0 Obtaining neighbourhoods data from Wikipedia "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Library Import\n",
    "import pandas as pd # library for data analsysis \n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: lxml in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (4.6.1)\n",
      "Requirement already satisfied: html5lib in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (0.9999999)\n",
      "Requirement already satisfied: six in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from html5lib) (1.15.0)\n",
      "Requirement already satisfied: lxml in /home/jupyterlab/conda/lib/python3.8/site-packages (4.6.1)\n"
     ]
    }
   ],
   "source": [
    "#This packagae nee to be installed in order to read the html\n",
    "!pip install lxml\n",
    "!pip install html5lib\n",
    "!pip3 install lxml\n",
    "import lxml\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M2A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code           Borough              Neighbourhood\n",
       "0         M1A      Not assigned               Not assigned\n",
       "1         M2A      Not assigned               Not assigned\n",
       "2         M3A        North York                  Parkwoods\n",
       "3         M4A        North York           Victoria Village\n",
       "4         M5A  Downtown Toronto  Regent Park, Harbourfront"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Scraping wikipedia table to pandas data frame\n",
    "import requests\n",
    "df = pd.read_html('https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M')[0]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 Ignore cells with a borough that is Not assigned"
   ]
  },
  {
   "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>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M6A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Lawrence Manor, Lawrence Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park, Ontario Provincial Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M9A</td>\n",
       "      <td>Etobicoke</td>\n",
       "      <td>Islington Avenue, Humber Valley Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Malvern, Rouge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M3B</td>\n",
       "      <td>North York</td>\n",
       "      <td>Don Mills</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M4B</td>\n",
       "      <td>East York</td>\n",
       "      <td>Parkview Hill, Woodbine Gardens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M5B</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Garden District, Ryerson</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code           Borough                                Neighbourhood\n",
       "0         M3A        North York                                    Parkwoods\n",
       "1         M4A        North York                             Victoria Village\n",
       "2         M5A  Downtown Toronto                    Regent Park, Harbourfront\n",
       "3         M6A        North York             Lawrence Manor, Lawrence Heights\n",
       "4         M7A  Downtown Toronto  Queen's Park, Ontario Provincial Government\n",
       "5         M9A         Etobicoke      Islington Avenue, Humber Valley Village\n",
       "6         M1B       Scarborough                               Malvern, Rouge\n",
       "7         M3B        North York                                    Don Mills\n",
       "8         M4B         East York              Parkview Hill, Woodbine Gardens\n",
       "9         M5B  Downtown Toronto                     Garden District, Ryerson"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Ignore cells with a borough that is Not assigned\n",
    "df.drop(df.loc[df['Borough']=='Not assigned'].index, inplace=True)\n",
    "df=df.reset_index(drop= True) #resetting the index\n",
    "df.head(10)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 Merge Boroughs that have the same postal code in a same row."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code      Borough                           Neighbourhood\n",
       "0         M1B  Scarborough                          Malvern, Rouge\n",
       "1         M1C  Scarborough  Rouge Hill, Port Union, Highland Creek\n",
       "2         M1E  Scarborough       Guildwood, Morningside, West Hill\n",
       "3         M1G  Scarborough                                  Woburn\n",
       "4         M1H  Scarborough                               Cedarbrae"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merge Boroughs that have the same postal code in a same row. Separate by comma\n",
    "df_borough=df.groupby('Postal Code').agg({'Borough':'first','Neighbourhood':', '.join}).reset_index()\n",
    "df_borough.sort_values(by=['Postal Code']).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 Assign the name of the Borough to not assiged neighbourhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code      Borough                           Neighbourhood\n",
       "0         M1B  Scarborough                          Malvern, Rouge\n",
       "1         M1C  Scarborough  Rouge Hill, Port Union, Highland Creek\n",
       "2         M1E  Scarborough       Guildwood, Morningside, West Hill\n",
       "3         M1G  Scarborough                                  Woburn\n",
       "4         M1H  Scarborough                               Cedarbrae"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Assign the name of the Borough to not assiged neighbourhood\n",
    "\n",
    "#Find the Not assigned Neighbourhood\n",
    "NA_Neighborhood= df_borough['Neighbourhood'] == 'Not assigned'\n",
    "#NA_Neighborhood[NA_Neighborhood ==False].shape[0] #Count where this condition apply\n",
    "\n",
    "#Assign Borough name to the neighbourhood that are Not Assigned\n",
    "df_borough.loc[NA_Neighborhood, 'Neighbourhood'] = df_borough.loc[NA_Neighborhood, 'Borough'] \n",
    "df_borough.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 Print Row of the DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103, 3)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_borough.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.0 Get the latitude and the longitude coordinates of each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting package metadata (current_repodata.json): done\n",
      "Solving environment: done\n",
      "\n",
      "# All requested packages already installed.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Import the library\n",
    "!conda install -c conda-forge geopy --yes \n",
    "from geopy.geocoders import Nominatim # convert an address into latitude and longitude values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: geocoder in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (1.38.1)\n",
      "Requirement already satisfied: ratelim in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (0.1.6)\n",
      "Requirement already satisfied: future in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (0.18.2)\n",
      "Requirement already satisfied: six in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (1.15.0)\n",
      "Requirement already satisfied: click in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (7.1.2)\n",
      "Requirement already satisfied: requests in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from geocoder) (2.24.0)\n",
      "Requirement already satisfied: decorator in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from ratelim->geocoder) (4.4.2)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (2.10)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (2020.6.20)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (1.25.11)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from requests->geocoder) (3.0.4)\n"
     ]
    }
   ],
   "source": [
    "#Install and import geoconder\n",
    "!pip install geocoder\n",
    "import geocoder # import geocoder\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: bs4 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (0.0.1)\n",
      "Requirement already satisfied: beautifulsoup4 in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from bs4) (4.9.3)\n",
      "Requirement already satisfied: soupsieve>1.2; python_version >= \"3.0\" in /home/jupyterlab/conda/envs/python/lib/python3.6/site-packages (from beautifulsoup4->bs4) (2.0.1)\n"
     ]
    }
   ],
   "source": [
    "#Install and import BeautifulSoup\n",
    "!pip install bs4\n",
    "from bs4 import BeautifulSoup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1B</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M1C</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M1E</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M1G</td>\n",
       "      <td>43.770992</td>\n",
       "      <td>-79.216917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M1H</td>\n",
       "      <td>43.773136</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code   Latitude  Longitude\n",
       "0         M1B  43.806686 -79.194353\n",
       "1         M1C  43.784535 -79.160497\n",
       "2         M1E  43.763573 -79.188711\n",
       "3         M1G  43.770992 -79.216917\n",
       "4         M1H  43.773136 -79.239476"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Getting the coordinates \n",
    "df_coordinate= pd.read_csv('https://cocl.us/Geospatial_data')\n",
    "df_coordinate.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>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>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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code      Borough                           Neighbourhood   Latitude  \\\n",
       "0         M1B  Scarborough                          Malvern, Rouge  43.806686   \n",
       "1         M1C  Scarborough  Rouge Hill, Port Union, Highland Creek  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  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merging the dataframes\n",
    "df_merged=pd.merge(df_borough, df_coordinate, on=\"Postal Code\")\n",
    "df_merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 3 - Explore and cluster the neighborhoods in Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1 Create a Map of Toronto with Boroughs and select one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The dataframe has 10 boroughs and 103 neighborhoods.\n"
     ]
    }
   ],
   "source": [
    "#Count Borough and Neighborhoods\n",
    "print('The dataframe has {} boroughs and {} neighborhoods.'.format(\n",
    "        len(df_merged['Borough'].unique()),\n",
    "        df_merged.shape[0]\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use geopy library to get the latitude and longitude values of Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Toronto are 43.65238435, -79.38356765.\n"
     ]
    }
   ],
   "source": [
    "address = 'Toronto, TO'\n",
    "\n",
    "#geolocator = Nominatim(user_agent=\"to_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a map of Toronto with neighborhoods superimposed on top"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium # map rendering library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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 src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS = false; L_NO_TOUCH = false; L_DISABLE_3D = false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.js"></script>
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.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@1.2.0/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://rawgit.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>
    
            <style> #map_59cd65205f444909bb4d2ad75f82121b {
                position : relative;
                width : 100.0%;
                height: 100.0%;
                left: 0.0%;
                top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_59cd65205f444909bb4d2ad75f82121b" ></div>
        
</body>
<script>    
    

            
                var bounds = null;
            

            var map_59cd65205f444909bb4d2ad75f82121b = L.map(
                                  'map_59cd65205f444909bb4d2ad75f82121b',
                                  {center: [43.65238435,-79.38356765],
                                  zoom: 10,
                                  maxBounds: bounds,
                                  layers: [],
                                  worldCopyJump: false,
                                  crs: L.CRS.EPSG3857
                                 });
            
        
    
            var tile_layer_1bcd93647eb649cd8f4b3bfd4e2abeac = L.tileLayer(
                'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
                {
  "attribution": null,
  "detectRetina": false,
  "maxZoom": 18,
  "minZoom": 1,
  "noWrap": false,
  "subdomains": "abc"
}
                ).addTo(map_59cd65205f444909bb4d2ad75f82121b);
        
    
            var circle_marker_0c4d18ca3ba7478284f98c84f01465a8 = L.circleMarker(
                [43.806686299999996,-79.19435340000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_f733f82e536949aeb2c8cc25856326c8 = L.popup({maxWidth: '300'});

            
                var html_509296be3d5d4966ae2d5e867e167ef7 = $('<div id="html_509296be3d5d4966ae2d5e867e167ef7" style="width: 100.0%; height: 100.0%;">Malvern, Rouge, Scarborough</div>')[0];
                popup_f733f82e536949aeb2c8cc25856326c8.setContent(html_509296be3d5d4966ae2d5e867e167ef7);
            

            circle_marker_0c4d18ca3ba7478284f98c84f01465a8.bindPopup(popup_f733f82e536949aeb2c8cc25856326c8);

            
        
    
            var circle_marker_f048f3313a934d678c06ecc90ed91ebd = L.circleMarker(
                [43.7845351,-79.16049709999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_2c14b09f17f0418c8fdb5b2731aff775 = L.popup({maxWidth: '300'});

            
                var html_81a3a34350264f5693a5dc792313da3e = $('<div id="html_81a3a34350264f5693a5dc792313da3e" style="width: 100.0%; height: 100.0%;">Rouge Hill, Port Union, Highland Creek, Scarborough</div>')[0];
                popup_2c14b09f17f0418c8fdb5b2731aff775.setContent(html_81a3a34350264f5693a5dc792313da3e);
            

            circle_marker_f048f3313a934d678c06ecc90ed91ebd.bindPopup(popup_2c14b09f17f0418c8fdb5b2731aff775);

            
        
    
            var circle_marker_cef157ad33aa4a759379405bcd65d589 = L.circleMarker(
                [43.7635726,-79.1887115],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_39ba770d13e34d4f9a484d6c4f6fb15f = L.popup({maxWidth: '300'});

            
                var html_1bcd54ac0f2f4d3e99c2353ca5003746 = $('<div id="html_1bcd54ac0f2f4d3e99c2353ca5003746" style="width: 100.0%; height: 100.0%;">Guildwood, Morningside, West Hill, Scarborough</div>')[0];
                popup_39ba770d13e34d4f9a484d6c4f6fb15f.setContent(html_1bcd54ac0f2f4d3e99c2353ca5003746);
            

            circle_marker_cef157ad33aa4a759379405bcd65d589.bindPopup(popup_39ba770d13e34d4f9a484d6c4f6fb15f);

            
        
    
            var circle_marker_8e024d05db7e42af80badce1691abf8a = L.circleMarker(
                [43.7709921,-79.21691740000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_192c904a0d194117910c1fbac4cc213e = L.popup({maxWidth: '300'});

            
                var html_a9104fc8a2494be29b0ef3eff642e15b = $('<div id="html_a9104fc8a2494be29b0ef3eff642e15b" style="width: 100.0%; height: 100.0%;">Woburn, Scarborough</div>')[0];
                popup_192c904a0d194117910c1fbac4cc213e.setContent(html_a9104fc8a2494be29b0ef3eff642e15b);
            

            circle_marker_8e024d05db7e42af80badce1691abf8a.bindPopup(popup_192c904a0d194117910c1fbac4cc213e);

            
        
    
            var circle_marker_24db11f000f64c399f7ed464757f8fe2 = L.circleMarker(
                [43.773136,-79.23947609999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d9ff5c7fe50941dbb9dc81e164128531 = L.popup({maxWidth: '300'});

            
                var html_f0d28ea153bd454f80e42caa12870150 = $('<div id="html_f0d28ea153bd454f80e42caa12870150" style="width: 100.0%; height: 100.0%;">Cedarbrae, Scarborough</div>')[0];
                popup_d9ff5c7fe50941dbb9dc81e164128531.setContent(html_f0d28ea153bd454f80e42caa12870150);
            

            circle_marker_24db11f000f64c399f7ed464757f8fe2.bindPopup(popup_d9ff5c7fe50941dbb9dc81e164128531);

            
        
    
            var circle_marker_0ce7283a25974a2eaded933a001dc269 = L.circleMarker(
                [43.7447342,-79.23947609999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_5f4eb93aa90546f28a255a0ed4c50a5b = L.popup({maxWidth: '300'});

            
                var html_f9ca2025bfcf4153a2ce317adc731ea4 = $('<div id="html_f9ca2025bfcf4153a2ce317adc731ea4" style="width: 100.0%; height: 100.0%;">Scarborough Village, Scarborough</div>')[0];
                popup_5f4eb93aa90546f28a255a0ed4c50a5b.setContent(html_f9ca2025bfcf4153a2ce317adc731ea4);
            

            circle_marker_0ce7283a25974a2eaded933a001dc269.bindPopup(popup_5f4eb93aa90546f28a255a0ed4c50a5b);

            
        
    
            var circle_marker_425ad5b86d9a4c24beae8843e81b0412 = L.circleMarker(
                [43.7279292,-79.26202940000002],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_78077ffa778141488f1bea1f69bc38b0 = L.popup({maxWidth: '300'});

            
                var html_8427254b3fc741c49d2b9c85ff4c0e61 = $('<div id="html_8427254b3fc741c49d2b9c85ff4c0e61" style="width: 100.0%; height: 100.0%;">Kennedy Park, Ionview, East Birchmount Park, Scarborough</div>')[0];
                popup_78077ffa778141488f1bea1f69bc38b0.setContent(html_8427254b3fc741c49d2b9c85ff4c0e61);
            

            circle_marker_425ad5b86d9a4c24beae8843e81b0412.bindPopup(popup_78077ffa778141488f1bea1f69bc38b0);

            
        
    
            var circle_marker_306036f2d1e8495ebadc56ee489b6b32 = L.circleMarker(
                [43.711111700000004,-79.2845772],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_b586e684d6f44ecbba948544df4b0397 = L.popup({maxWidth: '300'});

            
                var html_1ec8bb53d0504f29abb6884c9f90f317 = $('<div id="html_1ec8bb53d0504f29abb6884c9f90f317" style="width: 100.0%; height: 100.0%;">Golden Mile, Clairlea, Oakridge, Scarborough</div>')[0];
                popup_b586e684d6f44ecbba948544df4b0397.setContent(html_1ec8bb53d0504f29abb6884c9f90f317);
            

            circle_marker_306036f2d1e8495ebadc56ee489b6b32.bindPopup(popup_b586e684d6f44ecbba948544df4b0397);

            
        
    
            var circle_marker_6b634a32dc2640a397563e1f485ba22b = L.circleMarker(
                [43.716316,-79.23947609999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_476aa86ce61945439819e4914e4975d4 = L.popup({maxWidth: '300'});

            
                var html_9d7a7978d23347158f39b0bbdab742b4 = $('<div id="html_9d7a7978d23347158f39b0bbdab742b4" style="width: 100.0%; height: 100.0%;">Cliffside, Cliffcrest, Scarborough Village West, Scarborough</div>')[0];
                popup_476aa86ce61945439819e4914e4975d4.setContent(html_9d7a7978d23347158f39b0bbdab742b4);
            

            circle_marker_6b634a32dc2640a397563e1f485ba22b.bindPopup(popup_476aa86ce61945439819e4914e4975d4);

            
        
    
            var circle_marker_aa44244e842048c89dcc64d13e98c86c = L.circleMarker(
                [43.692657000000004,-79.2648481],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_9b8c93b373764317810aec0a8cad790d = L.popup({maxWidth: '300'});

            
                var html_e7d63cc996ad472dbdbec2af320d1694 = $('<div id="html_e7d63cc996ad472dbdbec2af320d1694" style="width: 100.0%; height: 100.0%;">Birch Cliff, Cliffside West, Scarborough</div>')[0];
                popup_9b8c93b373764317810aec0a8cad790d.setContent(html_e7d63cc996ad472dbdbec2af320d1694);
            

            circle_marker_aa44244e842048c89dcc64d13e98c86c.bindPopup(popup_9b8c93b373764317810aec0a8cad790d);

            
        
    
            var circle_marker_c1e8f414251d4396b266ad963decca10 = L.circleMarker(
                [43.7574096,-79.27330400000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_a739b1e0a624418a81a0be0ebccc7efb = L.popup({maxWidth: '300'});

            
                var html_958fb0761cd14b62b35f3ec4a583acaa = $('<div id="html_958fb0761cd14b62b35f3ec4a583acaa" style="width: 100.0%; height: 100.0%;">Dorset Park, Wexford Heights, Scarborough Town Centre, Scarborough</div>')[0];
                popup_a739b1e0a624418a81a0be0ebccc7efb.setContent(html_958fb0761cd14b62b35f3ec4a583acaa);
            

            circle_marker_c1e8f414251d4396b266ad963decca10.bindPopup(popup_a739b1e0a624418a81a0be0ebccc7efb);

            
        
    
            var circle_marker_0f2ad91fa0674cc5a1e90ad5419d0d55 = L.circleMarker(
                [43.750071500000004,-79.2958491],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_47a3ee409bfb4744a24a2eb45815db43 = L.popup({maxWidth: '300'});

            
                var html_1b1016280ac94272b4ccd69360140d6e = $('<div id="html_1b1016280ac94272b4ccd69360140d6e" style="width: 100.0%; height: 100.0%;">Wexford, Maryvale, Scarborough</div>')[0];
                popup_47a3ee409bfb4744a24a2eb45815db43.setContent(html_1b1016280ac94272b4ccd69360140d6e);
            

            circle_marker_0f2ad91fa0674cc5a1e90ad5419d0d55.bindPopup(popup_47a3ee409bfb4744a24a2eb45815db43);

            
        
    
            var circle_marker_fb2bcf23f4f645b39aaa28f48aedefac = L.circleMarker(
                [43.7942003,-79.26202940000002],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_b6aed24b7d8b455fa4e668c30d3d301b = L.popup({maxWidth: '300'});

            
                var html_e307b63e9eba49f1be4f2e6225e14914 = $('<div id="html_e307b63e9eba49f1be4f2e6225e14914" style="width: 100.0%; height: 100.0%;">Agincourt, Scarborough</div>')[0];
                popup_b6aed24b7d8b455fa4e668c30d3d301b.setContent(html_e307b63e9eba49f1be4f2e6225e14914);
            

            circle_marker_fb2bcf23f4f645b39aaa28f48aedefac.bindPopup(popup_b6aed24b7d8b455fa4e668c30d3d301b);

            
        
    
            var circle_marker_0308c7f754b247fea6d25591b8c6af94 = L.circleMarker(
                [43.7816375,-79.3043021],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_b310c6902fff4e82a750e2fdfed16436 = L.popup({maxWidth: '300'});

            
                var html_f6028ce9dd7e4978a7c807ab6dcf69bb = $('<div id="html_f6028ce9dd7e4978a7c807ab6dcf69bb" style="width: 100.0%; height: 100.0%;">Clarks Corners, Tam O&#39;Shanter, Sullivan, Scarborough</div>')[0];
                popup_b310c6902fff4e82a750e2fdfed16436.setContent(html_f6028ce9dd7e4978a7c807ab6dcf69bb);
            

            circle_marker_0308c7f754b247fea6d25591b8c6af94.bindPopup(popup_b310c6902fff4e82a750e2fdfed16436);

            
        
    
            var circle_marker_9a2e6cb0bf5548cea1a59f1aaa6df3ce = L.circleMarker(
                [43.8152522,-79.2845772],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_e00f1ad125a44107a7f192e8596dd34f = L.popup({maxWidth: '300'});

            
                var html_93ac63ec42fc40a9b818c000af3e6149 = $('<div id="html_93ac63ec42fc40a9b818c000af3e6149" style="width: 100.0%; height: 100.0%;">Milliken, Agincourt North, Steeles East, L&#39;Amoreaux East, Scarborough</div>')[0];
                popup_e00f1ad125a44107a7f192e8596dd34f.setContent(html_93ac63ec42fc40a9b818c000af3e6149);
            

            circle_marker_9a2e6cb0bf5548cea1a59f1aaa6df3ce.bindPopup(popup_e00f1ad125a44107a7f192e8596dd34f);

            
        
    
            var circle_marker_680a1a8717654e989d7aff3a5d41de16 = L.circleMarker(
                [43.799525200000005,-79.3183887],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_05d88ddccaf84a83bea3609bc41451c7 = L.popup({maxWidth: '300'});

            
                var html_684e9272f686460a986e083dcbfaa8d7 = $('<div id="html_684e9272f686460a986e083dcbfaa8d7" style="width: 100.0%; height: 100.0%;">Steeles West, L&#39;Amoreaux West, Scarborough</div>')[0];
                popup_05d88ddccaf84a83bea3609bc41451c7.setContent(html_684e9272f686460a986e083dcbfaa8d7);
            

            circle_marker_680a1a8717654e989d7aff3a5d41de16.bindPopup(popup_05d88ddccaf84a83bea3609bc41451c7);

            
        
    
            var circle_marker_0a1efbdd63c44034b9f2776e36c6acf3 = L.circleMarker(
                [43.836124700000006,-79.20563609999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_3a2461269c7a4be2af43c6823f71f2ae = L.popup({maxWidth: '300'});

            
                var html_8c50a57f438842a0a5edb10f982a8652 = $('<div id="html_8c50a57f438842a0a5edb10f982a8652" style="width: 100.0%; height: 100.0%;">Upper Rouge, Scarborough</div>')[0];
                popup_3a2461269c7a4be2af43c6823f71f2ae.setContent(html_8c50a57f438842a0a5edb10f982a8652);
            

            circle_marker_0a1efbdd63c44034b9f2776e36c6acf3.bindPopup(popup_3a2461269c7a4be2af43c6823f71f2ae);

            
        
    
            var circle_marker_320a08d9cd65459dbe9ad686b54a4c2b = L.circleMarker(
                [43.8037622,-79.3634517],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_3248f05d9d3d4ab48c448d162112ba22 = L.popup({maxWidth: '300'});

            
                var html_ecf8fe5d21ee412fb68e6c1b1e3e7ac2 = $('<div id="html_ecf8fe5d21ee412fb68e6c1b1e3e7ac2" style="width: 100.0%; height: 100.0%;">Hillcrest Village, North York</div>')[0];
                popup_3248f05d9d3d4ab48c448d162112ba22.setContent(html_ecf8fe5d21ee412fb68e6c1b1e3e7ac2);
            

            circle_marker_320a08d9cd65459dbe9ad686b54a4c2b.bindPopup(popup_3248f05d9d3d4ab48c448d162112ba22);

            
        
    
            var circle_marker_0d492d31ba444361b6f8388f102d4b75 = L.circleMarker(
                [43.7785175,-79.3465557],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_c47280c5b3bd468b993b61dfea42a2c6 = L.popup({maxWidth: '300'});

            
                var html_37a3123213344ba0b54480afd8f356fc = $('<div id="html_37a3123213344ba0b54480afd8f356fc" style="width: 100.0%; height: 100.0%;">Fairview, Henry Farm, Oriole, North York</div>')[0];
                popup_c47280c5b3bd468b993b61dfea42a2c6.setContent(html_37a3123213344ba0b54480afd8f356fc);
            

            circle_marker_0d492d31ba444361b6f8388f102d4b75.bindPopup(popup_c47280c5b3bd468b993b61dfea42a2c6);

            
        
    
            var circle_marker_469e0fcfa5804db98d73a2c3cafe1ee0 = L.circleMarker(
                [43.7869473,-79.385975],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_dbfc675149fa48f8ad9131917591b3a5 = L.popup({maxWidth: '300'});

            
                var html_bf3a5649fc6c427e844cba128652d5c5 = $('<div id="html_bf3a5649fc6c427e844cba128652d5c5" style="width: 100.0%; height: 100.0%;">Bayview Village, North York</div>')[0];
                popup_dbfc675149fa48f8ad9131917591b3a5.setContent(html_bf3a5649fc6c427e844cba128652d5c5);
            

            circle_marker_469e0fcfa5804db98d73a2c3cafe1ee0.bindPopup(popup_dbfc675149fa48f8ad9131917591b3a5);

            
        
    
            var circle_marker_a346241481594d78b2816816dcd207c0 = L.circleMarker(
                [43.7574902,-79.37471409999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_ba39a990e05d4f8eac30570bfbdbf99e = L.popup({maxWidth: '300'});

            
                var html_f76d445b7e42469e8cedf318836d46f4 = $('<div id="html_f76d445b7e42469e8cedf318836d46f4" style="width: 100.0%; height: 100.0%;">York Mills, Silver Hills, North York</div>')[0];
                popup_ba39a990e05d4f8eac30570bfbdbf99e.setContent(html_f76d445b7e42469e8cedf318836d46f4);
            

            circle_marker_a346241481594d78b2816816dcd207c0.bindPopup(popup_ba39a990e05d4f8eac30570bfbdbf99e);

            
        
    
            var circle_marker_38af6a2379f34571b96a2a6853780463 = L.circleMarker(
                [43.789053,-79.40849279999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_9c98d27a79894741b8df6fb1b45c6dd7 = L.popup({maxWidth: '300'});

            
                var html_8562909b34e743b78ad13710ad2d08e6 = $('<div id="html_8562909b34e743b78ad13710ad2d08e6" style="width: 100.0%; height: 100.0%;">Willowdale, Newtonbrook, North York</div>')[0];
                popup_9c98d27a79894741b8df6fb1b45c6dd7.setContent(html_8562909b34e743b78ad13710ad2d08e6);
            

            circle_marker_38af6a2379f34571b96a2a6853780463.bindPopup(popup_9c98d27a79894741b8df6fb1b45c6dd7);

            
        
    
            var circle_marker_37934c2172b444c7bb159cd15da714c7 = L.circleMarker(
                [43.7701199,-79.40849279999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_bfcf6a5e794b4c19b60cddbec186594f = L.popup({maxWidth: '300'});

            
                var html_2a365af34cb146b8a61a38a57fe330f4 = $('<div id="html_2a365af34cb146b8a61a38a57fe330f4" style="width: 100.0%; height: 100.0%;">Willowdale, Willowdale East, North York</div>')[0];
                popup_bfcf6a5e794b4c19b60cddbec186594f.setContent(html_2a365af34cb146b8a61a38a57fe330f4);
            

            circle_marker_37934c2172b444c7bb159cd15da714c7.bindPopup(popup_bfcf6a5e794b4c19b60cddbec186594f);

            
        
    
            var circle_marker_7be156fa038f4c97b67e299400a618e2 = L.circleMarker(
                [43.752758299999996,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_cc7c542c609d4909b649f8a84a6dff10 = L.popup({maxWidth: '300'});

            
                var html_76d67d597e5d41ddb2134f4a090e0c76 = $('<div id="html_76d67d597e5d41ddb2134f4a090e0c76" style="width: 100.0%; height: 100.0%;">York Mills West, North York</div>')[0];
                popup_cc7c542c609d4909b649f8a84a6dff10.setContent(html_76d67d597e5d41ddb2134f4a090e0c76);
            

            circle_marker_7be156fa038f4c97b67e299400a618e2.bindPopup(popup_cc7c542c609d4909b649f8a84a6dff10);

            
        
    
            var circle_marker_933311df057346d98e026ef4e726333e = L.circleMarker(
                [43.7827364,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d9216ae5ce714771bfffd1c7bfbb69cb = L.popup({maxWidth: '300'});

            
                var html_4b2ef39cf8cd48b9a5ed672eed429765 = $('<div id="html_4b2ef39cf8cd48b9a5ed672eed429765" style="width: 100.0%; height: 100.0%;">Willowdale, Willowdale West, North York</div>')[0];
                popup_d9216ae5ce714771bfffd1c7bfbb69cb.setContent(html_4b2ef39cf8cd48b9a5ed672eed429765);
            

            circle_marker_933311df057346d98e026ef4e726333e.bindPopup(popup_d9216ae5ce714771bfffd1c7bfbb69cb);

            
        
    
            var circle_marker_485027a5db1d4251a0884476e501c83e = L.circleMarker(
                [43.7532586,-79.3296565],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_0d0be528f35241cb90f138e5d65cd230 = L.popup({maxWidth: '300'});

            
                var html_ebb3ab4c9024443b9639548709795153 = $('<div id="html_ebb3ab4c9024443b9639548709795153" style="width: 100.0%; height: 100.0%;">Parkwoods, North York</div>')[0];
                popup_0d0be528f35241cb90f138e5d65cd230.setContent(html_ebb3ab4c9024443b9639548709795153);
            

            circle_marker_485027a5db1d4251a0884476e501c83e.bindPopup(popup_0d0be528f35241cb90f138e5d65cd230);

            
        
    
            var circle_marker_e81b2d2750fe4781a2f92cf502c55c12 = L.circleMarker(
                [43.745905799999996,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_b125e1a034234ca3b774eb56890db74a = L.popup({maxWidth: '300'});

            
                var html_b0b97689c9744e8da3b63908d58277e7 = $('<div id="html_b0b97689c9744e8da3b63908d58277e7" style="width: 100.0%; height: 100.0%;">Don Mills, North York</div>')[0];
                popup_b125e1a034234ca3b774eb56890db74a.setContent(html_b0b97689c9744e8da3b63908d58277e7);
            

            circle_marker_e81b2d2750fe4781a2f92cf502c55c12.bindPopup(popup_b125e1a034234ca3b774eb56890db74a);

            
        
    
            var circle_marker_db39250591264212b518edfb9184bf64 = L.circleMarker(
                [43.72589970000001,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_1b49b813c08d4153834f78425ef26a10 = L.popup({maxWidth: '300'});

            
                var html_b930f548453a447d8d15294fce0aff5b = $('<div id="html_b930f548453a447d8d15294fce0aff5b" style="width: 100.0%; height: 100.0%;">Don Mills, North York</div>')[0];
                popup_1b49b813c08d4153834f78425ef26a10.setContent(html_b930f548453a447d8d15294fce0aff5b);
            

            circle_marker_db39250591264212b518edfb9184bf64.bindPopup(popup_1b49b813c08d4153834f78425ef26a10);

            
        
    
            var circle_marker_b21bb4aea6794fa5b5e3d78f721b49c9 = L.circleMarker(
                [43.7543283,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_07da5d9012d54a418085bc86f2a863eb = L.popup({maxWidth: '300'});

            
                var html_a77d6910bf58436faa185d67d27e3bb8 = $('<div id="html_a77d6910bf58436faa185d67d27e3bb8" style="width: 100.0%; height: 100.0%;">Bathurst Manor, Wilson Heights, Downsview North, North York</div>')[0];
                popup_07da5d9012d54a418085bc86f2a863eb.setContent(html_a77d6910bf58436faa185d67d27e3bb8);
            

            circle_marker_b21bb4aea6794fa5b5e3d78f721b49c9.bindPopup(popup_07da5d9012d54a418085bc86f2a863eb);

            
        
    
            var circle_marker_ba41ba2798a1413c954d2dc8e540c5fe = L.circleMarker(
                [43.7679803,-79.48726190000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_ec85764bb9034a1ebf2dbdcac501e976 = L.popup({maxWidth: '300'});

            
                var html_b0c5831b95bd4bebb8b4d5dd3e36e990 = $('<div id="html_b0c5831b95bd4bebb8b4d5dd3e36e990" style="width: 100.0%; height: 100.0%;">Northwood Park, York University, North York</div>')[0];
                popup_ec85764bb9034a1ebf2dbdcac501e976.setContent(html_b0c5831b95bd4bebb8b4d5dd3e36e990);
            

            circle_marker_ba41ba2798a1413c954d2dc8e540c5fe.bindPopup(popup_ec85764bb9034a1ebf2dbdcac501e976);

            
        
    
            var circle_marker_64b2ae5802ed47168bd9a38439cf4ca7 = L.circleMarker(
                [43.737473200000004,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_0652bf7084ae4981bcecebc61208d18c = L.popup({maxWidth: '300'});

            
                var html_8d574ccec9564eb4aa2d59f951ec542f = $('<div id="html_8d574ccec9564eb4aa2d59f951ec542f" style="width: 100.0%; height: 100.0%;">Downsview, North York</div>')[0];
                popup_0652bf7084ae4981bcecebc61208d18c.setContent(html_8d574ccec9564eb4aa2d59f951ec542f);
            

            circle_marker_64b2ae5802ed47168bd9a38439cf4ca7.bindPopup(popup_0652bf7084ae4981bcecebc61208d18c);

            
        
    
            var circle_marker_a0b69e62445e42f8980f3b39854ccef6 = L.circleMarker(
                [43.7390146,-79.5069436],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_40c1261d8fc44880951443caad7cbf67 = L.popup({maxWidth: '300'});

            
                var html_14ab4a6359024f638d78d84c70b5f45d = $('<div id="html_14ab4a6359024f638d78d84c70b5f45d" style="width: 100.0%; height: 100.0%;">Downsview, North York</div>')[0];
                popup_40c1261d8fc44880951443caad7cbf67.setContent(html_14ab4a6359024f638d78d84c70b5f45d);
            

            circle_marker_a0b69e62445e42f8980f3b39854ccef6.bindPopup(popup_40c1261d8fc44880951443caad7cbf67);

            
        
    
            var circle_marker_6d17938cfebe48eba619a70942697497 = L.circleMarker(
                [43.7284964,-79.49569740000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_8e7b5ee6804b4ff18b2d9e62534b3663 = L.popup({maxWidth: '300'});

            
                var html_6c0815a2323d4045a320e2e4c7f99d43 = $('<div id="html_6c0815a2323d4045a320e2e4c7f99d43" style="width: 100.0%; height: 100.0%;">Downsview, North York</div>')[0];
                popup_8e7b5ee6804b4ff18b2d9e62534b3663.setContent(html_6c0815a2323d4045a320e2e4c7f99d43);
            

            circle_marker_6d17938cfebe48eba619a70942697497.bindPopup(popup_8e7b5ee6804b4ff18b2d9e62534b3663);

            
        
    
            var circle_marker_2dfd5b4d19014bce8913b4270a4a3ff4 = L.circleMarker(
                [43.7616313,-79.52099940000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_f2f183197644400792f63cf42a04d184 = L.popup({maxWidth: '300'});

            
                var html_e059dc1e7d2c40719e49f4f919372600 = $('<div id="html_e059dc1e7d2c40719e49f4f919372600" style="width: 100.0%; height: 100.0%;">Downsview, North York</div>')[0];
                popup_f2f183197644400792f63cf42a04d184.setContent(html_e059dc1e7d2c40719e49f4f919372600);
            

            circle_marker_2dfd5b4d19014bce8913b4270a4a3ff4.bindPopup(popup_f2f183197644400792f63cf42a04d184);

            
        
    
            var circle_marker_f4807dc0fe3a44179fbd384b7158d101 = L.circleMarker(
                [43.725882299999995,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_18115d231d234ff99536e849c03a6a41 = L.popup({maxWidth: '300'});

            
                var html_b5c52890ffbc47d0bd6833aa7d960290 = $('<div id="html_b5c52890ffbc47d0bd6833aa7d960290" style="width: 100.0%; height: 100.0%;">Victoria Village, North York</div>')[0];
                popup_18115d231d234ff99536e849c03a6a41.setContent(html_b5c52890ffbc47d0bd6833aa7d960290);
            

            circle_marker_f4807dc0fe3a44179fbd384b7158d101.bindPopup(popup_18115d231d234ff99536e849c03a6a41);

            
        
    
            var circle_marker_31c8fc20431c4a74822184fc62b92fcd = L.circleMarker(
                [43.7063972,-79.309937],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_c5c427ba30bf4b96933390aaf754a9cb = L.popup({maxWidth: '300'});

            
                var html_9d41a506765c4e32946e489a3e8f2f5e = $('<div id="html_9d41a506765c4e32946e489a3e8f2f5e" style="width: 100.0%; height: 100.0%;">Parkview Hill, Woodbine Gardens, East York</div>')[0];
                popup_c5c427ba30bf4b96933390aaf754a9cb.setContent(html_9d41a506765c4e32946e489a3e8f2f5e);
            

            circle_marker_31c8fc20431c4a74822184fc62b92fcd.bindPopup(popup_c5c427ba30bf4b96933390aaf754a9cb);

            
        
    
            var circle_marker_240658c1bd1e454bbcef61c15d215147 = L.circleMarker(
                [43.695343900000005,-79.3183887],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_e34758765ebc4b9ea65a687c85978af3 = L.popup({maxWidth: '300'});

            
                var html_0d0666d6058042bdba850fd42ff231b6 = $('<div id="html_0d0666d6058042bdba850fd42ff231b6" style="width: 100.0%; height: 100.0%;">Woodbine Heights, East York</div>')[0];
                popup_e34758765ebc4b9ea65a687c85978af3.setContent(html_0d0666d6058042bdba850fd42ff231b6);
            

            circle_marker_240658c1bd1e454bbcef61c15d215147.bindPopup(popup_e34758765ebc4b9ea65a687c85978af3);

            
        
    
            var circle_marker_ee78f7d6a9684e608dae704820238dd7 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_1896e6c18bea4683a33d32c0cdff4985 = L.popup({maxWidth: '300'});

            
                var html_ff2e49ed6bfe4a639beae53d7bc2f0f3 = $('<div id="html_ff2e49ed6bfe4a639beae53d7bc2f0f3" style="width: 100.0%; height: 100.0%;">The Beaches, East Toronto</div>')[0];
                popup_1896e6c18bea4683a33d32c0cdff4985.setContent(html_ff2e49ed6bfe4a639beae53d7bc2f0f3);
            

            circle_marker_ee78f7d6a9684e608dae704820238dd7.bindPopup(popup_1896e6c18bea4683a33d32c0cdff4985);

            
        
    
            var circle_marker_a41edd1048094214acbe1ffa6e3f6362 = L.circleMarker(
                [43.7090604,-79.3634517],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d845cec924524aa7acc7b1f1ba309a54 = L.popup({maxWidth: '300'});

            
                var html_f2bde383fbf04e289b7f71aa8694533c = $('<div id="html_f2bde383fbf04e289b7f71aa8694533c" style="width: 100.0%; height: 100.0%;">Leaside, East York</div>')[0];
                popup_d845cec924524aa7acc7b1f1ba309a54.setContent(html_f2bde383fbf04e289b7f71aa8694533c);
            

            circle_marker_a41edd1048094214acbe1ffa6e3f6362.bindPopup(popup_d845cec924524aa7acc7b1f1ba309a54);

            
        
    
            var circle_marker_d91d5ae2595e461593e6824d0fd8ba3a = L.circleMarker(
                [43.7053689,-79.34937190000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_557a36f3cb3d4b75beeaecf62a4798d0 = L.popup({maxWidth: '300'});

            
                var html_34e99fbc9c80418ab921718f436f40e3 = $('<div id="html_34e99fbc9c80418ab921718f436f40e3" style="width: 100.0%; height: 100.0%;">Thorncliffe Park, East York</div>')[0];
                popup_557a36f3cb3d4b75beeaecf62a4798d0.setContent(html_34e99fbc9c80418ab921718f436f40e3);
            

            circle_marker_d91d5ae2595e461593e6824d0fd8ba3a.bindPopup(popup_557a36f3cb3d4b75beeaecf62a4798d0);

            
        
    
            var circle_marker_d7e8d41e4fe749e1ac9c74808940fa36 = L.circleMarker(
                [43.685347,-79.3381065],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_95d94a389c5a439ca09bfb69a5c3fadd = L.popup({maxWidth: '300'});

            
                var html_1e6aa6c378c84ebc9f17ba9bd122d3f6 = $('<div id="html_1e6aa6c378c84ebc9f17ba9bd122d3f6" style="width: 100.0%; height: 100.0%;">East Toronto, Broadview North (Old East York), East York</div>')[0];
                popup_95d94a389c5a439ca09bfb69a5c3fadd.setContent(html_1e6aa6c378c84ebc9f17ba9bd122d3f6);
            

            circle_marker_d7e8d41e4fe749e1ac9c74808940fa36.bindPopup(popup_95d94a389c5a439ca09bfb69a5c3fadd);

            
        
    
            var circle_marker_c1f0069dd5764f7181ae82a6c8481909 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d372de055ebb4f2b937fd7399e634b59 = L.popup({maxWidth: '300'});

            
                var html_b5101b08f7c84daeb0f448a82125163c = $('<div id="html_b5101b08f7c84daeb0f448a82125163c" style="width: 100.0%; height: 100.0%;">The Danforth West, Riverdale, East Toronto</div>')[0];
                popup_d372de055ebb4f2b937fd7399e634b59.setContent(html_b5101b08f7c84daeb0f448a82125163c);
            

            circle_marker_c1f0069dd5764f7181ae82a6c8481909.bindPopup(popup_d372de055ebb4f2b937fd7399e634b59);

            
        
    
            var circle_marker_1ed42c0ee6dc4d11852f770f5ac07474 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_ad091456d6ec46d685901649ca7cad4a = L.popup({maxWidth: '300'});

            
                var html_cd110e31622548d79a3d4e80db6de7f2 = $('<div id="html_cd110e31622548d79a3d4e80db6de7f2" style="width: 100.0%; height: 100.0%;">India Bazaar, The Beaches West, East Toronto</div>')[0];
                popup_ad091456d6ec46d685901649ca7cad4a.setContent(html_cd110e31622548d79a3d4e80db6de7f2);
            

            circle_marker_1ed42c0ee6dc4d11852f770f5ac07474.bindPopup(popup_ad091456d6ec46d685901649ca7cad4a);

            
        
    
            var circle_marker_af1fce59dfb340c69a3d63cae8f2472b = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_ec6f17ff383449909d50df69889ca1a3 = L.popup({maxWidth: '300'});

            
                var html_8a34278439b648f2bddd93b24e97e918 = $('<div id="html_8a34278439b648f2bddd93b24e97e918" style="width: 100.0%; height: 100.0%;">Studio District, East Toronto</div>')[0];
                popup_ec6f17ff383449909d50df69889ca1a3.setContent(html_8a34278439b648f2bddd93b24e97e918);
            

            circle_marker_af1fce59dfb340c69a3d63cae8f2472b.bindPopup(popup_ec6f17ff383449909d50df69889ca1a3);

            
        
    
            var circle_marker_beedd84467b34e8bbd824248ecb01748 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_218b9c11954c4e92bd0163e2d22b7da3 = L.popup({maxWidth: '300'});

            
                var html_2f53fe41c4ec4452866efad025b87d6c = $('<div id="html_2f53fe41c4ec4452866efad025b87d6c" style="width: 100.0%; height: 100.0%;">Lawrence Park, Central Toronto</div>')[0];
                popup_218b9c11954c4e92bd0163e2d22b7da3.setContent(html_2f53fe41c4ec4452866efad025b87d6c);
            

            circle_marker_beedd84467b34e8bbd824248ecb01748.bindPopup(popup_218b9c11954c4e92bd0163e2d22b7da3);

            
        
    
            var circle_marker_dd3ba1b23f454aa0884ea6961f4b1bac = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d77e4418d877454d90e2b4b3c2c31305 = L.popup({maxWidth: '300'});

            
                var html_e9b9cbb8822b4bc295457ce4fdbc42e6 = $('<div id="html_e9b9cbb8822b4bc295457ce4fdbc42e6" style="width: 100.0%; height: 100.0%;">Davisville North, Central Toronto</div>')[0];
                popup_d77e4418d877454d90e2b4b3c2c31305.setContent(html_e9b9cbb8822b4bc295457ce4fdbc42e6);
            

            circle_marker_dd3ba1b23f454aa0884ea6961f4b1bac.bindPopup(popup_d77e4418d877454d90e2b4b3c2c31305);

            
        
    
            var circle_marker_03d0521c533548c98ecfbc24c252266e = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_fd355b0baea8405592644d1e3c8e2e3a = L.popup({maxWidth: '300'});

            
                var html_8bdafae9b38a409fb655bc04f860a4c4 = $('<div id="html_8bdafae9b38a409fb655bc04f860a4c4" style="width: 100.0%; height: 100.0%;">North Toronto West, Lawrence Park, Central Toronto</div>')[0];
                popup_fd355b0baea8405592644d1e3c8e2e3a.setContent(html_8bdafae9b38a409fb655bc04f860a4c4);
            

            circle_marker_03d0521c533548c98ecfbc24c252266e.bindPopup(popup_fd355b0baea8405592644d1e3c8e2e3a);

            
        
    
            var circle_marker_fb530e40506e4b79b68d8cd7ffde675e = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_c7e55c03a4234450a76f9d591721f6e8 = L.popup({maxWidth: '300'});

            
                var html_4edad48a19134788987fcfecf670876e = $('<div id="html_4edad48a19134788987fcfecf670876e" style="width: 100.0%; height: 100.0%;">Davisville, Central Toronto</div>')[0];
                popup_c7e55c03a4234450a76f9d591721f6e8.setContent(html_4edad48a19134788987fcfecf670876e);
            

            circle_marker_fb530e40506e4b79b68d8cd7ffde675e.bindPopup(popup_c7e55c03a4234450a76f9d591721f6e8);

            
        
    
            var circle_marker_e14a26c8d8ef472594b4aa5430809048 = L.circleMarker(
                [43.6895743,-79.38315990000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_9b99bc298a7745f894c4447d0e88c45b = L.popup({maxWidth: '300'});

            
                var html_0cf58783dcc047ce91ce832a4073ae0f = $('<div id="html_0cf58783dcc047ce91ce832a4073ae0f" style="width: 100.0%; height: 100.0%;">Moore Park, Summerhill East, Central Toronto</div>')[0];
                popup_9b99bc298a7745f894c4447d0e88c45b.setContent(html_0cf58783dcc047ce91ce832a4073ae0f);
            

            circle_marker_e14a26c8d8ef472594b4aa5430809048.bindPopup(popup_9b99bc298a7745f894c4447d0e88c45b);

            
        
    
            var circle_marker_a91348613df94f0b918016266ab74a08 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_6b0d10e1931843d4b87400b971078417 = L.popup({maxWidth: '300'});

            
                var html_c208be6e3e9540ca92d6d268a7662fa5 = $('<div id="html_c208be6e3e9540ca92d6d268a7662fa5" style="width: 100.0%; height: 100.0%;">Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park, Central Toronto</div>')[0];
                popup_6b0d10e1931843d4b87400b971078417.setContent(html_c208be6e3e9540ca92d6d268a7662fa5);
            

            circle_marker_a91348613df94f0b918016266ab74a08.bindPopup(popup_6b0d10e1931843d4b87400b971078417);

            
        
    
            var circle_marker_aead6e3583bf482989dd2b80a9c7168d = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_8181faeb77b9480d8e7fac91a5ef223e = L.popup({maxWidth: '300'});

            
                var html_e219c4fc98654cdbaff7b36d2bc3e5bd = $('<div id="html_e219c4fc98654cdbaff7b36d2bc3e5bd" style="width: 100.0%; height: 100.0%;">Rosedale, Downtown Toronto</div>')[0];
                popup_8181faeb77b9480d8e7fac91a5ef223e.setContent(html_e219c4fc98654cdbaff7b36d2bc3e5bd);
            

            circle_marker_aead6e3583bf482989dd2b80a9c7168d.bindPopup(popup_8181faeb77b9480d8e7fac91a5ef223e);

            
        
    
            var circle_marker_095cbc91b47c44429b9e900a2b1b5f4f = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_40c8dfc3329e44379eae62f6aeaa58e9 = L.popup({maxWidth: '300'});

            
                var html_cc5ae420bb9241ec893251c6e6869f66 = $('<div id="html_cc5ae420bb9241ec893251c6e6869f66" style="width: 100.0%; height: 100.0%;">St. James Town, Cabbagetown, Downtown Toronto</div>')[0];
                popup_40c8dfc3329e44379eae62f6aeaa58e9.setContent(html_cc5ae420bb9241ec893251c6e6869f66);
            

            circle_marker_095cbc91b47c44429b9e900a2b1b5f4f.bindPopup(popup_40c8dfc3329e44379eae62f6aeaa58e9);

            
        
    
            var circle_marker_60be162e1891418faa53ef87ab465582 = L.circleMarker(
                [43.6658599,-79.38315990000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_02b25382df4045589c2b6c1400de2494 = L.popup({maxWidth: '300'});

            
                var html_516f3b01a4a643ecb013c575b7d4763a = $('<div id="html_516f3b01a4a643ecb013c575b7d4763a" style="width: 100.0%; height: 100.0%;">Church and Wellesley, Downtown Toronto</div>')[0];
                popup_02b25382df4045589c2b6c1400de2494.setContent(html_516f3b01a4a643ecb013c575b7d4763a);
            

            circle_marker_60be162e1891418faa53ef87ab465582.bindPopup(popup_02b25382df4045589c2b6c1400de2494);

            
        
    
            var circle_marker_dce11f592bbf4305a08623f9d47f5d2a = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_89c42d066d32442cbfaa80be2307f27f = L.popup({maxWidth: '300'});

            
                var html_bfaf808f1f40441d976d8e392e53fc4b = $('<div id="html_bfaf808f1f40441d976d8e392e53fc4b" style="width: 100.0%; height: 100.0%;">Regent Park, Harbourfront, Downtown Toronto</div>')[0];
                popup_89c42d066d32442cbfaa80be2307f27f.setContent(html_bfaf808f1f40441d976d8e392e53fc4b);
            

            circle_marker_dce11f592bbf4305a08623f9d47f5d2a.bindPopup(popup_89c42d066d32442cbfaa80be2307f27f);

            
        
    
            var circle_marker_6739b5a101134e469418e1cbd48fc8c1 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d8ffa6338fae48d2970c3ea7dc7d88ff = L.popup({maxWidth: '300'});

            
                var html_2ab7de391e614a589cf04cb222387bde = $('<div id="html_2ab7de391e614a589cf04cb222387bde" style="width: 100.0%; height: 100.0%;">Garden District, Ryerson, Downtown Toronto</div>')[0];
                popup_d8ffa6338fae48d2970c3ea7dc7d88ff.setContent(html_2ab7de391e614a589cf04cb222387bde);
            

            circle_marker_6739b5a101134e469418e1cbd48fc8c1.bindPopup(popup_d8ffa6338fae48d2970c3ea7dc7d88ff);

            
        
    
            var circle_marker_304a6c0c82854a36ae1905211937d003 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_337dcec5354c4281882a991837b52f32 = L.popup({maxWidth: '300'});

            
                var html_2197dbc33ffb4e3eae2cc43a826a45d0 = $('<div id="html_2197dbc33ffb4e3eae2cc43a826a45d0" style="width: 100.0%; height: 100.0%;">St. James Town, Downtown Toronto</div>')[0];
                popup_337dcec5354c4281882a991837b52f32.setContent(html_2197dbc33ffb4e3eae2cc43a826a45d0);
            

            circle_marker_304a6c0c82854a36ae1905211937d003.bindPopup(popup_337dcec5354c4281882a991837b52f32);

            
        
    
            var circle_marker_bafe8c31a6b24474a2751672724d06e2 = L.circleMarker(
                [43.644770799999996,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_9b6218690db84a8a9467330e782dc759 = L.popup({maxWidth: '300'});

            
                var html_7a2e5897982041a192a76e20d01d3f29 = $('<div id="html_7a2e5897982041a192a76e20d01d3f29" style="width: 100.0%; height: 100.0%;">Berczy Park, Downtown Toronto</div>')[0];
                popup_9b6218690db84a8a9467330e782dc759.setContent(html_7a2e5897982041a192a76e20d01d3f29);
            

            circle_marker_bafe8c31a6b24474a2751672724d06e2.bindPopup(popup_9b6218690db84a8a9467330e782dc759);

            
        
    
            var circle_marker_fcb8f44b8d6f4a70834975c7da5fa66e = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_cd12ef9a253e4d27a1da38f0c808dd40 = L.popup({maxWidth: '300'});

            
                var html_0138dfcf9c404964a48e8e55dbe0eead = $('<div id="html_0138dfcf9c404964a48e8e55dbe0eead" style="width: 100.0%; height: 100.0%;">Central Bay Street, Downtown Toronto</div>')[0];
                popup_cd12ef9a253e4d27a1da38f0c808dd40.setContent(html_0138dfcf9c404964a48e8e55dbe0eead);
            

            circle_marker_fcb8f44b8d6f4a70834975c7da5fa66e.bindPopup(popup_cd12ef9a253e4d27a1da38f0c808dd40);

            
        
    
            var circle_marker_e56257bff4fa4579b453fe21dbae91b0 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_70a9d2ff76294507913811bebf868093 = L.popup({maxWidth: '300'});

            
                var html_de701a740fe6431e9fd2887da2ef832c = $('<div id="html_de701a740fe6431e9fd2887da2ef832c" style="width: 100.0%; height: 100.0%;">Richmond, Adelaide, King, Downtown Toronto</div>')[0];
                popup_70a9d2ff76294507913811bebf868093.setContent(html_de701a740fe6431e9fd2887da2ef832c);
            

            circle_marker_e56257bff4fa4579b453fe21dbae91b0.bindPopup(popup_70a9d2ff76294507913811bebf868093);

            
        
    
            var circle_marker_3aae8ec5e1024acdad8952d2e2dea93e = L.circleMarker(
                [43.6408157,-79.38175229999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_96c27b4a853c46c3ace64e71583521c0 = L.popup({maxWidth: '300'});

            
                var html_59e71ab9502b4e2fb0419c99728b0de5 = $('<div id="html_59e71ab9502b4e2fb0419c99728b0de5" style="width: 100.0%; height: 100.0%;">Harbourfront East, Union Station, Toronto Islands, Downtown Toronto</div>')[0];
                popup_96c27b4a853c46c3ace64e71583521c0.setContent(html_59e71ab9502b4e2fb0419c99728b0de5);
            

            circle_marker_3aae8ec5e1024acdad8952d2e2dea93e.bindPopup(popup_96c27b4a853c46c3ace64e71583521c0);

            
        
    
            var circle_marker_6edfa7237ee54b16a305d7dec4cd4813 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_2476db3de1e04ef7afdef5dbb5d7340a = L.popup({maxWidth: '300'});

            
                var html_2bbc477d75654b51b71f09eb210abaac = $('<div id="html_2bbc477d75654b51b71f09eb210abaac" style="width: 100.0%; height: 100.0%;">Toronto Dominion Centre, Design Exchange, Downtown Toronto</div>')[0];
                popup_2476db3de1e04ef7afdef5dbb5d7340a.setContent(html_2bbc477d75654b51b71f09eb210abaac);
            

            circle_marker_6edfa7237ee54b16a305d7dec4cd4813.bindPopup(popup_2476db3de1e04ef7afdef5dbb5d7340a);

            
        
    
            var circle_marker_5a2d56c3f85b4fdc864dc7906d5cb585 = L.circleMarker(
                [43.6481985,-79.37981690000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_688983d7192f4e99a5d6f982ca8a0b15 = L.popup({maxWidth: '300'});

            
                var html_f30e5da5a986485ca1341d10115e844d = $('<div id="html_f30e5da5a986485ca1341d10115e844d" style="width: 100.0%; height: 100.0%;">Commerce Court, Victoria Hotel, Downtown Toronto</div>')[0];
                popup_688983d7192f4e99a5d6f982ca8a0b15.setContent(html_f30e5da5a986485ca1341d10115e844d);
            

            circle_marker_5a2d56c3f85b4fdc864dc7906d5cb585.bindPopup(popup_688983d7192f4e99a5d6f982ca8a0b15);

            
        
    
            var circle_marker_c629938858054e29ac0ede509001fa74 = L.circleMarker(
                [43.7332825,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_5c62ba7101f94466b866636c6969e61c = L.popup({maxWidth: '300'});

            
                var html_90a101787ad444b3950fdf4fba152f32 = $('<div id="html_90a101787ad444b3950fdf4fba152f32" style="width: 100.0%; height: 100.0%;">Bedford Park, Lawrence Manor East, North York</div>')[0];
                popup_5c62ba7101f94466b866636c6969e61c.setContent(html_90a101787ad444b3950fdf4fba152f32);
            

            circle_marker_c629938858054e29ac0ede509001fa74.bindPopup(popup_5c62ba7101f94466b866636c6969e61c);

            
        
    
            var circle_marker_4766d768f7844edd969737e4662c56c3 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_abc544073bb6455196d7d51803e9522f = L.popup({maxWidth: '300'});

            
                var html_3a8f0f4c3d4c41e0b84295c8ff251906 = $('<div id="html_3a8f0f4c3d4c41e0b84295c8ff251906" style="width: 100.0%; height: 100.0%;">Roselawn, Central Toronto</div>')[0];
                popup_abc544073bb6455196d7d51803e9522f.setContent(html_3a8f0f4c3d4c41e0b84295c8ff251906);
            

            circle_marker_4766d768f7844edd969737e4662c56c3.bindPopup(popup_abc544073bb6455196d7d51803e9522f);

            
        
    
            var circle_marker_8e8cf352a12948dca78b5547c47926eb = L.circleMarker(
                [43.6969476,-79.41130720000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_0c8cb63e2d894f44889806a0d51f1bef = L.popup({maxWidth: '300'});

            
                var html_b9484c78421b42c3a073b914cf365f6d = $('<div id="html_b9484c78421b42c3a073b914cf365f6d" style="width: 100.0%; height: 100.0%;">Forest Hill North &amp; West, Forest Hill Road Park, Central Toronto</div>')[0];
                popup_0c8cb63e2d894f44889806a0d51f1bef.setContent(html_b9484c78421b42c3a073b914cf365f6d);
            

            circle_marker_8e8cf352a12948dca78b5547c47926eb.bindPopup(popup_0c8cb63e2d894f44889806a0d51f1bef);

            
        
    
            var circle_marker_1463890a2ba54b1cab79031c78ba7436 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_5461de5d43aa4caeb88efd2efd97dc4f = L.popup({maxWidth: '300'});

            
                var html_61ffaef1cd95400ba3faedf9f2e38ed3 = $('<div id="html_61ffaef1cd95400ba3faedf9f2e38ed3" style="width: 100.0%; height: 100.0%;">The Annex, North Midtown, Yorkville, Central Toronto</div>')[0];
                popup_5461de5d43aa4caeb88efd2efd97dc4f.setContent(html_61ffaef1cd95400ba3faedf9f2e38ed3);
            

            circle_marker_1463890a2ba54b1cab79031c78ba7436.bindPopup(popup_5461de5d43aa4caeb88efd2efd97dc4f);

            
        
    
            var circle_marker_6134cfd67a2c4f6893d4d0cfb063b82d = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_2c90bb2cad82444b8caac343cb575d77 = L.popup({maxWidth: '300'});

            
                var html_3f3476aee16c41b1b9bb3ff0ab6857fe = $('<div id="html_3f3476aee16c41b1b9bb3ff0ab6857fe" style="width: 100.0%; height: 100.0%;">University of Toronto, Harbord, Downtown Toronto</div>')[0];
                popup_2c90bb2cad82444b8caac343cb575d77.setContent(html_3f3476aee16c41b1b9bb3ff0ab6857fe);
            

            circle_marker_6134cfd67a2c4f6893d4d0cfb063b82d.bindPopup(popup_2c90bb2cad82444b8caac343cb575d77);

            
        
    
            var circle_marker_73eff4a4d0274e1bbdcf8cf08ecc5c5c = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_5e9bf83ecf34461da0afabc62cf2ff92 = L.popup({maxWidth: '300'});

            
                var html_c892d166b7f14416a901c3a7ea2b1e53 = $('<div id="html_c892d166b7f14416a901c3a7ea2b1e53" style="width: 100.0%; height: 100.0%;">Kensington Market, Chinatown, Grange Park, Downtown Toronto</div>')[0];
                popup_5e9bf83ecf34461da0afabc62cf2ff92.setContent(html_c892d166b7f14416a901c3a7ea2b1e53);
            

            circle_marker_73eff4a4d0274e1bbdcf8cf08ecc5c5c.bindPopup(popup_5e9bf83ecf34461da0afabc62cf2ff92);

            
        
    
            var circle_marker_f152c11a00fc4a17a029baed98601583 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_8d81233716494b3bbf4a81088b66032d = L.popup({maxWidth: '300'});

            
                var html_950a1ebbebac450b961a414f5ac2ea0b = $('<div id="html_950a1ebbebac450b961a414f5ac2ea0b" style="width: 100.0%; height: 100.0%;">CN Tower, King and Spadina, Railway Lands, Harbourfront West, Bathurst Quay, South Niagara, Island airport, Downtown Toronto</div>')[0];
                popup_8d81233716494b3bbf4a81088b66032d.setContent(html_950a1ebbebac450b961a414f5ac2ea0b);
            

            circle_marker_f152c11a00fc4a17a029baed98601583.bindPopup(popup_8d81233716494b3bbf4a81088b66032d);

            
        
    
            var circle_marker_ea2170d11f68467f9f9c6846b67950b3 = L.circleMarker(
                [43.6464352,-79.37484599999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_40dce74c8fb74d74b5b500a34cbc83cc = L.popup({maxWidth: '300'});

            
                var html_cae3412aebd746eea4b8cf4ff628ca0c = $('<div id="html_cae3412aebd746eea4b8cf4ff628ca0c" style="width: 100.0%; height: 100.0%;">Stn A PO Boxes, Downtown Toronto</div>')[0];
                popup_40dce74c8fb74d74b5b500a34cbc83cc.setContent(html_cae3412aebd746eea4b8cf4ff628ca0c);
            

            circle_marker_ea2170d11f68467f9f9c6846b67950b3.bindPopup(popup_40dce74c8fb74d74b5b500a34cbc83cc);

            
        
    
            var circle_marker_4490f5a9c1964e9fa68d4186d73cf55d = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_570664bd4a8341679c6ffd2ec4511773 = L.popup({maxWidth: '300'});

            
                var html_3d715d3d9c264a579d3df2816eaf263d = $('<div id="html_3d715d3d9c264a579d3df2816eaf263d" style="width: 100.0%; height: 100.0%;">First Canadian Place, Underground city, Downtown Toronto</div>')[0];
                popup_570664bd4a8341679c6ffd2ec4511773.setContent(html_3d715d3d9c264a579d3df2816eaf263d);
            

            circle_marker_4490f5a9c1964e9fa68d4186d73cf55d.bindPopup(popup_570664bd4a8341679c6ffd2ec4511773);

            
        
    
            var circle_marker_cba27fb13c4c48d0a1d73d4d385e4d13 = L.circleMarker(
                [43.718517999999996,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_4e2a1ba830f94b09b9d07c4da425f676 = L.popup({maxWidth: '300'});

            
                var html_b7760fbe298a4681b076160b2f3cfb25 = $('<div id="html_b7760fbe298a4681b076160b2f3cfb25" style="width: 100.0%; height: 100.0%;">Lawrence Manor, Lawrence Heights, North York</div>')[0];
                popup_4e2a1ba830f94b09b9d07c4da425f676.setContent(html_b7760fbe298a4681b076160b2f3cfb25);
            

            circle_marker_cba27fb13c4c48d0a1d73d4d385e4d13.bindPopup(popup_4e2a1ba830f94b09b9d07c4da425f676);

            
        
    
            var circle_marker_37da4bdbf2aa47cd81c44b866640f751 = L.circleMarker(
                [43.709577,-79.44507259999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_bf696cedbdcd4282b25c2d1a850a0ba7 = L.popup({maxWidth: '300'});

            
                var html_52c9e68b04c3483f8d4a175e6dd2e5cf = $('<div id="html_52c9e68b04c3483f8d4a175e6dd2e5cf" style="width: 100.0%; height: 100.0%;">Glencairn, North York</div>')[0];
                popup_bf696cedbdcd4282b25c2d1a850a0ba7.setContent(html_52c9e68b04c3483f8d4a175e6dd2e5cf);
            

            circle_marker_37da4bdbf2aa47cd81c44b866640f751.bindPopup(popup_bf696cedbdcd4282b25c2d1a850a0ba7);

            
        
    
            var circle_marker_c1f64dff14f845e9970aed2a1aaaff1e = L.circleMarker(
                [43.6937813,-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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_d96f7592699a4ae7b9ac6f3f8f3686cf = L.popup({maxWidth: '300'});

            
                var html_02c7baaabe034be4841979a4b51cf4e1 = $('<div id="html_02c7baaabe034be4841979a4b51cf4e1" style="width: 100.0%; height: 100.0%;">Humewood-Cedarvale, York</div>')[0];
                popup_d96f7592699a4ae7b9ac6f3f8f3686cf.setContent(html_02c7baaabe034be4841979a4b51cf4e1);
            

            circle_marker_c1f64dff14f845e9970aed2a1aaaff1e.bindPopup(popup_d96f7592699a4ae7b9ac6f3f8f3686cf);

            
        
    
            var circle_marker_744e825bbd004dfea9874b67ef58afe1 = L.circleMarker(
                [43.6890256,-79.453512],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_6f32c54cf0834f55b96fd27b639bad90 = L.popup({maxWidth: '300'});

            
                var html_66228c8ba3b648ecb2ff21bea72166f5 = $('<div id="html_66228c8ba3b648ecb2ff21bea72166f5" style="width: 100.0%; height: 100.0%;">Caledonia-Fairbanks, York</div>')[0];
                popup_6f32c54cf0834f55b96fd27b639bad90.setContent(html_66228c8ba3b648ecb2ff21bea72166f5);
            

            circle_marker_744e825bbd004dfea9874b67ef58afe1.bindPopup(popup_6f32c54cf0834f55b96fd27b639bad90);

            
        
    
            var circle_marker_d6c7683314754f0fa8d37b50d55df10c = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_5df464f7ace146969260c58633c265bf = L.popup({maxWidth: '300'});

            
                var html_ce5b6fe4fca648948b4133042bf5bf98 = $('<div id="html_ce5b6fe4fca648948b4133042bf5bf98" style="width: 100.0%; height: 100.0%;">Christie, Downtown Toronto</div>')[0];
                popup_5df464f7ace146969260c58633c265bf.setContent(html_ce5b6fe4fca648948b4133042bf5bf98);
            

            circle_marker_d6c7683314754f0fa8d37b50d55df10c.bindPopup(popup_5df464f7ace146969260c58633c265bf);

            
        
    
            var circle_marker_5454b81ea2344f90b47204c50560016e = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_570652b030be4b94a394da370bec8974 = L.popup({maxWidth: '300'});

            
                var html_b69d6e99b460447cbbe23e4aab917592 = $('<div id="html_b69d6e99b460447cbbe23e4aab917592" style="width: 100.0%; height: 100.0%;">Dufferin, Dovercourt Village, West Toronto</div>')[0];
                popup_570652b030be4b94a394da370bec8974.setContent(html_b69d6e99b460447cbbe23e4aab917592);
            

            circle_marker_5454b81ea2344f90b47204c50560016e.bindPopup(popup_570652b030be4b94a394da370bec8974);

            
        
    
            var circle_marker_1088989c8e63473f95330e382e52c907 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_a9df645bff414c2d8eba42fb30efa515 = L.popup({maxWidth: '300'});

            
                var html_49df7f1d77424c4ba6591167e7778671 = $('<div id="html_49df7f1d77424c4ba6591167e7778671" style="width: 100.0%; height: 100.0%;">Little Portugal, Trinity, West Toronto</div>')[0];
                popup_a9df645bff414c2d8eba42fb30efa515.setContent(html_49df7f1d77424c4ba6591167e7778671);
            

            circle_marker_1088989c8e63473f95330e382e52c907.bindPopup(popup_a9df645bff414c2d8eba42fb30efa515);

            
        
    
            var circle_marker_bfde0e2c18c6416a90dc8523d40644c1 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_adc56aa00331434d9c7f17c198bb921b = L.popup({maxWidth: '300'});

            
                var html_c6ce39fca7da42d2abaf7113fc2e6946 = $('<div id="html_c6ce39fca7da42d2abaf7113fc2e6946" style="width: 100.0%; height: 100.0%;">Brockton, Parkdale Village, Exhibition Place, West Toronto</div>')[0];
                popup_adc56aa00331434d9c7f17c198bb921b.setContent(html_c6ce39fca7da42d2abaf7113fc2e6946);
            

            circle_marker_bfde0e2c18c6416a90dc8523d40644c1.bindPopup(popup_adc56aa00331434d9c7f17c198bb921b);

            
        
    
            var circle_marker_c2a54118da1242d28bf8be01b9d129fd = L.circleMarker(
                [43.713756200000006,-79.4900738],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_acd31820abf04d61bce85064f95b5ae3 = L.popup({maxWidth: '300'});

            
                var html_6e3045ee26dd461db07323051c5bd180 = $('<div id="html_6e3045ee26dd461db07323051c5bd180" style="width: 100.0%; height: 100.0%;">North Park, Maple Leaf Park, Upwood Park, North York</div>')[0];
                popup_acd31820abf04d61bce85064f95b5ae3.setContent(html_6e3045ee26dd461db07323051c5bd180);
            

            circle_marker_c2a54118da1242d28bf8be01b9d129fd.bindPopup(popup_acd31820abf04d61bce85064f95b5ae3);

            
        
    
            var circle_marker_cbb044c3af1a421d935b79e1a78b089b = L.circleMarker(
                [43.6911158,-79.47601329999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_bbb6c5587a3f48049ce818e10e82d7ff = L.popup({maxWidth: '300'});

            
                var html_7fef01482889436b826f7274111019cc = $('<div id="html_7fef01482889436b826f7274111019cc" style="width: 100.0%; height: 100.0%;">Del Ray, Mount Dennis, Keelsdale and Silverthorn, York</div>')[0];
                popup_bbb6c5587a3f48049ce818e10e82d7ff.setContent(html_7fef01482889436b826f7274111019cc);
            

            circle_marker_cbb044c3af1a421d935b79e1a78b089b.bindPopup(popup_bbb6c5587a3f48049ce818e10e82d7ff);

            
        
    
            var circle_marker_cdca0524e26440d9a3262a93890df9cb = L.circleMarker(
                [43.67318529999999,-79.48726190000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_787d429454c142488c3da2c1f73923c4 = L.popup({maxWidth: '300'});

            
                var html_605bc058a69940f6a48e39dfb7ac696b = $('<div id="html_605bc058a69940f6a48e39dfb7ac696b" style="width: 100.0%; height: 100.0%;">Runnymede, The Junction North, York</div>')[0];
                popup_787d429454c142488c3da2c1f73923c4.setContent(html_605bc058a69940f6a48e39dfb7ac696b);
            

            circle_marker_cdca0524e26440d9a3262a93890df9cb.bindPopup(popup_787d429454c142488c3da2c1f73923c4);

            
        
    
            var circle_marker_cbb4cf3b7ab74677b1c17ff9f553420a = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_c808a254dbee45bfadb19d08d28de165 = L.popup({maxWidth: '300'});

            
                var html_d3358da742004ae5a24882caeebf2065 = $('<div id="html_d3358da742004ae5a24882caeebf2065" style="width: 100.0%; height: 100.0%;">High Park, The Junction South, West Toronto</div>')[0];
                popup_c808a254dbee45bfadb19d08d28de165.setContent(html_d3358da742004ae5a24882caeebf2065);
            

            circle_marker_cbb4cf3b7ab74677b1c17ff9f553420a.bindPopup(popup_c808a254dbee45bfadb19d08d28de165);

            
        
    
            var circle_marker_94faab827abf4056be64cdfb4219765a = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_bc8cc5d1d6614501b70d0b6cad6bbfae = L.popup({maxWidth: '300'});

            
                var html_1382474517dc4e43a19f58d243826a7b = $('<div id="html_1382474517dc4e43a19f58d243826a7b" style="width: 100.0%; height: 100.0%;">Parkdale, Roncesvalles, West Toronto</div>')[0];
                popup_bc8cc5d1d6614501b70d0b6cad6bbfae.setContent(html_1382474517dc4e43a19f58d243826a7b);
            

            circle_marker_94faab827abf4056be64cdfb4219765a.bindPopup(popup_bc8cc5d1d6614501b70d0b6cad6bbfae);

            
        
    
            var circle_marker_4b782e6ab23a46ba8119471f19bd46f6 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_e145647bf3d74a6ab36407fbe241c950 = L.popup({maxWidth: '300'});

            
                var html_269bb0e450154851a8fffb009b457ecc = $('<div id="html_269bb0e450154851a8fffb009b457ecc" style="width: 100.0%; height: 100.0%;">Runnymede, Swansea, West Toronto</div>')[0];
                popup_e145647bf3d74a6ab36407fbe241c950.setContent(html_269bb0e450154851a8fffb009b457ecc);
            

            circle_marker_4b782e6ab23a46ba8119471f19bd46f6.bindPopup(popup_e145647bf3d74a6ab36407fbe241c950);

            
        
    
            var circle_marker_3d1f494454404d92ab1210a4e88255ff = L.circleMarker(
                [43.6623015,-79.3894938],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_145012acb5534b1ab181ed619ce1a1a8 = L.popup({maxWidth: '300'});

            
                var html_ee4e1d4bb69c4b45845c0b76fb4fe67b = $('<div id="html_ee4e1d4bb69c4b45845c0b76fb4fe67b" style="width: 100.0%; height: 100.0%;">Queen&#39;s Park, Ontario Provincial Government, Downtown Toronto</div>')[0];
                popup_145012acb5534b1ab181ed619ce1a1a8.setContent(html_ee4e1d4bb69c4b45845c0b76fb4fe67b);
            

            circle_marker_3d1f494454404d92ab1210a4e88255ff.bindPopup(popup_145012acb5534b1ab181ed619ce1a1a8);

            
        
    
            var circle_marker_6ef1eb83643d4354acbfa7d58366fa79 = L.circleMarker(
                [43.6369656,-79.61581899999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_74f08b8dc706459195072b583a2ead9b = L.popup({maxWidth: '300'});

            
                var html_a03f502492ff4f069cafc82f67ea79e6 = $('<div id="html_a03f502492ff4f069cafc82f67ea79e6" style="width: 100.0%; height: 100.0%;">Canada Post Gateway Processing Centre, Mississauga</div>')[0];
                popup_74f08b8dc706459195072b583a2ead9b.setContent(html_a03f502492ff4f069cafc82f67ea79e6);
            

            circle_marker_6ef1eb83643d4354acbfa7d58366fa79.bindPopup(popup_74f08b8dc706459195072b583a2ead9b);

            
        
    
            var circle_marker_4e4c2fd4b1594b74b5e16cd2ba6d4264 = 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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_c8a5063f9b514e909329bd543da7b63b = L.popup({maxWidth: '300'});

            
                var html_ff2e7d4b9d1f4855b4695339b04c3e7a = $('<div id="html_ff2e7d4b9d1f4855b4695339b04c3e7a" style="width: 100.0%; height: 100.0%;">Business reply mail Processing Centre, South Central Letter Processing Plant Toronto, East Toronto</div>')[0];
                popup_c8a5063f9b514e909329bd543da7b63b.setContent(html_ff2e7d4b9d1f4855b4695339b04c3e7a);
            

            circle_marker_4e4c2fd4b1594b74b5e16cd2ba6d4264.bindPopup(popup_c8a5063f9b514e909329bd543da7b63b);

            
        
    
            var circle_marker_57fa1bfc0f3347ee95d2b4e9dbeb9abe = L.circleMarker(
                [43.6056466,-79.50132070000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_2b06ea19c31c45b898f0e975551c4791 = L.popup({maxWidth: '300'});

            
                var html_316910d4707a4bd9a2acb2d273fe4e65 = $('<div id="html_316910d4707a4bd9a2acb2d273fe4e65" style="width: 100.0%; height: 100.0%;">New Toronto, Mimico South, Humber Bay Shores, Etobicoke</div>')[0];
                popup_2b06ea19c31c45b898f0e975551c4791.setContent(html_316910d4707a4bd9a2acb2d273fe4e65);
            

            circle_marker_57fa1bfc0f3347ee95d2b4e9dbeb9abe.bindPopup(popup_2b06ea19c31c45b898f0e975551c4791);

            
        
    
            var circle_marker_63bfa96150af42bfa202b922dd5568cd = L.circleMarker(
                [43.60241370000001,-79.54348409999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_fc734e8bf80847968f61233e01813996 = L.popup({maxWidth: '300'});

            
                var html_596d6cceebd341078ef0390b87f57d98 = $('<div id="html_596d6cceebd341078ef0390b87f57d98" style="width: 100.0%; height: 100.0%;">Alderwood, Long Branch, Etobicoke</div>')[0];
                popup_fc734e8bf80847968f61233e01813996.setContent(html_596d6cceebd341078ef0390b87f57d98);
            

            circle_marker_63bfa96150af42bfa202b922dd5568cd.bindPopup(popup_fc734e8bf80847968f61233e01813996);

            
        
    
            var circle_marker_fb1e9ba850c34b03844fbc82e7f9859b = L.circleMarker(
                [43.653653600000005,-79.5069436],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_8015d3b5d8154116854a33ad9ce5f989 = L.popup({maxWidth: '300'});

            
                var html_a051ab7920464d4099a5ad7c99da1b9b = $('<div id="html_a051ab7920464d4099a5ad7c99da1b9b" style="width: 100.0%; height: 100.0%;">The Kingsway, Montgomery Road, Old Mill North, Etobicoke</div>')[0];
                popup_8015d3b5d8154116854a33ad9ce5f989.setContent(html_a051ab7920464d4099a5ad7c99da1b9b);
            

            circle_marker_fb1e9ba850c34b03844fbc82e7f9859b.bindPopup(popup_8015d3b5d8154116854a33ad9ce5f989);

            
        
    
            var circle_marker_5726331219fb4f2a99d209211b4f727d = L.circleMarker(
                [43.6362579,-79.49850909999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_2476ca102fa9480cb586becf8e5c2307 = L.popup({maxWidth: '300'});

            
                var html_2d89cfa253aa4a678dff68aa0ff3049c = $('<div id="html_2d89cfa253aa4a678dff68aa0ff3049c" style="width: 100.0%; height: 100.0%;">Old Mill South, King&#39;s Mill Park, Sunnylea, Humber Bay, Mimico NE, The Queensway East, Royal York South East, Kingsway Park South East, Etobicoke</div>')[0];
                popup_2476ca102fa9480cb586becf8e5c2307.setContent(html_2d89cfa253aa4a678dff68aa0ff3049c);
            

            circle_marker_5726331219fb4f2a99d209211b4f727d.bindPopup(popup_2476ca102fa9480cb586becf8e5c2307);

            
        
    
            var circle_marker_664f78d8159c4d82911130ce46d7fbe3 = L.circleMarker(
                [43.6288408,-79.52099940000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_f0ba30a4d0104dc8a1ccea74c311a195 = L.popup({maxWidth: '300'});

            
                var html_261f7f4123524ad4bbaf5bdc15bff390 = $('<div id="html_261f7f4123524ad4bbaf5bdc15bff390" style="width: 100.0%; height: 100.0%;">Mimico NW, The Queensway West, South of Bloor, Kingsway Park South West, Royal York South West, Etobicoke</div>')[0];
                popup_f0ba30a4d0104dc8a1ccea74c311a195.setContent(html_261f7f4123524ad4bbaf5bdc15bff390);
            

            circle_marker_664f78d8159c4d82911130ce46d7fbe3.bindPopup(popup_f0ba30a4d0104dc8a1ccea74c311a195);

            
        
    
            var circle_marker_7ad43004e3304538805228688e12ca06 = L.circleMarker(
                [43.6678556,-79.53224240000002],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_0d8ad6f104904a29a6d4e1b8699be49e = L.popup({maxWidth: '300'});

            
                var html_5ce2535126dc4d1ab9fdb79cddba0d31 = $('<div id="html_5ce2535126dc4d1ab9fdb79cddba0d31" style="width: 100.0%; height: 100.0%;">Islington Avenue, Humber Valley Village, Etobicoke</div>')[0];
                popup_0d8ad6f104904a29a6d4e1b8699be49e.setContent(html_5ce2535126dc4d1ab9fdb79cddba0d31);
            

            circle_marker_7ad43004e3304538805228688e12ca06.bindPopup(popup_0d8ad6f104904a29a6d4e1b8699be49e);

            
        
    
            var circle_marker_5f644ea7d63c4ab7a001c3625f8f2b72 = L.circleMarker(
                [43.6509432,-79.55472440000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_08d06e6d9f5d44858ce9925ded000e69 = L.popup({maxWidth: '300'});

            
                var html_faf020247c14491bb8c9fce61f14d342 = $('<div id="html_faf020247c14491bb8c9fce61f14d342" style="width: 100.0%; height: 100.0%;">West Deane Park, Princess Gardens, Martin Grove, Islington, Cloverdale, Etobicoke</div>')[0];
                popup_08d06e6d9f5d44858ce9925ded000e69.setContent(html_faf020247c14491bb8c9fce61f14d342);
            

            circle_marker_5f644ea7d63c4ab7a001c3625f8f2b72.bindPopup(popup_08d06e6d9f5d44858ce9925ded000e69);

            
        
    
            var circle_marker_6a83b95f322c4b8c967bbc4ae656c7f1 = L.circleMarker(
                [43.6435152,-79.57720079999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_67fdbb61d42b4645a798bc0cc6df993c = L.popup({maxWidth: '300'});

            
                var html_98cca91ae3bd4d23903e82083ea8526f = $('<div id="html_98cca91ae3bd4d23903e82083ea8526f" style="width: 100.0%; height: 100.0%;">Eringate, Bloordale Gardens, Old Burnhamthorpe, Markland Wood, Etobicoke</div>')[0];
                popup_67fdbb61d42b4645a798bc0cc6df993c.setContent(html_98cca91ae3bd4d23903e82083ea8526f);
            

            circle_marker_6a83b95f322c4b8c967bbc4ae656c7f1.bindPopup(popup_67fdbb61d42b4645a798bc0cc6df993c);

            
        
    
            var circle_marker_5e59e452c8ca424ea309a8279acb16a5 = L.circleMarker(
                [43.7563033,-79.56596329999999],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_44f25670ba85485fa8f63b753c67eb56 = L.popup({maxWidth: '300'});

            
                var html_ded8475caba345eeb81c9f8c047b6066 = $('<div id="html_ded8475caba345eeb81c9f8c047b6066" style="width: 100.0%; height: 100.0%;">Humber Summit, North York</div>')[0];
                popup_44f25670ba85485fa8f63b753c67eb56.setContent(html_ded8475caba345eeb81c9f8c047b6066);
            

            circle_marker_5e59e452c8ca424ea309a8279acb16a5.bindPopup(popup_44f25670ba85485fa8f63b753c67eb56);

            
        
    
            var circle_marker_9fabe952cb2a471faf2b7b58cc577ad2 = L.circleMarker(
                [43.7247659,-79.53224240000002],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_b5bbd76577124498988f09229a53c459 = L.popup({maxWidth: '300'});

            
                var html_569135e8be4346f0abf3edc25cd8b45c = $('<div id="html_569135e8be4346f0abf3edc25cd8b45c" style="width: 100.0%; height: 100.0%;">Humberlea, Emery, North York</div>')[0];
                popup_b5bbd76577124498988f09229a53c459.setContent(html_569135e8be4346f0abf3edc25cd8b45c);
            

            circle_marker_9fabe952cb2a471faf2b7b58cc577ad2.bindPopup(popup_b5bbd76577124498988f09229a53c459);

            
        
    
            var circle_marker_64ee0d1c6aec4c9b8b61f2c70d7610bc = L.circleMarker(
                [43.706876,-79.51818840000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_ec853ff0d2e647939c10df3add3d212d = L.popup({maxWidth: '300'});

            
                var html_50f9ac217e164a66955222a01e57a8ca = $('<div id="html_50f9ac217e164a66955222a01e57a8ca" style="width: 100.0%; height: 100.0%;">Weston, York</div>')[0];
                popup_ec853ff0d2e647939c10df3add3d212d.setContent(html_50f9ac217e164a66955222a01e57a8ca);
            

            circle_marker_64ee0d1c6aec4c9b8b61f2c70d7610bc.bindPopup(popup_ec853ff0d2e647939c10df3add3d212d);

            
        
    
            var circle_marker_224ffc3077c74bde81b88d3e97ffda2d = L.circleMarker(
                [43.696319,-79.53224240000002],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_6624eaf02f3c463a9e92ea75395043af = L.popup({maxWidth: '300'});

            
                var html_bc1084d414954aacb5a9f118dc905aac = $('<div id="html_bc1084d414954aacb5a9f118dc905aac" style="width: 100.0%; height: 100.0%;">Westmount, Etobicoke</div>')[0];
                popup_6624eaf02f3c463a9e92ea75395043af.setContent(html_bc1084d414954aacb5a9f118dc905aac);
            

            circle_marker_224ffc3077c74bde81b88d3e97ffda2d.bindPopup(popup_6624eaf02f3c463a9e92ea75395043af);

            
        
    
            var circle_marker_e1df596b13b1431bb8c63e227221c15a = L.circleMarker(
                [43.6889054,-79.55472440000001],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_08a31df339b546cab80cc998483e9f12 = L.popup({maxWidth: '300'});

            
                var html_832d499b17b8478a88a7272ac67f30a5 = $('<div id="html_832d499b17b8478a88a7272ac67f30a5" style="width: 100.0%; height: 100.0%;">Kingsview Village, St. Phillips, Martin Grove Gardens, Richview Gardens, Etobicoke</div>')[0];
                popup_08a31df339b546cab80cc998483e9f12.setContent(html_832d499b17b8478a88a7272ac67f30a5);
            

            circle_marker_e1df596b13b1431bb8c63e227221c15a.bindPopup(popup_08a31df339b546cab80cc998483e9f12);

            
        
    
            var circle_marker_4c462bd3b6b448049a60e2c4ef220e12 = L.circleMarker(
                [43.739416399999996,-79.5884369],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_6ff284753c4a494bb7da2cd169e358b9 = L.popup({maxWidth: '300'});

            
                var html_59bb0b965cf040aa8df1458cfd0af97d = $('<div id="html_59bb0b965cf040aa8df1458cfd0af97d" style="width: 100.0%; height: 100.0%;">South Steeles, Silverstone, Humbergate, Jamestown, Mount Olive, Beaumond Heights, Thistletown, Albion Gardens, Etobicoke</div>')[0];
                popup_6ff284753c4a494bb7da2cd169e358b9.setContent(html_59bb0b965cf040aa8df1458cfd0af97d);
            

            circle_marker_4c462bd3b6b448049a60e2c4ef220e12.bindPopup(popup_6ff284753c4a494bb7da2cd169e358b9);

            
        
    
            var circle_marker_1ff32c1a840649d7beab2b9b2871bbca = L.circleMarker(
                [43.706748299999994,-79.5940544],
                {
  "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_59cd65205f444909bb4d2ad75f82121b);
            
    
            var popup_4448bcfd27a24230b8b3b26de9bcd0df = L.popup({maxWidth: '300'});

            
                var html_71ad504ce68b4fc6968e8aa085b8e5ca = $('<div id="html_71ad504ce68b4fc6968e8aa085b8e5ca" style="width: 100.0%; height: 100.0%;">Northwest, West Humber - Clairville, Etobicoke</div>')[0];
                popup_4448bcfd27a24230b8b3b26de9bcd0df.setContent(html_71ad504ce68b4fc6968e8aa085b8e5ca);
            

            circle_marker_1ff32c1a840649d7beab2b9b2871bbca.bindPopup(popup_4448bcfd27a24230b8b3b26de9bcd0df);

            
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fb232535b00>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Toronto using latitude and longitude values\n",
    "map_toronto = folium.Map(location=[latitude, longitude], zoom_start=10)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, borough, neighborhood in zip(df_merged['Latitude'], df_merged['Longitude'], df_merged['Borough'], df_merged['Neighbourhood']):\n",
    "    label = '{}, {}'.format(neighborhood, borough)\n",
    "    label = folium.Popup(label, parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lng],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color='blue',\n",
    "        fill=True,\n",
    "        fill_color='#3186cc',\n",
    "        fill_opacity=0.7,\n",
    "        parse_html=False).add_to(map_toronto)  \n",
    "    \n",
    "map_toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### To simplify the visualisation we focus on Central Toronto "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M4N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M4R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>43.715383</td>\n",
       "      <td>-79.405678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4S</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "      <td>43.704324</td>\n",
       "      <td>-79.388790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M4T</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>43.689574</td>\n",
       "      <td>-79.383160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M4V</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Summerhill West, Rathnelly, South Hill, Forest...</td>\n",
       "      <td>43.686412</td>\n",
       "      <td>-79.400049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M5N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Roselawn</td>\n",
       "      <td>43.711695</td>\n",
       "      <td>-79.416936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M5P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Forest Hill North &amp; West, Forest Hill Road Park</td>\n",
       "      <td>43.696948</td>\n",
       "      <td>-79.411307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M5R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.672710</td>\n",
       "      <td>-79.405678</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code          Borough  \\\n",
       "0         M4N  Central Toronto   \n",
       "1         M4P  Central Toronto   \n",
       "2         M4R  Central Toronto   \n",
       "3         M4S  Central Toronto   \n",
       "4         M4T  Central Toronto   \n",
       "5         M4V  Central Toronto   \n",
       "6         M5N  Central Toronto   \n",
       "7         M5P  Central Toronto   \n",
       "8         M5R  Central Toronto   \n",
       "\n",
       "                                       Neighbourhood   Latitude  Longitude  \n",
       "0                                      Lawrence Park  43.728020 -79.388790  \n",
       "1                                   Davisville North  43.712751 -79.390197  \n",
       "2                  North Toronto West, Lawrence Park  43.715383 -79.405678  \n",
       "3                                         Davisville  43.704324 -79.388790  \n",
       "4                        Moore Park, Summerhill East  43.689574 -79.383160  \n",
       "5  Summerhill West, Rathnelly, South Hill, Forest...  43.686412 -79.400049  \n",
       "6                                           Roselawn  43.711695 -79.416936  \n",
       "7    Forest Hill North & West, Forest Hill Road Park  43.696948 -79.411307  \n",
       "8                The Annex, North Midtown, Yorkville  43.672710 -79.405678  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_to_data= df_merged[df_merged['Borough'] == 'Central Toronto'].reset_index(drop=True)\n",
    "central_to_data.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's get the coordinate of Central Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Central Toronto are 43.6534817, -79.3839347.\n"
     ]
    }
   ],
   "source": [
    "address_central_to = 'Central Toronto'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"central_toronto_explorer\")\n",
    "location_central_to = geolocator.geocode(address_central_to)\n",
    "latitude_central_to = location.latitude\n",
    "longitude_central_to = location.longitude\n",
    "print('The geograpical coordinate of Central Toronto are {}, {}.'.format(latitude_central_to, longitude_central_to))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Map of Central Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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 src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS = false; L_NO_TOUCH = false; L_DISABLE_3D = false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.js"></script>
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.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@1.2.0/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://rawgit.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>
    
            <style> #map_3ffb405e12914b83b6b06aac876ba2d4 {
                position : relative;
                width : 100.0%;
                height: 100.0%;
                left: 0.0%;
                top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_3ffb405e12914b83b6b06aac876ba2d4" ></div>
        
</body>
<script>    
    

            
                var bounds = null;
            

            var map_3ffb405e12914b83b6b06aac876ba2d4 = L.map(
                                  'map_3ffb405e12914b83b6b06aac876ba2d4',
                                  {center: [43.6534817,-79.3839347],
                                  zoom: 12,
                                  maxBounds: bounds,
                                  layers: [],
                                  worldCopyJump: false,
                                  crs: L.CRS.EPSG3857
                                 });
            
        
    
            var tile_layer_62f7c5ff86a8484a90e0a55ccb93112e = L.tileLayer(
                'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
                {
  "attribution": null,
  "detectRetina": false,
  "maxZoom": 18,
  "minZoom": 1,
  "noWrap": false,
  "subdomains": "abc"
}
                ).addTo(map_3ffb405e12914b83b6b06aac876ba2d4);
        
    
            var circle_marker_5b1279892a10407cad9c500e13f801ff = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_7694976eff03475eb1fab085566888a9 = L.popup({maxWidth: '300'});

            
                var html_26351786c0a84feb9222eca92f661491 = $('<div id="html_26351786c0a84feb9222eca92f661491" style="width: 100.0%; height: 100.0%;">Lawrence Park</div>')[0];
                popup_7694976eff03475eb1fab085566888a9.setContent(html_26351786c0a84feb9222eca92f661491);
            

            circle_marker_5b1279892a10407cad9c500e13f801ff.bindPopup(popup_7694976eff03475eb1fab085566888a9);

            
        
    
            var circle_marker_6c785632d4554f0e947dd31d6ab259a3 = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_2878288233ba4c12876f274142221a5e = L.popup({maxWidth: '300'});

            
                var html_3754312a0bab42b4b027367a4f7c0f84 = $('<div id="html_3754312a0bab42b4b027367a4f7c0f84" style="width: 100.0%; height: 100.0%;">Davisville North</div>')[0];
                popup_2878288233ba4c12876f274142221a5e.setContent(html_3754312a0bab42b4b027367a4f7c0f84);
            

            circle_marker_6c785632d4554f0e947dd31d6ab259a3.bindPopup(popup_2878288233ba4c12876f274142221a5e);

            
        
    
            var circle_marker_45a40775561d4ae089c48ce4614d6a74 = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_976342baac844de09e122b58e1065b1e = L.popup({maxWidth: '300'});

            
                var html_0b7530dc48d14266b874b02f96b6326b = $('<div id="html_0b7530dc48d14266b874b02f96b6326b" style="width: 100.0%; height: 100.0%;">North Toronto West, Lawrence Park</div>')[0];
                popup_976342baac844de09e122b58e1065b1e.setContent(html_0b7530dc48d14266b874b02f96b6326b);
            

            circle_marker_45a40775561d4ae089c48ce4614d6a74.bindPopup(popup_976342baac844de09e122b58e1065b1e);

            
        
    
            var circle_marker_2194d7bca9d547639241c9a13225cd6a = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_615c9e63616e4f93a9c100cd2ed8ebc3 = L.popup({maxWidth: '300'});

            
                var html_08a39d76c64f44fe9e340d26866d8f8a = $('<div id="html_08a39d76c64f44fe9e340d26866d8f8a" style="width: 100.0%; height: 100.0%;">Davisville</div>')[0];
                popup_615c9e63616e4f93a9c100cd2ed8ebc3.setContent(html_08a39d76c64f44fe9e340d26866d8f8a);
            

            circle_marker_2194d7bca9d547639241c9a13225cd6a.bindPopup(popup_615c9e63616e4f93a9c100cd2ed8ebc3);

            
        
    
            var circle_marker_7a917ace9b0d46a19189c9c2c3fc3fe0 = L.circleMarker(
                [43.6895743,-79.38315990000001],
                {
  "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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_df7d562d33414ae1a6a63518e1c1ca6c = L.popup({maxWidth: '300'});

            
                var html_11c7e4de30e048ec8960b065c27ef887 = $('<div id="html_11c7e4de30e048ec8960b065c27ef887" style="width: 100.0%; height: 100.0%;">Moore Park, Summerhill East</div>')[0];
                popup_df7d562d33414ae1a6a63518e1c1ca6c.setContent(html_11c7e4de30e048ec8960b065c27ef887);
            

            circle_marker_7a917ace9b0d46a19189c9c2c3fc3fe0.bindPopup(popup_df7d562d33414ae1a6a63518e1c1ca6c);

            
        
    
            var circle_marker_0077078ebbd34bd985f467d648e800a4 = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_19bcc2a7bf2447aa88c6ef853c939ff5 = L.popup({maxWidth: '300'});

            
                var html_a946c3b66f414bec87b17a8169794b97 = $('<div id="html_a946c3b66f414bec87b17a8169794b97" style="width: 100.0%; height: 100.0%;">Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park</div>')[0];
                popup_19bcc2a7bf2447aa88c6ef853c939ff5.setContent(html_a946c3b66f414bec87b17a8169794b97);
            

            circle_marker_0077078ebbd34bd985f467d648e800a4.bindPopup(popup_19bcc2a7bf2447aa88c6ef853c939ff5);

            
        
    
            var circle_marker_624936f536924aaea5e3fa265b72433b = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_62ffcd66ac724569aeb74df502274d4a = L.popup({maxWidth: '300'});

            
                var html_f446587c604d4b11990b7ecbaaa2b3d3 = $('<div id="html_f446587c604d4b11990b7ecbaaa2b3d3" style="width: 100.0%; height: 100.0%;">Roselawn</div>')[0];
                popup_62ffcd66ac724569aeb74df502274d4a.setContent(html_f446587c604d4b11990b7ecbaaa2b3d3);
            

            circle_marker_624936f536924aaea5e3fa265b72433b.bindPopup(popup_62ffcd66ac724569aeb74df502274d4a);

            
        
    
            var circle_marker_836939772d3f4616a4aa06fa9f4e2524 = L.circleMarker(
                [43.6969476,-79.41130720000001],
                {
  "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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_ce501d553e2140e3b05c9392a9e567e8 = L.popup({maxWidth: '300'});

            
                var html_36cc2cb4a0c64b15931abe3e3cf15d81 = $('<div id="html_36cc2cb4a0c64b15931abe3e3cf15d81" style="width: 100.0%; height: 100.0%;">Forest Hill North &amp; West, Forest Hill Road Park</div>')[0];
                popup_ce501d553e2140e3b05c9392a9e567e8.setContent(html_36cc2cb4a0c64b15931abe3e3cf15d81);
            

            circle_marker_836939772d3f4616a4aa06fa9f4e2524.bindPopup(popup_ce501d553e2140e3b05c9392a9e567e8);

            
        
    
            var circle_marker_b65a5189ec974797935c38d836123855 = 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_3ffb405e12914b83b6b06aac876ba2d4);
            
    
            var popup_5d06e7b0f1bb4bbcbc859a611d586cad = L.popup({maxWidth: '300'});

            
                var html_dd1c12b4e3a6414588af8564d3406853 = $('<div id="html_dd1c12b4e3a6414588af8564d3406853" style="width: 100.0%; height: 100.0%;">The Annex, North Midtown, Yorkville</div>')[0];
                popup_5d06e7b0f1bb4bbcbc859a611d586cad.setContent(html_dd1c12b4e3a6414588af8564d3406853);
            

            circle_marker_b65a5189ec974797935c38d836123855.bindPopup(popup_5d06e7b0f1bb4bbcbc859a611d586cad);

            
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fb23231e320>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Manhattan using latitude and longitude values\n",
    "map_central_to = folium.Map(location=[latitude_central_to, longitude_central_to], zoom_start=12)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, label in zip(central_to_data['Latitude'], central_to_data['Longitude'],central_to_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_central_to)  \n",
    "    \n",
    "map_central_to"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2 Explore the neighborhoods and segment them with Foursquare API to"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define Foursquare credential "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's explore the first neighborhood in our dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Lawrence Park'"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_to_data.loc[0, 'Neighbourhood']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the neighborhood's latitude and longitude values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Latitude and longitude values of Lawrence Park are 43.7280205, -79.3887901.\n"
     ]
    }
   ],
   "source": [
    "neighborhood_latitude = central_to_data.loc[0, 'Latitude'] # neighborhood latitude value\n",
    "neighborhood_longitude = central_to_data.loc[0, 'Longitude'] # neighborhood longitude value\n",
    "\n",
    "neighborhood_name = central_to_data.loc[0, 'Neighbourhood'] # neighborhood name\n",
    "\n",
    "print('Latitude and longitude values of {} are {}, {}.'.format(neighborhood_name, \n",
    "                                                               neighborhood_latitude, \n",
    "                                                               neighborhood_longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now, let's get the top 100 venues that are in Lawrence Park within a radius of 500 meters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "LIMIT = 50 # limit of number of venues returned by Foursquare API\n",
    "radius = 500 # define radius\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Send the GET request and examine the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'meta': {'code': 200, 'requestId': '5fa432d3960f157f9119000f'},\n",
       " 'response': {'warning': {'text': \"There aren't a lot of results near you. Try something more general, reset your filters, or expand the search area.\"},\n",
       "  'headerLocation': 'Toronto',\n",
       "  'headerFullLocation': 'Toronto',\n",
       "  'headerLocationGranularity': 'city',\n",
       "  'totalResults': 3,\n",
       "  'suggestedBounds': {'ne': {'lat': 43.7325205045, 'lng': -79.3825744605273},\n",
       "   'sw': {'lat': 43.7235204955, 'lng': -79.3950057394727}},\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': '50e6da19e4b0d8a78a0e9794',\n",
       "       'name': 'Lawrence Park Ravine',\n",
       "       'location': {'address': '3055 Yonge Street',\n",
       "        'crossStreet': 'Lawrence Avenue East',\n",
       "        'lat': 43.72696303913755,\n",
       "        'lng': -79.39438246708775,\n",
       "        'labeledLatLngs': [{'label': 'display',\n",
       "          'lat': 43.72696303913755,\n",
       "          'lng': -79.39438246708775}],\n",
       "        'distance': 465,\n",
       "        'cc': 'CA',\n",
       "        'city': 'Toronto',\n",
       "        'state': 'ON',\n",
       "        'country': 'Canada',\n",
       "        'formattedAddress': ['3055 Yonge Street (Lawrence Avenue East)',\n",
       "         'Toronto ON',\n",
       "         'Canada']},\n",
       "       'categories': [{'id': '4bf58dd8d48988d163941735',\n",
       "         'name': 'Park',\n",
       "         'pluralName': 'Parks',\n",
       "         'shortName': 'Park',\n",
       "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/parks_outdoors/park_',\n",
       "          'suffix': '.png'},\n",
       "         'primary': True}],\n",
       "       'photos': {'count': 0, 'groups': []}},\n",
       "      'referralId': 'e-0-50e6da19e4b0d8a78a0e9794-0'},\n",
       "     {'reasons': {'count': 0,\n",
       "       'items': [{'summary': 'This spot is popular',\n",
       "         'type': 'general',\n",
       "         'reasonName': 'globalInteractionReason'}]},\n",
       "      'venue': {'id': '5082ef77e4b0a7491cf7b022',\n",
       "       'name': 'Zodiac Swim School',\n",
       "       'location': {'lat': 43.72853205765438,\n",
       "        'lng': -79.3828602612317,\n",
       "        'labeledLatLngs': [{'label': 'display',\n",
       "          'lat': 43.72853205765438,\n",
       "          'lng': -79.3828602612317}],\n",
       "        'distance': 480,\n",
       "        'cc': 'CA',\n",
       "        'country': 'Canada',\n",
       "        'formattedAddress': ['Canada']},\n",
       "       'categories': [{'id': '52e81612bcbc57f1066b7a44',\n",
       "         'name': 'Swim School',\n",
       "         'pluralName': 'Swim Schools',\n",
       "         'shortName': 'Swim School',\n",
       "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/parks_outdoors/pool_',\n",
       "          'suffix': '.png'},\n",
       "         'primary': True}],\n",
       "       'photos': {'count': 0, 'groups': []}},\n",
       "      'referralId': 'e-0-5082ef77e4b0a7491cf7b022-1'},\n",
       "     {'reasons': {'count': 0,\n",
       "       'items': [{'summary': 'This spot is popular',\n",
       "         'type': 'general',\n",
       "         'reasonName': 'globalInteractionReason'}]},\n",
       "      'venue': {'id': '50ed9da8e4b081eabee12672',\n",
       "       'name': 'TTC Bus #162 - Lawrence-Donway',\n",
       "       'location': {'lat': 43.72802605799448,\n",
       "        'lng': -79.38280527753858,\n",
       "        'labeledLatLngs': [{'label': 'display',\n",
       "          'lat': 43.72802605799448,\n",
       "          'lng': -79.38280527753858}],\n",
       "        'distance': 481,\n",
       "        'cc': 'CA',\n",
       "        'city': 'Toronto',\n",
       "        'state': 'ON',\n",
       "        'country': 'Canada',\n",
       "        'formattedAddress': ['Toronto ON', 'Canada']},\n",
       "       'categories': [{'id': '4bf58dd8d48988d12b951735',\n",
       "         'name': 'Bus Line',\n",
       "         'pluralName': 'Bus Lines',\n",
       "         'shortName': 'Bus',\n",
       "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/travel/busstation_',\n",
       "          'suffix': '.png'},\n",
       "         'primary': True}],\n",
       "       'photos': {'count': 0, 'groups': []}},\n",
       "      'referralId': 'e-0-50ed9da8e4b081eabee12672-2'}]}]}}"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = requests.get(url).json()\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  let's borrow the get_category_type function from the Foursquare lab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function that extracts the category of the venue\n",
    "def get_category_type(row):\n",
    "    try:\n",
    "        categories_list = row['categories']\n",
    "    except:\n",
    "        categories_list = row['venue.categories']\n",
    "        \n",
    "    if len(categories_list) == 0:\n",
    "        return None\n",
    "    else:\n",
    "        return categories_list[0]['name']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Convert the venues find in a Panda DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json # library to handle JSON files\n",
    "import requests # library to handle requests\n",
    "from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:3: FutureWarning: pandas.io.json.json_normalize is deprecated, use pandas.json_normalize instead\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>categories</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lawrence Park Ravine</td>\n",
       "      <td>Park</td>\n",
       "      <td>43.726963</td>\n",
       "      <td>-79.394382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Zodiac Swim School</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>43.728532</td>\n",
       "      <td>-79.382860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TTC Bus #162 - Lawrence-Donway</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>43.728026</td>\n",
       "      <td>-79.382805</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             name   categories        lat        lng\n",
       "0            Lawrence Park Ravine         Park  43.726963 -79.394382\n",
       "1              Zodiac Swim School  Swim School  43.728532 -79.382860\n",
       "2  TTC Bus #162 - Lawrence-Donway     Bus Line  43.728026 -79.382805"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "venues = results['response']['groups'][0]['items']\n",
    "    \n",
    "nearby_venues = json_normalize(venues) # flatten JSON\n",
    "\n",
    "# filter columns\n",
    "filtered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']\n",
    "nearby_venues =nearby_venues.loc[:, filtered_columns]\n",
    "\n",
    "# filter the category for each row\n",
    "nearby_venues['venue.categories'] = nearby_venues.apply(get_category_type, axis=1)\n",
    "\n",
    "# clean columns\n",
    "nearby_venues.columns = [col.split(\".\")[-1] for col in nearby_venues.columns]\n",
    "\n",
    "nearby_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 venues were returned by Foursquare.\n"
     ]
    }
   ],
   "source": [
    "#venues returned\n",
    "print('{} venues were returned by Foursquare.'.format(nearby_venues.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore all Neighborhoods in Central Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getNearbyVenues(names, latitudes, longitudes, radius=500):\n",
    "    \n",
    "    venues_list=[]\n",
    "    for name, lat, lng in zip(names, latitudes, longitudes):\n",
    "        print(name)\n",
    "            \n",
    "        # create the API request URL\n",
    "        url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(\n",
    "            CLIENT_ID, \n",
    "            CLIENT_SECRET, \n",
    "            VERSION, \n",
    "            lat, \n",
    "            lng, \n",
    "            radius, \n",
    "            LIMIT)\n",
    "            \n",
    "        # make the GET request\n",
    "        results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n",
    "        \n",
    "        # return only relevant information for each nearby venue\n",
    "        venues_list.append([(\n",
    "            name, \n",
    "            lat, \n",
    "            lng, \n",
    "            v['venue']['name'], \n",
    "            v['venue']['location']['lat'], \n",
    "            v['venue']['location']['lng'],  \n",
    "            v['venue']['categories'][0]['name']) for v in results])\n",
    "\n",
    "    nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])\n",
    "    nearby_venues.columns = ['Neighborhood', \n",
    "                  'Neighborhood Latitude', \n",
    "                  'Neighborhood Longitude', \n",
    "                  'Venue', \n",
    "                  'Venue Latitude', \n",
    "                  'Venue Longitude', \n",
    "                  'Venue Category']\n",
    "    \n",
    "    return(nearby_venues)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now write the code to run the above function on each neighborhood and create a new dataframe called central_toronto_venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lawrence Park\n",
      "Davisville North\n",
      "North Toronto West, Lawrence Park\n",
      "Davisville\n",
      "Moore Park, Summerhill East\n",
      "Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park\n",
      "Roselawn\n",
      "Forest Hill North & West, Forest Hill Road Park\n",
      "The Annex, North Midtown, Yorkville\n"
     ]
    }
   ],
   "source": [
    "# type your answer here\n",
    "central_toronto_venues = getNearbyVenues(names=central_to_data['Neighbourhood'],\n",
    "                                   latitudes=central_to_data['Latitude'],\n",
    "                                   longitudes=central_to_data['Longitude']\n",
    "                                  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(104, 7)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>Lawrence Park Ravine</td>\n",
       "      <td>43.726963</td>\n",
       "      <td>-79.394382</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>Zodiac Swim School</td>\n",
       "      <td>43.728532</td>\n",
       "      <td>-79.382860</td>\n",
       "      <td>Swim School</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>TTC Bus #162 - Lawrence-Donway</td>\n",
       "      <td>43.728026</td>\n",
       "      <td>-79.382805</td>\n",
       "      <td>Bus Line</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>Homeway Restaurant &amp; Brunch</td>\n",
       "      <td>43.712641</td>\n",
       "      <td>-79.391557</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>Sherwood Park</td>\n",
       "      <td>43.716551</td>\n",
       "      <td>-79.387776</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Neighborhood  Neighborhood Latitude  Neighborhood Longitude  \\\n",
       "0     Lawrence Park              43.728020              -79.388790   \n",
       "1     Lawrence Park              43.728020              -79.388790   \n",
       "2     Lawrence Park              43.728020              -79.388790   \n",
       "3  Davisville North              43.712751              -79.390197   \n",
       "4  Davisville North              43.712751              -79.390197   \n",
       "\n",
       "                            Venue  Venue Latitude  Venue Longitude  \\\n",
       "0            Lawrence Park Ravine       43.726963       -79.394382   \n",
       "1              Zodiac Swim School       43.728532       -79.382860   \n",
       "2  TTC Bus #162 - Lawrence-Donway       43.728026       -79.382805   \n",
       "3     Homeway Restaurant & Brunch       43.712641       -79.391557   \n",
       "4                   Sherwood Park       43.716551       -79.387776   \n",
       "\n",
       "   Venue Category  \n",
       "0            Park  \n",
       "1     Swim School  \n",
       "2        Bus Line  \n",
       "3  Breakfast Spot  \n",
       "4            Park  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(central_toronto_venues.shape)\n",
    "central_toronto_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neighborhood</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Davisville</th>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Davisville North</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forest Hill North &amp; West, Forest Hill Road Park</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lawrence Park</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moore Park, Summerhill East</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Toronto West, Lawrence Park</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roselawn</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Annex, North Midtown, Yorkville</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Neighborhood Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Davisville                                                             33   \n",
       "Davisville North                                                        9   \n",
       "Forest Hill North & West, Forest Hill Road Park                         4   \n",
       "Lawrence Park                                                           3   \n",
       "Moore Park, Summerhill East                                             2   \n",
       "North Toronto West, Lawrence Park                                      18   \n",
       "Roselawn                                                                2   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...                     14   \n",
       "The Annex, North Midtown, Yorkville                                    19   \n",
       "\n",
       "                                                    Neighborhood Longitude  \\\n",
       "Neighborhood                                                                 \n",
       "Davisville                                                              33   \n",
       "Davisville North                                                         9   \n",
       "Forest Hill North & West, Forest Hill Road Park                          4   \n",
       "Lawrence Park                                                            3   \n",
       "Moore Park, Summerhill East                                              2   \n",
       "North Toronto West, Lawrence Park                                       18   \n",
       "Roselawn                                                                 2   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...                      14   \n",
       "The Annex, North Midtown, Yorkville                                     19   \n",
       "\n",
       "                                                    Venue  Venue Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Davisville                                             33              33   \n",
       "Davisville North                                        9               9   \n",
       "Forest Hill North & West, Forest Hill Road Park         4               4   \n",
       "Lawrence Park                                           3               3   \n",
       "Moore Park, Summerhill East                             2               2   \n",
       "North Toronto West, Lawrence Park                      18              18   \n",
       "Roselawn                                                2               2   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...     14              14   \n",
       "The Annex, North Midtown, Yorkville                    19              19   \n",
       "\n",
       "                                                    Venue Longitude  \\\n",
       "Neighborhood                                                          \n",
       "Davisville                                                       33   \n",
       "Davisville North                                                  9   \n",
       "Forest Hill North & West, Forest Hill Road Park                   4   \n",
       "Lawrence Park                                                     3   \n",
       "Moore Park, Summerhill East                                       2   \n",
       "North Toronto West, Lawrence Park                                18   \n",
       "Roselawn                                                          2   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...               14   \n",
       "The Annex, North Midtown, Yorkville                              19   \n",
       "\n",
       "                                                    Venue Category  \n",
       "Neighborhood                                                        \n",
       "Davisville                                                      33  \n",
       "Davisville North                                                 9  \n",
       "Forest Hill North & West, Forest Hill Road Park                  4  \n",
       "Lawrence Park                                                    3  \n",
       "Moore Park, Summerhill East                                      2  \n",
       "North Toronto West, Lawrence Park                               18  \n",
       "Roselawn                                                         2  \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...              14  \n",
       "The Annex, North Midtown, Yorkville                             19  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#How many venue for Neighbourhood\n",
    "central_toronto_venues.groupby('Neighborhood').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 60 uniques categories.\n"
     ]
    }
   ],
   "source": [
    "#Check the unique venues\n",
    "\n",
    "print('There are {} uniques categories.'.format(len(central_toronto_venues['Venue Category'].unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3 Analyze Each Neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Café</th>\n",
       "      <th>...</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Trail</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>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>Lawrence Park</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>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>1</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>Lawrence Park</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <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>Davisville North</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <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>Davisville North</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>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 × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Neighborhood  American Restaurant  BBQ Joint  Bagel Shop  Bank  \\\n",
       "0     Lawrence Park                    0          0           0     0   \n",
       "1     Lawrence Park                    0          0           0     0   \n",
       "2     Lawrence Park                    0          0           0     0   \n",
       "3  Davisville North                    0          0           0     0   \n",
       "4  Davisville North                    0          0           0     0   \n",
       "\n",
       "   Breakfast Spot  Brewery  Burger Joint  Bus Line  Café  ...  Spa  \\\n",
       "0               0        0             0         0     0  ...    0   \n",
       "1               0        0             0         0     0  ...    0   \n",
       "2               0        0             0         1     0  ...    0   \n",
       "3               1        0             0         0     0  ...    0   \n",
       "4               0        0             0         0     0  ...    0   \n",
       "\n",
       "   Sporting Goods Shop  Supermarket  Sushi Restaurant  Swim School  \\\n",
       "0                    0            0                 0            0   \n",
       "1                    0            0                 0            1   \n",
       "2                    0            0                 0            0   \n",
       "3                    0            0                 0            0   \n",
       "4                    0            0                 0            0   \n",
       "\n",
       "   Thai Restaurant  Toy / Game Store  Trail  Vietnamese Restaurant  \\\n",
       "0                0                 0      0                      0   \n",
       "1                0                 0      0                      0   \n",
       "2                0                 0      0                      0   \n",
       "3                0                 0      0                      0   \n",
       "4                0                 0      0                      0   \n",
       "\n",
       "   Yoga Studio  \n",
       "0            0  \n",
       "1            0  \n",
       "2            0  \n",
       "3            0  \n",
       "4            0  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "central_toronto_onehot = pd.get_dummies(central_toronto_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "central_toronto_onehot['Neighborhood'] = central_toronto_venues['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [central_toronto_onehot.columns[-1]] + list(central_toronto_onehot.columns[:-1])\n",
    "central_toronto_onehot = central_toronto_onehot[fixed_columns]\n",
    "\n",
    "central_toronto_onehot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(104, 61)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check the size of the dataframe \n",
    "central_toronto_onehot.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Café</th>\n",
       "      <th>...</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Trail</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</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>0.030303</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.060606</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.060606</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</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>0.111111</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Forest Hill North &amp; West, Forest Hill Road 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>0.000000</td>\n",
       "      <td>0.000000</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>0.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</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>0.000000</td>\n",
       "      <td>0.333333</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>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</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>0.000000</td>\n",
       "      <td>0.000000</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>0.50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.055556</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>0.055556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.055556</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",
       "      <td>0.055556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</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>0.000000</td>\n",
       "      <td>0.000000</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>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Summerhill West, Rathnelly, South Hill, Forest...</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>0.071429</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>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.157895</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>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood  American Restaurant  \\\n",
       "0                                         Davisville             0.000000   \n",
       "1                                   Davisville North             0.000000   \n",
       "2    Forest Hill North & West, Forest Hill Road Park             0.000000   \n",
       "3                                      Lawrence Park             0.000000   \n",
       "4                        Moore Park, Summerhill East             0.000000   \n",
       "5                  North Toronto West, Lawrence Park             0.000000   \n",
       "6                                           Roselawn             0.000000   \n",
       "7  Summerhill West, Rathnelly, South Hill, Forest...             0.071429   \n",
       "8                The Annex, North Midtown, Yorkville             0.000000   \n",
       "\n",
       "   BBQ Joint  Bagel Shop      Bank  Breakfast Spot   Brewery  Burger Joint  \\\n",
       "0   0.000000    0.000000  0.000000        0.000000  0.030303      0.000000   \n",
       "1   0.000000    0.000000  0.000000        0.111111  0.000000      0.000000   \n",
       "2   0.000000    0.000000  0.000000        0.000000  0.000000      0.000000   \n",
       "3   0.000000    0.000000  0.000000        0.000000  0.000000      0.000000   \n",
       "4   0.000000    0.000000  0.000000        0.000000  0.000000      0.000000   \n",
       "5   0.000000    0.055556  0.000000        0.000000  0.000000      0.000000   \n",
       "6   0.000000    0.000000  0.000000        0.000000  0.000000      0.000000   \n",
       "7   0.000000    0.071429  0.071429        0.000000  0.000000      0.000000   \n",
       "8   0.052632    0.000000  0.000000        0.000000  0.000000      0.052632   \n",
       "\n",
       "   Bus Line      Café  ...       Spa  Sporting Goods Shop  Supermarket  \\\n",
       "0  0.000000  0.060606  ...  0.000000             0.000000     0.000000   \n",
       "1  0.000000  0.000000  ...  0.000000             0.000000     0.000000   \n",
       "2  0.000000  0.000000  ...  0.000000             0.000000     0.000000   \n",
       "3  0.333333  0.000000  ...  0.000000             0.000000     0.000000   \n",
       "4  0.000000  0.000000  ...  0.000000             0.000000     0.000000   \n",
       "5  0.000000  0.055556  ...  0.055556             0.055556     0.000000   \n",
       "6  0.000000  0.000000  ...  0.000000             0.000000     0.000000   \n",
       "7  0.000000  0.000000  ...  0.000000             0.000000     0.071429   \n",
       "8  0.000000  0.157895  ...  0.000000             0.000000     0.000000   \n",
       "\n",
       "   Sushi Restaurant  Swim School  Thai Restaurant  Toy / Game Store  Trail  \\\n",
       "0          0.060606     0.000000         0.030303          0.030303   0.00   \n",
       "1          0.000000     0.000000         0.000000          0.000000   0.00   \n",
       "2          0.250000     0.000000         0.000000          0.000000   0.25   \n",
       "3          0.000000     0.333333         0.000000          0.000000   0.00   \n",
       "4          0.000000     0.000000         0.000000          0.000000   0.50   \n",
       "5          0.000000     0.000000         0.000000          0.000000   0.00   \n",
       "6          0.000000     0.000000         0.000000          0.000000   0.00   \n",
       "7          0.071429     0.000000         0.000000          0.000000   0.00   \n",
       "8          0.000000     0.000000         0.000000          0.000000   0.00   \n",
       "\n",
       "   Vietnamese Restaurant  Yoga Studio  \n",
       "0               0.000000     0.000000  \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",
       "5               0.000000     0.055556  \n",
       "6               0.000000     0.000000  \n",
       "7               0.071429     0.000000  \n",
       "8               0.000000     0.000000  \n",
       "\n",
       "[9 rows x 61 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_toronto_grouped = central_toronto_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "central_toronto_grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 61)"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#New size\n",
    "central_toronto_grouped.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's print each neighborhood along with the top 5 most common venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----Davisville----\n",
      "                venue  freq\n",
      "0         Pizza Place  0.09\n",
      "1        Dessert Shop  0.09\n",
      "2      Sandwich Place  0.09\n",
      "3  Italian Restaurant  0.06\n",
      "4                 Gym  0.06\n",
      "\n",
      "\n",
      "----Davisville North----\n",
      "                  venue  freq\n",
      "0                 Hotel  0.11\n",
      "1          Dance Studio  0.11\n",
      "2  Gym / Fitness Center  0.11\n",
      "3                  Park  0.11\n",
      "4     Food & Drink Shop  0.11\n",
      "\n",
      "\n",
      "----Forest Hill North & West, Forest Hill Road Park----\n",
      "                 venue  freq\n",
      "0                Trail  0.25\n",
      "1        Jewelry Store  0.25\n",
      "2     Sushi Restaurant  0.25\n",
      "3                 Park  0.25\n",
      "4  American Restaurant  0.00\n",
      "\n",
      "\n",
      "----Lawrence Park----\n",
      "                 venue  freq\n",
      "0          Swim School  0.33\n",
      "1             Bus Line  0.33\n",
      "2                 Park  0.33\n",
      "3  American Restaurant  0.00\n",
      "4                  Pub  0.00\n",
      "\n",
      "\n",
      "----Moore Park, Summerhill East----\n",
      "                 venue  freq\n",
      "0           Playground   0.5\n",
      "1                Trail   0.5\n",
      "2  American Restaurant   0.0\n",
      "3    Indian Restaurant   0.0\n",
      "4     Indoor Play Area   0.0\n",
      "\n",
      "\n",
      "----North Toronto West, Lawrence Park----\n",
      "                  venue  freq\n",
      "0           Coffee Shop  0.11\n",
      "1        Clothing Store  0.11\n",
      "2            Restaurant  0.06\n",
      "3    Salon / Barbershop  0.06\n",
      "4  Fast Food Restaurant  0.06\n",
      "\n",
      "\n",
      "----Roselawn----\n",
      "                 venue  freq\n",
      "0               Garden   0.5\n",
      "1          Music Venue   0.5\n",
      "2  American Restaurant   0.0\n",
      "3       Ice Cream Shop   0.0\n",
      "4     Indoor Play Area   0.0\n",
      "\n",
      "\n",
      "----Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.14\n",
      "1  American Restaurant  0.07\n",
      "2         Liquor Store  0.07\n",
      "3                  Pub  0.07\n",
      "4           Restaurant  0.07\n",
      "\n",
      "\n",
      "----The Annex, North Midtown, Yorkville----\n",
      "               venue  freq\n",
      "0               Café  0.16\n",
      "1     Sandwich Place  0.16\n",
      "2        Coffee Shop  0.11\n",
      "3  Indian Restaurant  0.05\n",
      "4           Pharmacy  0.05\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "num_top_venues = 5\n",
    "\n",
    "for hood in central_toronto_grouped['Neighborhood']:\n",
    "    print(\"----\"+hood+\"----\")\n",
    "    temp = central_toronto_grouped[central_toronto_grouped['Neighborhood'] == hood].T.reset_index()\n",
    "    temp.columns = ['venue','freq']\n",
    "    temp = temp.iloc[1:]\n",
    "    temp['freq'] = temp['freq'].astype(float)\n",
    "    temp = temp.round({'freq': 2})\n",
    "    print(temp.sort_values('freq', ascending=False).reset_index(drop=True).head(num_top_venues))\n",
    "    print('\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Convert the previous info in a Pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Descending the venues in descending order\n",
    "def return_most_common_venues(row, num_top_venues):\n",
    "    row_categories = row.iloc[1:]\n",
    "    row_categories_sorted = row_categories.sort_values(ascending=False)\n",
    "    \n",
    "    return row_categories_sorted.index.values[0:num_top_venues]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Dataframe with top 10 venues per Neiborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Davisville</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Park</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Garden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Forest Hill North &amp; West, Forest Hill Road Park</td>\n",
       "      <td>Park</td>\n",
       "      <td>Jewelry Store</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Park</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Neighborhood 1st Most Common Venue  \\\n",
       "0                                       Davisville          Dessert Shop   \n",
       "1                                 Davisville North  Gym / Fitness Center   \n",
       "2  Forest Hill North & West, Forest Hill Road Park                  Park   \n",
       "3                                    Lawrence Park           Swim School   \n",
       "4                      Moore Park, Summerhill East            Playground   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0           Pizza Place        Sandwich Place    Italian Restaurant   \n",
       "1                  Park      Department Store          Dance Studio   \n",
       "2         Jewelry Store                 Trail      Sushi Restaurant   \n",
       "3              Bus Line                  Park           Yoga Studio   \n",
       "4                 Trail      Department Store      Greek Restaurant   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0           Coffee Shop      Sushi Restaurant                  Café   \n",
       "1        Sandwich Place     Food & Drink Shop               Dog Run   \n",
       "2                 Diner               Dog Run            Donut Shop   \n",
       "3                 Diner      Greek Restaurant          Gourmet Shop   \n",
       "4          Gourmet Shop           Gas Station                Garden   \n",
       "\n",
       "    8th Most Common Venue 9th Most Common Venue  10th Most Common Venue  \n",
       "0                     Gym        Farmers Market       Indian Restaurant  \n",
       "1          Breakfast Spot                 Hotel                  Garden  \n",
       "2          Farmers Market  Fast Food Restaurant             Yoga Studio  \n",
       "3             Gas Station                Garden  Furniture / Home Store  \n",
       "4  Furniture / Home Store   Fried Chicken Joint       Food & Drink Shop  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_top_venues = 10\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for ind in np.arange(num_top_venues):\n",
    "    try:\n",
    "        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n",
    "    except:\n",
    "        columns.append('{}th Most Common Venue'.format(ind+1))\n",
    "\n",
    "# create a new dataframe\n",
    "neighborhoods_venues_sorted = pd.DataFrame(columns=columns)\n",
    "neighborhoods_venues_sorted['Neighborhood'] = central_toronto_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(central_toronto_grouped.shape[0]):\n",
    "    neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(central_toronto_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "neighborhoods_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.4 Clustering "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import k-means from clustering stage\n",
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 3, 4, 2, 0, 1, 0, 0], dtype=int32)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 5\n",
    "\n",
    "central_toronto_grouped_clustering = central_toronto_grouped.drop('Neighborhood', 1)\n",
    "\n",
    "# run k-means clustering\n",
    "kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(central_toronto_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "kmeans.labels_[0:10] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's create a new dataframe that includes the cluster as well as the top 10 venues for each neighborhood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M4N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>4</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Park</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>0</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Park</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Garden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M4R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>43.715383</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4S</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "      <td>43.704324</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>0</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M4T</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>43.689574</td>\n",
       "      <td>-79.383160</td>\n",
       "      <td>2</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code          Borough                      Neighbourhood   Latitude  \\\n",
       "0         M4N  Central Toronto                      Lawrence Park  43.728020   \n",
       "1         M4P  Central Toronto                   Davisville North  43.712751   \n",
       "2         M4R  Central Toronto  North Toronto West, Lawrence Park  43.715383   \n",
       "3         M4S  Central Toronto                         Davisville  43.704324   \n",
       "4         M4T  Central Toronto        Moore Park, Summerhill East  43.689574   \n",
       "\n",
       "   Longitude  Cluster Labels 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "0 -79.388790               4           Swim School              Bus Line   \n",
       "1 -79.390197               0  Gym / Fitness Center                  Park   \n",
       "2 -79.405678               0           Coffee Shop        Clothing Store   \n",
       "3 -79.388790               0          Dessert Shop           Pizza Place   \n",
       "4 -79.383160               2            Playground                 Trail   \n",
       "\n",
       "  3rd Most Common Venue   4th Most Common Venue 5th Most Common Venue  \\\n",
       "0                  Park             Yoga Studio                 Diner   \n",
       "1      Department Store            Dance Studio        Sandwich Place   \n",
       "2    Salon / Barbershop  Furniture / Home Store        Ice Cream Shop   \n",
       "3        Sandwich Place      Italian Restaurant           Coffee Shop   \n",
       "4      Department Store        Greek Restaurant          Gourmet Shop   \n",
       "\n",
       "  6th Most Common Venue 7th Most Common Venue   8th Most Common Venue  \\\n",
       "0      Greek Restaurant          Gourmet Shop             Gas Station   \n",
       "1     Food & Drink Shop               Dog Run          Breakfast Spot   \n",
       "2  Fast Food Restaurant                 Diner      Mexican Restaurant   \n",
       "3      Sushi Restaurant                  Café                     Gym   \n",
       "4           Gas Station                Garden  Furniture / Home Store   \n",
       "\n",
       "  9th Most Common Venue  10th Most Common Venue  \n",
       "0                Garden  Furniture / Home Store  \n",
       "1                 Hotel                  Garden  \n",
       "2                  Park      Chinese Restaurant  \n",
       "3        Farmers Market       Indian Restaurant  \n",
       "4   Fried Chicken Joint       Food & Drink Shop  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# add clustering labels\n",
    "#neighborhoods_venues_sorted.insert(0, 'Cluster Labels', kmeans.labels_)\n",
    "\n",
    "central_toronto_merged = central_to_data\n",
    "\n",
    "#merge manhattan_grouped with manhattan_data to add latitude/longitude for each neighborhood\n",
    "central_toronto_merged = central_toronto_merged.join(neighborhoods_venues_sorted.set_index('Neighborhood'), on='Neighbourhood')\n",
    "\n",
    "central_toronto_merged.head() # check the last columns!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualise the cluster "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "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 src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS = false; L_NO_TOUCH = false; L_DISABLE_3D = false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.js"></script>
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.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@1.2.0/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://rawgit.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>
    
            <style> #map_23b1e44cfa754cceb6271dcfc2db83f7 {
                position : relative;
                width : 100.0%;
                height: 100.0%;
                left: 0.0%;
                top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_23b1e44cfa754cceb6271dcfc2db83f7" ></div>
        
</body>
<script>    
    

            
                var bounds = null;
            

            var map_23b1e44cfa754cceb6271dcfc2db83f7 = L.map(
                                  'map_23b1e44cfa754cceb6271dcfc2db83f7',
                                  {center: [43.6534817,-79.3839347],
                                  zoom: 11,
                                  maxBounds: bounds,
                                  layers: [],
                                  worldCopyJump: false,
                                  crs: L.CRS.EPSG3857
                                 });
            
        
    
            var tile_layer_870c1617467541b5ba1839833a10dd7e = L.tileLayer(
                'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
                {
  "attribution": null,
  "detectRetina": false,
  "maxZoom": 18,
  "minZoom": 1,
  "noWrap": false,
  "subdomains": "abc"
}
                ).addTo(map_23b1e44cfa754cceb6271dcfc2db83f7);
        
    
            var circle_marker_36a63f29c5ec4fadade964314abb7dc3 = L.circleMarker(
                [43.7280205,-79.3887901],
                {
  "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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_163820d518f5491783a2ffc34d29d6dd = L.popup({maxWidth: '300'});

            
                var html_0ab547b75c3a42b19b25a549a4a074bf = $('<div id="html_0ab547b75c3a42b19b25a549a4a074bf" style="width: 100.0%; height: 100.0%;">Lawrence Park Cluster 4</div>')[0];
                popup_163820d518f5491783a2ffc34d29d6dd.setContent(html_0ab547b75c3a42b19b25a549a4a074bf);
            

            circle_marker_36a63f29c5ec4fadade964314abb7dc3.bindPopup(popup_163820d518f5491783a2ffc34d29d6dd);

            
        
    
            var circle_marker_0900b3688af04967b0ef03599b9458eb = 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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_fc7a474bbd2c410dba588551a2663ae9 = L.popup({maxWidth: '300'});

            
                var html_9af8515d82814a81b26114fff7846fa2 = $('<div id="html_9af8515d82814a81b26114fff7846fa2" style="width: 100.0%; height: 100.0%;">Davisville North Cluster 0</div>')[0];
                popup_fc7a474bbd2c410dba588551a2663ae9.setContent(html_9af8515d82814a81b26114fff7846fa2);
            

            circle_marker_0900b3688af04967b0ef03599b9458eb.bindPopup(popup_fc7a474bbd2c410dba588551a2663ae9);

            
        
    
            var circle_marker_3767be3992464df9a1d1a627a5c2ce91 = 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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_3121322d47384e07bfd616fc9e1f19b9 = L.popup({maxWidth: '300'});

            
                var html_80026495275f4a6480b04154cb4f82bb = $('<div id="html_80026495275f4a6480b04154cb4f82bb" style="width: 100.0%; height: 100.0%;">North Toronto West, Lawrence Park Cluster 0</div>')[0];
                popup_3121322d47384e07bfd616fc9e1f19b9.setContent(html_80026495275f4a6480b04154cb4f82bb);
            

            circle_marker_3767be3992464df9a1d1a627a5c2ce91.bindPopup(popup_3121322d47384e07bfd616fc9e1f19b9);

            
        
    
            var circle_marker_5dda67a592a54086a86907ded551a453 = 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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_aa0aa02ffff6434781599562fb8b5fb0 = L.popup({maxWidth: '300'});

            
                var html_3d4fba5faef14f8cb6ff154fbe57816c = $('<div id="html_3d4fba5faef14f8cb6ff154fbe57816c" style="width: 100.0%; height: 100.0%;">Davisville Cluster 0</div>')[0];
                popup_aa0aa02ffff6434781599562fb8b5fb0.setContent(html_3d4fba5faef14f8cb6ff154fbe57816c);
            

            circle_marker_5dda67a592a54086a86907ded551a453.bindPopup(popup_aa0aa02ffff6434781599562fb8b5fb0);

            
        
    
            var circle_marker_c475ce01f0fa40979349f49631cf22bd = L.circleMarker(
                [43.6895743,-79.38315990000001],
                {
  "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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_2e1b024a10b440459e0294e5eab86ac6 = L.popup({maxWidth: '300'});

            
                var html_5b73bbf69eeb44c4ab7399c8a5753c8a = $('<div id="html_5b73bbf69eeb44c4ab7399c8a5753c8a" style="width: 100.0%; height: 100.0%;">Moore Park, Summerhill East Cluster 2</div>')[0];
                popup_2e1b024a10b440459e0294e5eab86ac6.setContent(html_5b73bbf69eeb44c4ab7399c8a5753c8a);
            

            circle_marker_c475ce01f0fa40979349f49631cf22bd.bindPopup(popup_2e1b024a10b440459e0294e5eab86ac6);

            
        
    
            var circle_marker_f76911889ec84ad7b6707c98d1bfe969 = 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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_7a21ca6de2ea4de4958ac3098dccbf82 = L.popup({maxWidth: '300'});

            
                var html_230a4bf8c84047799d36401a30a847c7 = $('<div id="html_230a4bf8c84047799d36401a30a847c7" style="width: 100.0%; height: 100.0%;">Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park Cluster 0</div>')[0];
                popup_7a21ca6de2ea4de4958ac3098dccbf82.setContent(html_230a4bf8c84047799d36401a30a847c7);
            

            circle_marker_f76911889ec84ad7b6707c98d1bfe969.bindPopup(popup_7a21ca6de2ea4de4958ac3098dccbf82);

            
        
    
            var circle_marker_e2a2fa9770ee4da7b6a3822cafe29b8e = L.circleMarker(
                [43.7116948,-79.41693559999999],
                {
  "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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_bf882ed7f4574220a21fca55814b1d38 = L.popup({maxWidth: '300'});

            
                var html_ae7909a05f4c43c1be7a86a2a8d8e040 = $('<div id="html_ae7909a05f4c43c1be7a86a2a8d8e040" style="width: 100.0%; height: 100.0%;">Roselawn Cluster 1</div>')[0];
                popup_bf882ed7f4574220a21fca55814b1d38.setContent(html_ae7909a05f4c43c1be7a86a2a8d8e040);
            

            circle_marker_e2a2fa9770ee4da7b6a3822cafe29b8e.bindPopup(popup_bf882ed7f4574220a21fca55814b1d38);

            
        
    
            var circle_marker_0c99b410b27f4cc9bf5537c0af1a8e84 = L.circleMarker(
                [43.6969476,-79.41130720000001],
                {
  "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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_2718b4da7f2348c7aaac7bb085dc1a6a = L.popup({maxWidth: '300'});

            
                var html_4fba00e8e1224ef594fe5e5c451bd1d2 = $('<div id="html_4fba00e8e1224ef594fe5e5c451bd1d2" style="width: 100.0%; height: 100.0%;">Forest Hill North &amp; West, Forest Hill Road Park Cluster 3</div>')[0];
                popup_2718b4da7f2348c7aaac7bb085dc1a6a.setContent(html_4fba00e8e1224ef594fe5e5c451bd1d2);
            

            circle_marker_0c99b410b27f4cc9bf5537c0af1a8e84.bindPopup(popup_2718b4da7f2348c7aaac7bb085dc1a6a);

            
        
    
            var circle_marker_9bfbe4ee134b4577aa81d432552e4d0b = 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_23b1e44cfa754cceb6271dcfc2db83f7);
            
    
            var popup_558cbf7bed6345a7bc5406ca2cc49cf8 = L.popup({maxWidth: '300'});

            
                var html_59cfc65254fe4f7b8f512243acb76046 = $('<div id="html_59cfc65254fe4f7b8f512243acb76046" style="width: 100.0%; height: 100.0%;">The Annex, North Midtown, Yorkville Cluster 0</div>')[0];
                popup_558cbf7bed6345a7bc5406ca2cc49cf8.setContent(html_59cfc65254fe4f7b8f512243acb76046);
            

            circle_marker_9bfbe4ee134b4577aa81d432552e4d0b.bindPopup(popup_558cbf7bed6345a7bc5406ca2cc49cf8);

            
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fb19657d6d8>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map\n",
    "map_clusters = folium.Map(location=[latitude, longitude], zoom_start=11)\n",
    "\n",
    "# set color scheme for the clusters\n",
    "x = np.arange(kclusters)\n",
    "ys = [i + x + (i*x)**2 for i in range(kclusters)]\n",
    "colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\n",
    "rainbow = [colors.rgb2hex(i) for i in colors_array]\n",
    "\n",
    "# add markers to the map\n",
    "markers_colors = []\n",
    "for lat, lon, poi, cluster in zip(central_toronto_merged['Latitude'], central_toronto_merged['Longitude'], central_toronto_merged['Neighbourhood'], central_toronto_merged['Cluster Labels']):\n",
    "    label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lon],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color=rainbow[cluster-1],\n",
    "        fill=True,\n",
    "        fill_color=rainbow[cluster-1],\n",
    "        fill_opacity=0.7).add_to(map_clusters)\n",
    "       \n",
    "map_clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.5 Examine the Cluster "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 0: Hang-out Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Park</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Garden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Pub</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Bank</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>History Museum</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Borough  Cluster Labels 1st Most Common Venue  \\\n",
       "1  Central Toronto               0  Gym / Fitness Center   \n",
       "2  Central Toronto               0           Coffee Shop   \n",
       "3  Central Toronto               0          Dessert Shop   \n",
       "5  Central Toronto               0           Coffee Shop   \n",
       "8  Central Toronto               0        Sandwich Place   \n",
       "\n",
       "  2nd Most Common Venue  3rd Most Common Venue   4th Most Common Venue  \\\n",
       "1                  Park       Department Store            Dance Studio   \n",
       "2        Clothing Store     Salon / Barbershop  Furniture / Home Store   \n",
       "3           Pizza Place         Sandwich Place      Italian Restaurant   \n",
       "5            Restaurant  Vietnamese Restaurant     Fried Chicken Joint   \n",
       "8                  Café            Coffee Shop          History Museum   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "1        Sandwich Place     Food & Drink Shop               Dog Run   \n",
       "2        Ice Cream Shop  Fast Food Restaurant                 Diner   \n",
       "3           Coffee Shop      Sushi Restaurant                  Café   \n",
       "5    Light Rail Station          Liquor Store           Pizza Place   \n",
       "8     Indian Restaurant            Donut Shop          Liquor Store   \n",
       "\n",
       "       8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "1             Breakfast Spot                 Hotel                 Garden  \n",
       "2         Mexican Restaurant                  Park     Chinese Restaurant  \n",
       "3                        Gym        Farmers Market      Indian Restaurant  \n",
       "5                        Pub   American Restaurant                   Bank  \n",
       "8  Middle Eastern Restaurant                  Park            Pizza Place  "
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_toronto_merged.loc[central_toronto_merged['Cluster Labels'] == 0, central_toronto_merged.columns[[1] + list(range(5, central_toronto_merged.shape[1]))]]\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 1: Quite Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>1</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Music Venue</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Borough  Cluster Labels 1st Most Common Venue  \\\n",
       "6  Central Toronto               1                Garden   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "6           Music Venue           Yoga Studio  Gym / Fitness Center   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "6      Greek Restaurant          Gourmet Shop           Gas Station   \n",
       "\n",
       "    8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "6  Furniture / Home Store   Fried Chicken Joint      Food & Drink Shop  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_toronto_merged.loc[central_toronto_merged['Cluster Labels'] == 1, central_toronto_merged.columns[[1] + list(range(5, central_toronto_merged.shape[1]))]]\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 2: Residential Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>2</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Borough  Cluster Labels 1st Most Common Venue  \\\n",
       "4  Central Toronto               2            Playground   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "4                 Trail      Department Store      Greek Restaurant   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "4          Gourmet Shop           Gas Station                Garden   \n",
       "\n",
       "    8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "4  Furniture / Home Store   Fried Chicken Joint      Food & Drink Shop  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_toronto_merged.loc[central_toronto_merged['Cluster Labels'] == 2, central_toronto_merged.columns[[1] + list(range(5, central_toronto_merged.shape[1]))]]\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 3: Quite Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Park</td>\n",
       "      <td>Jewelry Store</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Borough  Cluster Labels 1st Most Common Venue  \\\n",
       "7  Central Toronto               3                  Park   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "7         Jewelry Store                 Trail      Sushi Restaurant   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "7                 Diner               Dog Run            Donut Shop   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "7        Farmers Market  Fast Food Restaurant            Yoga Studio  "
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_toronto_merged.loc[central_toronto_merged['Cluster Labels'] == 3, central_toronto_merged.columns[[1] + list(range(5, central_toronto_merged.shape[1]))]]\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cluster 4: Residential Area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Borough</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Park</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Borough  Cluster Labels 1st Most Common Venue  \\\n",
       "0  Central Toronto               4           Swim School   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0              Bus Line                  Park           Yoga Studio   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0                 Diner      Greek Restaurant          Gourmet Shop   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue  10th Most Common Venue  \n",
       "0           Gas Station                Garden  Furniture / Home Store  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central_toronto_merged.loc[central_toronto_merged['Cluster Labels'] == 4, central_toronto_merged.columns[[1] + list(range(5, central_toronto_merged.shape[1]))]]\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python",
   "language": "python",
   "name": "conda-env-python-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}