Skip to content

Instantly share code, notes, and snippets.

@SonerYldrm

SonerYldrm/Coursera_Canada_PostalCodes.ipynb

Created April 15, 2019 12:41
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save SonerYldrm/b5adcc6ddc51dcc15fcf32833dffc00e to your computer and use it in GitHub Desktop.
Save SonerYldrm/b5adcc6ddc51dcc15fcf32833dffc00e to your computer and use it in GitHub Desktop.
Download ZIP
Created on Cognitive Class Labs
Display the source blob
Display the rendered blob
Raw
Coursera_Canada_PostalCodes.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#import required libraries\n",
"import requests\n",
"import lxml.html as lh\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"url='https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M'\n",
"#Create a handle, page, to handle the contents of the website\n",
"page = requests.get(url)\n",
"#Store the contents of the website under doc\n",
"doc = lh.fromstring(page.content)\n",
"#Parse data that are stored between <tr>..</tr> of HTML\n",
"tr_elements = doc.xpath('//tr')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Check the length of the first 12 rows\n",
"[len(T) for T in tr_elements[:12]]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1:\"Postcode\"\n",
"2:\"Borough\"\n",
"3:\"Neighbourhood\n",
"\"\n"
]
}
],
"source": [
"tr_elements = doc.xpath('//tr')\n",
"#Create empty list\n",
"col=[]\n",
"i=0\n",
"#For each row, store each first element (header) and an empty list\n",
"for t in tr_elements[0]:\n",
" i+=1\n",
" name=t.text_content()\n",
" print('%d:\"%s\"'%(i,name))\n",
" col.append((name,[]))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"294"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(tr_elements)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#Since out first row is the header, data is stored on the second row onwards\n",
"for j in range(1,len(tr_elements)):\n",
" #T is our j'th row\n",
" T=tr_elements[j]\n",
" \n",
" #If row is not of size 3, the //tr data is not from our table \n",
" if len(T)!=3:\n",
" break\n",
" \n",
" #i is the index of our column\n",
" i=0\n",
" \n",
" #Iterate through each element of the row\n",
" for t in T.iterchildren():\n",
" data=t.text_content() \n",
" #Check if row is empty\n",
"\n",
" #Append the data to the empty list of the i'th column\n",
" col[i][1].append(data)\n",
" #Increment i for the next column\n",
" i+=1"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[288, 288, 288]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[len(C) for (title,C) in col]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"#Create a dataframe with exported data\n",
"Dict={title:column for (title,column) in col}\n",
"df=pd.DataFrame(Dict)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"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>Postcode</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\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>M2A</td>\n",
" <td>Not assigned</td>\n",
" <td>Not assigned\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>M3A</td>\n",
" <td>North York</td>\n",
" <td>Parkwoods\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>M4A</td>\n",
" <td>North York</td>\n",
" <td>Victoria Village\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Harbourfront\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Regent Park\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>M6A</td>\n",
" <td>North York</td>\n",
" <td>Lawrence Heights\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>M6A</td>\n",
" <td>North York</td>\n",
" <td>Lawrence Manor\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>M7A</td>\n",
" <td>Queen's Park</td>\n",
" <td>Not assigned\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>M8A</td>\n",
" <td>Not assigned</td>\n",
" <td>Not assigned\\n</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Borough Neighbourhood\\n\n",
"0 M1A Not assigned Not assigned\\n\n",
"1 M2A Not assigned Not assigned\\n\n",
"2 M3A North York Parkwoods\\n\n",
"3 M4A North York Victoria Village\\n\n",
"4 M5A Downtown Toronto Harbourfront\\n\n",
"5 M5A Downtown Toronto Regent Park\\n\n",
"6 M6A North York Lawrence Heights\\n\n",
"7 M6A North York Lawrence Manor\\n\n",
"8 M7A Queen's Park Not assigned\\n\n",
"9 M8A Not assigned Not assigned\\n"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(288, 3)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# Ignore cells with a borough that is Not assigned.\n",
"df_1 = df[df['Borough'] != 'Not assigned'].reset_index()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"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>index</th>\n",
" <th>Postcode</th>\n",
" <th>Borough</th>\n",
" <th>Neighbourhood</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2</td>\n",
" <td>M3A</td>\n",
" <td>North York</td>\n",
" <td>Parkwoods\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3</td>\n",
" <td>M4A</td>\n",
" <td>North York</td>\n",
" <td>Victoria Village\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4</td>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Harbourfront\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5</td>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Regent Park\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>6</td>\n",
" <td>M6A</td>\n",
" <td>North York</td>\n",
" <td>Lawrence Heights\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>7</td>\n",
" <td>M6A</td>\n",
" <td>North York</td>\n",
" <td>Lawrence Manor\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>8</td>\n",
" <td>M7A</td>\n",
" <td>Queen's Park</td>\n",
" <td>Not assigned\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>10</td>\n",
" <td>M9A</td>\n",
" <td>Etobicoke</td>\n",
" <td>Islington Avenue\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>11</td>\n",
" <td>M1B</td>\n",
" <td>Scarborough</td>\n",
" <td>Rouge\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>12</td>\n",
" <td>M1B</td>\n",
" <td>Scarborough</td>\n",
" <td>Malvern\\n</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" index Postcode Borough Neighbourhood\\n\n",
"0 2 M3A North York Parkwoods\\n\n",
"1 3 M4A North York Victoria Village\\n\n",
"2 4 M5A Downtown Toronto Harbourfront\\n\n",
"3 5 M5A Downtown Toronto Regent Park\\n\n",
"4 6 M6A North York Lawrence Heights\\n\n",
"5 7 M6A North York Lawrence Manor\\n\n",
"6 8 M7A Queen's Park Not assigned\\n\n",
"7 10 M9A Etobicoke Islington Avenue\\n\n",
"8 11 M1B Scarborough Rouge\\n\n",
"9 12 M1B Scarborough Malvern\\n"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_1.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"103"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_1['Postcode'].unique().size"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"df_1.columns = ['Drop','Postcode', 'Borough', 'Neighborhood']"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Drop</th>\n",
" <th>Postcode</th>\n",
" <th>Borough</th>\n",
" <th>Neighborhood</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2</td>\n",
" <td>M3A</td>\n",
" <td>North York</td>\n",
" <td>Parkwoods\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3</td>\n",
" <td>M4A</td>\n",
" <td>North York</td>\n",
" <td>Victoria Village\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4</td>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Harbourfront\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5</td>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Regent Park\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>6</td>\n",
" <td>M6A</td>\n",
" <td>North York</td>\n",
" <td>Lawrence Heights\\n</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Drop Postcode Borough Neighborhood\n",
"0 2 M3A North York Parkwoods\\n\n",
"1 3 M4A North York Victoria Village\\n\n",
"2 4 M5A Downtown Toronto Harbourfront\\n\n",
"3 5 M5A Downtown Toronto Regent Park\\n\n",
"4 6 M6A North York Lawrence Heights\\n"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_1.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"df_2 = df_1[['Postcode','Borough','Neighborhood']]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Postcode</th>\n",
" <th>Borough</th>\n",
" <th>Neighborhood</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>M3A</td>\n",
" <td>North York</td>\n",
" <td>Parkwoods\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>M4A</td>\n",
" <td>North York</td>\n",
" <td>Victoria Village\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Harbourfront\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>M5A</td>\n",
" <td>Downtown Toronto</td>\n",
" <td>Regent Park\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>M6A</td>\n",
" <td>North York</td>\n",
" <td>Lawrence Heights\\n</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Borough Neighborhood\n",
"0 M3A North York Parkwoods\\n\n",
"1 M4A North York Victoria Village\\n\n",
"2 M5A Downtown Toronto Harbourfront\\n\n",
"3 M5A Downtown Toronto Regent Park\\n\n",
"4 M6A North York Lawrence Heights\\n"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_2.head()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"df_2 = df_2.groupby(['Postcode','Borough'])['Neighborhood'].apply(', '.join).reset_index()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"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>Postcode</th>\n",
" <th>Borough</th>\n",
" <th>Neighborhood</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>M1B</td>\n",
" <td>Scarborough</td>\n",
" <td>Rouge\\n, Malvern\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>M1C</td>\n",
" <td>Scarborough</td>\n",
" <td>Highland Creek\\n, Rouge Hill\\n, Port Union\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>M1E</td>\n",
" <td>Scarborough</td>\n",
" <td>Guildwood\\n, Morningside\\n, West Hill\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>M1G</td>\n",
" <td>Scarborough</td>\n",
" <td>Woburn\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>M1H</td>\n",
" <td>Scarborough</td>\n",
" <td>Cedarbrae\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>M1J</td>\n",
" <td>Scarborough</td>\n",
" <td>Scarborough Village\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>M1K</td>\n",
" <td>Scarborough</td>\n",
" <td>East Birchmount Park\\n, Ionview\\n, Kennedy Park\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>M1L</td>\n",
" <td>Scarborough</td>\n",
" <td>Clairlea\\n, Golden Mile\\n, Oakridge\\n</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>M1M</td>\n",
" <td>Scarborough</td>\n",
" <td>Cliffcrest\\n, Cliffside\\n, Scarborough Village...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>M1N</td>\n",
" <td>Scarborough</td>\n",
" <td>Birch Cliff\\n, Cliffside West\\n</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Borough Neighborhood\n",
"0 M1B Scarborough Rouge\\n, Malvern\\n\n",
"1 M1C Scarborough Highland Creek\\n, Rouge Hill\\n, Port Union\\n\n",
"2 M1E Scarborough Guildwood\\n, Morningside\\n, West Hill\\n\n",
"3 M1G Scarborough Woburn\\n\n",
"4 M1H Scarborough Cedarbrae\\n\n",
"5 M1J Scarborough Scarborough Village\\n\n",
"6 M1K Scarborough East Birchmount Park\\n, Ionview\\n, Kennedy Park\\n\n",
"7 M1L Scarborough Clairlea\\n, Golden Mile\\n, Oakridge\\n\n",
"8 M1M Scarborough Cliffcrest\\n, Cliffside\\n, Scarborough Village...\n",
"9 M1N Scarborough Birch Cliff\\n, Cliffside West\\n"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_2.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(103, 3)"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_2.shape"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"#Create a dataframe including lotitude and longitude data\n",
"url_coordinates = 'http://cocl.us/Geospatial_data'\n",
"coordinates = pd.read_csv(url_coordinates)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>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": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"coordinates.head()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"#Change the name of column in order to merge with other dataframe\n",
"coordinates.rename(columns={\"Postal Code\":\"Postcode\"}, inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"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>Postcode</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": [
" Postcode 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": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"coordinates.head()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"df_merged = pd.merge(df_2, coordinates, on='Postcode') # Merge two dataframes on Postcode"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Postcode</th>\n",
" <th>Borough</th>\n",
" <th>Neighborhood</th>\n",
" <th>Latitude</th>\n",
" <th>Longitude</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>M1B</td>\n",
" <td>Scarborough</td>\n",
" <td>Rouge\\n, Malvern\\n</td>\n",
" <td>43.806686</td>\n",
" <td>-79.194353</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>M1C</td>\n",
" <td>Scarborough</td>\n",
" <td>Highland Creek\\n, Rouge Hill\\n, Port Union\\n</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\\n, Morningside\\n, West Hill\\n</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\\n</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\\n</td>\n",
" <td>43.773136</td>\n",
" <td>-79.239476</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Borough Neighborhood \\\n",
"0 M1B Scarborough Rouge\\n, Malvern\\n \n",
"1 M1C Scarborough Highland Creek\\n, Rouge Hill\\n, Port Union\\n \n",
"2 M1E Scarborough Guildwood\\n, Morningside\\n, West Hill\\n \n",
"3 M1G Scarborough Woburn\\n \n",
"4 M1H Scarborough Cedarbrae\\n \n",
"\n",
" Latitude Longitude \n",
"0 43.806686 -79.194353 \n",
"1 43.784535 -79.160497 \n",
"2 43.763573 -79.188711 \n",
"3 43.770992 -79.216917 \n",
"4 43.773136 -79.239476 "
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_merged.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Before we start exploring, let's download all the dependencies that we will need."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Libraries imported.\n"
]
}
],
"source": [
"import numpy as np # library to handle data in a vectorized manner\n",
"\n",
"import pandas as pd # library for data analsysis\n",
"pd.set_option('display.max_columns', None)\n",
"pd.set_option('display.max_rows', None)\n",
"\n",
"import json # library to handle JSON files\n",
"\n",
"#!conda install -c conda-forge geopy --yes # uncomment this line if you haven't completed the Foursquare API lab\n",
"from geopy.geocoders import Nominatim # convert an address into latitude and longitude values\n",
"\n",
"import requests # library to handle requests\n",
"from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe\n",
"\n",
"# Matplotlib and associated plotting modules\n",
"import matplotlib.cm as cm\n",
"import matplotlib.colors as colors\n",
"\n",
"# import k-means from clustering stage\n",
"from sklearn.cluster import KMeans\n",
"\n",
"#!conda install -c conda-forge folium=0.5.0 --yes # uncomment this line if you haven't completed the Foursquare API lab\n",
"import folium # map rendering library\n",
"\n",
"print('Libraries imported.')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Use geopy library to get the latitude and longitude values of New York City"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The geograpical coordinate of Toronto are 43.653963, -79.387207.\n"
]
}
],
"source": [
"address = 'Toronto, CA'\n",
"\n",
"geolocator = Nominatim(user_agent=\"toronto_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 New York with neighborhoods superimposed on top."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_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_6568f48dacbc4d47b196db0e807804fb {
                position : relative;
                width : 100.0%;
                height: 100.0%;
                left: 0.0%;
                top: 0.0%;
                }
            </style>
        
</head>
<body>    
    
            <div class="folium-map" id="map_6568f48dacbc4d47b196db0e807804fb" ></div>
        
</body>
<script>    
    

            
                var bounds = null;
            

            var map_6568f48dacbc4d47b196db0e807804fb = L.map(
                                  'map_6568f48dacbc4d47b196db0e807804fb',
                                  {center: [43.653963,-79.387207],
                                  zoom: 10,
                                  maxBounds: bounds,
                                  layers: [],
                                  worldCopyJump: false,
                                  crs: L.CRS.EPSG3857
                                 });
            
        
    
            var tile_layer_ab71bba5ff88431f9b35cb317f53f235 = 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_6568f48dacbc4d47b196db0e807804fb);
        
    
            var circle_marker_f43bc8c70af44612ac83e380295ad23a = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_8a96546c7ae6476f97d8dc3b2ef8dfc9 = L.popup({maxWidth: '300'});

            
                var html_74d6b4ed33f94a638073437e8cae3e90 = $('<div id="html_74d6b4ed33f94a638073437e8cae3e90" style="width: 100.0%; height: 100.0%;">Rouge , Malvern , Scarborough</div>')[0];
                popup_8a96546c7ae6476f97d8dc3b2ef8dfc9.setContent(html_74d6b4ed33f94a638073437e8cae3e90);
            

            circle_marker_f43bc8c70af44612ac83e380295ad23a.bindPopup(popup_8a96546c7ae6476f97d8dc3b2ef8dfc9);

            
        
    
            var circle_marker_f1c4f3070c794ecaa9fae793ea9e5fd2 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_443321c73fa14efe8ddd35cad4b698cd = L.popup({maxWidth: '300'});

            
                var html_66c459dc4e714ab9922c7089599d10ab = $('<div id="html_66c459dc4e714ab9922c7089599d10ab" style="width: 100.0%; height: 100.0%;">Highland Creek , Rouge Hill , Port Union , Scarborough</div>')[0];
                popup_443321c73fa14efe8ddd35cad4b698cd.setContent(html_66c459dc4e714ab9922c7089599d10ab);
            

            circle_marker_f1c4f3070c794ecaa9fae793ea9e5fd2.bindPopup(popup_443321c73fa14efe8ddd35cad4b698cd);

            
        
    
            var circle_marker_4dd987c55ff042cebce06c9cec0e21fc = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_5933d3ffcc5d4c16bc5054cfc2ab07cf = L.popup({maxWidth: '300'});

            
                var html_fad6fa92fe8a4b4a986a73ce96364909 = $('<div id="html_fad6fa92fe8a4b4a986a73ce96364909" style="width: 100.0%; height: 100.0%;">Guildwood , Morningside , West Hill , Scarborough</div>')[0];
                popup_5933d3ffcc5d4c16bc5054cfc2ab07cf.setContent(html_fad6fa92fe8a4b4a986a73ce96364909);
            

            circle_marker_4dd987c55ff042cebce06c9cec0e21fc.bindPopup(popup_5933d3ffcc5d4c16bc5054cfc2ab07cf);

            
        
    
            var circle_marker_d57ae9876b11428e93fd6b9838f1896c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_0076e68aea394544a33c6a2e30d20d8c = L.popup({maxWidth: '300'});

            
                var html_385b3eef208741a29622bd723f5af1a1 = $('<div id="html_385b3eef208741a29622bd723f5af1a1" style="width: 100.0%; height: 100.0%;">Woburn , Scarborough</div>')[0];
                popup_0076e68aea394544a33c6a2e30d20d8c.setContent(html_385b3eef208741a29622bd723f5af1a1);
            

            circle_marker_d57ae9876b11428e93fd6b9838f1896c.bindPopup(popup_0076e68aea394544a33c6a2e30d20d8c);

            
        
    
            var circle_marker_48a43e8d7674468096d4d3b9f375c0ab = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_f7155809c6ef4dc0882f4711a812ed5b = L.popup({maxWidth: '300'});

            
                var html_2ea0a4b8fa9b44788ca93f28ac6af488 = $('<div id="html_2ea0a4b8fa9b44788ca93f28ac6af488" style="width: 100.0%; height: 100.0%;">Cedarbrae , Scarborough</div>')[0];
                popup_f7155809c6ef4dc0882f4711a812ed5b.setContent(html_2ea0a4b8fa9b44788ca93f28ac6af488);
            

            circle_marker_48a43e8d7674468096d4d3b9f375c0ab.bindPopup(popup_f7155809c6ef4dc0882f4711a812ed5b);

            
        
    
            var circle_marker_b5d7f295d0b845cb80c40fa9e9d17bb7 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_fcc14126514c481099f5c7c1d18667ea = L.popup({maxWidth: '300'});

            
                var html_84e322d48f424f1c863587cf17b137ff = $('<div id="html_84e322d48f424f1c863587cf17b137ff" style="width: 100.0%; height: 100.0%;">Scarborough Village , Scarborough</div>')[0];
                popup_fcc14126514c481099f5c7c1d18667ea.setContent(html_84e322d48f424f1c863587cf17b137ff);
            

            circle_marker_b5d7f295d0b845cb80c40fa9e9d17bb7.bindPopup(popup_fcc14126514c481099f5c7c1d18667ea);

            
        
    
            var circle_marker_e5da89ef7f824358b23772dcb8caf01e = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_4e6df9f2d59b461e80567f0c93c143a1 = L.popup({maxWidth: '300'});

            
                var html_dbe8c637cbcb4dc58b19ab23ac7c5eb9 = $('<div id="html_dbe8c637cbcb4dc58b19ab23ac7c5eb9" style="width: 100.0%; height: 100.0%;">East Birchmount Park , Ionview , Kennedy Park , Scarborough</div>')[0];
                popup_4e6df9f2d59b461e80567f0c93c143a1.setContent(html_dbe8c637cbcb4dc58b19ab23ac7c5eb9);
            

            circle_marker_e5da89ef7f824358b23772dcb8caf01e.bindPopup(popup_4e6df9f2d59b461e80567f0c93c143a1);

            
        
    
            var circle_marker_a9aa07100b9c4b039202b0d778d1e662 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_8223c381a1374b378075d900295a320c = L.popup({maxWidth: '300'});

            
                var html_793c6facfd754fac9096f56b2aec88d6 = $('<div id="html_793c6facfd754fac9096f56b2aec88d6" style="width: 100.0%; height: 100.0%;">Clairlea , Golden Mile , Oakridge , Scarborough</div>')[0];
                popup_8223c381a1374b378075d900295a320c.setContent(html_793c6facfd754fac9096f56b2aec88d6);
            

            circle_marker_a9aa07100b9c4b039202b0d778d1e662.bindPopup(popup_8223c381a1374b378075d900295a320c);

            
        
    
            var circle_marker_bfeb91243ba947bba83039f72c7f9612 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_ed85ddff4bdf48cc8c1fa40eff6bd1b3 = L.popup({maxWidth: '300'});

            
                var html_b27e9b3e8f7746449d5ecc3100beebe9 = $('<div id="html_b27e9b3e8f7746449d5ecc3100beebe9" style="width: 100.0%; height: 100.0%;">Cliffcrest , Cliffside , Scarborough Village West , Scarborough</div>')[0];
                popup_ed85ddff4bdf48cc8c1fa40eff6bd1b3.setContent(html_b27e9b3e8f7746449d5ecc3100beebe9);
            

            circle_marker_bfeb91243ba947bba83039f72c7f9612.bindPopup(popup_ed85ddff4bdf48cc8c1fa40eff6bd1b3);

            
        
    
            var circle_marker_6eb0a2df98574af2a2ae11789e805a45 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_719d06109cc94491882b84f5effe26e8 = L.popup({maxWidth: '300'});

            
                var html_2e23e556ed4544f9af48a133b9b69d49 = $('<div id="html_2e23e556ed4544f9af48a133b9b69d49" style="width: 100.0%; height: 100.0%;">Birch Cliff , Cliffside West , Scarborough</div>')[0];
                popup_719d06109cc94491882b84f5effe26e8.setContent(html_2e23e556ed4544f9af48a133b9b69d49);
            

            circle_marker_6eb0a2df98574af2a2ae11789e805a45.bindPopup(popup_719d06109cc94491882b84f5effe26e8);

            
        
    
            var circle_marker_ce4c866313b948339261151f38801c1c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_e34f03ff7322440c95624964bdcc9ac4 = L.popup({maxWidth: '300'});

            
                var html_98bfc4b31ba2473e83f6f4bc9a6f11f1 = $('<div id="html_98bfc4b31ba2473e83f6f4bc9a6f11f1" style="width: 100.0%; height: 100.0%;">Dorset Park , Scarborough Town Centre , Wexford Heights , Scarborough</div>')[0];
                popup_e34f03ff7322440c95624964bdcc9ac4.setContent(html_98bfc4b31ba2473e83f6f4bc9a6f11f1);
            

            circle_marker_ce4c866313b948339261151f38801c1c.bindPopup(popup_e34f03ff7322440c95624964bdcc9ac4);

            
        
    
            var circle_marker_855659c680a640c6b3fac384632d7329 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_50eaa01be07a46959cff3c964d555b9d = L.popup({maxWidth: '300'});

            
                var html_742a605874754deda06189f07c882658 = $('<div id="html_742a605874754deda06189f07c882658" style="width: 100.0%; height: 100.0%;">Maryvale , Wexford , Scarborough</div>')[0];
                popup_50eaa01be07a46959cff3c964d555b9d.setContent(html_742a605874754deda06189f07c882658);
            

            circle_marker_855659c680a640c6b3fac384632d7329.bindPopup(popup_50eaa01be07a46959cff3c964d555b9d);

            
        
    
            var circle_marker_b91f68b16e334c2bbf01ee1b724bae11 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b23a6388116c4d4b86ed66df6c6b6be4 = L.popup({maxWidth: '300'});

            
                var html_99724792371c4ebb8874e046c9bbd1b5 = $('<div id="html_99724792371c4ebb8874e046c9bbd1b5" style="width: 100.0%; height: 100.0%;">Agincourt , Scarborough</div>')[0];
                popup_b23a6388116c4d4b86ed66df6c6b6be4.setContent(html_99724792371c4ebb8874e046c9bbd1b5);
            

            circle_marker_b91f68b16e334c2bbf01ee1b724bae11.bindPopup(popup_b23a6388116c4d4b86ed66df6c6b6be4);

            
        
    
            var circle_marker_087de7561ed8436c8357f20a17dfd5c7 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_a5f07fc7881e4de4b145da298ae2103a = L.popup({maxWidth: '300'});

            
                var html_03389371077b485eab2fffda1f81edcf = $('<div id="html_03389371077b485eab2fffda1f81edcf" style="width: 100.0%; height: 100.0%;">Clarks Corners , Sullivan , Tam O&#39;Shanter , Scarborough</div>')[0];
                popup_a5f07fc7881e4de4b145da298ae2103a.setContent(html_03389371077b485eab2fffda1f81edcf);
            

            circle_marker_087de7561ed8436c8357f20a17dfd5c7.bindPopup(popup_a5f07fc7881e4de4b145da298ae2103a);

            
        
    
            var circle_marker_477a0b3fcae24eb19cc034da04a8fdb3 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_ab288c396f484eb09c74304fad738052 = L.popup({maxWidth: '300'});

            
                var html_f3ecb2d1f3ae4b5d9b3f30669f38bf75 = $('<div id="html_f3ecb2d1f3ae4b5d9b3f30669f38bf75" style="width: 100.0%; height: 100.0%;">Agincourt North , L&#39;Amoreaux East , Milliken , Steeles East , Scarborough</div>')[0];
                popup_ab288c396f484eb09c74304fad738052.setContent(html_f3ecb2d1f3ae4b5d9b3f30669f38bf75);
            

            circle_marker_477a0b3fcae24eb19cc034da04a8fdb3.bindPopup(popup_ab288c396f484eb09c74304fad738052);

            
        
    
            var circle_marker_586095b6a4d7457791a9d1ecb8bd7f9b = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_164242af024b49e3a1c51bbc481414fe = L.popup({maxWidth: '300'});

            
                var html_7c57cdea21e34b47ad055d8956d3e228 = $('<div id="html_7c57cdea21e34b47ad055d8956d3e228" style="width: 100.0%; height: 100.0%;">L&#39;Amoreaux West , Scarborough</div>')[0];
                popup_164242af024b49e3a1c51bbc481414fe.setContent(html_7c57cdea21e34b47ad055d8956d3e228);
            

            circle_marker_586095b6a4d7457791a9d1ecb8bd7f9b.bindPopup(popup_164242af024b49e3a1c51bbc481414fe);

            
        
    
            var circle_marker_03dbf946fdc243c3a987d5977cc84bbe = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_57fe9449bce64121ab59455694c43a1a = L.popup({maxWidth: '300'});

            
                var html_3e481c1a45a141198809fbf99f28a482 = $('<div id="html_3e481c1a45a141198809fbf99f28a482" style="width: 100.0%; height: 100.0%;">Upper Rouge , Scarborough</div>')[0];
                popup_57fe9449bce64121ab59455694c43a1a.setContent(html_3e481c1a45a141198809fbf99f28a482);
            

            circle_marker_03dbf946fdc243c3a987d5977cc84bbe.bindPopup(popup_57fe9449bce64121ab59455694c43a1a);

            
        
    
            var circle_marker_58d72d7ee62f4c01b43c72840094c042 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b6a88ff68c9744d8bb2290d6c555684c = L.popup({maxWidth: '300'});

            
                var html_271aba1214af45eabf5943a36a9893d9 = $('<div id="html_271aba1214af45eabf5943a36a9893d9" style="width: 100.0%; height: 100.0%;">Hillcrest Village , North York</div>')[0];
                popup_b6a88ff68c9744d8bb2290d6c555684c.setContent(html_271aba1214af45eabf5943a36a9893d9);
            

            circle_marker_58d72d7ee62f4c01b43c72840094c042.bindPopup(popup_b6a88ff68c9744d8bb2290d6c555684c);

            
        
    
            var circle_marker_5bf1d9b98cf4408eae602bb90037585c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_7cbaa418dcf14ba5b6c62c1dabdc4198 = L.popup({maxWidth: '300'});

            
                var html_f67f312fc3f44fc4a64b65377fad58a3 = $('<div id="html_f67f312fc3f44fc4a64b65377fad58a3" style="width: 100.0%; height: 100.0%;">Fairview , Henry Farm , Oriole , North York</div>')[0];
                popup_7cbaa418dcf14ba5b6c62c1dabdc4198.setContent(html_f67f312fc3f44fc4a64b65377fad58a3);
            

            circle_marker_5bf1d9b98cf4408eae602bb90037585c.bindPopup(popup_7cbaa418dcf14ba5b6c62c1dabdc4198);

            
        
    
            var circle_marker_52f62959c6224fd4a9e46fba4a4a008c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_fbedadf8065d477fb3b23edb9b5de086 = L.popup({maxWidth: '300'});

            
                var html_f192d084599f489e8efcceee675ac134 = $('<div id="html_f192d084599f489e8efcceee675ac134" style="width: 100.0%; height: 100.0%;">Bayview Village , North York</div>')[0];
                popup_fbedadf8065d477fb3b23edb9b5de086.setContent(html_f192d084599f489e8efcceee675ac134);
            

            circle_marker_52f62959c6224fd4a9e46fba4a4a008c.bindPopup(popup_fbedadf8065d477fb3b23edb9b5de086);

            
        
    
            var circle_marker_fa904788a9c3401daf9a49f501fd8b28 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_a084aad65d74489fb55a044c7c0b70ea = L.popup({maxWidth: '300'});

            
                var html_af43a62060164ea6b994da5f90ec193c = $('<div id="html_af43a62060164ea6b994da5f90ec193c" style="width: 100.0%; height: 100.0%;">Silver Hills , York Mills , North York</div>')[0];
                popup_a084aad65d74489fb55a044c7c0b70ea.setContent(html_af43a62060164ea6b994da5f90ec193c);
            

            circle_marker_fa904788a9c3401daf9a49f501fd8b28.bindPopup(popup_a084aad65d74489fb55a044c7c0b70ea);

            
        
    
            var circle_marker_ae0a1caed28f49148275f04b1139a59f = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_aefd090adeff40ba9cec4e0ad874d90e = L.popup({maxWidth: '300'});

            
                var html_f682cfb43f8549438a76b05d64e58d6c = $('<div id="html_f682cfb43f8549438a76b05d64e58d6c" style="width: 100.0%; height: 100.0%;">Newtonbrook , Willowdale , North York</div>')[0];
                popup_aefd090adeff40ba9cec4e0ad874d90e.setContent(html_f682cfb43f8549438a76b05d64e58d6c);
            

            circle_marker_ae0a1caed28f49148275f04b1139a59f.bindPopup(popup_aefd090adeff40ba9cec4e0ad874d90e);

            
        
    
            var circle_marker_e0dc67b2ca04433c9d20e1be1d69c9ad = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_e8ebaba6b58c489491d11581d29d72dd = L.popup({maxWidth: '300'});

            
                var html_6b437d4427d94e3e8b75b509d6d769da = $('<div id="html_6b437d4427d94e3e8b75b509d6d769da" style="width: 100.0%; height: 100.0%;">Willowdale South , North York</div>')[0];
                popup_e8ebaba6b58c489491d11581d29d72dd.setContent(html_6b437d4427d94e3e8b75b509d6d769da);
            

            circle_marker_e0dc67b2ca04433c9d20e1be1d69c9ad.bindPopup(popup_e8ebaba6b58c489491d11581d29d72dd);

            
        
    
            var circle_marker_0aefe8f1f7044d98b4bf38da2fe0cc26 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_c5fa573ebf874da2aada1462f6fc29c4 = L.popup({maxWidth: '300'});

            
                var html_d1ee0fc8203a477aab70e6553d9119d2 = $('<div id="html_d1ee0fc8203a477aab70e6553d9119d2" style="width: 100.0%; height: 100.0%;">York Mills West , North York</div>')[0];
                popup_c5fa573ebf874da2aada1462f6fc29c4.setContent(html_d1ee0fc8203a477aab70e6553d9119d2);
            

            circle_marker_0aefe8f1f7044d98b4bf38da2fe0cc26.bindPopup(popup_c5fa573ebf874da2aada1462f6fc29c4);

            
        
    
            var circle_marker_feb301d6756b4d5bb37f42a49e619c72 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_320c9e6ed90f488e9def10fc3d6d47d3 = L.popup({maxWidth: '300'});

            
                var html_051a0df153014d2e8c741389e863b642 = $('<div id="html_051a0df153014d2e8c741389e863b642" style="width: 100.0%; height: 100.0%;">Willowdale West , North York</div>')[0];
                popup_320c9e6ed90f488e9def10fc3d6d47d3.setContent(html_051a0df153014d2e8c741389e863b642);
            

            circle_marker_feb301d6756b4d5bb37f42a49e619c72.bindPopup(popup_320c9e6ed90f488e9def10fc3d6d47d3);

            
        
    
            var circle_marker_106d9e7c93434c2e904db1f2f4d91343 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b30c0120b92647dcaf7a8aa62ed47db4 = L.popup({maxWidth: '300'});

            
                var html_2d595ecccb9d467cafab70d562809869 = $('<div id="html_2d595ecccb9d467cafab70d562809869" style="width: 100.0%; height: 100.0%;">Parkwoods , North York</div>')[0];
                popup_b30c0120b92647dcaf7a8aa62ed47db4.setContent(html_2d595ecccb9d467cafab70d562809869);
            

            circle_marker_106d9e7c93434c2e904db1f2f4d91343.bindPopup(popup_b30c0120b92647dcaf7a8aa62ed47db4);

            
        
    
            var circle_marker_78ef472393474f239da923b5a08336c7 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_c27df86ed74c4bee9f200648f4441ec2 = L.popup({maxWidth: '300'});

            
                var html_009b345ebbf6420088ac76935d044870 = $('<div id="html_009b345ebbf6420088ac76935d044870" style="width: 100.0%; height: 100.0%;">Don Mills North , North York</div>')[0];
                popup_c27df86ed74c4bee9f200648f4441ec2.setContent(html_009b345ebbf6420088ac76935d044870);
            

            circle_marker_78ef472393474f239da923b5a08336c7.bindPopup(popup_c27df86ed74c4bee9f200648f4441ec2);

            
        
    
            var circle_marker_c5599d0b78874d94a5c7e678da5aa9a6 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_82fa133900a7418eb6987b6aa5d85fc4 = L.popup({maxWidth: '300'});

            
                var html_e00806a616264d3b85ff75c360588489 = $('<div id="html_e00806a616264d3b85ff75c360588489" style="width: 100.0%; height: 100.0%;">Flemingdon Park , Don Mills South , North York</div>')[0];
                popup_82fa133900a7418eb6987b6aa5d85fc4.setContent(html_e00806a616264d3b85ff75c360588489);
            

            circle_marker_c5599d0b78874d94a5c7e678da5aa9a6.bindPopup(popup_82fa133900a7418eb6987b6aa5d85fc4);

            
        
    
            var circle_marker_1c7eafdcc90e48edb669e56f45b9ba83 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_fa32e8d1bdd14b6591ce6af4c1fdb808 = L.popup({maxWidth: '300'});

            
                var html_1af96619d3f446d0b8257c74536966e4 = $('<div id="html_1af96619d3f446d0b8257c74536966e4" style="width: 100.0%; height: 100.0%;">Bathurst Manor , Downsview North , Wilson Heights , North York</div>')[0];
                popup_fa32e8d1bdd14b6591ce6af4c1fdb808.setContent(html_1af96619d3f446d0b8257c74536966e4);
            

            circle_marker_1c7eafdcc90e48edb669e56f45b9ba83.bindPopup(popup_fa32e8d1bdd14b6591ce6af4c1fdb808);

            
        
    
            var circle_marker_32e2169747c1449cbaca3ff999bba24f = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_ad063ead5bac485e9d2a3c6eb4151c51 = L.popup({maxWidth: '300'});

            
                var html_e7e10cde5bb945fd93e08b2c79462ce0 = $('<div id="html_e7e10cde5bb945fd93e08b2c79462ce0" style="width: 100.0%; height: 100.0%;">Northwood Park , York University , North York</div>')[0];
                popup_ad063ead5bac485e9d2a3c6eb4151c51.setContent(html_e7e10cde5bb945fd93e08b2c79462ce0);
            

            circle_marker_32e2169747c1449cbaca3ff999bba24f.bindPopup(popup_ad063ead5bac485e9d2a3c6eb4151c51);

            
        
    
            var circle_marker_4e1b1be8abc24ac7aa170e3ea70847ed = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b6580bf0c38f485b9278fccad6f434c6 = L.popup({maxWidth: '300'});

            
                var html_b3e6c039d23f4289805955dcbc5093ec = $('<div id="html_b3e6c039d23f4289805955dcbc5093ec" style="width: 100.0%; height: 100.0%;">CFB Toronto , Downsview East , North York</div>')[0];
                popup_b6580bf0c38f485b9278fccad6f434c6.setContent(html_b3e6c039d23f4289805955dcbc5093ec);
            

            circle_marker_4e1b1be8abc24ac7aa170e3ea70847ed.bindPopup(popup_b6580bf0c38f485b9278fccad6f434c6);

            
        
    
            var circle_marker_2339862ca6184f389ad0c868eda4cd71 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_e0e7f81f6b6c4fa3b7642b6b30a9bd87 = L.popup({maxWidth: '300'});

            
                var html_90944d618af04231abb8a383658edbdc = $('<div id="html_90944d618af04231abb8a383658edbdc" style="width: 100.0%; height: 100.0%;">Downsview West , North York</div>')[0];
                popup_e0e7f81f6b6c4fa3b7642b6b30a9bd87.setContent(html_90944d618af04231abb8a383658edbdc);
            

            circle_marker_2339862ca6184f389ad0c868eda4cd71.bindPopup(popup_e0e7f81f6b6c4fa3b7642b6b30a9bd87);

            
        
    
            var circle_marker_378c85ee3dd34e628fb2ca1bd2352f11 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_7d96ce118ac6471cbbf45d99e14d3153 = L.popup({maxWidth: '300'});

            
                var html_467ca117c2bd464bab6fb92ca39d5c4f = $('<div id="html_467ca117c2bd464bab6fb92ca39d5c4f" style="width: 100.0%; height: 100.0%;">Downsview Central , North York</div>')[0];
                popup_7d96ce118ac6471cbbf45d99e14d3153.setContent(html_467ca117c2bd464bab6fb92ca39d5c4f);
            

            circle_marker_378c85ee3dd34e628fb2ca1bd2352f11.bindPopup(popup_7d96ce118ac6471cbbf45d99e14d3153);

            
        
    
            var circle_marker_1d6e2ba7d74a463f9859fe0927f8689f = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_aac8b00a3b024c6391400fb6694e5b52 = L.popup({maxWidth: '300'});

            
                var html_30a48b86f75c4d34bb5bec005f4351e6 = $('<div id="html_30a48b86f75c4d34bb5bec005f4351e6" style="width: 100.0%; height: 100.0%;">Downsview Northwest , North York</div>')[0];
                popup_aac8b00a3b024c6391400fb6694e5b52.setContent(html_30a48b86f75c4d34bb5bec005f4351e6);
            

            circle_marker_1d6e2ba7d74a463f9859fe0927f8689f.bindPopup(popup_aac8b00a3b024c6391400fb6694e5b52);

            
        
    
            var circle_marker_b991c35e68be4f919cdb4b5954dbfab0 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_58cbb3d1bcc74c12bb3ddc49cdc5a455 = L.popup({maxWidth: '300'});

            
                var html_b45bd8d361b3448e88a6841e756e00d2 = $('<div id="html_b45bd8d361b3448e88a6841e756e00d2" style="width: 100.0%; height: 100.0%;">Victoria Village , North York</div>')[0];
                popup_58cbb3d1bcc74c12bb3ddc49cdc5a455.setContent(html_b45bd8d361b3448e88a6841e756e00d2);
            

            circle_marker_b991c35e68be4f919cdb4b5954dbfab0.bindPopup(popup_58cbb3d1bcc74c12bb3ddc49cdc5a455);

            
        
    
            var circle_marker_838cdd2e14fd4033a31d182d1a2c7792 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b80f84a808f1452e9fc39d371b544680 = L.popup({maxWidth: '300'});

            
                var html_ca3d099554934d1ca3524b7690eda738 = $('<div id="html_ca3d099554934d1ca3524b7690eda738" style="width: 100.0%; height: 100.0%;">Woodbine Gardens , Parkview Hill , East York</div>')[0];
                popup_b80f84a808f1452e9fc39d371b544680.setContent(html_ca3d099554934d1ca3524b7690eda738);
            

            circle_marker_838cdd2e14fd4033a31d182d1a2c7792.bindPopup(popup_b80f84a808f1452e9fc39d371b544680);

            
        
    
            var circle_marker_a256105abeaf454dac84ddec45d35457 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_c962c686e97c4ba49e112b80a94967db = L.popup({maxWidth: '300'});

            
                var html_77c186e715ee4b778f4c68b355531616 = $('<div id="html_77c186e715ee4b778f4c68b355531616" style="width: 100.0%; height: 100.0%;">Woodbine Heights , East York</div>')[0];
                popup_c962c686e97c4ba49e112b80a94967db.setContent(html_77c186e715ee4b778f4c68b355531616);
            

            circle_marker_a256105abeaf454dac84ddec45d35457.bindPopup(popup_c962c686e97c4ba49e112b80a94967db);

            
        
    
            var circle_marker_eb03a1d3555f49688170241e47c3e146 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b89593457cb4479f80fb2797a919b53b = L.popup({maxWidth: '300'});

            
                var html_7fe9a0d0a5124ef4a1a78fe46572bbf8 = $('<div id="html_7fe9a0d0a5124ef4a1a78fe46572bbf8" style="width: 100.0%; height: 100.0%;">The Beaches , East Toronto</div>')[0];
                popup_b89593457cb4479f80fb2797a919b53b.setContent(html_7fe9a0d0a5124ef4a1a78fe46572bbf8);
            

            circle_marker_eb03a1d3555f49688170241e47c3e146.bindPopup(popup_b89593457cb4479f80fb2797a919b53b);

            
        
    
            var circle_marker_dfc3d0c23c4040fb9a8a00052a664209 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_7cc7c1cd5654428b8c047f7bc5ee103d = L.popup({maxWidth: '300'});

            
                var html_69aa9ccd45f34969beda214c9a363388 = $('<div id="html_69aa9ccd45f34969beda214c9a363388" style="width: 100.0%; height: 100.0%;">Leaside , East York</div>')[0];
                popup_7cc7c1cd5654428b8c047f7bc5ee103d.setContent(html_69aa9ccd45f34969beda214c9a363388);
            

            circle_marker_dfc3d0c23c4040fb9a8a00052a664209.bindPopup(popup_7cc7c1cd5654428b8c047f7bc5ee103d);

            
        
    
            var circle_marker_22a15f8e7563459bafbd3322c547455a = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_55ce98b8b7304da19e9850b240095765 = L.popup({maxWidth: '300'});

            
                var html_267e8cb208f249d88e355371db121d06 = $('<div id="html_267e8cb208f249d88e355371db121d06" style="width: 100.0%; height: 100.0%;">Thorncliffe Park , East York</div>')[0];
                popup_55ce98b8b7304da19e9850b240095765.setContent(html_267e8cb208f249d88e355371db121d06);
            

            circle_marker_22a15f8e7563459bafbd3322c547455a.bindPopup(popup_55ce98b8b7304da19e9850b240095765);

            
        
    
            var circle_marker_5e93c8c869bd41bb80b51e2cd7b2c1f7 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_6ac8777fc3874c04930e10193cfcb77b = L.popup({maxWidth: '300'});

            
                var html_282942d730c1430ebe92ad74689820b2 = $('<div id="html_282942d730c1430ebe92ad74689820b2" style="width: 100.0%; height: 100.0%;">East Toronto , East York</div>')[0];
                popup_6ac8777fc3874c04930e10193cfcb77b.setContent(html_282942d730c1430ebe92ad74689820b2);
            

            circle_marker_5e93c8c869bd41bb80b51e2cd7b2c1f7.bindPopup(popup_6ac8777fc3874c04930e10193cfcb77b);

            
        
    
            var circle_marker_059dafa6f7404b8facc5fa3fb046b495 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_1c7c9ae725e44c70a1c2a43b4adee422 = L.popup({maxWidth: '300'});

            
                var html_dfc54ce1b6bd4ceca36ac13aa6594472 = $('<div id="html_dfc54ce1b6bd4ceca36ac13aa6594472" style="width: 100.0%; height: 100.0%;">The Danforth West , Riverdale , East Toronto</div>')[0];
                popup_1c7c9ae725e44c70a1c2a43b4adee422.setContent(html_dfc54ce1b6bd4ceca36ac13aa6594472);
            

            circle_marker_059dafa6f7404b8facc5fa3fb046b495.bindPopup(popup_1c7c9ae725e44c70a1c2a43b4adee422);

            
        
    
            var circle_marker_0d94e9dc6bb0452ab666565edc4b0389 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b319bb39b6e24687a48e0dcb324df5e7 = L.popup({maxWidth: '300'});

            
                var html_3efb9978c64a4d1d9afebb7005e958da = $('<div id="html_3efb9978c64a4d1d9afebb7005e958da" style="width: 100.0%; height: 100.0%;">The Beaches West , India Bazaar , East Toronto</div>')[0];
                popup_b319bb39b6e24687a48e0dcb324df5e7.setContent(html_3efb9978c64a4d1d9afebb7005e958da);
            

            circle_marker_0d94e9dc6bb0452ab666565edc4b0389.bindPopup(popup_b319bb39b6e24687a48e0dcb324df5e7);

            
        
    
            var circle_marker_d4500e002b064c15ab7215f74333603a = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_3399e22994e74eaaa5872474a4cebe17 = L.popup({maxWidth: '300'});

            
                var html_ea39d128d19643d597bf25907f08273b = $('<div id="html_ea39d128d19643d597bf25907f08273b" style="width: 100.0%; height: 100.0%;">Studio District , East Toronto</div>')[0];
                popup_3399e22994e74eaaa5872474a4cebe17.setContent(html_ea39d128d19643d597bf25907f08273b);
            

            circle_marker_d4500e002b064c15ab7215f74333603a.bindPopup(popup_3399e22994e74eaaa5872474a4cebe17);

            
        
    
            var circle_marker_a69f91818bf84431b15385688dad608e = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_f5f3b260cdb1447b8dbddd8209441b40 = L.popup({maxWidth: '300'});

            
                var html_336ef444fed242ebbf7ee2fe7970b1f2 = $('<div id="html_336ef444fed242ebbf7ee2fe7970b1f2" style="width: 100.0%; height: 100.0%;">Lawrence Park , Central Toronto</div>')[0];
                popup_f5f3b260cdb1447b8dbddd8209441b40.setContent(html_336ef444fed242ebbf7ee2fe7970b1f2);
            

            circle_marker_a69f91818bf84431b15385688dad608e.bindPopup(popup_f5f3b260cdb1447b8dbddd8209441b40);

            
        
    
            var circle_marker_58ab4974cc454e65b02619393ccf4c4b = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_fc42765ef0c24446a2244c19d9d60f34 = L.popup({maxWidth: '300'});

            
                var html_183563b0379f4b9d9ad6608aef44efa6 = $('<div id="html_183563b0379f4b9d9ad6608aef44efa6" style="width: 100.0%; height: 100.0%;">Davisville North , Central Toronto</div>')[0];
                popup_fc42765ef0c24446a2244c19d9d60f34.setContent(html_183563b0379f4b9d9ad6608aef44efa6);
            

            circle_marker_58ab4974cc454e65b02619393ccf4c4b.bindPopup(popup_fc42765ef0c24446a2244c19d9d60f34);

            
        
    
            var circle_marker_6d990bd262c4400fac32657a27a1db4b = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_b213946115634598914c55acafc83174 = L.popup({maxWidth: '300'});

            
                var html_bd6ea5c1ae0448658580a818f252dc81 = $('<div id="html_bd6ea5c1ae0448658580a818f252dc81" style="width: 100.0%; height: 100.0%;">North Toronto West , Central Toronto</div>')[0];
                popup_b213946115634598914c55acafc83174.setContent(html_bd6ea5c1ae0448658580a818f252dc81);
            

            circle_marker_6d990bd262c4400fac32657a27a1db4b.bindPopup(popup_b213946115634598914c55acafc83174);

            
        
    
            var circle_marker_5b7677191bef4637bb4627c1a71a25cc = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_a2544c5cb0dc47a8bf34be8783c7058a = L.popup({maxWidth: '300'});

            
                var html_2bc86c5eb4c54f3db124d9749a6d6fa9 = $('<div id="html_2bc86c5eb4c54f3db124d9749a6d6fa9" style="width: 100.0%; height: 100.0%;">Davisville , Central Toronto</div>')[0];
                popup_a2544c5cb0dc47a8bf34be8783c7058a.setContent(html_2bc86c5eb4c54f3db124d9749a6d6fa9);
            

            circle_marker_5b7677191bef4637bb4627c1a71a25cc.bindPopup(popup_a2544c5cb0dc47a8bf34be8783c7058a);

            
        
    
            var circle_marker_6e61cbb7ff24418fabb1c7333d091594 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_5e5941dcba0d4ca09885431e6c3fc196 = L.popup({maxWidth: '300'});

            
                var html_d78227d1a1924efdab6b4ec002d1c405 = $('<div id="html_d78227d1a1924efdab6b4ec002d1c405" style="width: 100.0%; height: 100.0%;">Moore Park , Summerhill East , Central Toronto</div>')[0];
                popup_5e5941dcba0d4ca09885431e6c3fc196.setContent(html_d78227d1a1924efdab6b4ec002d1c405);
            

            circle_marker_6e61cbb7ff24418fabb1c7333d091594.bindPopup(popup_5e5941dcba0d4ca09885431e6c3fc196);

            
        
    
            var circle_marker_2d657963a2154b83ae6c7a0a56ea2210 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_81e29053f9a54a7ca253be2b71299a18 = L.popup({maxWidth: '300'});

            
                var html_1e7910827a28423eb25054333e492b7d = $('<div id="html_1e7910827a28423eb25054333e492b7d" style="width: 100.0%; height: 100.0%;">Deer Park , Forest Hill SE , Rathnelly , South Hill , Summerhill West , Central Toronto</div>')[0];
                popup_81e29053f9a54a7ca253be2b71299a18.setContent(html_1e7910827a28423eb25054333e492b7d);
            

            circle_marker_2d657963a2154b83ae6c7a0a56ea2210.bindPopup(popup_81e29053f9a54a7ca253be2b71299a18);

            
        
    
            var circle_marker_41960993211f4408a0405602c8f37438 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_f1436e575ebf46d499e1494a772b97ca = L.popup({maxWidth: '300'});

            
                var html_77c82278f6384968865aace9b8a210a9 = $('<div id="html_77c82278f6384968865aace9b8a210a9" style="width: 100.0%; height: 100.0%;">Rosedale , Downtown Toronto</div>')[0];
                popup_f1436e575ebf46d499e1494a772b97ca.setContent(html_77c82278f6384968865aace9b8a210a9);
            

            circle_marker_41960993211f4408a0405602c8f37438.bindPopup(popup_f1436e575ebf46d499e1494a772b97ca);

            
        
    
            var circle_marker_9aed0fbc90e04dc197c8b4d78e2dd561 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_ae48f72cc1924944ae2b45dbd77abcc4 = L.popup({maxWidth: '300'});

            
                var html_136d91cae8a54626bce24c190fc0826a = $('<div id="html_136d91cae8a54626bce24c190fc0826a" style="width: 100.0%; height: 100.0%;">Cabbagetown , St. James Town , Downtown Toronto</div>')[0];
                popup_ae48f72cc1924944ae2b45dbd77abcc4.setContent(html_136d91cae8a54626bce24c190fc0826a);
            

            circle_marker_9aed0fbc90e04dc197c8b4d78e2dd561.bindPopup(popup_ae48f72cc1924944ae2b45dbd77abcc4);

            
        
    
            var circle_marker_16e7a22cf1dd49c4881341cf6fa5cfe6 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_9e4f4e188f94470f80726d0e6841d36a = L.popup({maxWidth: '300'});

            
                var html_d51409413f9e406e86c04c7e6d50c21d = $('<div id="html_d51409413f9e406e86c04c7e6d50c21d" style="width: 100.0%; height: 100.0%;">Church and Wellesley , Downtown Toronto</div>')[0];
                popup_9e4f4e188f94470f80726d0e6841d36a.setContent(html_d51409413f9e406e86c04c7e6d50c21d);
            

            circle_marker_16e7a22cf1dd49c4881341cf6fa5cfe6.bindPopup(popup_9e4f4e188f94470f80726d0e6841d36a);

            
        
    
            var circle_marker_43c8c10dec414d0fa68bdb97b0760338 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_58e03b150242405da95a7deb4de8f3fe = L.popup({maxWidth: '300'});

            
                var html_70c32765afbc40dfa3eeb889affd7c8c = $('<div id="html_70c32765afbc40dfa3eeb889affd7c8c" style="width: 100.0%; height: 100.0%;">Harbourfront , Regent Park , Downtown Toronto</div>')[0];
                popup_58e03b150242405da95a7deb4de8f3fe.setContent(html_70c32765afbc40dfa3eeb889affd7c8c);
            

            circle_marker_43c8c10dec414d0fa68bdb97b0760338.bindPopup(popup_58e03b150242405da95a7deb4de8f3fe);

            
        
    
            var circle_marker_d2d895ec3d1f4b29b32fcaa4adc3d93f = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_3a419e5a70ca4bc2aa8516b79f2a9921 = L.popup({maxWidth: '300'});

            
                var html_91fb11b90b584503937105834a32d4b3 = $('<div id="html_91fb11b90b584503937105834a32d4b3" style="width: 100.0%; height: 100.0%;">Ryerson , Garden District , Downtown Toronto</div>')[0];
                popup_3a419e5a70ca4bc2aa8516b79f2a9921.setContent(html_91fb11b90b584503937105834a32d4b3);
            

            circle_marker_d2d895ec3d1f4b29b32fcaa4adc3d93f.bindPopup(popup_3a419e5a70ca4bc2aa8516b79f2a9921);

            
        
    
            var circle_marker_b054241139684c02bec0231bafbe9ca7 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_95a3549779974c83a1d838cb226116e7 = L.popup({maxWidth: '300'});

            
                var html_e10206f11de64c619353d509af20f2a7 = $('<div id="html_e10206f11de64c619353d509af20f2a7" style="width: 100.0%; height: 100.0%;">St. James Town , Downtown Toronto</div>')[0];
                popup_95a3549779974c83a1d838cb226116e7.setContent(html_e10206f11de64c619353d509af20f2a7);
            

            circle_marker_b054241139684c02bec0231bafbe9ca7.bindPopup(popup_95a3549779974c83a1d838cb226116e7);

            
        
    
            var circle_marker_6554f277882648b3a49ef19e2283f068 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_f55cb8cecdb44f5392dc6bb6744ea48d = L.popup({maxWidth: '300'});

            
                var html_d16ddaef85414acfa2f6cfd809eb57e1 = $('<div id="html_d16ddaef85414acfa2f6cfd809eb57e1" style="width: 100.0%; height: 100.0%;">Berczy Park , Downtown Toronto</div>')[0];
                popup_f55cb8cecdb44f5392dc6bb6744ea48d.setContent(html_d16ddaef85414acfa2f6cfd809eb57e1);
            

            circle_marker_6554f277882648b3a49ef19e2283f068.bindPopup(popup_f55cb8cecdb44f5392dc6bb6744ea48d);

            
        
    
            var circle_marker_d32ccdb52d034d8f8dff42f5cc53fd97 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_3b8fed3523cd47ea945d32d5bc039f8c = L.popup({maxWidth: '300'});

            
                var html_4f1af1cc057c4f32a9bfecedda15b41a = $('<div id="html_4f1af1cc057c4f32a9bfecedda15b41a" style="width: 100.0%; height: 100.0%;">Central Bay Street , Downtown Toronto</div>')[0];
                popup_3b8fed3523cd47ea945d32d5bc039f8c.setContent(html_4f1af1cc057c4f32a9bfecedda15b41a);
            

            circle_marker_d32ccdb52d034d8f8dff42f5cc53fd97.bindPopup(popup_3b8fed3523cd47ea945d32d5bc039f8c);

            
        
    
            var circle_marker_02a63d3a8eab4d7681b2d9378cc894e4 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_5ae15d9c85784111b95163b82ef01cc0 = L.popup({maxWidth: '300'});

            
                var html_87db30d2e3d344519744955ceb7dfa79 = $('<div id="html_87db30d2e3d344519744955ceb7dfa79" style="width: 100.0%; height: 100.0%;">Adelaide , King , Richmond , Downtown Toronto</div>')[0];
                popup_5ae15d9c85784111b95163b82ef01cc0.setContent(html_87db30d2e3d344519744955ceb7dfa79);
            

            circle_marker_02a63d3a8eab4d7681b2d9378cc894e4.bindPopup(popup_5ae15d9c85784111b95163b82ef01cc0);

            
        
    
            var circle_marker_267e7442626244c58a4062c634eaaf1f = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_defeb3deaf5a412285336394fad3a548 = L.popup({maxWidth: '300'});

            
                var html_4bf48ad8f1054a3890385b21173e4049 = $('<div id="html_4bf48ad8f1054a3890385b21173e4049" style="width: 100.0%; height: 100.0%;">Harbourfront East , Toronto Islands , Union Station , Downtown Toronto</div>')[0];
                popup_defeb3deaf5a412285336394fad3a548.setContent(html_4bf48ad8f1054a3890385b21173e4049);
            

            circle_marker_267e7442626244c58a4062c634eaaf1f.bindPopup(popup_defeb3deaf5a412285336394fad3a548);

            
        
    
            var circle_marker_1e5c5395cf6a4085ad480fce8acc47de = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_48b306666f5c45c5937c18cd9cb9b377 = L.popup({maxWidth: '300'});

            
                var html_7b37f3976c194bf1ac0e9c705afff1d1 = $('<div id="html_7b37f3976c194bf1ac0e9c705afff1d1" style="width: 100.0%; height: 100.0%;">Design Exchange , Toronto Dominion Centre , Downtown Toronto</div>')[0];
                popup_48b306666f5c45c5937c18cd9cb9b377.setContent(html_7b37f3976c194bf1ac0e9c705afff1d1);
            

            circle_marker_1e5c5395cf6a4085ad480fce8acc47de.bindPopup(popup_48b306666f5c45c5937c18cd9cb9b377);

            
        
    
            var circle_marker_cd9d90d562f04ccaa33ac8abe0677d26 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_001042e39cf1459c87970923242e38de = L.popup({maxWidth: '300'});

            
                var html_98267ef1809a445db996da0da9ddee4b = $('<div id="html_98267ef1809a445db996da0da9ddee4b" style="width: 100.0%; height: 100.0%;">Commerce Court , Victoria Hotel , Downtown Toronto</div>')[0];
                popup_001042e39cf1459c87970923242e38de.setContent(html_98267ef1809a445db996da0da9ddee4b);
            

            circle_marker_cd9d90d562f04ccaa33ac8abe0677d26.bindPopup(popup_001042e39cf1459c87970923242e38de);

            
        
    
            var circle_marker_9afca875c7414b5f803e32e7c316f744 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_a49c5cc186054d488d09e5bd2c94ba72 = L.popup({maxWidth: '300'});

            
                var html_df076035cb7549f4a7d6404e0f4b8ae2 = $('<div id="html_df076035cb7549f4a7d6404e0f4b8ae2" style="width: 100.0%; height: 100.0%;">Bedford Park , Lawrence Manor East , North York</div>')[0];
                popup_a49c5cc186054d488d09e5bd2c94ba72.setContent(html_df076035cb7549f4a7d6404e0f4b8ae2);
            

            circle_marker_9afca875c7414b5f803e32e7c316f744.bindPopup(popup_a49c5cc186054d488d09e5bd2c94ba72);

            
        
    
            var circle_marker_217af8d40d0b4da3b7df3a9eff3f4de8 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_6b82a6f1502247389e9b36ee852873b9 = L.popup({maxWidth: '300'});

            
                var html_c68c108f62114ba1ad47c936a808877b = $('<div id="html_c68c108f62114ba1ad47c936a808877b" style="width: 100.0%; height: 100.0%;">Roselawn , Central Toronto</div>')[0];
                popup_6b82a6f1502247389e9b36ee852873b9.setContent(html_c68c108f62114ba1ad47c936a808877b);
            

            circle_marker_217af8d40d0b4da3b7df3a9eff3f4de8.bindPopup(popup_6b82a6f1502247389e9b36ee852873b9);

            
        
    
            var circle_marker_e06cac6b6db74ad89ac2f7689dbe2803 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_19bcf615b7304521b65b8203b5d1af7c = L.popup({maxWidth: '300'});

            
                var html_723a1832e49e499f9bcbe4feaadae3d3 = $('<div id="html_723a1832e49e499f9bcbe4feaadae3d3" style="width: 100.0%; height: 100.0%;">Forest Hill North , Forest Hill West , Central Toronto</div>')[0];
                popup_19bcf615b7304521b65b8203b5d1af7c.setContent(html_723a1832e49e499f9bcbe4feaadae3d3);
            

            circle_marker_e06cac6b6db74ad89ac2f7689dbe2803.bindPopup(popup_19bcf615b7304521b65b8203b5d1af7c);

            
        
    
            var circle_marker_f964e3b8d37e41e187e44d3100a1f8da = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_7725c89ed25441c5b500f6a14c79da0f = L.popup({maxWidth: '300'});

            
                var html_4b0307b1a6e64aaca196ef0c7264348a = $('<div id="html_4b0307b1a6e64aaca196ef0c7264348a" style="width: 100.0%; height: 100.0%;">The Annex , North Midtown , Yorkville , Central Toronto</div>')[0];
                popup_7725c89ed25441c5b500f6a14c79da0f.setContent(html_4b0307b1a6e64aaca196ef0c7264348a);
            

            circle_marker_f964e3b8d37e41e187e44d3100a1f8da.bindPopup(popup_7725c89ed25441c5b500f6a14c79da0f);

            
        
    
            var circle_marker_ddbebd169f154afd9d38e1eb483b6f6c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_9c98953da8df409ca3f7f35ce7664b82 = L.popup({maxWidth: '300'});

            
                var html_e0e265706f304014a2069b63f4d3317b = $('<div id="html_e0e265706f304014a2069b63f4d3317b" style="width: 100.0%; height: 100.0%;">Harbord , University of Toronto , Downtown Toronto</div>')[0];
                popup_9c98953da8df409ca3f7f35ce7664b82.setContent(html_e0e265706f304014a2069b63f4d3317b);
            

            circle_marker_ddbebd169f154afd9d38e1eb483b6f6c.bindPopup(popup_9c98953da8df409ca3f7f35ce7664b82);

            
        
    
            var circle_marker_5a282b610c384fdab8862e0992c2dc1e = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_c57cfa8705ac435aad64e1063266720a = L.popup({maxWidth: '300'});

            
                var html_e05b62ed5b4c436795f0930eb878a638 = $('<div id="html_e05b62ed5b4c436795f0930eb878a638" style="width: 100.0%; height: 100.0%;">Chinatown , Grange Park , Kensington Market , Downtown Toronto</div>')[0];
                popup_c57cfa8705ac435aad64e1063266720a.setContent(html_e05b62ed5b4c436795f0930eb878a638);
            

            circle_marker_5a282b610c384fdab8862e0992c2dc1e.bindPopup(popup_c57cfa8705ac435aad64e1063266720a);

            
        
    
            var circle_marker_b6d1304ceb8148d5bf0160c52d1f221d = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_5051ab4fd52d4ffa98ecfb51bac1a9a7 = L.popup({maxWidth: '300'});

            
                var html_86995416c2c64e0ba3097ab3016d8733 = $('<div id="html_86995416c2c64e0ba3097ab3016d8733" style="width: 100.0%; height: 100.0%;">CN Tower , Bathurst Quay , Island airport , Harbourfront West , King and Spadina , Railway Lands , South Niagara , Downtown Toronto</div>')[0];
                popup_5051ab4fd52d4ffa98ecfb51bac1a9a7.setContent(html_86995416c2c64e0ba3097ab3016d8733);
            

            circle_marker_b6d1304ceb8148d5bf0160c52d1f221d.bindPopup(popup_5051ab4fd52d4ffa98ecfb51bac1a9a7);

            
        
    
            var circle_marker_54370bcaf2ca40139f871d924bf67dc0 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_9c904122b48842ba97c9dc0f3dafd5cc = L.popup({maxWidth: '300'});

            
                var html_d5bd69a72a3647088235a6ac1ae38e42 = $('<div id="html_d5bd69a72a3647088235a6ac1ae38e42" style="width: 100.0%; height: 100.0%;">Stn A PO Boxes 25 The Esplanade , Downtown Toronto</div>')[0];
                popup_9c904122b48842ba97c9dc0f3dafd5cc.setContent(html_d5bd69a72a3647088235a6ac1ae38e42);
            

            circle_marker_54370bcaf2ca40139f871d924bf67dc0.bindPopup(popup_9c904122b48842ba97c9dc0f3dafd5cc);

            
        
    
            var circle_marker_0a15cab411674770927570173c37b1fc = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_df8f4932ccfd4472b44f7e5ed03ccfb9 = L.popup({maxWidth: '300'});

            
                var html_df19b2cfa4e24dec88413a6227436337 = $('<div id="html_df19b2cfa4e24dec88413a6227436337" style="width: 100.0%; height: 100.0%;">First Canadian Place , Underground city , Downtown Toronto</div>')[0];
                popup_df8f4932ccfd4472b44f7e5ed03ccfb9.setContent(html_df19b2cfa4e24dec88413a6227436337);
            

            circle_marker_0a15cab411674770927570173c37b1fc.bindPopup(popup_df8f4932ccfd4472b44f7e5ed03ccfb9);

            
        
    
            var circle_marker_2fcd62dda34f42fbb0ca148cec0639f0 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_26f1e2d29d8c4ca382485083889118af = L.popup({maxWidth: '300'});

            
                var html_b79222ae48f64878879f58a28417b58b = $('<div id="html_b79222ae48f64878879f58a28417b58b" style="width: 100.0%; height: 100.0%;">Lawrence Heights , Lawrence Manor , North York</div>')[0];
                popup_26f1e2d29d8c4ca382485083889118af.setContent(html_b79222ae48f64878879f58a28417b58b);
            

            circle_marker_2fcd62dda34f42fbb0ca148cec0639f0.bindPopup(popup_26f1e2d29d8c4ca382485083889118af);

            
        
    
            var circle_marker_6ee4135b5551451f9b26457c266e1f49 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_8bb137c6b64c405b8f555c929870ccc2 = L.popup({maxWidth: '300'});

            
                var html_5379ea3a2e9e4747870c1a25130e7558 = $('<div id="html_5379ea3a2e9e4747870c1a25130e7558" style="width: 100.0%; height: 100.0%;">Glencairn , North York</div>')[0];
                popup_8bb137c6b64c405b8f555c929870ccc2.setContent(html_5379ea3a2e9e4747870c1a25130e7558);
            

            circle_marker_6ee4135b5551451f9b26457c266e1f49.bindPopup(popup_8bb137c6b64c405b8f555c929870ccc2);

            
        
    
            var circle_marker_b9a03ba7e0794c2cbd7acdebe03655d5 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_61215142e34e412cabc2eb6694a053ba = L.popup({maxWidth: '300'});

            
                var html_566e3d25a039401d8844991aeb101c7d = $('<div id="html_566e3d25a039401d8844991aeb101c7d" style="width: 100.0%; height: 100.0%;">Humewood-Cedarvale , York</div>')[0];
                popup_61215142e34e412cabc2eb6694a053ba.setContent(html_566e3d25a039401d8844991aeb101c7d);
            

            circle_marker_b9a03ba7e0794c2cbd7acdebe03655d5.bindPopup(popup_61215142e34e412cabc2eb6694a053ba);

            
        
    
            var circle_marker_b5d903a22c16472f9c3cb48209a7bac6 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_2b78cf418a374187a54db666d7c639bf = L.popup({maxWidth: '300'});

            
                var html_e80265b710eb416f8e5a58f69cc4b11a = $('<div id="html_e80265b710eb416f8e5a58f69cc4b11a" style="width: 100.0%; height: 100.0%;">Caledonia-Fairbanks , York</div>')[0];
                popup_2b78cf418a374187a54db666d7c639bf.setContent(html_e80265b710eb416f8e5a58f69cc4b11a);
            

            circle_marker_b5d903a22c16472f9c3cb48209a7bac6.bindPopup(popup_2b78cf418a374187a54db666d7c639bf);

            
        
    
            var circle_marker_b34222c856134db69f2b0db817dfa9d4 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_e80638efd49e4a4c97317c19c1873489 = L.popup({maxWidth: '300'});

            
                var html_e14952bd6bbf43c38034978921741ba9 = $('<div id="html_e14952bd6bbf43c38034978921741ba9" style="width: 100.0%; height: 100.0%;">Christie , Downtown Toronto</div>')[0];
                popup_e80638efd49e4a4c97317c19c1873489.setContent(html_e14952bd6bbf43c38034978921741ba9);
            

            circle_marker_b34222c856134db69f2b0db817dfa9d4.bindPopup(popup_e80638efd49e4a4c97317c19c1873489);

            
        
    
            var circle_marker_008dcac3281b4bfbb64524a465801934 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_8348d339aae340e49620218b8378e730 = L.popup({maxWidth: '300'});

            
                var html_2482fc2a8a94495bb8c735c7f34a14d2 = $('<div id="html_2482fc2a8a94495bb8c735c7f34a14d2" style="width: 100.0%; height: 100.0%;">Dovercourt Village , Dufferin , West Toronto</div>')[0];
                popup_8348d339aae340e49620218b8378e730.setContent(html_2482fc2a8a94495bb8c735c7f34a14d2);
            

            circle_marker_008dcac3281b4bfbb64524a465801934.bindPopup(popup_8348d339aae340e49620218b8378e730);

            
        
    
            var circle_marker_09b8882b176a4522b0d490fae9c7a730 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_81146450d6a349bd947acdfd3c5b7984 = L.popup({maxWidth: '300'});

            
                var html_6a236e9d766e4d40afb2dbf97d0e8bc2 = $('<div id="html_6a236e9d766e4d40afb2dbf97d0e8bc2" style="width: 100.0%; height: 100.0%;">Little Portugal , Trinity , West Toronto</div>')[0];
                popup_81146450d6a349bd947acdfd3c5b7984.setContent(html_6a236e9d766e4d40afb2dbf97d0e8bc2);
            

            circle_marker_09b8882b176a4522b0d490fae9c7a730.bindPopup(popup_81146450d6a349bd947acdfd3c5b7984);

            
        
    
            var circle_marker_240a669f0bef4776888be62279bd9798 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_4183fb7b2f73444d9f8a31b7ca204f98 = L.popup({maxWidth: '300'});

            
                var html_f67aabee9e844179995188bba292bbe4 = $('<div id="html_f67aabee9e844179995188bba292bbe4" style="width: 100.0%; height: 100.0%;">Brockton , Exhibition Place , Parkdale Village , West Toronto</div>')[0];
                popup_4183fb7b2f73444d9f8a31b7ca204f98.setContent(html_f67aabee9e844179995188bba292bbe4);
            

            circle_marker_240a669f0bef4776888be62279bd9798.bindPopup(popup_4183fb7b2f73444d9f8a31b7ca204f98);

            
        
    
            var circle_marker_6875569cabf94faabd9a24081431509c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_0999948887344a438824b1f14cd8dcaf = L.popup({maxWidth: '300'});

            
                var html_67cd357ccfad4ec4bb503932dde67068 = $('<div id="html_67cd357ccfad4ec4bb503932dde67068" style="width: 100.0%; height: 100.0%;">Downsview , North Park , Upwood Park , North York</div>')[0];
                popup_0999948887344a438824b1f14cd8dcaf.setContent(html_67cd357ccfad4ec4bb503932dde67068);
            

            circle_marker_6875569cabf94faabd9a24081431509c.bindPopup(popup_0999948887344a438824b1f14cd8dcaf);

            
        
    
            var circle_marker_7908efba410948d5ac150a5472aabde5 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_bf93fff31a30482fa6a068947697a60d = L.popup({maxWidth: '300'});

            
                var html_1ea350ff821a48e6bea94848cae7d82f = $('<div id="html_1ea350ff821a48e6bea94848cae7d82f" style="width: 100.0%; height: 100.0%;">Del Ray , Keelesdale , Mount Dennis , Silverthorn , York</div>')[0];
                popup_bf93fff31a30482fa6a068947697a60d.setContent(html_1ea350ff821a48e6bea94848cae7d82f);
            

            circle_marker_7908efba410948d5ac150a5472aabde5.bindPopup(popup_bf93fff31a30482fa6a068947697a60d);

            
        
    
            var circle_marker_8921b19c594f44e3b109d90fb9c65a9c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_5fd491145d15426788a951ef19da324d = L.popup({maxWidth: '300'});

            
                var html_254ae779af204aab93fbe8546b6d05ef = $('<div id="html_254ae779af204aab93fbe8546b6d05ef" style="width: 100.0%; height: 100.0%;">The Junction North , Runnymede , York</div>')[0];
                popup_5fd491145d15426788a951ef19da324d.setContent(html_254ae779af204aab93fbe8546b6d05ef);
            

            circle_marker_8921b19c594f44e3b109d90fb9c65a9c.bindPopup(popup_5fd491145d15426788a951ef19da324d);

            
        
    
            var circle_marker_156a4a409a174f9598ba4f27f52dbb54 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_facbab0e4d7140aa9d8993b79f1722db = L.popup({maxWidth: '300'});

            
                var html_6541ddefa7f54e7f85816cc35f24f6bc = $('<div id="html_6541ddefa7f54e7f85816cc35f24f6bc" style="width: 100.0%; height: 100.0%;">High Park , The Junction South , West Toronto</div>')[0];
                popup_facbab0e4d7140aa9d8993b79f1722db.setContent(html_6541ddefa7f54e7f85816cc35f24f6bc);
            

            circle_marker_156a4a409a174f9598ba4f27f52dbb54.bindPopup(popup_facbab0e4d7140aa9d8993b79f1722db);

            
        
    
            var circle_marker_7545c645fe52446cbe3a47480ebd11e4 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_edec747f355b4234952ffc1f73360fb4 = L.popup({maxWidth: '300'});

            
                var html_6808e0e1e63249629c46afba4a93dffc = $('<div id="html_6808e0e1e63249629c46afba4a93dffc" style="width: 100.0%; height: 100.0%;">Parkdale , Roncesvalles , West Toronto</div>')[0];
                popup_edec747f355b4234952ffc1f73360fb4.setContent(html_6808e0e1e63249629c46afba4a93dffc);
            

            circle_marker_7545c645fe52446cbe3a47480ebd11e4.bindPopup(popup_edec747f355b4234952ffc1f73360fb4);

            
        
    
            var circle_marker_e6e0a9ffce024e5a8b1bbad9b71d6b3c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_987d6dab14f1474abfe3cb653dd4b3e7 = L.popup({maxWidth: '300'});

            
                var html_544f7e920b8848b4bcb5da1b7cdfd15e = $('<div id="html_544f7e920b8848b4bcb5da1b7cdfd15e" style="width: 100.0%; height: 100.0%;">Runnymede , Swansea , West Toronto</div>')[0];
                popup_987d6dab14f1474abfe3cb653dd4b3e7.setContent(html_544f7e920b8848b4bcb5da1b7cdfd15e);
            

            circle_marker_e6e0a9ffce024e5a8b1bbad9b71d6b3c.bindPopup(popup_987d6dab14f1474abfe3cb653dd4b3e7);

            
        
    
            var circle_marker_71aae701ba1d4c88b046b82498a4e7f3 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_37fb1e2632b942bbb95e400adfc0c9fb = L.popup({maxWidth: '300'});

            
                var html_6510e3fb25314e7c87f2bb4582fc1096 = $('<div id="html_6510e3fb25314e7c87f2bb4582fc1096" style="width: 100.0%; height: 100.0%;">Not assigned , Queen&#39;s Park</div>')[0];
                popup_37fb1e2632b942bbb95e400adfc0c9fb.setContent(html_6510e3fb25314e7c87f2bb4582fc1096);
            

            circle_marker_71aae701ba1d4c88b046b82498a4e7f3.bindPopup(popup_37fb1e2632b942bbb95e400adfc0c9fb);

            
        
    
            var circle_marker_f1b28d15f21444b4a0be794e00e512dd = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_73694785bb064d0a801f816697038861 = L.popup({maxWidth: '300'});

            
                var html_095980d3fe11441dbd41a32740308ecf = $('<div id="html_095980d3fe11441dbd41a32740308ecf" style="width: 100.0%; height: 100.0%;">Canada Post Gateway Processing Centre , Mississauga</div>')[0];
                popup_73694785bb064d0a801f816697038861.setContent(html_095980d3fe11441dbd41a32740308ecf);
            

            circle_marker_f1b28d15f21444b4a0be794e00e512dd.bindPopup(popup_73694785bb064d0a801f816697038861);

            
        
    
            var circle_marker_0bd69f1e423f4bc084c0467de8bfd38b = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_4171e6199b4d44d9bfe691795189fe9d = L.popup({maxWidth: '300'});

            
                var html_17423dbf0fa1415885509bfa87ad24a2 = $('<div id="html_17423dbf0fa1415885509bfa87ad24a2" style="width: 100.0%; height: 100.0%;">Business Reply Mail Processing Centre 969 Eastern , East Toronto</div>')[0];
                popup_4171e6199b4d44d9bfe691795189fe9d.setContent(html_17423dbf0fa1415885509bfa87ad24a2);
            

            circle_marker_0bd69f1e423f4bc084c0467de8bfd38b.bindPopup(popup_4171e6199b4d44d9bfe691795189fe9d);

            
        
    
            var circle_marker_80fa68e7378c498cb1c04d277663fe9f = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_e0b9084f94034148ac8c98080416ac4a = L.popup({maxWidth: '300'});

            
                var html_4cc2bf62cf5a461aa53d7b61d73ff563 = $('<div id="html_4cc2bf62cf5a461aa53d7b61d73ff563" style="width: 100.0%; height: 100.0%;">Humber Bay Shores , Mimico South , New Toronto , Etobicoke</div>')[0];
                popup_e0b9084f94034148ac8c98080416ac4a.setContent(html_4cc2bf62cf5a461aa53d7b61d73ff563);
            

            circle_marker_80fa68e7378c498cb1c04d277663fe9f.bindPopup(popup_e0b9084f94034148ac8c98080416ac4a);

            
        
    
            var circle_marker_571541a1533643429603d68cce1c9a8d = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_56bac77e764a408d9a1641f2d134b5c8 = L.popup({maxWidth: '300'});

            
                var html_0fa51d3a20de42cb873f88f83d813c4e = $('<div id="html_0fa51d3a20de42cb873f88f83d813c4e" style="width: 100.0%; height: 100.0%;">Alderwood , Long Branch , Etobicoke</div>')[0];
                popup_56bac77e764a408d9a1641f2d134b5c8.setContent(html_0fa51d3a20de42cb873f88f83d813c4e);
            

            circle_marker_571541a1533643429603d68cce1c9a8d.bindPopup(popup_56bac77e764a408d9a1641f2d134b5c8);

            
        
    
            var circle_marker_1046702292ee4ca3aa4fc17249b3d549 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_30e56276d1234601b061e6bb9303a29d = L.popup({maxWidth: '300'});

            
                var html_1ea78c104a0b47308a53dd550092cb2a = $('<div id="html_1ea78c104a0b47308a53dd550092cb2a" style="width: 100.0%; height: 100.0%;">The Kingsway , Montgomery Road , Old Mill North , Etobicoke</div>')[0];
                popup_30e56276d1234601b061e6bb9303a29d.setContent(html_1ea78c104a0b47308a53dd550092cb2a);
            

            circle_marker_1046702292ee4ca3aa4fc17249b3d549.bindPopup(popup_30e56276d1234601b061e6bb9303a29d);

            
        
    
            var circle_marker_8211d34c53094fc7a39e481e958112a8 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_ff3979d0df444384805368161d08036b = L.popup({maxWidth: '300'});

            
                var html_2120553d59614371a2e843278c646a3f = $('<div id="html_2120553d59614371a2e843278c646a3f" style="width: 100.0%; height: 100.0%;">Humber Bay , King&#39;s Mill Park , Kingsway Park South East , Mimico NE , Old Mill South , The Queensway East , Royal York South East , Sunnylea , Etobicoke</div>')[0];
                popup_ff3979d0df444384805368161d08036b.setContent(html_2120553d59614371a2e843278c646a3f);
            

            circle_marker_8211d34c53094fc7a39e481e958112a8.bindPopup(popup_ff3979d0df444384805368161d08036b);

            
        
    
            var circle_marker_592a0e99fcee4dd4acb7193e95e375ab = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_d256166b5a5c40738a01615960bd8ea5 = L.popup({maxWidth: '300'});

            
                var html_1c334c70ee4a44a1a9077afb51033c30 = $('<div id="html_1c334c70ee4a44a1a9077afb51033c30" style="width: 100.0%; height: 100.0%;">Kingsway Park South West , Mimico NW , The Queensway West , Royal York South West , South of Bloor , Etobicoke</div>')[0];
                popup_d256166b5a5c40738a01615960bd8ea5.setContent(html_1c334c70ee4a44a1a9077afb51033c30);
            

            circle_marker_592a0e99fcee4dd4acb7193e95e375ab.bindPopup(popup_d256166b5a5c40738a01615960bd8ea5);

            
        
    
            var circle_marker_d6e41992fcb64aaa828a7ee89ac419cf = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_8925aafb19914dc9b87cf904732269ab = L.popup({maxWidth: '300'});

            
                var html_df21c56d086c47f9b50724eca0d62aa1 = $('<div id="html_df21c56d086c47f9b50724eca0d62aa1" style="width: 100.0%; height: 100.0%;">Islington Avenue , Etobicoke</div>')[0];
                popup_8925aafb19914dc9b87cf904732269ab.setContent(html_df21c56d086c47f9b50724eca0d62aa1);
            

            circle_marker_d6e41992fcb64aaa828a7ee89ac419cf.bindPopup(popup_8925aafb19914dc9b87cf904732269ab);

            
        
    
            var circle_marker_1bdf9297839c4d80b8e3ee574f681a9c = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_256d4c7c25314dda9c53a8dea44aa516 = L.popup({maxWidth: '300'});

            
                var html_9bf556422bb4474db90e3ec6af189e18 = $('<div id="html_9bf556422bb4474db90e3ec6af189e18" style="width: 100.0%; height: 100.0%;">Cloverdale , Islington , Martin Grove , Princess Gardens , West Deane Park , Etobicoke</div>')[0];
                popup_256d4c7c25314dda9c53a8dea44aa516.setContent(html_9bf556422bb4474db90e3ec6af189e18);
            

            circle_marker_1bdf9297839c4d80b8e3ee574f681a9c.bindPopup(popup_256d4c7c25314dda9c53a8dea44aa516);

            
        
    
            var circle_marker_1130693af92b42338990c816202d4726 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_77ae88c33bd54f44b75f62402998d154 = L.popup({maxWidth: '300'});

            
                var html_7372e691450e4f9bbc497edceb79e3f4 = $('<div id="html_7372e691450e4f9bbc497edceb79e3f4" style="width: 100.0%; height: 100.0%;">Bloordale Gardens , Eringate , Markland Wood , Old Burnhamthorpe , Etobicoke</div>')[0];
                popup_77ae88c33bd54f44b75f62402998d154.setContent(html_7372e691450e4f9bbc497edceb79e3f4);
            

            circle_marker_1130693af92b42338990c816202d4726.bindPopup(popup_77ae88c33bd54f44b75f62402998d154);

            
        
    
            var circle_marker_24447b35af3b4a3d82d343796e4f0b55 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_d6f0f81668b94f92bf4d5f2f81ccade6 = L.popup({maxWidth: '300'});

            
                var html_296f961b5e0143c4a09458d92de1ce98 = $('<div id="html_296f961b5e0143c4a09458d92de1ce98" style="width: 100.0%; height: 100.0%;">Humber Summit , North York</div>')[0];
                popup_d6f0f81668b94f92bf4d5f2f81ccade6.setContent(html_296f961b5e0143c4a09458d92de1ce98);
            

            circle_marker_24447b35af3b4a3d82d343796e4f0b55.bindPopup(popup_d6f0f81668b94f92bf4d5f2f81ccade6);

            
        
    
            var circle_marker_9b76c1cdf46d465a9bcfcd1c64aa882a = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_c4ae2c3e39d9453ca265df6e963942ad = L.popup({maxWidth: '300'});

            
                var html_3425aa46d5d34f2496842b2bdbb574f4 = $('<div id="html_3425aa46d5d34f2496842b2bdbb574f4" style="width: 100.0%; height: 100.0%;">Emery , Humberlea , North York</div>')[0];
                popup_c4ae2c3e39d9453ca265df6e963942ad.setContent(html_3425aa46d5d34f2496842b2bdbb574f4);
            

            circle_marker_9b76c1cdf46d465a9bcfcd1c64aa882a.bindPopup(popup_c4ae2c3e39d9453ca265df6e963942ad);

            
        
    
            var circle_marker_8295f5833b4f48b1ae20c36e9bf5011e = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_a2505e88d0174074b690fe6a74c23cb0 = L.popup({maxWidth: '300'});

            
                var html_10a746ec1baa49b087ea9adcad0efa7e = $('<div id="html_10a746ec1baa49b087ea9adcad0efa7e" style="width: 100.0%; height: 100.0%;">Weston , York</div>')[0];
                popup_a2505e88d0174074b690fe6a74c23cb0.setContent(html_10a746ec1baa49b087ea9adcad0efa7e);
            

            circle_marker_8295f5833b4f48b1ae20c36e9bf5011e.bindPopup(popup_a2505e88d0174074b690fe6a74c23cb0);

            
        
    
            var circle_marker_9d5622b687194ea2b31e575e5f7f312d = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_dc89c657165d427f84b224f754009366 = L.popup({maxWidth: '300'});

            
                var html_82b40bb9fe3048028d6b25c3bc2a42b9 = $('<div id="html_82b40bb9fe3048028d6b25c3bc2a42b9" style="width: 100.0%; height: 100.0%;">Westmount , Etobicoke</div>')[0];
                popup_dc89c657165d427f84b224f754009366.setContent(html_82b40bb9fe3048028d6b25c3bc2a42b9);
            

            circle_marker_9d5622b687194ea2b31e575e5f7f312d.bindPopup(popup_dc89c657165d427f84b224f754009366);

            
        
    
            var circle_marker_58bfaf3be3bd4966b0428604ad503ef6 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_ea99ccabf6f54b31b7e744f9699717c1 = L.popup({maxWidth: '300'});

            
                var html_1353203c418d4089a4ea36b7b2d11701 = $('<div id="html_1353203c418d4089a4ea36b7b2d11701" style="width: 100.0%; height: 100.0%;">Kingsview Village , Martin Grove Gardens , Richview Gardens , St. Phillips , Etobicoke</div>')[0];
                popup_ea99ccabf6f54b31b7e744f9699717c1.setContent(html_1353203c418d4089a4ea36b7b2d11701);
            

            circle_marker_58bfaf3be3bd4966b0428604ad503ef6.bindPopup(popup_ea99ccabf6f54b31b7e744f9699717c1);

            
        
    
            var circle_marker_0126c4bc43dd4805bf9250cc39df1c45 = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_2a6d437209c1463f929fafbc5b563c48 = L.popup({maxWidth: '300'});

            
                var html_d5777908080b4f079d8ca918fb16dbe1 = $('<div id="html_d5777908080b4f079d8ca918fb16dbe1" style="width: 100.0%; height: 100.0%;">Albion Gardens , Beaumond Heights , Humbergate , Jamestown , Mount Olive , Silverstone , South Steeles , Thistletown , Etobicoke</div>')[0];
                popup_2a6d437209c1463f929fafbc5b563c48.setContent(html_d5777908080b4f079d8ca918fb16dbe1);
            

            circle_marker_0126c4bc43dd4805bf9250cc39df1c45.bindPopup(popup_2a6d437209c1463f929fafbc5b563c48);

            
        
    
            var circle_marker_95ba196e180d4265aa4a097e3e1541ef = 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_6568f48dacbc4d47b196db0e807804fb);
            
    
            var popup_45419624a2704121b02002028a6afb8a = L.popup({maxWidth: '300'});

            
                var html_ec6cebe73ba24541b151a12a4c8f51ee = $('<div id="html_ec6cebe73ba24541b151a12a4c8f51ee" style="width: 100.0%; height: 100.0%;">Northwest , Etobicoke</div>')[0];
                popup_45419624a2704121b02002028a6afb8a.setContent(html_ec6cebe73ba24541b151a12a4c8f51ee);
            

            circle_marker_95ba196e180d4265aa4a097e3e1541ef.bindPopup(popup_45419624a2704121b02002028a6afb8a);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
],
"text/plain": [
"<folium.folium.Map at 0x7f7bc1715b70>"
]
},
"execution_count": 37,
"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['Neighborhood']):\n",
" label = '{}, {}'.format(neighborhood, borough)\n",
" label = folium.Popup(label, parse_html=True)\n",
" folium.CircleMarker(\n",
" [lat, lng],\n",
" radius=5,\n",
" popup=label,\n",
" color='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": [
"Define Foursquare credentials and version"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Your credentails:\n",
"CLIENT_ID: PA04CRFBNVV4WQU3UFGCK1PJLLR1PTXMDZQ0CMAUFYXKNLYS\n",
"CLIENT_SECRET:T0M2PTV1RT4ROGFBMTATPW042TBGXVEQ23WYNJRUZFFNWWB0\n"
]
}
],
"source": [
"CLIENT_ID = 'PA04CRFBNVV4WQU3UFGCK1PJLLR1PTXMDZQ0CMAUFYXKNLYS' # your Foursquare ID\n",
"CLIENT_SECRET = 'T0M2PTV1RT4ROGFBMTATPW042TBGXVEQ23WYNJRUZFFNWWB0' # your Foursquare Secret\n",
"VERSION = '20180605' # Foursquare API version\n",
"\n",
"print('Your credentails:')\n",
"print('CLIENT_ID: ' + CLIENT_ID)\n",
"print('CLIENT_SECRET:' + CLIENT_SECRET)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's explore the first borough in our dataframe"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Scarborough'"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_merged.loc[0, 'Borough']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Get the borough's latitude and longitude values."
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Latitude and longitude values of Scarborough are 43.806686299999996, -79.19435340000001.\n"
]
}
],
"source": [
"borough_latitude = df_merged.loc[0, 'Latitude'] # borough latitude value\n",
"borough_longitude = df_merged.loc[0, 'Longitude'] # borough longitude value\n",
"\n",
"borough_name = df_merged.loc[0, 'Borough'] # borough name\n",
"\n",
"print('Latitude and longitude values of {} are {}, {}.'.format(borough_name, \n",
" borough_latitude, \n",
" borough_longitude))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, let's get the top 50 venues that are in Marble Hill within a radius of 2000 meters."
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'https://api.foursquare.com/v2/venues/explore?&client_id=PA04CRFBNVV4WQU3UFGCK1PJLLR1PTXMDZQ0CMAUFYXKNLYS&client_secret=T0M2PTV1RT4ROGFBMTATPW042TBGXVEQ23WYNJRUZFFNWWB0&v=20180605&ll=43.806686299999996,-79.19435340000001&radius=1000&limit=50'"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LIMIT = 50 # limit of number of venues returned by Foursquare API\n",
"\n",
"radius = 1000 # define radius\n",
"\n",
"# create 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",
" borough_latitude, \n",
" borough_longitude, \n",
" radius, \n",
" LIMIT)\n",
"url # display URL"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'meta': {'code': 200, 'requestId': '5cb47661db04f530c743a0ec'},\n",
" 'response': {'suggestedFilters': {'header': 'Tap to show:',\n",
" 'filters': [{'name': 'Open now', 'key': 'openNow'}]},\n",
" 'headerLocation': 'Malvern',\n",
" 'headerFullLocation': 'Malvern, Toronto',\n",
" 'headerLocationGranularity': 'neighborhood',\n",
" 'totalResults': 15,\n",
" 'suggestedBounds': {'ne': {'lat': 43.81568630900001,\n",
" 'lng': -79.18190576146081},\n",
" 'sw': {'lat': 43.797686290999984, 'lng': -79.20680103853921}},\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': '4d669cba83865481c948fa53',\n",
" 'name': 'Images Salon & Spa',\n",
" 'location': {'address': '8130 Sheppard Ave E',\n",
" 'crossStreet': 'Morningside Ave',\n",
" 'lat': 43.80228301948931,\n",
" 'lng': -79.19856472801668,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.80228301948931,\n",
" 'lng': -79.19856472801668}],\n",
" 'distance': 595,\n",
" 'postalCode': 'M1B 3W3',\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['8130 Sheppard Ave E (Morningside Ave)',\n",
" 'Toronto ON M1B 3W3',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d1ed941735',\n",
" 'name': 'Spa',\n",
" 'pluralName': 'Spas',\n",
" 'shortName': 'Spa',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/spa_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4d669cba83865481c948fa53-0'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4b914562f964a520d4ae33e3',\n",
" 'name': 'Caribbean Wave',\n",
" 'location': {'address': '875 Milner Ave',\n",
" 'crossStreet': 'Milner and Morningside',\n",
" 'lat': 43.798557859976256,\n",
" 'lng': -79.19577725412623,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.798557859976256,\n",
" 'lng': -79.19577725412623}],\n",
" 'distance': 912,\n",
" 'postalCode': 'M1B',\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['875 Milner Ave (Milner and Morningside)',\n",
" 'Toronto ON M1B',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d144941735',\n",
" 'name': 'Caribbean Restaurant',\n",
" 'pluralName': 'Caribbean Restaurants',\n",
" 'shortName': 'Caribbean',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/caribbean_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4b914562f964a520d4ae33e3-1'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4b6718c2f964a5203f3a2be3',\n",
" 'name': \"Harvey's\",\n",
" 'location': {'address': '853 Milner Ave',\n",
" 'crossStreet': 'at Morningside Ave',\n",
" 'lat': 43.80010575211872,\n",
" 'lng': -79.19825833589329,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.80010575211872,\n",
" 'lng': -79.19825833589329}],\n",
" 'distance': 796,\n",
" 'postalCode': 'M1B 5N6',\n",
" 'cc': 'CA',\n",
" 'city': 'Scarborough',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['853 Milner Ave (at Morningside Ave)',\n",
" 'Scarborough ON M1B 5N6',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d16e941735',\n",
" 'name': 'Fast Food Restaurant',\n",
" 'pluralName': 'Fast Food Restaurants',\n",
" 'shortName': 'Fast Food',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/fastfood_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4b6718c2f964a5203f3a2be3-2'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4bcb612d3740b713f0606265',\n",
" 'name': 'Staples Morningside',\n",
" 'location': {'address': '850 Milner Avenue',\n",
" 'lat': 43.80028467632823,\n",
" 'lng': -79.19660657644272,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.80028467632823,\n",
" 'lng': -79.19660657644272}],\n",
" 'distance': 735,\n",
" 'postalCode': 'M1B 5N7',\n",
" 'cc': 'CA',\n",
" 'city': 'Scarborough',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['850 Milner Avenue',\n",
" 'Scarborough ON M1B 5N7',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d121951735',\n",
" 'name': 'Paper / Office Supplies Store',\n",
" 'pluralName': 'Paper / Office Supplies Stores',\n",
" 'shortName': 'Office Supplies',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/papergoods_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4bcb612d3740b713f0606265-3'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '579a91b3498e9bd833afa78a',\n",
" 'name': \"Wendy's\",\n",
" 'location': {'address': '8129 Sheppard Avenue',\n",
" 'lat': 43.8020084,\n",
" 'lng': -79.1980797,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.8020084,\n",
" 'lng': -79.1980797}],\n",
" 'distance': 600,\n",
" 'postalCode': 'M1B 6A3',\n",
" 'cc': 'CA',\n",
" 'city': 'Scarborough',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['8129 Sheppard Avenue',\n",
" 'Scarborough ON M1B 6A3',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d16e941735',\n",
" 'name': 'Fast Food Restaurant',\n",
" 'pluralName': 'Fast Food Restaurants',\n",
" 'shortName': 'Fast Food',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/fastfood_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-579a91b3498e9bd833afa78a-4'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4bb6b9446edc76b0d771311c',\n",
" 'name': \"Wendy's\",\n",
" 'location': {'crossStreet': 'Morningside & Sheppard',\n",
" 'lat': 43.80744841934756,\n",
" 'lng': -79.19905558052072,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.80744841934756,\n",
" 'lng': -79.19905558052072}],\n",
" 'distance': 387,\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['Toronto ON', 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d16e941735',\n",
" 'name': 'Fast Food Restaurant',\n",
" 'pluralName': 'Fast Food Restaurants',\n",
" 'shortName': 'Fast Food',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/fastfood_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4bb6b9446edc76b0d771311c-5'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4b16e23bf964a520edbe23e3',\n",
" 'name': 'Tim Hortons',\n",
" 'location': {'address': '8129 Sheppard Ave',\n",
" 'crossStreet': 'Morningside Ave',\n",
" 'lat': 43.801999861382,\n",
" 'lng': -79.1981689631939,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.801999861382,\n",
" 'lng': -79.1981689631939}],\n",
" 'distance': 605,\n",
" 'postalCode': 'M1B 6A3',\n",
" 'cc': 'CA',\n",
" 'city': 'Scarborough',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['8129 Sheppard Ave (Morningside Ave)',\n",
" 'Scarborough ON M1B 6A3',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d1e0931735',\n",
" 'name': 'Coffee Shop',\n",
" 'pluralName': 'Coffee Shops',\n",
" 'shortName': 'Coffee Shop',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/coffeeshop_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4b16e23bf964a520edbe23e3-6'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4bd08ceeb221c9b6cbe8d3d0',\n",
" 'name': 'Lee Valley',\n",
" 'location': {'address': '1275 Morningside',\n",
" 'lat': 43.803161304831846,\n",
" 'lng': -79.19968142252247,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.803161304831846,\n",
" 'lng': -79.19968142252247}],\n",
" 'distance': 580,\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['1275 Morningside', 'Toronto ON', 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d1fb941735',\n",
" 'name': 'Hobby Shop',\n",
" 'pluralName': 'Hobby Shops',\n",
" 'shortName': 'Hobbies',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/hobbyshop_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4bd08ceeb221c9b6cbe8d3d0-7'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4e0b137722713e13018e7117',\n",
" 'name': 'Tim Hortons / Esso',\n",
" 'location': {'address': 'Morningside and sheppard',\n",
" 'lat': 43.801659656390676,\n",
" 'lng': -79.1991327091692,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.801659656390676,\n",
" 'lng': -79.1991327091692}],\n",
" 'distance': 678,\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['Morningside and sheppard',\n",
" 'Toronto ON',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d1e0931735',\n",
" 'name': 'Coffee Shop',\n",
" 'pluralName': 'Coffee Shops',\n",
" 'shortName': 'Coffee Shop',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/coffeeshop_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4e0b137722713e13018e7117-8'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4ceaa2f0f8653704f906bec4',\n",
" 'name': 'Mr Jerk',\n",
" 'location': {'address': '1161 Morningside Avenue',\n",
" 'crossStreet': 'Morningside &Sheppard',\n",
" 'lat': 43.801262219554275,\n",
" 'lng': -79.19975818333775,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.801262219554275,\n",
" 'lng': -79.19975818333775}],\n",
" 'distance': 743,\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['1161 Morningside Avenue (Morningside &Sheppard)',\n",
" 'Toronto ON',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d1c8941735',\n",
" 'name': 'African Restaurant',\n",
" 'pluralName': 'African Restaurants',\n",
" 'shortName': 'African',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/african_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4ceaa2f0f8653704f906bec4-9'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4c706524df6b8cfab244b84d',\n",
" 'name': \"Charley's Exotic Cuisine\",\n",
" 'location': {'address': '3-1158 Morningside Ave',\n",
" 'crossStreet': 'Sheppard Ave',\n",
" 'lat': 43.80098159718747,\n",
" 'lng': -79.20023292303085,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.80098159718747,\n",
" 'lng': -79.20023292303085}],\n",
" 'distance': 791,\n",
" 'postalCode': 'M1B 3A4',\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['3-1158 Morningside Ave (Sheppard Ave)',\n",
" 'Toronto ON M1B 3A4',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d145941735',\n",
" 'name': 'Chinese Restaurant',\n",
" 'pluralName': 'Chinese Restaurants',\n",
" 'shortName': 'Chinese',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/asian_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4c706524df6b8cfab244b84d-10'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '539641d9498ee4f723c48089',\n",
" 'name': 'Fusion Supermarket',\n",
" 'location': {'address': '1150 Morningside Ave',\n",
" 'crossStreet': 'Milner',\n",
" 'lat': 43.800527899352915,\n",
" 'lng': -79.2000637571665,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.800527899352915,\n",
" 'lng': -79.2000637571665}],\n",
" 'distance': 824,\n",
" 'postalCode': 'M1B 3A4',\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['1150 Morningside Ave (Milner)',\n",
" 'Toronto ON M1B 3A4',\n",
" 'Canada']},\n",
" 'categories': [{'id': '52f2ab2ebcbc57f1066b8b1c',\n",
" 'name': 'Fruit & Vegetable Store',\n",
" 'pluralName': 'Fruit & Vegetable Stores',\n",
" 'shortName': 'Fruit & Vegetable Store',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/food_grocery_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-539641d9498ee4f723c48089-11'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '55e34982498ea9b7a8027f90',\n",
" 'name': 'Fit4Less',\n",
" 'location': {'address': '855 Milner Ave',\n",
" 'lat': 43.799668506947064,\n",
" 'lng': -79.19820682728174,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.799668506947064,\n",
" 'lng': -79.19820682728174}],\n",
" 'distance': 840,\n",
" 'postalCode': 'M1B 5N6',\n",
" 'cc': 'CA',\n",
" 'city': 'Scarborough',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['855 Milner Ave',\n",
" 'Scarborough ON M1B 5N6',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d176941735',\n",
" 'name': 'Gym',\n",
" 'pluralName': 'Gyms',\n",
" 'shortName': 'Gym',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/building/gym_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-55e34982498ea9b7a8027f90-12'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4b89abadf964a520ae4a32e3',\n",
" 'name': 'Quiznos',\n",
" 'location': {'address': '875 Milner Ave',\n",
" 'crossStreet': 'at Morningside Ave',\n",
" 'lat': 43.798773188206816,\n",
" 'lng': -79.19655550872147,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.798773188206816,\n",
" 'lng': -79.19655550872147}],\n",
" 'distance': 898,\n",
" 'postalCode': 'M1B 5N6',\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['875 Milner Ave (at Morningside Ave)',\n",
" 'Toronto ON M1B 5N6',\n",
" 'Canada']},\n",
" 'categories': [{'id': '4bf58dd8d48988d1c5941735',\n",
" 'name': 'Sandwich Place',\n",
" 'pluralName': 'Sandwich Places',\n",
" 'shortName': 'Sandwiches',\n",
" 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/deli_',\n",
" 'suffix': '.png'},\n",
" 'primary': True}],\n",
" 'photos': {'count': 0, 'groups': []}},\n",
" 'referralId': 'e-0-4b89abadf964a520ae4a32e3-13'},\n",
" {'reasons': {'count': 0,\n",
" 'items': [{'summary': 'This spot is popular',\n",
" 'type': 'general',\n",
" 'reasonName': 'globalInteractionReason'}]},\n",
" 'venue': {'id': '4fdb659ee4b0fcb93efc18d7',\n",
" 'name': 'joyce trimmer park',\n",
" 'location': {'address': '8450 Sheppard Ave E',\n",
" 'crossStreet': 'Conlins and Sheppard',\n",
" 'lat': 43.80626621064408,\n",
" 'lng': -79.18267533364352,\n",
" 'labeledLatLngs': [{'label': 'display',\n",
" 'lat': 43.80626621064408,\n",
" 'lng': -79.18267533364352}],\n",
" 'distance': 939,\n",
" 'cc': 'CA',\n",
" 'city': 'Toronto',\n",
" 'state': 'ON',\n",
" 'country': 'Canada',\n",
" 'formattedAddress': ['8450 Sheppard Ave E (Conlins and Sheppard)',\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-0-4fdb659ee4b0fcb93efc18d7-14'}]}]}}"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Get the results\n",
"results = requests.get(url).json()\n",
"results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Clean the json and structure it into a pandas dataframe."
]
},
{
"cell_type": "code",
"execution_count": 69,
"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": "code",
"execution_count": 70,
"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>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>Images Salon &amp; Spa</td>\n",
" <td>Spa</td>\n",
" <td>43.802283</td>\n",
" <td>-79.198565</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Caribbean Wave</td>\n",
" <td>Caribbean Restaurant</td>\n",
" <td>43.798558</td>\n",
" <td>-79.195777</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Harvey's</td>\n",
" <td>Fast Food Restaurant</td>\n",
" <td>43.800106</td>\n",
" <td>-79.198258</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Staples Morningside</td>\n",
" <td>Paper / Office Supplies Store</td>\n",
" <td>43.800285</td>\n",
" <td>-79.196607</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Wendy's</td>\n",
" <td>Fast Food Restaurant</td>\n",
" <td>43.802008</td>\n",
" <td>-79.198080</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name categories lat lng\n",
"0 Images Salon & Spa Spa 43.802283 -79.198565\n",
"1 Caribbean Wave Caribbean Restaurant 43.798558 -79.195777\n",
"2 Harvey's Fast Food Restaurant 43.800106 -79.198258\n",
"3 Staples Morningside Paper / Office Supplies Store 43.800285 -79.196607\n",
"4 Wendy's Fast Food Restaurant 43.802008 -79.198080"
]
},
"execution_count": 70,
"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": 71,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"15 venues were returned by Foursquare.\n"
]
}
],
"source": [
"print('{} venues were returned by Foursquare.'.format(nearby_venues.shape[0]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"create a function to repeat the same process to all boroughs in Toronto"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"def getNearbyVenues(names, latitudes, longitudes, radius=1000):\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 = ['Borough', \n",
" 'Borough Latitude', \n",
" 'Borough Longitude', \n",
" 'Venue', \n",
" 'Venue Latitude', \n",
" 'Venue Longitude', \n",
" 'Venue Category']\n",
" \n",
" return(nearby_venues)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"Scarborough\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"North York\n",
"East York\n",
"East York\n",
"East Toronto\n",
"East York\n",
"East York\n",
"East York\n",
"East Toronto\n",
"East Toronto\n",
"East Toronto\n",
"Central Toronto\n",
"Central Toronto\n",
"Central Toronto\n",
"Central Toronto\n",
"Central Toronto\n",
"Central Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"North York\n",
"Central Toronto\n",
"Central Toronto\n",
"Central Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"Downtown Toronto\n",
"North York\n",
"North York\n",
"York\n",
"York\n",
"Downtown Toronto\n",
"West Toronto\n",
"West Toronto\n",
"West Toronto\n",
"North York\n",
"York\n",
"York\n",
"West Toronto\n",
"West Toronto\n",
"West Toronto\n",
"Queen's Park\n",
"Mississauga\n",
"East Toronto\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"North York\n",
"North York\n",
"York\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n",
"Etobicoke\n"
]
}
],
"source": [
"#Toronto venues\n",
"toronto_venues = getNearbyVenues(names=df_merged['Borough'],\n",
" latitudes=df_merged['Latitude'],\n",
" longitudes=df_merged['Longitude']\n",
" )\n"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(3344, 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>Borough</th>\n",
" <th>Borough Latitude</th>\n",
" <th>Borough 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>Scarborough</td>\n",
" <td>43.806686</td>\n",
" <td>-79.194353</td>\n",
" <td>Images Salon &amp; Spa</td>\n",
" <td>43.802283</td>\n",
" <td>-79.198565</td>\n",
" <td>Spa</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Scarborough</td>\n",
" <td>43.806686</td>\n",
" <td>-79.194353</td>\n",
" <td>Caribbean Wave</td>\n",
" <td>43.798558</td>\n",
" <td>-79.195777</td>\n",
" <td>Caribbean Restaurant</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Scarborough</td>\n",
" <td>43.806686</td>\n",
" <td>-79.194353</td>\n",
" <td>Harvey's</td>\n",
" <td>43.800106</td>\n",
" <td>-79.198258</td>\n",
" <td>Fast Food Restaurant</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Scarborough</td>\n",
" <td>43.806686</td>\n",
" <td>-79.194353</td>\n",
" <td>Staples Morningside</td>\n",
" <td>43.800285</td>\n",
" <td>-79.196607</td>\n",
" <td>Paper / Office Supplies Store</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Scarborough</td>\n",
" <td>43.806686</td>\n",
" <td>-79.194353</td>\n",
" <td>Wendy's</td>\n",
" <td>43.802008</td>\n",
" <td>-79.198080</td>\n",
" <td>Fast Food Restaurant</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Borough Borough Latitude Borough Longitude Venue \\\n",
"0 Scarborough 43.806686 -79.194353 Images Salon & Spa \n",
"1 Scarborough 43.806686 -79.194353 Caribbean Wave \n",
"2 Scarborough 43.806686 -79.194353 Harvey's \n",
"3 Scarborough 43.806686 -79.194353 Staples Morningside \n",
"4 Scarborough 43.806686 -79.194353 Wendy's \n",
"\n",
" Venue Latitude Venue Longitude Venue Category \n",
"0 43.802283 -79.198565 Spa \n",
"1 43.798558 -79.195777 Caribbean Restaurant \n",
"2 43.800106 -79.198258 Fast Food Restaurant \n",
"3 43.800285 -79.196607 Paper / Office Supplies Store \n",
"4 43.802008 -79.198080 Fast Food Restaurant "
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(toronto_venues.shape)\n",
"toronto_venues.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's check how many venues were returned for each borough"
]
},
{
"cell_type": "code",
"execution_count": 77,
"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 Latitude</th>\n",
" <th>Borough 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>Borough</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>Central Toronto</th>\n",
" <td>366</td>\n",
" <td>366</td>\n",
" <td>366</td>\n",
" <td>366</td>\n",
" <td>366</td>\n",
" <td>366</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Downtown Toronto</th>\n",
" <td>826</td>\n",
" <td>826</td>\n",
" <td>826</td>\n",
" <td>826</td>\n",
" <td>826</td>\n",
" <td>826</td>\n",
" </tr>\n",
" <tr>\n",
" <th>East Toronto</th>\n",
" <td>248</td>\n",
" <td>248</td>\n",
" <td>248</td>\n",
" <td>248</td>\n",
" <td>248</td>\n",
" <td>248</td>\n",
" </tr>\n",
" <tr>\n",
" <th>East York</th>\n",
" <td>193</td>\n",
" <td>193</td>\n",
" <td>193</td>\n",
" <td>193</td>\n",
" <td>193</td>\n",
" <td>193</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Etobicoke</th>\n",
" <td>240</td>\n",
" <td>240</td>\n",
" <td>240</td>\n",
" <td>240</td>\n",
" <td>240</td>\n",
" <td>240</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Mississauga</th>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>North York</th>\n",
" <td>560</td>\n",
" <td>560</td>\n",
" <td>560</td>\n",
" <td>560</td>\n",
" <td>560</td>\n",
" <td>560</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Queen's Park</th>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Scarborough</th>\n",
" <td>380</td>\n",
" <td>380</td>\n",
" <td>380</td>\n",
" <td>380</td>\n",
" <td>380</td>\n",
" <td>380</td>\n",
" </tr>\n",
" <tr>\n",
" <th>West Toronto</th>\n",
" <td>300</td>\n",
" <td>300</td>\n",
" <td>300</td>\n",
" <td>300</td>\n",
" <td>300</td>\n",
" <td>300</td>\n",
" </tr>\n",
" <tr>\n",
" <th>York</th>\n",
" <td>131</td>\n",
" <td>131</td>\n",
" <td>131</td>\n",
" <td>131</td>\n",
" <td>131</td>\n",
" <td>131</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Borough Latitude Borough Longitude Venue Venue Latitude \\\n",
"Borough \n",
"Central Toronto 366 366 366 366 \n",
"Downtown Toronto 826 826 826 826 \n",
"East Toronto 248 248 248 248 \n",
"East York 193 193 193 193 \n",
"Etobicoke 240 240 240 240 \n",
"Mississauga 50 50 50 50 \n",
"North York 560 560 560 560 \n",
"Queen's Park 50 50 50 50 \n",
"Scarborough 380 380 380 380 \n",
"West Toronto 300 300 300 300 \n",
"York 131 131 131 131 \n",
"\n",
" Venue Longitude Venue Category \n",
"Borough \n",
"Central Toronto 366 366 \n",
"Downtown Toronto 826 826 \n",
"East Toronto 248 248 \n",
"East York 193 193 \n",
"Etobicoke 240 240 \n",
"Mississauga 50 50 \n",
"North York 560 560 \n",
"Queen's Park 50 50 \n",
"Scarborough 380 380 \n",
"West Toronto 300 300 \n",
"York 131 131 "
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"toronto_venues.groupby('Borough').count()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's find out how many unique categories can be curated from all the returned venues"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are 313 uniques categories.\n"
]
}
],
"source": [
"print('There are {} uniques categories.'.format(len(toronto_venues['Venue Category'].unique())))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Analyze Each Neighborhood"
]
},
{
"cell_type": "code",
"execution_count": 79,
"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>Accessories Store</th>\n",
" <th>Adult Boutique</th>\n",
" <th>Afghan Restaurant</th>\n",
" <th>African Restaurant</th>\n",
" <th>Airport</th>\n",
" <th>Airport Lounge</th>\n",
" <th>American Restaurant</th>\n",
" <th>Amphitheater</th>\n",
" <th>Animal Shelter</th>\n",
" <th>Antique Shop</th>\n",
" <th>Aquarium</th>\n",
" <th>Art Gallery</th>\n",
" <th>Art Museum</th>\n",
" <th>Arts &amp; Crafts Store</th>\n",
" <th>Asian Restaurant</th>\n",
" <th>Athletics &amp; Sports</th>\n",
" <th>Auto Dealership</th>\n",
" <th>Auto Garage</th>\n",
" <th>Automotive Shop</th>\n",
" <th>BBQ Joint</th>\n",
" <th>Baby Store</th>\n",
" <th>Badminton Court</th>\n",
" <th>Bagel Shop</th>\n",
" <th>Bakery</th>\n",
" <th>Bank</th>\n",
" <th>Bar</th>\n",
" <th>Baseball Field</th>\n",
" <th>Baseball Stadium</th>\n",
" <th>Basketball Court</th>\n",
" <th>Basketball Stadium</th>\n",
" <th>Beach</th>\n",
" <th>Beach Bar</th>\n",
" <th>Beer Bar</th>\n",
" <th>Beer Store</th>\n",
" <th>Belgian Restaurant</th>\n",
" <th>Bike Shop</th>\n",
" <th>Bistro</th>\n",
" <th>Bookstore</th>\n",
" <th>Boutique</th>\n",
" <th>Bowling Alley</th>\n",
" <th>Brazilian Restaurant</th>\n",
" <th>Breakfast Spot</th>\n",
" <th>Brewery</th>\n",
" <th>Bridal Shop</th>\n",
" <th>Bridge</th>\n",
" <th>Bubble Tea Shop</th>\n",
" <th>Burger Joint</th>\n",
" <th>Burrito Place</th>\n",
" <th>Bus Line</th>\n",
" <th>Bus Station</th>\n",
" <th>Bus Stop</th>\n",
" <th>Business Service</th>\n",
" <th>Butcher</th>\n",
" <th>Cafeteria</th>\n",
" <th>Café</th>\n",
" <th>Cajun / Creole Restaurant</th>\n",
" <th>Candy Store</th>\n",
" <th>Cantonese Restaurant</th>\n",
" <th>Caribbean Restaurant</th>\n",
" <th>Castle</th>\n",
" <th>Cemetery</th>\n",
" <th>Check Cashing Service</th>\n",
" <th>Cheese Shop</th>\n",
" <th>Chinese Restaurant</th>\n",
" <th>Chiropractor</th>\n",
" <th>Chocolate Shop</th>\n",
" <th>Church</th>\n",
" <th>Churrascaria</th>\n",
" <th>Climbing Gym</th>\n",
" <th>Clothing Store</th>\n",
" <th>Cocktail Bar</th>\n",
" <th>Coffee Shop</th>\n",
" <th>College Gym</th>\n",
" <th>College Quad</th>\n",
" <th>College Rec Center</th>\n",
" <th>College Stadium</th>\n",
" <th>Comedy Club</th>\n",
" <th>Comfort Food Restaurant</th>\n",
" <th>Comic Shop</th>\n",
" <th>Community Center</th>\n",
" <th>Concert Hall</th>\n",
" <th>Construction &amp; Landscaping</th>\n",
" <th>Convenience Store</th>\n",
" <th>Cosmetics Shop</th>\n",
" <th>Coworking Space</th>\n",
" <th>Creperie</th>\n",
" <th>Cuban Restaurant</th>\n",
" <th>Cupcake Shop</th>\n",
" <th>Curling Ice</th>\n",
" <th>Dance Studio</th>\n",
" <th>Deli / Bodega</th>\n",
" <th>Department Store</th>\n",
" <th>Design Studio</th>\n",
" <th>Dessert Shop</th>\n",
" <th>Dim Sum Restaurant</th>\n",
" <th>Diner</th>\n",
" <th>Discount Store</th>\n",
" <th>Dive Bar</th>\n",
" <th>Dog Run</th>\n",
" <th>Doner Restaurant</th>\n",
" <th>Donut Shop</th>\n",
" <th>Dumpling Restaurant</th>\n",
" <th>Eastern European Restaurant</th>\n",
" <th>Electronics Store</th>\n",
" <th>Elementary School</th>\n",
" <th>Empanada Restaurant</th>\n",
" <th>Ethiopian Restaurant</th>\n",
" <th>Event Space</th>\n",
" <th>Falafel Restaurant</th>\n",
" <th>Farm</th>\n",
" <th>Farmers Market</th>\n",
" <th>Fast Food Restaurant</th>\n",
" <th>Field</th>\n",
" <th>Filipino Restaurant</th>\n",
" <th>Fireworks Store</th>\n",
" <th>Fish &amp; Chips Shop</th>\n",
" <th>Fish Market</th>\n",
" <th>Flea Market</th>\n",
" <th>Flower Shop</th>\n",
" <th>Food</th>\n",
" <th>Food &amp; Drink Shop</th>\n",
" <th>Food Court</th>\n",
" <th>Food Truck</th>\n",
" <th>Fountain</th>\n",
" <th>Frame Store</th>\n",
" <th>French Restaurant</th>\n",
" <th>Fried Chicken Joint</th>\n",
" <th>Frozen Yogurt Shop</th>\n",
" <th>Fruit &amp; Vegetable Store</th>\n",
" <th>Furniture / Home Store</th>\n",
" <th>Gaming Cafe</th>\n",
" <th>Garden</th>\n",
" <th>Garden Center</th>\n",
" <th>Gas Station</th>\n",
" <th>Gastropub</th>\n",
" <th>Gay Bar</th>\n",
" <th>General Entertainment</th>\n",
" <th>German Restaurant</th>\n",
" <th>Gift Shop</th>\n",
" <th>Golf Course</th>\n",
" <th>Golf Driving Range</th>\n",
" <th>Gourmet Shop</th>\n",
" <th>Greek Restaurant</th>\n",
" <th>Grocery Store</th>\n",
" <th>Gym</th>\n",
" <th>Gym / Fitness Center</th>\n",
" <th>Gym Pool</th>\n",
" <th>Hakka Restaurant</th>\n",
" <th>Harbor / Marina</th>\n",
" <th>Hardware Store</th>\n",
" <th>Hawaiian Restaurant</th>\n",
" <th>Health Food Store</th>\n",
" <th>Historic Site</th>\n",
" <th>History Museum</th>\n",
" <th>Hobby Shop</th>\n",
" <th>Hockey Arena</th>\n",
" <th>Home Service</th>\n",
" <th>Hong Kong Restaurant</th>\n",
" <th>Hookah Bar</th>\n",
" <th>Hostel</th>\n",
" <th>Hot Dog Joint</th>\n",
" <th>Hotel</th>\n",
" <th>Hotpot Restaurant</th>\n",
" <th>Housing Development</th>\n",
" <th>Ice Cream Shop</th>\n",
" <th>Indian Chinese Restaurant</th>\n",
" <th>Indian Restaurant</th>\n",
" <th>Indie Movie Theater</th>\n",
" <th>Indie Theater</th>\n",
" <th>Indonesian Restaurant</th>\n",
" <th>Intersection</th>\n",
" <th>Italian Restaurant</th>\n",
" <th>Japanese Restaurant</th>\n",
" <th>Jazz Club</th>\n",
" <th>Jewelry Store</th>\n",
" <th>Jewish Restaurant</th>\n",
" <th>Juice Bar</th>\n",
" <th>Kitchen Supply Store</th>\n",
" <th>Korean Restaurant</th>\n",
" <th>Lake</th>\n",
" <th>Latin American Restaurant</th>\n",
" <th>Laundromat</th>\n",
" <th>Laundry Service</th>\n",
" <th>Light Rail Station</th>\n",
" <th>Liquor Store</th>\n",
" <th>Lounge</th>\n",
" <th>Mac &amp; Cheese Joint</th>\n",
" <th>Malay Restaurant</th>\n",
" <th>Market</th>\n",
" <th>Martial Arts Dojo</th>\n",
" <th>Massage Studio</th>\n",
" <th>Mediterranean Restaurant</th>\n",
" <th>Men's Store</th>\n",
" <th>Metro Station</th>\n",
" <th>Mexican Restaurant</th>\n",
" <th>Middle Eastern Restaurant</th>\n",
" <th>Miscellaneous Shop</th>\n",
" <th>Mobile Phone Shop</th>\n",
" <th>Modern European Restaurant</th>\n",
" <th>Monument / Landmark</th>\n",
" <th>Moroccan Restaurant</th>\n",
" <th>Motorcycle Shop</th>\n",
" <th>Movie Theater</th>\n",
" <th>Museum</th>\n",
" <th>Music School</th>\n",
" <th>Music Store</th>\n",
" <th>Music Venue</th>\n",
" <th>Nail Salon</th>\n",
" <th>Neighborhood</th>\n",
" <th>New American Restaurant</th>\n",
" <th>Nightclub</th>\n",
" <th>Noodle House</th>\n",
" <th>Office</th>\n",
" <th>Opera House</th>\n",
" <th>Optical Shop</th>\n",
" <th>Organic Grocery</th>\n",
" <th>Other Great Outdoors</th>\n",
" <th>Other Repair Shop</th>\n",
" <th>Pakistani Restaurant</th>\n",
" <th>Paper / Office Supplies Store</th>\n",
" <th>Park</th>\n",
" <th>Pastry Shop</th>\n",
" <th>Performing Arts Venue</th>\n",
" <th>Persian Restaurant</th>\n",
" <th>Pet Store</th>\n",
" <th>Pharmacy</th>\n",
" <th>Photography Lab</th>\n",
" <th>Pie Shop</th>\n",
" <th>Pilates Studio</th>\n",
" <th>Pizza Place</th>\n",
" <th>Playground</th>\n",
" <th>Plaza</th>\n",
" <th>Poke Place</th>\n",
" <th>Pool</th>\n",
" <th>Pool Hall</th>\n",
" <th>Portuguese Restaurant</th>\n",
" <th>Poutine Place</th>\n",
" <th>Pub</th>\n",
" <th>Ramen Restaurant</th>\n",
" <th>Record Shop</th>\n",
" <th>Recreation Center</th>\n",
" <th>Rental Car Location</th>\n",
" <th>Residential Building (Apartment / Condo)</th>\n",
" <th>Restaurant</th>\n",
" <th>River</th>\n",
" <th>Road</th>\n",
" <th>Rock Climbing Spot</th>\n",
" <th>Rock Club</th>\n",
" <th>Salad Place</th>\n",
" <th>Salon / Barbershop</th>\n",
" <th>Sandwich Place</th>\n",
" <th>Scenic Lookout</th>\n",
" <th>School</th>\n",
" <th>Sculpture Garden</th>\n",
" <th>Seafood Restaurant</th>\n",
" <th>Shanghai Restaurant</th>\n",
" <th>Shoe Store</th>\n",
" <th>Shop &amp; Service</th>\n",
" <th>Shopping Mall</th>\n",
" <th>Skate Park</th>\n",
" <th>Skating Rink</th>\n",
" <th>Ski Area</th>\n",
" <th>Ski Chalet</th>\n",
" <th>Smoke Shop</th>\n",
" <th>Smoothie Shop</th>\n",
" <th>Snack Place</th>\n",
" <th>Soccer Field</th>\n",
" <th>Soccer Stadium</th>\n",
" <th>Social Club</th>\n",
" <th>Soup Place</th>\n",
" <th>South American Restaurant</th>\n",
" <th>Spa</th>\n",
" <th>Spanish Restaurant</th>\n",
" <th>Speakeasy</th>\n",
" <th>Sporting Goods Shop</th>\n",
" <th>Sports Bar</th>\n",
" <th>Sports Club</th>\n",
" <th>Sri Lankan Restaurant</th>\n",
" <th>Stadium</th>\n",
" <th>Stationery Store</th>\n",
" <th>Steakhouse</th>\n",
" <th>Storage Facility</th>\n",
" <th>Supermarket</th>\n",
" <th>Supplement Shop</th>\n",
" <th>Sushi Restaurant</th>\n",
" <th>Taco Place</th>\n",
" <th>Tailor Shop</th>\n",
" <th>Taiwanese Restaurant</th>\n",
" <th>Tanning Salon</th>\n",
" <th>Tapas Restaurant</th>\n",
" <th>Tea Room</th>\n",
" <th>Tech Startup</th>\n",
" <th>Tennis Court</th>\n",
" <th>Thai Restaurant</th>\n",
" <th>Theater</th>\n",
" <th>Theme Restaurant</th>\n",
" <th>Thrift / Vintage Store</th>\n",
" <th>Tibetan Restaurant</th>\n",
" <th>Toy / Game Store</th>\n",
" <th>Track</th>\n",
" <th>Trail</th>\n",
" <th>Train Station</th>\n",
" <th>Turkish Restaurant</th>\n",
" <th>Vegetarian / Vegan Restaurant</th>\n",
" <th>Video Game Store</th>\n",
" <th>Video Store</th>\n",
" <th>Vietnamese Restaurant</th>\n",
" <th>Warehouse Store</th>\n",
" <th>Wine Bar</th>\n",
" <th>Wine Shop</th>\n",
" <th>Wings Joint</th>\n",
" <th>Women's Store</th>\n",
" <th>Yoga Studio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Scarborough</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Scarborough</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Scarborough</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <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>Scarborough</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>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>Scarborough</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Borough Accessories Store Adult Boutique Afghan Restaurant \\\n",
"0 Scarborough 0 0 0 \n",
"1 Scarborough 0 0 0 \n",
"2 Scarborough 0 0 0 \n",
"3 Scarborough 0 0 0 \n",
"4 Scarborough 0 0 0 \n",
"\n",
" African Restaurant Airport Airport Lounge American Restaurant \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Amphitheater Animal Shelter Antique Shop Aquarium Art Gallery \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Art Museum Arts & Crafts Store Asian Restaurant Athletics & Sports \\\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",
" Auto Dealership Auto Garage Automotive Shop BBQ Joint Baby Store \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Badminton Court Bagel Shop Bakery Bank Bar Baseball Field \\\n",
"0 0 0 0 0 0 0 \n",
"1 0 0 0 0 0 0 \n",
"2 0 0 0 0 0 0 \n",
"3 0 0 0 0 0 0 \n",
"4 0 0 0 0 0 0 \n",
"\n",
" Baseball Stadium Basketball Court Basketball Stadium Beach Beach Bar \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Beer Bar Beer Store Belgian Restaurant Bike Shop Bistro Bookstore \\\n",
"0 0 0 0 0 0 0 \n",
"1 0 0 0 0 0 0 \n",
"2 0 0 0 0 0 0 \n",
"3 0 0 0 0 0 0 \n",
"4 0 0 0 0 0 0 \n",
"\n",
" Boutique Bowling Alley Brazilian Restaurant Breakfast Spot Brewery \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Bridal Shop Bridge Bubble Tea Shop Burger Joint Burrito Place \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Bus Line Bus Station Bus Stop Business Service Butcher Cafeteria \\\n",
"0 0 0 0 0 0 0 \n",
"1 0 0 0 0 0 0 \n",
"2 0 0 0 0 0 0 \n",
"3 0 0 0 0 0 0 \n",
"4 0 0 0 0 0 0 \n",
"\n",
" Café Cajun / Creole Restaurant Candy Store Cantonese 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",
" Caribbean Restaurant Castle Cemetery Check Cashing Service Cheese Shop \\\n",
"0 0 0 0 0 0 \n",
"1 1 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Chinese Restaurant Chiropractor Chocolate Shop Church Churrascaria \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Climbing Gym Clothing Store Cocktail Bar Coffee Shop College Gym \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" College Quad College Rec Center College Stadium Comedy Club \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Comfort Food Restaurant Comic Shop Community Center Concert Hall \\\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",
" Construction & Landscaping Convenience Store Cosmetics Shop \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Coworking Space Creperie Cuban Restaurant Cupcake Shop Curling Ice \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Dance Studio Deli / Bodega Department Store Design Studio Dessert Shop \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Dim Sum Restaurant Diner Discount Store Dive Bar Dog Run \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Doner Restaurant Donut Shop Dumpling Restaurant \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Eastern European Restaurant Electronics Store Elementary School \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Empanada Restaurant Ethiopian Restaurant Event Space Falafel 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",
" Farm Farmers Market Fast Food Restaurant Field Filipino Restaurant \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 1 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 1 0 0 \n",
"\n",
" Fireworks Store Fish & Chips Shop Fish Market Flea Market Flower Shop \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Food Food & Drink Shop Food Court Food Truck Fountain Frame Store \\\n",
"0 0 0 0 0 0 0 \n",
"1 0 0 0 0 0 0 \n",
"2 0 0 0 0 0 0 \n",
"3 0 0 0 0 0 0 \n",
"4 0 0 0 0 0 0 \n",
"\n",
" French Restaurant Fried Chicken Joint Frozen Yogurt Shop \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Fruit & Vegetable Store Furniture / Home Store Gaming Cafe Garden \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Garden Center Gas Station Gastropub Gay Bar General Entertainment \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" German Restaurant Gift Shop Golf Course Golf Driving Range \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Gourmet Shop Greek Restaurant Grocery Store Gym Gym / Fitness Center \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Gym Pool Hakka Restaurant Harbor / Marina Hardware Store \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Hawaiian Restaurant Health Food Store Historic Site History Museum \\\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",
" Hobby Shop Hockey Arena Home Service Hong Kong Restaurant Hookah Bar \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Hostel Hot Dog Joint Hotel Hotpot Restaurant Housing Development \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Ice Cream Shop Indian Chinese Restaurant Indian Restaurant \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Indie Movie Theater Indie Theater Indonesian Restaurant Intersection \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Italian Restaurant Japanese Restaurant Jazz Club Jewelry Store \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Jewish Restaurant Juice Bar Kitchen Supply Store Korean 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",
" Lake Latin American Restaurant Laundromat Laundry Service \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Light Rail Station Liquor Store Lounge Mac & Cheese Joint \\\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",
" Malay Restaurant Market Martial Arts Dojo Massage Studio \\\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",
" Mediterranean Restaurant Men's Store Metro Station Mexican Restaurant \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Middle Eastern Restaurant Miscellaneous Shop Mobile Phone Shop \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Modern European Restaurant Monument / Landmark Moroccan Restaurant \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Motorcycle Shop Movie Theater Museum Music School Music Store \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Music Venue Nail Salon Neighborhood New American Restaurant Nightclub \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Noodle House Office Opera House Optical Shop Organic Grocery \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Other Great Outdoors Other Repair Shop Pakistani Restaurant \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Paper / Office Supplies Store Park Pastry Shop Performing Arts Venue \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 1 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Persian Restaurant Pet Store Pharmacy Photography Lab Pie Shop \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Pilates Studio Pizza Place Playground Plaza Poke Place Pool \\\n",
"0 0 0 0 0 0 0 \n",
"1 0 0 0 0 0 0 \n",
"2 0 0 0 0 0 0 \n",
"3 0 0 0 0 0 0 \n",
"4 0 0 0 0 0 0 \n",
"\n",
" Pool Hall Portuguese Restaurant Poutine Place Pub Ramen Restaurant \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Record Shop Recreation Center Rental Car Location \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Residential Building (Apartment / Condo) Restaurant River Road \\\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",
" Rock Climbing Spot Rock Club Salad Place Salon / Barbershop \\\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",
" Sandwich Place Scenic Lookout School Sculpture Garden \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Seafood Restaurant Shanghai Restaurant Shoe Store Shop & Service \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Shopping Mall Skate Park Skating Rink Ski Area Ski Chalet Smoke Shop \\\n",
"0 0 0 0 0 0 0 \n",
"1 0 0 0 0 0 0 \n",
"2 0 0 0 0 0 0 \n",
"3 0 0 0 0 0 0 \n",
"4 0 0 0 0 0 0 \n",
"\n",
" Smoothie Shop Snack Place Soccer Field Soccer Stadium Social Club \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Soup Place South American Restaurant Spa Spanish Restaurant Speakeasy \\\n",
"0 0 0 1 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Sporting Goods Shop Sports Bar Sports Club Sri Lankan 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",
" Stadium Stationery Store Steakhouse Storage Facility Supermarket \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Supplement Shop Sushi Restaurant Taco Place Tailor Shop \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Taiwanese Restaurant Tanning Salon Tapas Restaurant Tea Room \\\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",
" Tech Startup Tennis Court Thai Restaurant Theater Theme Restaurant \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Thrift / Vintage Store Tibetan Restaurant Toy / Game Store Track Trail \\\n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 \n",
"\n",
" Train Station Turkish Restaurant Vegetarian / Vegan Restaurant \\\n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"\n",
" Video Game Store Video Store Vietnamese Restaurant Warehouse Store \\\n",
"0 0 0 0 0 \n",
"1 0 0 0 0 \n",
"2 0 0 0 0 \n",
"3 0 0 0 0 \n",
"4 0 0 0 0 \n",
"\n",
" Wine Bar Wine Shop Wings Joint Women's Store Yoga Studio \n",
"0 0 0 0 0 0 \n",
"1 0 0 0 0 0 \n",
"2 0 0 0 0 0 \n",
"3 0 0 0 0 0 \n",
"4 0 0 0 0 0 "
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# one hot encoding\n",
"toronto_onehot = pd.get_dummies(toronto_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
"\n",
"# add neighborhood column back to dataframe\n",
"toronto_onehot['Borough'] = toronto_venues['Borough'] \n",
"\n",
"# move neighborhood column to the first column\n",
"fixed_columns = [toronto_onehot.columns[-1]] + list(toronto_onehot.columns[:-1])\n",
"toronto_onehot = toronto_onehot[fixed_columns]\n",
"\n",
"toronto_onehot.head()"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(3344, 314)"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"toronto_onehot.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category"
]
},
{
"cell_type": "code",
"execution_count": 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>Borough</th>\n",
" <th>Accessories Store</th>\n",
" <th>Adult Boutique</th>\n",
" <th>Afghan Restaurant</th>\n",
" <th>African Restaurant</th>\n",
" <th>Airport</th>\n",
" <th>Airport Lounge</th>\n",
" <th>American Restaurant</th>\n",
" <th>Amphitheater</th>\n",
" <th>Animal Shelter</th>\n",
" <th>Antique Shop</th>\n",
" <th>Aquarium</th>\n",
" <th>Art Gallery</th>\n",
" <th>Art Museum</th>\n",
" <th>Arts &amp; Crafts Store</th>\n",
" <th>Asian Restaurant</th>\n",
" <th>Athletics &amp; Sports</th>\n",
" <th>Auto Dealership</th>\n",
" <th>Auto Garage</th>\n",
" <th>Automotive Shop</th>\n",
" <th>BBQ Joint</th>\n",
" <th>Baby Store</th>\n",
" <th>Badminton Court</th>\n",
" <th>Bagel Shop</th>\n",
" <th>Bakery</th>\n",
" <th>Bank</th>\n",
" <th>Bar</th>\n",
" <th>Baseball Field</th>\n",
" <th>Baseball Stadium</th>\n",
" <th>Basketball Court</th>\n",
" <th>Basketball Stadium</th>\n",
" <th>Beach</th>\n",
" <th>Beach Bar</th>\n",
" <th>Beer Bar</th>\n",
" <th>Beer Store</th>\n",
" <th>Belgian Restaurant</th>\n",
" <th>Bike Shop</th>\n",
" <th>Bistro</th>\n",
" <th>Bookstore</th>\n",
" <th>Boutique</th>\n",
" <th>Bowling Alley</th>\n",
" <th>Brazilian Restaurant</th>\n",
" <th>Breakfast Spot</th>\n",
" <th>Brewery</th>\n",
" <th>Bridal Shop</th>\n",
" <th>Bridge</th>\n",
" <th>Bubble Tea Shop</th>\n",
" <th>Burger Joint</th>\n",
" <th>Burrito Place</th>\n",
" <th>Bus Line</th>\n",
" <th>Bus Station</th>\n",
" <th>Bus Stop</th>\n",
" <th>Business Service</th>\n",
" <th>Butcher</th>\n",
" <th>Cafeteria</th>\n",
" <th>Café</th>\n",
" <th>Cajun / Creole Restaurant</th>\n",
" <th>Candy Store</th>\n",
" <th>Cantonese Restaurant</th>\n",
" <th>Caribbean Restaurant</th>\n",
" <th>Castle</th>\n",
" <th>Cemetery</th>\n",
" <th>Check Cashing Service</th>\n",
" <th>Cheese Shop</th>\n",
" <th>Chinese Restaurant</th>\n",
" <th>Chiropractor</th>\n",
" <th>Chocolate Shop</th>\n",
" <th>Church</th>\n",
" <th>Churrascaria</th>\n",
" <th>Climbing Gym</th>\n",
" <th>Clothing Store</th>\n",
" <th>Cocktail Bar</th>\n",
" <th>Coffee Shop</th>\n",
" <th>College Gym</th>\n",
" <th>College Quad</th>\n",
" <th>College Rec Center</th>\n",
" <th>College Stadium</th>\n",
" <th>Comedy Club</th>\n",
" <th>Comfort Food Restaurant</th>\n",
" <th>Comic Shop</th>\n",
" <th>Community Center</th>\n",
" <th>Concert Hall</th>\n",
" <th>Construction &amp; Landscaping</th>\n",
" <th>Convenience Store</th>\n",
" <th>Cosmetics Shop</th>\n",
" <th>Coworking Space</th>\n",
" <th>Creperie</th>\n",
" <th>Cuban Restaurant</th>\n",
" <th>Cupcake Shop</th>\n",
" <th>Curling Ice</th>\n",
" <th>Dance Studio</th>\n",
" <th>Deli / Bodega</th>\n",
" <th>Department Store</th>\n",
" <th>Design Studio</th>\n",
" <th>Dessert Shop</th>\n",
" <th>Dim Sum Restaurant</th>\n",
" <th>Diner</th>\n",
" <th>Discount Store</th>\n",
" <th>Dive Bar</th>\n",
" <th>Dog Run</th>\n",
" <th>Doner Restaurant</th>\n",
" <th>Donut Shop</th>\n",
" <th>Dumpling Restaurant</th>\n",
" <th>Eastern European Restaurant</th>\n",
" <th>Electronics Store</th>\n",
" <th>Elementary School</th>\n",
" <th>Empanada Restaurant</th>\n",
" <th>Ethiopian Restaurant</th>\n",
" <th>Event Space</th>\n",
" <th>Falafel Restaurant</th>\n",
" <th>Farm</th>\n",
" <th>Farmers Market</th>\n",
" <th>Fast Food Restaurant</th>\n",
" <th>Field</th>\n",
" <th>Filipino Restaurant</th>\n",
" <th>Fireworks Store</th>\n",
" <th>Fish &amp; Chips Shop</th>\n",
" <th>Fish Market</th>\n",
" <th>Flea Market</th>\n",
" <th>Flower Shop</th>\n",
" <th>Food</th>\n",
" <th>Food &amp; Drink Shop</th>\n",
" <th>Food Court</th>\n",
" <th>Food Truck</th>\n",
" <th>Fountain</th>\n",
" <th>Frame Store</th>\n",
" <th>French Restaurant</th>\n",
" <th>Fried Chicken Joint</th>\n",
" <th>Frozen Yogurt Shop</th>\n",
" <th>Fruit &amp; Vegetable Store</th>\n",
" <th>Furniture / Home Store</th>\n",
" <th>Gaming Cafe</th>\n",
" <th>Garden</th>\n",
" <th>Garden Center</th>\n",
" <th>Gas Station</th>\n",
" <th>Gastropub</th>\n",
" <th>Gay Bar</th>\n",
" <th>General Entertainment</th>\n",
" <th>German Restaurant</th>\n",
" <th>Gift Shop</th>\n",
" <th>Golf Course</th>\n",
" <th>Golf Driving Range</th>\n",
" <th>Gourmet Shop</th>\n",
" <th>Greek Restaurant</th>\n",
" <th>Grocery Store</th>\n",
" <th>Gym</th>\n",
" <th>Gym / Fitness Center</th>\n",
" <th>Gym Pool</th>\n",
" <th>Hakka Restaurant</th>\n",
" <th>Harbor / Marina</th>\n",
" <th>Hardware Store</th>\n",
" <th>Hawaiian Restaurant</th>\n",
" <th>Health Food Store</th>\n",
" <th>Historic Site</th>\n",
" <th>History Museum</th>\n",
" <th>Hobby Shop</th>\n",
" <th>Hockey Arena</th>\n",
" <th>Home Service</th>\n",
" <th>Hong Kong Restaurant</th>\n",
" <th>Hookah Bar</th>\n",
" <th>Hostel</th>\n",
" <th>Hot Dog Joint</th>\n",
" <th>Hotel</th>\n",
" <th>Hotpot Restaurant</th>\n",
" <th>Housing Development</th>\n",
" <th>Ice Cream Shop</th>\n",
" <th>Indian Chinese Restaurant</th>\n",
" <th>Indian Restaurant</th>\n",
" <th>Indie Movie Theater</th>\n",
" <th>Indie Theater</th>\n",
" <th>Indonesian Restaurant</th>\n",
" <th>Intersection</th>\n",
" <th>Italian Restaurant</th>\n",
" <th>Japanese Restaurant</th>\n",
" <th>Jazz Club</th>\n",
" <th>Jewelry Store</th>\n",
" <th>Jewish Restaurant</th>\n",
" <th>Juice Bar</th>\n",
" <th>Kitchen Supply Store</th>\n",
" <th>Korean Restaurant</th>\n",
" <th>Lake</th>\n",
" <th>Latin American Restaurant</th>\n",
" <th>Laundromat</th>\n",
" <th>Laundry Service</th>\n",
" <th>Light Rail Station</th>\n",
" <th>Liquor Store</th>\n",
" <th>Lounge</th>\n",
" <th>Mac &amp; Cheese Joint</th>\n",
" <th>Malay Restaurant</th>\n",
" <th>Market</th>\n",
" <th>Martial Arts Dojo</th>\n",
" <th>Massage Studio</th>\n",
" <th>Mediterranean Restaurant</th>\n",
" <th>Men's Store</th>\n",
" <th>Metro Station</th>\n",
" <th>Mexican Restaurant</th>\n",
" <th>Middle Eastern Restaurant</th>\n",
" <th>Miscellaneous Shop</th>\n",
" <th>Mobile Phone Shop</th>\n",
" <th>Modern European Restaurant</th>\n",
" <th>Monument / Landmark</th>\n",
" <th>Moroccan Restaurant</th>\n",
" <th>Motorcycle Shop</th>\n",
" <th>Movie Theater</th>\n",
" <th>Museum</th>\n",
" <th>Music School</th>\n",
" <th>Music Store</th>\n",
" <th>Music Venue</th>\n",
" <th>Nail Salon</th>\n",
" <th>Neighborhood</th>\n",
" <th>New American Restaurant</th>\n",
" <th>Nightclub</th>\n",
" <th>Noodle House</th>\n",
" <th>Office</th>\n",
" <th>Opera House</th>\n",
" <th>Optical Shop</th>\n",
" <th>Organic Grocery</th>\n",
" <th>Other Great Outdoors</th>\n",
" <th>Other Repair Shop</th>\n",
" <th>Pakistani Restaurant</th>\n",
" <th>Paper / Office Supplies Store</th>\n",
" <th>Park</th>\n",
" <th>Pastry Shop</th>\n",
" <th>Performing Arts Venue</th>\n",
" <th>Persian Restaurant</th>\n",
" <th>Pet Store</th>\n",
" <th>Pharmacy</th>\n",
" <th>Photography Lab</th>\n",
" <th>Pie Shop</th>\n",
" <th>Pilates Studio</th>\n",
" <th>Pizza Place</th>\n",
" <th>Playground</th>\n",
" <th>Plaza</th>\n",
" <th>Poke Place</th>\n",
" <th>Pool</th>\n",
" <th>Pool Hall</th>\n",
" <th>Portuguese Restaurant</th>\n",
" <th>Poutine Place</th>\n",
" <th>Pub</th>\n",
" <th>Ramen Restaurant</th>\n",
" <th>Record Shop</th>\n",
" <th>Recreation Center</th>\n",
" <th>Rental Car Location</th>\n",
" <th>Residential Building (Apartment / Condo)</th>\n",
" <th>Restaurant</th>\n",
" <th>River</th>\n",
" <th>Road</th>\n",
" <th>Rock Climbing Spot</th>\n",
" <th>Rock Club</th>\n",
" <th>Salad Place</th>\n",
" <th>Salon / Barbershop</th>\n",
" <th>Sandwich Place</th>\n",
" <th>Scenic Lookout</th>\n",
" <th>School</th>\n",
" <th>Sculpture Garden</th>\n",
" <th>Seafood Restaurant</th>\n",
" <th>Shanghai Restaurant</th>\n",
" <th>Shoe Store</th>\n",
" <th>Shop &amp; Service</th>\n",
" <th>Shopping Mall</th>\n",
" <th>Skate Park</th>\n",
" <th>Skating Rink</th>\n",
" <th>Ski Area</th>\n",
" <th>Ski Chalet</th>\n",
" <th>Smoke Shop</th>\n",
" <th>Smoothie Shop</th>\n",
" <th>Snack Place</th>\n",
" <th>Soccer Field</th>\n",
" <th>Soccer Stadium</th>\n",
" <th>Social Club</th>\n",
" <th>Soup Place</th>\n",
" <th>South American Restaurant</th>\n",
" <th>Spa</th>\n",
" <th>Spanish Restaurant</th>\n",
" <th>Speakeasy</th>\n",
" <th>Sporting Goods Shop</th>\n",
" <th>Sports Bar</th>\n",
" <th>Sports Club</th>\n",
" <th>Sri Lankan Restaurant</th>\n",
" <th>Stadium</th>\n",
" <th>Stationery Store</th>\n",
" <th>Steakhouse</th>\n",
" <th>Storage Facility</th>\n",
" <th>Supermarket</th>\n",
" <th>Supplement Shop</th>\n",
" <th>Sushi Restaurant</th>\n",
" <th>Taco Place</th>\n",
" <th>Tailor Shop</th>\n",
" <th>Taiwanese Restaurant</th>\n",
" <th>Tanning Salon</th>\n",
" <th>Tapas Restaurant</th>\n",
" <th>Tea Room</th>\n",
" <th>Tech Startup</th>\n",
" <th>Tennis Court</th>\n",
" <th>Thai Restaurant</th>\n",
" <th>Theater</th>\n",
" <th>Theme Restaurant</th>\n",
" <th>Thrift / Vintage Store</th>\n",
" <th>Tibetan Restaurant</th>\n",
" <th>Toy / Game Store</th>\n",
" <th>Track</th>\n",
" <th>Trail</th>\n",
" <th>Train Station</th>\n",
" <th>Turkish Restaurant</th>\n",
" <th>Vegetarian / Vegan Restaurant</th>\n",
" <th>Video Game Store</th>\n",
" <th>Video Store</th>\n",
" <th>Vietnamese Restaurant</th>\n",
" <th>Warehouse Store</th>\n",
" <th>Wine Bar</th>\n",
" <th>Wine Shop</th>\n",
" <th>Wings Joint</th>\n",
" <th>Women's Store</th>\n",
" <th>Yoga Studio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Central Toronto</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008197</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>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.021858</td>\n",
" <td>0.016393</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</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>0.000000</td>\n",
" <td>0.016393</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008197</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016393</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>0.057377</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.073770</td>\n",
" <td>0.002732</td>\n",
" <td>0.002732</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>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</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>0.016393</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.013661</td>\n",
" <td>0.000000</td>\n",
" <td>0.010929</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.005464</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>0.005464</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>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010929</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.005464</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.019126</td>\n",
" <td>0.027322</td>\n",
" <td>0.013661</td>\n",
" <td>0.005464</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>0.002732</td>\n",
" <td>0.002732</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>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010929</td>\n",
" <td>0.000000</td>\n",
" <td>0.013661</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.071038</td>\n",
" <td>0.019126</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</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>0.002732</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>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010929</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.002732</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.043716</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.013661</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.030055</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.013661</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.019126</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.002732</td>\n",
" <td>0.016393</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</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>0.010929</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>0.000000</td>\n",
" <td>0.010929</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008197</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.008197</td>\n",
" <td>0.000000</td>\n",
" <td>0.043716</td>\n",
" <td>0.005464</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005464</td>\n",
" <td>0.013661</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.019126</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>0.005464</td>\n",
" <td>0.008197</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.019126</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008197</td>\n",
" <td>0.000000</td>\n",
" <td>0.008197</td>\n",
" <td>0.000000</td>\n",
" <td>0.002732</td>\n",
" <td>0.000000</td>\n",
" <td>0.016393</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Downtown Toronto</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.018160</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.012107</td>\n",
" <td>0.001211</td>\n",
" <td>0.003632</td>\n",
" <td>0.004843</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.024213</td>\n",
" <td>0.002421</td>\n",
" <td>0.012107</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.004843</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.014528</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.006053</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.009685</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007264</td>\n",
" <td>0.006053</td>\n",
" <td>0.003632</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>0.072639</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.004843</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004843</td>\n",
" <td>0.013317</td>\n",
" <td>0.078692</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.003632</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.012107</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.006053</td>\n",
" <td>0.000000</td>\n",
" <td>0.006053</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.006053</td>\n",
" <td>0.012107</td>\n",
" <td>0.004843</td>\n",
" <td>0.001211</td>\n",
" <td>0.004843</td>\n",
" <td>0.000000</td>\n",
" <td>0.007264</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.009685</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.004843</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.006053</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.026634</td>\n",
" <td>0.002421</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.006053</td>\n",
" <td>0.008475</td>\n",
" <td>0.013317</td>\n",
" <td>0.006053</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.027845</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007264</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.021792</td>\n",
" <td>0.021792</td>\n",
" <td>0.004843</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.006053</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.010896</td>\n",
" <td>0.002421</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.008475</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.006053</td>\n",
" <td>0.00</td>\n",
" <td>0.003632</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.024213</td>\n",
" <td>0.001211</td>\n",
" <td>0.004843</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.015738</td>\n",
" <td>0.002421</td>\n",
" <td>0.007264</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.014528</td>\n",
" <td>0.006053</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.030266</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.006053</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.013317</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002421</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.006053</td>\n",
" <td>0.001211</td>\n",
" <td>0.003632</td>\n",
" <td>0.004843</td>\n",
" <td>0.002421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.018160</td>\n",
" <td>0.000000</td>\n",
" <td>0.004843</td>\n",
" <td>0.000000</td>\n",
" <td>0.004843</td>\n",
" <td>0.001211</td>\n",
" <td>0.002421</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.010896</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.014528</td>\n",
" <td>0.012107</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.001211</td>\n",
" <td>0.004843</td>\n",
" <td>0.000000</td>\n",
" <td>0.014528</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" <td>0.000000</td>\n",
" <td>0.001211</td>\n",
" <td>0.000000</td>\n",
" <td>0.003632</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>East Toronto</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016129</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>0.004032</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012097</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.040323</td>\n",
" <td>0.000000</td>\n",
" <td>0.024194</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.024194</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>0.004032</td>\n",
" <td>0.012097</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016129</td>\n",
" <td>0.024194</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.016129</td>\n",
" <td>0.012097</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.028226</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012097</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.064516</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>0.004032</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.016129</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008065</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>0.008065</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008065</td>\n",
" <td>0.004032</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>0.012097</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</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>0.004032</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>0.040323</td>\n",
" <td>0.016129</td>\n",
" <td>0.012097</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</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>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.024194</td>\n",
" <td>0.004032</td>\n",
" <td>0.024194</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.032258</td>\n",
" <td>0.012097</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012097</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>0.004032</td>\n",
" <td>0.008065</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>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.036290</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012097</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.024194</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>0.040323</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016129</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016129</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008065</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>0.008065</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>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.016129</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008065</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</td>\n",
" <td>0.004032</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004032</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>0.004032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>East York</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</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>0.010363</td>\n",
" <td>0.015544</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015544</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.015544</td>\n",
" <td>0.020725</td>\n",
" <td>0.005181</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>0.010363</td>\n",
" <td>0.015544</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</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>0.010363</td>\n",
" <td>0.031088</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.025907</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.036269</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>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>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.088083</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>0.005181</td>\n",
" <td>0.005181</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.015544</td>\n",
" <td>0.005181</td>\n",
" <td>0.005181</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.015544</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</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>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015544</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>0.005181</td>\n",
" <td>0.025907</td>\n",
" <td>0.020725</td>\n",
" <td>0.010363</td>\n",
" <td>0.005181</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>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.020725</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.005181</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015544</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>0.005181</td>\n",
" <td>0.005181</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</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",
" <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>0.005181</td>\n",
" <td>0.020725</td>\n",
" <td>0.005181</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.015544</td>\n",
" <td>0.020725</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.036269</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>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.020725</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.025907</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>0.015544</td>\n",
" <td>0.000000</td>\n",
" <td>0.020725</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015544</td>\n",
" <td>0.010363</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>0.015544</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</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>0.015544</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>0.010363</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005181</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Etobicoke</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020833</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>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.008333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020833</td>\n",
" <td>0.029167</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>0.012500</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>0.012500</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016667</td>\n",
" <td>0.012500</td>\n",
" <td>0.012500</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>0.020833</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>0.008333</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>0.054167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.016667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012500</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.025000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</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>0.004167</td>\n",
" <td>0.012500</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</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>0.008333</td>\n",
" <td>0.008333</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>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.041667</td>\n",
" <td>0.008333</td>\n",
" <td>0.016667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012500</td>\n",
" <td>0.025000</td>\n",
" <td>0.004167</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>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.025000</td>\n",
" <td>0.004167</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>0.012500</td>\n",
" <td>0.008333</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</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",
" <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>0.066667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.045833</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.058333</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016667</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>0.016667</td>\n",
" <td>0.004167</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>0.029167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.012500</td>\n",
" <td>0.000000</td>\n",
" <td>0.016667</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>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</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>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.008333</td>\n",
" <td>0.016667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.004167</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>0.004167</td>\n",
" <td>0.000000</td>\n",
" <td>0.008333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Mississauga</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>0.020000</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>0.040000</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>0.020000</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>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>0.020000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.060000</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>0.100000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>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>0.020000</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>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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.040000</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>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>0.020000</td>\n",
" <td>0.020000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.060000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>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>0.040000</td>\n",
" <td>0.060000</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>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>0.02</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>0.020000</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>0.020000</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.040000</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>0.020000</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>0.020000</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>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>0.020000</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>0.040000</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>0.020000</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>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>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>North York</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.010714</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>0.001786</td>\n",
" <td>0.007143</td>\n",
" <td>0.010714</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.016071</td>\n",
" <td>0.025000</td>\n",
" <td>0.005357</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007143</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.003571</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.008929</td>\n",
" <td>0.001786</td>\n",
" <td>0.007143</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.021429</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.007143</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.012500</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>0.019643</td>\n",
" <td>0.000000</td>\n",
" <td>0.075000</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>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016071</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.005357</td>\n",
" <td>0.003571</td>\n",
" <td>0.005357</td>\n",
" <td>0.008929</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.007143</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.041071</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.014286</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.010714</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>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.005357</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005357</td>\n",
" <td>0.030357</td>\n",
" <td>0.010714</td>\n",
" <td>0.008929</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.010714</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.007143</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.007143</td>\n",
" <td>0.012500</td>\n",
" <td>0.028571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.017857</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.007143</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008929</td>\n",
" <td>0.003571</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>0.003571</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>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.041071</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.008929</td>\n",
" <td>0.023214</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.039286</td>\n",
" <td>0.005357</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.005357</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.010714</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.028571</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.025000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.019643</td>\n",
" <td>0.001786</td>\n",
" <td>0.005357</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007143</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.010714</td>\n",
" <td>0.001786</td>\n",
" <td>0.010714</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>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.003571</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.000000</td>\n",
" <td>0.003571</td>\n",
" <td>0.001786</td>\n",
" <td>0.003571</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.003571</td>\n",
" <td>0.014286</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" <td>0.001786</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Queen's 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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.040000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.040000</td>\n",
" <td>0.020000</td>\n",
" <td>0.020000</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>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>0.020000</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>0.120000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.040000</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>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>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>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>0.040000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.020000</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>0.020000</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>0.020000</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>0.020000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>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>0.020000</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>0.020000</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>0.02</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>0.040000</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>0.040000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.020000</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>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>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>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.020000</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>0.020000</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>0.020000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Scarborough</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</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>0.000000</td>\n",
" <td>0.010526</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.005263</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.039474</td>\n",
" <td>0.021053</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007895</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>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.010526</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.023684</td>\n",
" <td>0.000000</td>\n",
" <td>0.010526</td>\n",
" <td>0.007895</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.015789</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.065789</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>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.073684</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</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>0.015789</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>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.007895</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.015789</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>0.010526</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.063158</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</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>0.010526</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.010526</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>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.028947</td>\n",
" <td>0.010526</td>\n",
" <td>0.002632</td>\n",
" <td>0.007895</td>\n",
" <td>0.002632</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>0.010526</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.018421</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.021053</td>\n",
" <td>0.007895</td>\n",
" <td>0.005263</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>0.007895</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.007895</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.002632</td>\n",
" <td>0.007895</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>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</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>0.007895</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.036842</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.031579</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.052632</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007895</td>\n",
" <td>0.000000</td>\n",
" <td>0.013158</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>0.028947</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007895</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.015789</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010526</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.007895</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" <td>0.002632</td>\n",
" <td>0.000000</td>\n",
" <td>0.010526</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.005263</td>\n",
" <td>0.000000</td>\n",
" <td>0.002632</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>West Toronto</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.046667</td>\n",
" <td>0.006667</td>\n",
" <td>0.063333</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>0.003333</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.013333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.016667</td>\n",
" <td>0.013333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.086667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</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>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.010000</td>\n",
" <td>0.066667</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>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.013333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.013333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.010000</td>\n",
" <td>0.006667</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</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>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.013333</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.033333</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.013333</td>\n",
" <td>0.003333</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>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.010000</td>\n",
" <td>0.00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.026667</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016667</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.003333</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020000</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>0.003333</td>\n",
" <td>0.013333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</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>0.003333</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.026667</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016667</td>\n",
" <td>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.003333</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>0.006667</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.010000</td>\n",
" <td>0.000000</td>\n",
" <td>0.003333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>York</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>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>0.015267</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015267</td>\n",
" <td>0.007634</td>\n",
" <td>0.022901</td>\n",
" <td>0.007634</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>0.015267</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>0.007634</td>\n",
" <td>0.015267</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.022901</td>\n",
" <td>0.000000</td>\n",
" <td>0.015267</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015267</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>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</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>0.076336</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>0.000000</td>\n",
" <td>0.038168</td>\n",
" <td>0.007634</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>0.015267</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.038168</td>\n",
" <td>0.007634</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>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.022901</td>\n",
" <td>0.007634</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>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.015267</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.015267</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.038168</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</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>0.038168</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>0.007634</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>0.007634</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>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.022901</td>\n",
" <td>0.007634</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>0.007634</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>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</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>0.015267</td>\n",
" <td>0.007634</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>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",
" <td>0.000000</td>\n",
" <td>0.007634</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>0.061069</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.030534</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.076336</td>\n",
" <td>0.007634</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>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</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>0.038168</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>0.007634</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>0.007634</td>\n",
" <td>0.007634</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>0.007634</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>0.007634</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>0.000000</td>\n",
" <td>0.015267</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>0.007634</td>\n",
" <td>0.015267</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.007634</td>\n",
" <td>0.007634</td>\n",
" <td>0.007634</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Borough Accessories Store Adult Boutique Afghan Restaurant \\\n",
"0 Central Toronto 0.000000 0.000000 0.000000 \n",
"1 Downtown Toronto 0.000000 0.001211 0.001211 \n",
"2 East Toronto 0.000000 0.000000 0.000000 \n",
"3 East York 0.000000 0.000000 0.010363 \n",
"4 Etobicoke 0.000000 0.004167 0.000000 \n",
"5 Mississauga 0.000000 0.000000 0.000000 \n",
"6 North York 0.003571 0.000000 0.000000 \n",
"7 Queen's Park 0.000000 0.000000 0.000000 \n",
"8 Scarborough 0.000000 0.000000 0.000000 \n",
"9 West Toronto 0.000000 0.000000 0.000000 \n",
"10 York 0.000000 0.000000 0.000000 \n",
"\n",
" African Restaurant Airport Airport Lounge American Restaurant \\\n",
"0 0.000000 0.000000 0.000000 0.008197 \n",
"1 0.000000 0.001211 0.001211 0.018160 \n",
"2 0.000000 0.000000 0.000000 0.016129 \n",
"3 0.000000 0.000000 0.000000 0.010363 \n",
"4 0.000000 0.000000 0.000000 0.020833 \n",
"5 0.000000 0.000000 0.000000 0.020000 \n",
"6 0.000000 0.001786 0.000000 0.010714 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.010000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Amphitheater Animal Shelter Antique Shop Aquarium Art Gallery \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.001211 0.000000 0.003632 0.012107 \n",
"2 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.006667 0.000000 0.006667 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Art Museum Arts & Crafts Store Asian Restaurant Athletics & Sports \\\n",
"0 0.000000 0.000000 0.002732 0.000000 \n",
"1 0.001211 0.003632 0.004843 0.001211 \n",
"2 0.000000 0.004032 0.008065 0.000000 \n",
"3 0.000000 0.000000 0.010363 0.015544 \n",
"4 0.000000 0.000000 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.040000 0.000000 \n",
"6 0.000000 0.001786 0.007143 0.010714 \n",
"7 0.000000 0.020000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.010526 0.002632 \n",
"9 0.000000 0.006667 0.010000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.015267 \n",
"\n",
" Auto Dealership Auto Garage Automotive Shop BBQ Joint Baby Store \\\n",
"0 0.000000 0.000000 0.000000 0.002732 0.000000 \n",
"1 0.000000 0.000000 0.000000 0.002421 0.000000 \n",
"2 0.000000 0.000000 0.000000 0.012097 0.000000 \n",
"3 0.005181 0.000000 0.000000 0.015544 0.000000 \n",
"4 0.000000 0.004167 0.004167 0.008333 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.002632 0.005263 0.002632 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Badminton Court Bagel Shop Bakery Bank Bar Baseball Field \\\n",
"0 0.000000 0.005464 0.021858 0.016393 0.000000 0.002732 \n",
"1 0.000000 0.001211 0.024213 0.002421 0.012107 0.000000 \n",
"2 0.000000 0.004032 0.040323 0.000000 0.024194 0.000000 \n",
"3 0.000000 0.005181 0.015544 0.020725 0.005181 0.000000 \n",
"4 0.000000 0.000000 0.020833 0.029167 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.020000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.016071 0.025000 0.005357 0.003571 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.020000 0.000000 \n",
"8 0.002632 0.000000 0.039474 0.021053 0.002632 0.000000 \n",
"9 0.000000 0.000000 0.046667 0.006667 0.063333 0.000000 \n",
"10 0.000000 0.015267 0.007634 0.022901 0.007634 0.000000 \n",
"\n",
" Baseball Stadium Basketball Court Basketball Stadium Beach \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.002421 0.000000 0.004843 0.001211 \n",
"2 0.000000 0.000000 0.000000 0.024194 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.005263 \n",
"9 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Beach Bar Beer Bar Beer Store Belgian Restaurant Bike Shop Bistro \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.014528 0.000000 0.002421 0.000000 0.003632 \n",
"2 0.000000 0.000000 0.000000 0.000000 0.000000 0.004032 \n",
"3 0.000000 0.010363 0.015544 0.000000 0.005181 0.000000 \n",
"4 0.000000 0.000000 0.012500 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.007143 0.000000 0.001786 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.007895 0.000000 0.000000 0.000000 \n",
"9 0.003333 0.006667 0.003333 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.015267 0.000000 0.000000 0.000000 \n",
"\n",
" Bookstore Boutique Bowling Alley Brazilian Restaurant Breakfast Spot \\\n",
"0 0.016393 0.000000 0.000000 0.000000 0.008197 \n",
"1 0.006053 0.000000 0.000000 0.001211 0.009685 \n",
"2 0.012097 0.004032 0.000000 0.000000 0.016129 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.010363 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.012500 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.020000 \n",
"6 0.001786 0.003571 0.003571 0.000000 0.001786 \n",
"7 0.040000 0.000000 0.000000 0.000000 0.020000 \n",
"8 0.000000 0.000000 0.005263 0.000000 0.010526 \n",
"9 0.013333 0.003333 0.000000 0.003333 0.016667 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.007634 \n",
"\n",
" Brewery Bridal Shop Bridge Bubble Tea Shop Burger Joint \\\n",
"0 0.005464 0.000000 0.000000 0.000000 0.016393 \n",
"1 0.002421 0.000000 0.000000 0.007264 0.006053 \n",
"2 0.024194 0.000000 0.000000 0.004032 0.016129 \n",
"3 0.031088 0.000000 0.005181 0.000000 0.025907 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.016667 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.003571 0.000000 0.001786 0.008929 \n",
"7 0.000000 0.000000 0.000000 0.040000 0.020000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.023684 \n",
"9 0.013333 0.000000 0.000000 0.000000 0.003333 \n",
"10 0.015267 0.000000 0.000000 0.000000 0.007634 \n",
"\n",
" Burrito Place Bus Line Bus Station Bus Stop Business Service \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.003632 0.000000 0.000000 0.000000 0.000000 \n",
"2 0.012097 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.005181 0.000000 0.000000 0.005181 \n",
"4 0.012500 0.012500 0.000000 0.000000 0.000000 \n",
"5 0.020000 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.001786 0.007143 0.000000 0.003571 0.001786 \n",
"7 0.020000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.010526 0.007895 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.022901 0.000000 0.015267 0.000000 \n",
"\n",
" Butcher Cafeteria Café Cajun / Creole Restaurant Candy Store \\\n",
"0 0.000000 0.000000 0.057377 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.072639 0.000000 0.001211 \n",
"2 0.004032 0.000000 0.028226 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.036269 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.020833 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.001786 0.021429 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.002632 0.002632 0.000000 \n",
"9 0.003333 0.000000 0.086667 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.015267 0.000000 0.000000 \n",
"\n",
" Cantonese Restaurant Caribbean Restaurant Castle Cemetery \\\n",
"0 0.005464 0.000000 0.002732 0.002732 \n",
"1 0.000000 0.003632 0.000000 0.000000 \n",
"2 0.000000 0.012097 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.000000 0.007143 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.005263 0.015789 0.000000 0.000000 \n",
"9 0.000000 0.003333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Check Cashing Service Cheese Shop Chinese Restaurant Chiropractor \\\n",
"0 0.000000 0.002732 0.000000 0.005464 \n",
"1 0.000000 0.002421 0.004843 0.000000 \n",
"2 0.000000 0.004032 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.008333 0.000000 \n",
"5 0.000000 0.000000 0.060000 0.000000 \n",
"6 0.000000 0.001786 0.012500 0.000000 \n",
"7 0.000000 0.000000 0.020000 0.000000 \n",
"8 0.000000 0.000000 0.065789 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.007634 0.000000 0.007634 0.000000 \n",
"\n",
" Chocolate Shop Church Churrascaria Climbing Gym Clothing Store \\\n",
"0 0.000000 0.000000 0.005464 0.000000 0.002732 \n",
"1 0.001211 0.002421 0.000000 0.000000 0.004843 \n",
"2 0.004032 0.000000 0.000000 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.005181 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.000000 0.019643 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.005263 \n",
"9 0.000000 0.000000 0.000000 0.000000 0.003333 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Cocktail Bar Coffee Shop College Gym College Quad College Rec Center \\\n",
"0 0.000000 0.073770 0.002732 0.002732 0.000000 \n",
"1 0.013317 0.078692 0.001211 0.000000 0.000000 \n",
"2 0.000000 0.064516 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.088083 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.054167 0.000000 0.000000 0.004167 \n",
"5 0.000000 0.100000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.075000 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.120000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.073684 0.000000 0.000000 0.000000 \n",
"9 0.010000 0.066667 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.076336 0.000000 0.000000 0.000000 \n",
"\n",
" College Stadium Comedy Club Comfort Food Restaurant Comic Shop \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.002421 0.003632 0.002421 \n",
"2 0.000000 0.000000 0.004032 0.008065 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.004167 0.000000 \n",
"5 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.001786 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Community Center Concert Hall Construction & Landscaping \\\n",
"0 0.000000 0.002732 0.000000 \n",
"1 0.000000 0.012107 0.000000 \n",
"2 0.000000 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.005181 \n",
"4 0.000000 0.000000 0.004167 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.000000 0.000000 \n",
"7 0.000000 0.020000 0.000000 \n",
"8 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Convenience Store Cosmetics Shop Coworking Space Creperie \\\n",
"0 0.002732 0.000000 0.000000 0.000000 \n",
"1 0.001211 0.006053 0.000000 0.006053 \n",
"2 0.000000 0.004032 0.004032 0.000000 \n",
"3 0.005181 0.010363 0.000000 0.000000 \n",
"4 0.016667 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.016071 0.003571 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.020000 \n",
"8 0.015789 0.000000 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.000000 0.000000 \n",
"10 0.038168 0.007634 0.000000 0.000000 \n",
"\n",
" Cuban Restaurant Cupcake Shop Curling Ice Dance Studio Deli / Bodega \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.016393 \n",
"1 0.000000 0.001211 0.000000 0.006053 0.012107 \n",
"2 0.004032 0.004032 0.004032 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.010363 0.000000 0.000000 \n",
"4 0.000000 0.004167 0.000000 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.000000 0.003571 \n",
"7 0.000000 0.000000 0.000000 0.020000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.002632 \n",
"9 0.006667 0.003333 0.000000 0.000000 0.003333 \n",
"10 0.000000 0.000000 0.000000 0.015267 0.000000 \n",
"\n",
" Department Store Design Studio Dessert Shop Dim Sum Restaurant \\\n",
"0 0.000000 0.002732 0.013661 0.000000 \n",
"1 0.004843 0.001211 0.004843 0.000000 \n",
"2 0.000000 0.000000 0.004032 0.000000 \n",
"3 0.005181 0.000000 0.015544 0.005181 \n",
"4 0.000000 0.000000 0.012500 0.000000 \n",
"5 0.000000 0.000000 0.020000 0.000000 \n",
"6 0.001786 0.000000 0.005357 0.003571 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.007895 0.000000 \n",
"9 0.000000 0.000000 0.010000 0.000000 \n",
"10 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Diner Discount Store Dive Bar Dog Run Doner Restaurant \\\n",
"0 0.010929 0.000000 0.000000 0.002732 0.000000 \n",
"1 0.007264 0.000000 0.000000 0.001211 0.002421 \n",
"2 0.016129 0.000000 0.004032 0.000000 0.000000 \n",
"3 0.005181 0.005181 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.025000 0.000000 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.005357 0.008929 0.000000 0.003571 0.000000 \n",
"7 0.040000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.015789 0.000000 0.000000 0.000000 \n",
"9 0.006667 0.003333 0.000000 0.010000 0.000000 \n",
"10 0.007634 0.038168 0.007634 0.000000 0.000000 \n",
"\n",
" Donut Shop Dumpling Restaurant Eastern European Restaurant \\\n",
"0 0.000000 0.000000 0.002732 \n",
"1 0.000000 0.002421 0.000000 \n",
"2 0.004032 0.000000 0.000000 \n",
"3 0.005181 0.000000 0.000000 \n",
"4 0.004167 0.000000 0.004167 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.006667 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Electronics Store Elementary School Empanada Restaurant \\\n",
"0 0.005464 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.000000 \n",
"2 0.008065 0.000000 0.000000 \n",
"3 0.005181 0.000000 0.000000 \n",
"4 0.000000 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.007143 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.010526 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Ethiopian Restaurant Event Space Falafel Restaurant Farm \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.002421 0.002421 0.000000 0.001211 \n",
"2 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.010363 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.020000 0.000000 \n",
"6 0.000000 0.001786 0.001786 0.000000 \n",
"7 0.020000 0.000000 0.020000 0.000000 \n",
"8 0.000000 0.002632 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.006667 0.000000 \n",
"10 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Farmers Market Fast Food Restaurant Field Filipino Restaurant \\\n",
"0 0.000000 0.005464 0.000000 0.000000 \n",
"1 0.009685 0.000000 0.000000 0.002421 \n",
"2 0.008065 0.008065 0.000000 0.000000 \n",
"3 0.010363 0.015544 0.000000 0.000000 \n",
"4 0.004167 0.012500 0.000000 0.000000 \n",
"5 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.001786 0.041071 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.063158 0.000000 0.000000 \n",
"9 0.000000 0.003333 0.000000 0.000000 \n",
"10 0.000000 0.022901 0.007634 0.000000 \n",
"\n",
" Fireworks Store Fish & Chips Shop Fish Market Flea Market Flower Shop \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.002732 \n",
"1 0.000000 0.000000 0.001211 0.000000 0.000000 \n",
"2 0.000000 0.008065 0.004032 0.000000 0.000000 \n",
"3 0.000000 0.005181 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.008333 0.000000 0.000000 0.004167 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.001786 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.002632 0.002632 0.000000 \n",
"9 0.000000 0.003333 0.003333 0.006667 0.003333 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Food Food & Drink Shop Food Court Food Truck Fountain \\\n",
"0 0.000000 0.005464 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.003632 0.004843 0.001211 \n",
"2 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.020000 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.001786 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.002632 0.000000 0.000000 0.000000 \n",
"9 0.003333 0.003333 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.007634 0.000000 0.015267 0.000000 \n",
"\n",
" Frame Store French Restaurant Fried Chicken Joint Frozen Yogurt Shop \\\n",
"0 0.000000 0.005464 0.002732 0.000000 \n",
"1 0.000000 0.006053 0.002421 0.000000 \n",
"2 0.000000 0.012097 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.005181 0.000000 \n",
"4 0.000000 0.008333 0.008333 0.000000 \n",
"5 0.000000 0.000000 0.040000 0.000000 \n",
"6 0.001786 0.001786 0.014286 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.010526 0.000000 \n",
"9 0.000000 0.010000 0.000000 0.003333 \n",
"10 0.000000 0.000000 0.015267 0.007634 \n",
"\n",
" Fruit & Vegetable Store Furniture / Home Store Gaming Cafe Garden \\\n",
"0 0.000000 0.002732 0.000000 0.005464 \n",
"1 0.000000 0.000000 0.002421 0.002421 \n",
"2 0.004032 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.010363 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.010714 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.010526 0.000000 0.000000 \n",
"9 0.000000 0.010000 0.000000 0.000000 \n",
"10 0.000000 0.038168 0.000000 0.000000 \n",
"\n",
" Garden Center Gas Station Gastropub Gay Bar General Entertainment \\\n",
"0 0.000000 0.000000 0.010929 0.000000 0.002732 \n",
"1 0.000000 0.000000 0.026634 0.002421 0.002421 \n",
"2 0.000000 0.000000 0.004032 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.015544 0.000000 0.000000 \n",
"4 0.004167 0.004167 0.004167 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.040000 0.000000 0.020000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.005263 \n",
"9 0.000000 0.000000 0.013333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.007634 0.000000 0.000000 \n",
"\n",
" German Restaurant Gift Shop Golf Course Golf Driving Range \\\n",
"0 0.005464 0.002732 0.000000 0.000000 \n",
"1 0.000000 0.003632 0.000000 0.000000 \n",
"2 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.008333 0.004167 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.005357 0.000000 \n",
"7 0.000000 0.020000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.002632 0.000000 \n",
"9 0.000000 0.013333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Gourmet Shop Greek Restaurant Grocery Store Gym \\\n",
"0 0.000000 0.002732 0.019126 0.027322 \n",
"1 0.001211 0.006053 0.008475 0.013317 \n",
"2 0.000000 0.040323 0.016129 0.012097 \n",
"3 0.005181 0.025907 0.020725 0.010363 \n",
"4 0.004167 0.004167 0.041667 0.008333 \n",
"5 0.000000 0.000000 0.000000 0.020000 \n",
"6 0.000000 0.005357 0.030357 0.010714 \n",
"7 0.000000 0.000000 0.000000 0.020000 \n",
"8 0.000000 0.005263 0.028947 0.010526 \n",
"9 0.006667 0.003333 0.010000 0.006667 \n",
"10 0.000000 0.000000 0.038168 0.000000 \n",
"\n",
" Gym / Fitness Center Gym Pool Hakka Restaurant Harbor / Marina \\\n",
"0 0.013661 0.005464 0.000000 0.000000 \n",
"1 0.006053 0.000000 0.000000 0.002421 \n",
"2 0.004032 0.000000 0.000000 0.004032 \n",
"3 0.005181 0.000000 0.000000 0.000000 \n",
"4 0.016667 0.000000 0.000000 0.000000 \n",
"5 0.020000 0.000000 0.000000 0.000000 \n",
"6 0.008929 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.007895 0.002632 0.000000 \n",
"9 0.006667 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Hardware Store Hawaiian Restaurant Health Food Store Historic Site \\\n",
"0 0.000000 0.000000 0.000000 0.002732 \n",
"1 0.000000 0.000000 0.001211 0.002421 \n",
"2 0.000000 0.000000 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.004167 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.003571 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.003333 0.000000 0.000000 \n",
"10 0.007634 0.000000 0.000000 0.000000 \n",
"\n",
" History Museum Hobby Shop Hockey Arena Home Service \\\n",
"0 0.002732 0.000000 0.000000 0.000000 \n",
"1 0.001211 0.001211 0.000000 0.000000 \n",
"2 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.005181 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.001786 0.000000 0.001786 0.000000 \n",
"7 0.000000 0.020000 0.000000 0.000000 \n",
"8 0.000000 0.010526 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.007634 \n",
"\n",
" Hong Kong Restaurant Hookah Bar Hostel Hot Dog Joint Hotel \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.002732 \n",
"1 0.000000 0.000000 0.003632 0.000000 0.027845 \n",
"2 0.000000 0.000000 0.000000 0.000000 0.004032 \n",
"3 0.000000 0.000000 0.005181 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.004167 \n",
"5 0.000000 0.020000 0.000000 0.000000 0.060000 \n",
"6 0.000000 0.001786 0.000000 0.001786 0.010714 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.005263 0.000000 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.000000 0.006667 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Hotpot Restaurant Housing Development Ice Cream Shop \\\n",
"0 0.000000 0.000000 0.010929 \n",
"1 0.000000 0.000000 0.007264 \n",
"2 0.000000 0.000000 0.024194 \n",
"3 0.000000 0.000000 0.005181 \n",
"4 0.000000 0.000000 0.008333 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.007143 \n",
"7 0.000000 0.000000 0.020000 \n",
"8 0.002632 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.013333 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Indian Chinese Restaurant Indian Restaurant Indie Movie Theater \\\n",
"0 0.000000 0.013661 0.002732 \n",
"1 0.000000 0.003632 0.001211 \n",
"2 0.004032 0.024194 0.004032 \n",
"3 0.000000 0.020725 0.000000 \n",
"4 0.000000 0.008333 0.004167 \n",
"5 0.000000 0.020000 0.000000 \n",
"6 0.000000 0.003571 0.000000 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.018421 0.000000 \n",
"9 0.000000 0.010000 0.003333 \n",
"10 0.000000 0.007634 0.000000 \n",
"\n",
" Indie Theater Indonesian Restaurant Intersection Italian Restaurant \\\n",
"0 0.000000 0.002732 0.000000 0.071038 \n",
"1 0.000000 0.000000 0.000000 0.021792 \n",
"2 0.004032 0.000000 0.000000 0.032258 \n",
"3 0.000000 0.000000 0.010363 0.005181 \n",
"4 0.000000 0.000000 0.012500 0.025000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.007143 0.012500 \n",
"7 0.000000 0.000000 0.000000 0.020000 \n",
"8 0.000000 0.000000 0.021053 0.007895 \n",
"9 0.000000 0.000000 0.000000 0.033333 \n",
"10 0.000000 0.000000 0.000000 0.022901 \n",
"\n",
" Japanese Restaurant Jazz Club Jewelry Store Jewish Restaurant \\\n",
"0 0.019126 0.000000 0.000000 0.005464 \n",
"1 0.021792 0.004843 0.001211 0.000000 \n",
"2 0.012097 0.004032 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.004167 0.000000 0.000000 0.000000 \n",
"5 0.020000 0.000000 0.000000 0.000000 \n",
"6 0.028571 0.000000 0.001786 0.000000 \n",
"7 0.020000 0.000000 0.000000 0.000000 \n",
"8 0.005263 0.000000 0.000000 0.000000 \n",
"9 0.006667 0.000000 0.000000 0.000000 \n",
"10 0.007634 0.000000 0.000000 0.000000 \n",
"\n",
" Juice Bar Kitchen Supply Store Korean Restaurant Lake \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.001211 0.000000 0.006053 0.001211 \n",
"2 0.008065 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.020000 0.000000 0.000000 0.000000 \n",
"6 0.003571 0.001786 0.017857 0.000000 \n",
"7 0.020000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.007895 0.000000 \n",
"9 0.003333 0.000000 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Latin American Restaurant Laundromat Laundry Service \\\n",
"0 0.000000 0.000000 0.000000 \n",
"1 0.002421 0.000000 0.000000 \n",
"2 0.004032 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.004167 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.003571 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.002632 0.000000 \n",
"9 0.003333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Light Rail Station Liquor Store Lounge Mac & Cheese Joint \\\n",
"0 0.000000 0.002732 0.000000 0.000000 \n",
"1 0.000000 0.003632 0.003632 0.000000 \n",
"2 0.000000 0.012097 0.000000 0.000000 \n",
"3 0.000000 0.015544 0.000000 0.000000 \n",
"4 0.000000 0.025000 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.007143 0.003571 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.007895 0.002632 0.002632 0.000000 \n",
"9 0.000000 0.006667 0.000000 0.003333 \n",
"10 0.000000 0.007634 0.000000 0.000000 \n",
"\n",
" Malay Restaurant Market Martial Arts Dojo Massage Studio \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.001211 0.000000 \n",
"2 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.005263 0.000000 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.007634 0.000000 0.000000 \n",
"\n",
" Mediterranean Restaurant Men's Store Metro Station Mexican Restaurant \\\n",
"0 0.005464 0.000000 0.000000 0.010929 \n",
"1 0.003632 0.002421 0.001211 0.010896 \n",
"2 0.000000 0.000000 0.000000 0.004032 \n",
"3 0.000000 0.000000 0.000000 0.005181 \n",
"4 0.000000 0.000000 0.000000 0.012500 \n",
"5 0.000000 0.000000 0.000000 0.040000 \n",
"6 0.003571 0.001786 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.020000 \n",
"8 0.002632 0.000000 0.005263 0.002632 \n",
"9 0.003333 0.003333 0.000000 0.013333 \n",
"10 0.000000 0.000000 0.000000 0.015267 \n",
"\n",
" Middle Eastern Restaurant Miscellaneous Shop Mobile Phone Shop \\\n",
"0 0.005464 0.000000 0.000000 \n",
"1 0.002421 0.002421 0.000000 \n",
"2 0.008065 0.000000 0.000000 \n",
"3 0.005181 0.000000 0.000000 \n",
"4 0.008333 0.000000 0.008333 \n",
"5 0.060000 0.000000 0.000000 \n",
"6 0.008929 0.003571 0.000000 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.007895 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.000000 \n",
"10 0.007634 0.000000 0.000000 \n",
"\n",
" Modern European Restaurant Monument / Landmark Moroccan Restaurant \\\n",
"0 0.005464 0.000000 0.000000 \n",
"1 0.002421 0.003632 0.000000 \n",
"2 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.004167 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Motorcycle Shop Movie Theater Museum Music School Music Store \\\n",
"0 0.000000 0.005464 0.002732 0.002732 0.000000 \n",
"1 0.000000 0.001211 0.008475 0.001211 0.001211 \n",
"2 0.000000 0.004032 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.004167 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.003571 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.020000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.000000 0.000000 0.002632 \n",
"9 0.000000 0.003333 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Music Venue Nail Salon Neighborhood New American Restaurant Nightclub \\\n",
"0 0.000000 0.000000 0.002732 0.000000 0.00 \n",
"1 0.001211 0.000000 0.003632 0.006053 0.00 \n",
"2 0.000000 0.004032 0.004032 0.004032 0.00 \n",
"3 0.000000 0.005181 0.000000 0.000000 0.00 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.00 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.02 \n",
"6 0.000000 0.000000 0.000000 0.000000 0.00 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.02 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.00 \n",
"9 0.006667 0.003333 0.003333 0.010000 0.00 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.00 \n",
"\n",
" Noodle House Office Opera House Optical Shop Organic Grocery \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.003632 0.002421 0.001211 0.000000 0.001211 \n",
"2 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.000000 0.001786 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.007895 0.000000 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.000000 0.003333 \n",
"10 0.000000 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Other Great Outdoors Other Repair Shop Pakistani Restaurant \\\n",
"0 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.000000 \n",
"2 0.000000 0.000000 0.004032 \n",
"3 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.000000 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.000000 \n",
"9 0.003333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 \n",
"\n",
" Paper / Office Supplies Store Park Pastry Shop \\\n",
"0 0.000000 0.043716 0.002732 \n",
"1 0.000000 0.024213 0.001211 \n",
"2 0.000000 0.036290 0.000000 \n",
"3 0.005181 0.020725 0.005181 \n",
"4 0.000000 0.066667 0.000000 \n",
"5 0.020000 0.000000 0.000000 \n",
"6 0.001786 0.041071 0.000000 \n",
"7 0.000000 0.040000 0.000000 \n",
"8 0.002632 0.036842 0.000000 \n",
"9 0.000000 0.026667 0.000000 \n",
"10 0.000000 0.061069 0.000000 \n",
"\n",
" Performing Arts Venue Persian Restaurant Pet Store Pharmacy \\\n",
"0 0.000000 0.002732 0.000000 0.013661 \n",
"1 0.004843 0.000000 0.001211 0.000000 \n",
"2 0.000000 0.000000 0.012097 0.004032 \n",
"3 0.005181 0.000000 0.015544 0.020725 \n",
"4 0.000000 0.000000 0.004167 0.045833 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.008929 0.023214 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.005263 0.031579 \n",
"9 0.003333 0.000000 0.006667 0.010000 \n",
"10 0.000000 0.000000 0.000000 0.030534 \n",
"\n",
" Photography Lab Pie Shop Pilates Studio Pizza Place Playground \\\n",
"0 0.000000 0.000000 0.002732 0.030055 0.000000 \n",
"1 0.000000 0.002421 0.000000 0.015738 0.002421 \n",
"2 0.000000 0.000000 0.000000 0.024194 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.036269 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.058333 0.004167 \n",
"5 0.000000 0.000000 0.000000 0.020000 0.000000 \n",
"6 0.001786 0.000000 0.000000 0.039286 0.005357 \n",
"7 0.000000 0.000000 0.000000 0.040000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.052632 0.002632 \n",
"9 0.000000 0.000000 0.000000 0.016667 0.003333 \n",
"10 0.000000 0.000000 0.000000 0.076336 0.007634 \n",
"\n",
" Plaza Poke Place Pool Pool Hall Portuguese Restaurant \\\n",
"0 0.005464 0.000000 0.005464 0.000000 0.000000 \n",
"1 0.007264 0.001211 0.002421 0.000000 0.001211 \n",
"2 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.010363 \n",
"4 0.000000 0.000000 0.004167 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.000000 0.005357 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.020000 \n",
"8 0.002632 0.000000 0.002632 0.002632 0.000000 \n",
"9 0.000000 0.000000 0.003333 0.000000 0.006667 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Poutine Place Pub Ramen Restaurant Record Shop Recreation Center \\\n",
"0 0.000000 0.013661 0.005464 0.000000 0.000000 \n",
"1 0.000000 0.014528 0.006053 0.001211 0.000000 \n",
"2 0.000000 0.040323 0.008065 0.000000 0.000000 \n",
"3 0.000000 0.010363 0.005181 0.000000 0.000000 \n",
"4 0.000000 0.016667 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.003571 0.010714 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.020000 0.000000 0.000000 \n",
"8 0.000000 0.002632 0.000000 0.000000 0.000000 \n",
"9 0.003333 0.006667 0.000000 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Rental Car Location Residential Building (Apartment / Condo) Restaurant \\\n",
"0 0.000000 0.000000 0.019126 \n",
"1 0.000000 0.000000 0.030266 \n",
"2 0.000000 0.000000 0.016129 \n",
"3 0.005181 0.000000 0.020725 \n",
"4 0.000000 0.000000 0.016667 \n",
"5 0.000000 0.000000 0.040000 \n",
"6 0.003571 0.001786 0.028571 \n",
"7 0.000000 0.000000 0.000000 \n",
"8 0.007895 0.000000 0.013158 \n",
"9 0.000000 0.000000 0.020000 \n",
"10 0.007634 0.000000 0.007634 \n",
"\n",
" River Road Rock Climbing Spot Rock Club Salad Place \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.002732 \n",
"1 0.000000 0.000000 0.000000 0.001211 0.002421 \n",
"2 0.000000 0.000000 0.000000 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.005181 0.000000 0.000000 \n",
"4 0.004167 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.003571 0.000000 0.000000 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Salon / Barbershop Sandwich Place Scenic Lookout School \\\n",
"0 0.002732 0.016393 0.000000 0.000000 \n",
"1 0.001211 0.006053 0.002421 0.001211 \n",
"2 0.000000 0.016129 0.000000 0.000000 \n",
"3 0.000000 0.025907 0.000000 0.000000 \n",
"4 0.000000 0.029167 0.000000 0.000000 \n",
"5 0.000000 0.020000 0.000000 0.000000 \n",
"6 0.001786 0.025000 0.000000 0.000000 \n",
"7 0.020000 0.020000 0.000000 0.000000 \n",
"8 0.000000 0.028947 0.000000 0.000000 \n",
"9 0.003333 0.013333 0.003333 0.000000 \n",
"10 0.000000 0.038168 0.000000 0.000000 \n",
"\n",
" Sculpture Garden Seafood Restaurant Shanghai Restaurant Shoe Store \\\n",
"0 0.000000 0.002732 0.000000 0.000000 \n",
"1 0.001211 0.013317 0.000000 0.001211 \n",
"2 0.000000 0.004032 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.004167 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.003571 0.000000 0.003571 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.007895 0.002632 0.000000 \n",
"9 0.000000 0.006667 0.000000 0.003333 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Shop & Service Shopping Mall Skate Park Skating Rink Ski Area \\\n",
"0 0.000000 0.000000 0.000000 0.010929 0.000000 \n",
"1 0.000000 0.001211 0.000000 0.001211 0.000000 \n",
"2 0.000000 0.000000 0.008065 0.000000 0.000000 \n",
"3 0.000000 0.015544 0.000000 0.020725 0.000000 \n",
"4 0.000000 0.012500 0.000000 0.016667 0.000000 \n",
"5 0.000000 0.020000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.019643 0.001786 0.005357 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.015789 0.000000 0.002632 0.000000 \n",
"9 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Ski Chalet Smoke Shop Smoothie Shop Snack Place Soccer Field \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.002421 0.002421 0.001211 0.000000 \n",
"2 0.000000 0.000000 0.000000 0.008065 0.000000 \n",
"3 0.000000 0.000000 0.010363 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.000000 0.001786 0.001786 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.002632 0.002632 0.000000 0.005263 \n",
"9 0.000000 0.000000 0.003333 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.007634 \n",
"\n",
" Soccer Stadium Social Club Soup Place South American Restaurant \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.000000 0.001211 \n",
"2 0.000000 0.000000 0.000000 0.000000 \n",
"3 0.005181 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.004167 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.003333 0.000000 \n",
"10 0.007634 0.000000 0.000000 0.000000 \n",
"\n",
" Spa Spanish Restaurant Speakeasy Sporting Goods Shop Sports Bar \\\n",
"0 0.010929 0.000000 0.000000 0.008197 0.002732 \n",
"1 0.006053 0.001211 0.003632 0.004843 0.002421 \n",
"2 0.004032 0.000000 0.000000 0.000000 0.004032 \n",
"3 0.010363 0.000000 0.000000 0.015544 0.010363 \n",
"4 0.004167 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.020000 0.000000 \n",
"6 0.003571 0.000000 0.000000 0.007143 0.003571 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.000000 0.002632 0.005263 \n",
"9 0.000000 0.000000 0.003333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Sports Club Sri Lankan Restaurant Stadium Stationery Store \\\n",
"0 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.000000 0.000000 0.000000 0.000000 \n",
"2 0.000000 0.000000 0.000000 0.004032 \n",
"3 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.002632 0.000000 0.000000 \n",
"9 0.000000 0.000000 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Steakhouse Storage Facility Supermarket Supplement Shop \\\n",
"0 0.002732 0.000000 0.008197 0.000000 \n",
"1 0.018160 0.000000 0.004843 0.000000 \n",
"2 0.008065 0.000000 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.015544 0.000000 \n",
"4 0.000000 0.000000 0.008333 0.008333 \n",
"5 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.001786 0.010714 0.001786 \n",
"7 0.000000 0.000000 0.020000 0.000000 \n",
"8 0.000000 0.000000 0.010526 0.000000 \n",
"9 0.000000 0.000000 0.006667 0.000000 \n",
"10 0.000000 0.000000 0.007634 0.000000 \n",
"\n",
" Sushi Restaurant Taco Place Tailor Shop Taiwanese Restaurant \\\n",
"0 0.043716 0.005464 0.000000 0.000000 \n",
"1 0.004843 0.001211 0.002421 0.001211 \n",
"2 0.016129 0.004032 0.000000 0.000000 \n",
"3 0.005181 0.000000 0.000000 0.000000 \n",
"4 0.016667 0.000000 0.000000 0.000000 \n",
"5 0.040000 0.000000 0.000000 0.000000 \n",
"6 0.010714 0.000000 0.000000 0.000000 \n",
"7 0.020000 0.000000 0.000000 0.000000 \n",
"8 0.002632 0.000000 0.000000 0.002632 \n",
"9 0.026667 0.003333 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Tanning Salon Tapas Restaurant Tea Room Tech Startup Tennis Court \\\n",
"0 0.000000 0.005464 0.013661 0.000000 0.002732 \n",
"1 0.000000 0.001211 0.010896 0.001211 0.000000 \n",
"2 0.000000 0.004032 0.008065 0.000000 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.004167 0.004167 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.000000 0.001786 0.000000 0.003571 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.000000 0.002632 \n",
"9 0.000000 0.000000 0.010000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"\n",
" Thai Restaurant Theater Theme Restaurant Thrift / Vintage Store \\\n",
"0 0.019126 0.000000 0.000000 0.000000 \n",
"1 0.014528 0.012107 0.001211 0.001211 \n",
"2 0.008065 0.000000 0.000000 0.000000 \n",
"3 0.015544 0.000000 0.000000 0.000000 \n",
"4 0.008333 0.004167 0.000000 0.004167 \n",
"5 0.020000 0.000000 0.000000 0.000000 \n",
"6 0.003571 0.003571 0.000000 0.000000 \n",
"7 0.000000 0.020000 0.000000 0.000000 \n",
"8 0.007895 0.000000 0.000000 0.002632 \n",
"9 0.016667 0.006667 0.000000 0.003333 \n",
"10 0.015267 0.000000 0.000000 0.000000 \n",
"\n",
" Tibetan Restaurant Toy / Game Store Track Trail Train Station \\\n",
"0 0.000000 0.000000 0.005464 0.008197 0.000000 \n",
"1 0.000000 0.000000 0.001211 0.001211 0.004843 \n",
"2 0.000000 0.004032 0.000000 0.004032 0.000000 \n",
"3 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"4 0.000000 0.004167 0.000000 0.004167 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.000000 0.001786 0.000000 0.003571 0.001786 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.000000 0.000000 0.002632 0.002632 \n",
"9 0.003333 0.000000 0.000000 0.000000 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.007634 0.015267 \n",
"\n",
" Turkish Restaurant Vegetarian / Vegan Restaurant Video Game Store \\\n",
"0 0.000000 0.019126 0.000000 \n",
"1 0.000000 0.014528 0.000000 \n",
"2 0.004032 0.004032 0.000000 \n",
"3 0.010363 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.003571 0.000000 0.001786 \n",
"7 0.000000 0.020000 0.000000 \n",
"8 0.000000 0.002632 0.002632 \n",
"9 0.000000 0.006667 0.000000 \n",
"10 0.000000 0.000000 0.007634 \n",
"\n",
" Video Store Vietnamese Restaurant Warehouse Store Wine Bar Wine Shop \\\n",
"0 0.000000 0.008197 0.000000 0.008197 0.000000 \n",
"1 0.000000 0.003632 0.000000 0.003632 0.000000 \n",
"2 0.000000 0.004032 0.000000 0.000000 0.000000 \n",
"3 0.005181 0.000000 0.005181 0.000000 0.000000 \n",
"4 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"5 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"6 0.003571 0.014286 0.000000 0.000000 0.000000 \n",
"7 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"8 0.000000 0.010526 0.000000 0.000000 0.000000 \n",
"9 0.000000 0.010000 0.000000 0.003333 0.000000 \n",
"10 0.000000 0.000000 0.000000 0.000000 0.007634 \n",
"\n",
" Wings Joint Women's Store Yoga Studio \n",
"0 0.002732 0.000000 0.016393 \n",
"1 0.001211 0.000000 0.003632 \n",
"2 0.000000 0.000000 0.004032 \n",
"3 0.000000 0.000000 0.005181 \n",
"4 0.004167 0.000000 0.008333 \n",
"5 0.000000 0.000000 0.000000 \n",
"6 0.001786 0.001786 0.001786 \n",
"7 0.020000 0.000000 0.020000 \n",
"8 0.005263 0.000000 0.002632 \n",
"9 0.000000 0.000000 0.006667 \n",
"10 0.007634 0.007634 0.000000 "
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"toronto_grouped = toronto_onehot.groupby('Borough').mean().reset_index()\n",
"toronto_grouped"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(11, 314)"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"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": 84,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"----Central Toronto----\n",
" venue freq\n",
"0 Italian Restaurant 0.07\n",
"1 Coffee Shop 0.07\n",
"2 Café 0.06\n",
"3 Park 0.04\n",
"4 Sushi Restaurant 0.04\n",
"\n",
"\n",
"----Downtown Toronto----\n",
" venue freq\n",
"0 Coffee Shop 0.08\n",
"1 Café 0.07\n",
"2 Hotel 0.03\n",
"3 Restaurant 0.03\n",
"4 Gastropub 0.03\n",
"\n",
"\n",
"----East Toronto----\n",
" venue freq\n",
"0 Coffee Shop 0.06\n",
"1 Park 0.04\n",
"2 Pub 0.04\n",
"3 Greek Restaurant 0.04\n",
"4 Bakery 0.04\n",
"\n",
"\n",
"----East York----\n",
" venue freq\n",
"0 Coffee Shop 0.09\n",
"1 Café 0.04\n",
"2 Pizza Place 0.04\n",
"3 Greek Restaurant 0.03\n",
"4 Sandwich Place 0.03\n",
"\n",
"\n",
"----Etobicoke----\n",
" venue freq\n",
"0 Park 0.07\n",
"1 Pizza Place 0.06\n",
"2 Pharmacy 0.05\n",
"3 Coffee Shop 0.05\n",
"4 Grocery Store 0.04\n",
"\n",
"\n",
"----Mississauga----\n",
" venue freq\n",
"0 Coffee Shop 0.10\n",
"1 Middle Eastern Restaurant 0.06\n",
"2 Hotel 0.06\n",
"3 Chinese Restaurant 0.06\n",
"4 Sushi Restaurant 0.04\n",
"\n",
"\n",
"----North York----\n",
" venue freq\n",
"0 Coffee Shop 0.08\n",
"1 Pizza Place 0.04\n",
"2 Fast Food Restaurant 0.04\n",
"3 Park 0.04\n",
"4 Grocery Store 0.03\n",
"\n",
"\n",
"----Queen's Park----\n",
" venue freq\n",
"0 Coffee Shop 0.12\n",
"1 Park 0.04\n",
"2 Bookstore 0.04\n",
"3 Gastropub 0.04\n",
"4 Bubble Tea Shop 0.04\n",
"\n",
"\n",
"----Scarborough----\n",
" venue freq\n",
"0 Coffee Shop 0.07\n",
"1 Chinese Restaurant 0.07\n",
"2 Fast Food Restaurant 0.06\n",
"3 Pizza Place 0.05\n",
"4 Park 0.04\n",
"\n",
"\n",
"----West Toronto----\n",
" venue freq\n",
"0 Café 0.09\n",
"1 Coffee Shop 0.07\n",
"2 Bar 0.06\n",
"3 Bakery 0.05\n",
"4 Sushi Restaurant 0.03\n",
"\n",
"\n",
"----York----\n",
" venue freq\n",
"0 Pizza Place 0.08\n",
"1 Coffee Shop 0.08\n",
"2 Park 0.06\n",
"3 Grocery Store 0.04\n",
"4 Discount Store 0.04\n",
"\n",
"\n"
]
}
],
"source": [
"num_top_venues = 5\n",
"\n",
"for hood in toronto_grouped['Borough']:\n",
" print(\"----\"+hood+\"----\")\n",
" temp = toronto_grouped[toronto_grouped['Borough'] == hood].T.reset_index()\n",
" temp.columns = ['venue','freq']\n",
" temp = temp.iloc[1:]\n",
" temp['freq'] = temp['freq'].astype(float)\n",
" temp = temp.round({'freq': 2})\n",
" print(temp.sort_values('freq', ascending=False).reset_index(drop=True).head(num_top_venues))\n",
" print('\\n')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's put that into a pandas dataframe"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [],
"source": [
"def return_most_common_venues(row, num_top_venues):\n",
" row_categories = row.iloc[1:]\n",
" row_categories_sorted = row_categories.sort_values(ascending=False)\n",
" \n",
" return row_categories_sorted.index.values[0:num_top_venues]"
]
},
{
"cell_type": "code",
"execution_count": 86,
"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>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>Coffee Shop</td>\n",
" <td>Italian Restaurant</td>\n",
" <td>Café</td>\n",
" <td>Sushi Restaurant</td>\n",
" <td>Park</td>\n",
" <td>Pizza Place</td>\n",
" <td>Gym</td>\n",
" <td>Bakery</td>\n",
" <td>Japanese Restaurant</td>\n",
" <td>Grocery Store</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Downtown Toronto</td>\n",
" <td>Coffee Shop</td>\n",
" <td>Café</td>\n",
" <td>Restaurant</td>\n",
" <td>Hotel</td>\n",
" <td>Gastropub</td>\n",
" <td>Park</td>\n",
" <td>Bakery</td>\n",
" <td>Japanese Restaurant</td>\n",
" <td>Italian Restaurant</td>\n",
" <td>American Restaurant</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>East Toronto</td>\n",
" <td>Coffee Shop</td>\n",
" <td>Bakery</td>\n",
" <td>Pub</td>\n",
" <td>Greek Restaurant</td>\n",
" <td>Park</td>\n",
" <td>Italian Restaurant</td>\n",
" <td>Café</td>\n",
" <td>Beach</td>\n",
" <td>Indian Restaurant</td>\n",
" <td>Pizza Place</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>East York</td>\n",
" <td>Coffee Shop</td>\n",
" <td>Pizza Place</td>\n",
" <td>Café</td>\n",
" <td>Brewery</td>\n",
" <td>Burger Joint</td>\n",
" <td>Greek Restaurant</td>\n",
" <td>Sandwich Place</td>\n",
" <td>Indian Restaurant</td>\n",
" <td>Bank</td>\n",
" <td>Skating Rink</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Etobicoke</td>\n",
" <td>Park</td>\n",
" <td>Pizza Place</td>\n",
" <td>Coffee Shop</td>\n",
" <td>Pharmacy</td>\n",
" <td>Grocery Store</td>\n",
" <td>Bank</td>\n",
" <td>Sandwich Place</td>\n",
" <td>Italian Restaurant</td>\n",
" <td>Liquor Store</td>\n",
" <td>Discount Store</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Borough 1st Most Common Venue 2nd Most Common Venue \\\n",
"0 Central Toronto Coffee Shop Italian Restaurant \n",
"1 Downtown Toronto Coffee Shop Café \n",
"2 East Toronto Coffee Shop Bakery \n",
"3 East York Coffee Shop Pizza Place \n",
"4 Etobicoke Park Pizza Place \n",
"\n",
" 3rd Most Common Venue 4th Most Common Venue 5th Most Common Venue \\\n",
"0 Café Sushi Restaurant Park \n",
"1 Restaurant Hotel Gastropub \n",
"2 Pub Greek Restaurant Park \n",
"3 Café Brewery Burger Joint \n",
"4 Coffee Shop Pharmacy Grocery Store \n",
"\n",
" 6th Most Common Venue 7th Most Common Venue 8th Most Common Venue \\\n",
"0 Pizza Place Gym Bakery \n",
"1 Park Bakery Japanese Restaurant \n",
"2 Italian Restaurant Café Beach \n",
"3 Greek Restaurant Sandwich Place Indian Restaurant \n",
"4 Bank Sandwich Place Italian Restaurant \n",
"\n",
" 9th Most Common Venue 10th Most Common Venue \n",
"0 Japanese Restaurant Grocery Store \n",
"1 Italian Restaurant American Restaurant \n",
"2 Indian Restaurant Pizza Place \n",
"3 Bank Skating Rink \n",
"4 Liquor Store Discount Store "
]
},
"execution_count": 86,
"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 = ['Borough']\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",
"boroughs_venues_sorted = pd.DataFrame(columns=columns)\n",
"boroughs_venues_sorted['Borough'] = toronto_grouped['Borough']\n",
"\n",
"for ind in np.arange(toronto_grouped.shape[0]):\n",
" boroughs_venues_sorted.iloc[ind, 1:] = return_most_common_venues(toronto_grouped.iloc[ind, :], num_top_venues)\n",
"\n",
"boroughs_venues_sorted.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment