Capstone Project - The Battle of the Neighborhoods.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Capstone Project - The Battle of the Neighborhoods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Toronto is the provincial capital of Ontario. With a recorded population of 2,731,571 in 2016, it is the most populous city in Canada and the fourth most populous city in North America. The city is the anchor of the Golden Horseshoe, an urban agglomeration of 9,245,438 people (as of 2016) surrounding the western end of Lake Ontario, while the Greater Toronto Area (GTA) proper had a 2016 population of 6,417,516. Toronto is an international centre of business, finance, arts, and culture, and is recognized as one of the most multicultural and cosmopolitan cities in the world.\n",
    "\n",
    "New York City, often called simply New York and abbreviated as NYC, is the most populous city in the United States. With an estimated 2019 population of 8,336,817 distributed over about 302.6 square miles (784 km2), New York City is also the most densely populated major city in the United States. Located at the southern tip of the U.S. state of New York, the city is the center of the New York metropolitan area, the largest metropolitan area in the world by urban landmass. With almost 20 million people in its metropolitan statistical area and approximately 23 million in its combined statistical area, it is one of the world's most populous megacities. New York City has been described as the cultural, financial, and media capital of the world, significantly influencing commerce, entertainment, research, technology, education, politics, tourism, art, fashion, and sports. Home to the headquarters of the United Nations, New York is an important center for international diplomacy.\n",
    "\n",
    "#### The problem\n",
    "Now let me explain the context of this Capstone project through a scenario. Suppose a friend who live on the west side of the city of Toronto in Canada, receive a job offer from a great company in New York, Manhattan borough. He has to move to New York City. He love his neighborhood in Toronto beacause of its variety of venues for food, parks, schools and entertainment places. Consequently he want to move in a similar zone in Manhattan borough. The aim of this project is to study and analyze the neighborhoods of Toronto city and New York city and group them into similar clusters. Finally I will use those information to find the most similar neighborhood of the two borough of the two cities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. The Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this project we need the following data :\n",
    "\n",
    "1. New York City data that contains list Boroughs, Neighborhoods along with their latitude and longitude.\n",
    " - Data source : https://cocl.us/new_york_dataset\n",
    "2. Toronto data that contains list Boroughs, Neighborhoods along with their latitude and longitude\n",
    " - Data source: https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M , http://cocl.us/Geospatial_data\n",
    "                  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Methodology"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Get the data of both cities into pandas dataframe and process them\n",
    "2. Use the Foursquare API to find all venues for each neighborhood and analyze them\n",
    "3. Use cluster algorithm to find similar neighborhood\n",
    "4. Compare clusters between the two cities"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1 Toronto data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Firstly let's import some useful libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Libraries imported.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "import pandas as pd\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\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\n",
    "import folium # map rendering library\n",
    "\n",
    "print('Libraries imported.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's scrap the data from Wikipedia page into a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M2A</td>\n",
       "      <td>Not assigned</td>\n",
       "      <td>Not assigned</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M3A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Parkwoods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4A</td>\n",
       "      <td>North York</td>\n",
       "      <td>Victoria Village</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M5A</td>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Regent Park, Harbourfront</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code           Borough               Neighborhood\n",
       "0         M1A      Not assigned               Not assigned\n",
       "1         M2A      Not assigned               Not assigned\n",
       "2         M3A        North York                  Parkwoods\n",
       "3         M4A        North York           Victoria Village\n",
       "4         M5A  Downtown Toronto  Regent Park, Harbourfront"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tor= pd.read_html('https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M')[0]\n",
    "df_tor.rename(columns={'Neighbourhood':'Neighborhood'}, inplace=True)\n",
    "df_tor.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataframe consist of three columns: PostalCode, Borough, and Neighborhood. Let's drop cells with a borough that is \"Not assigned\". We notice that more than one neighborhood can exist in one postal code area. For example, in the table on the Wikipedia page, M5A is listed twice and has two neighborhoods: Harbourfront and Regent Park. These two rows will be combined into one row with the neighborhoods separated with a comma. Moreover if a cell has a borough but a Not assigned neighborhood, then the neighborhood will be the same as the borough"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Malvern, Rouge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge Hill, Port Union, Highland Creek</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood, Morningside, West Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M1G</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Woburn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M1H</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cedarbrae</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code      Borough                            Neighborhood\n",
       "0         M1B  Scarborough                          Malvern, Rouge\n",
       "1         M1C  Scarborough  Rouge Hill, Port Union, Highland Creek\n",
       "2         M1E  Scarborough       Guildwood, Morningside, West Hill\n",
       "3         M1G  Scarborough                                  Woburn\n",
       "4         M1H  Scarborough                               Cedarbrae"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tor1=df_tor[~df_tor.Borough.str.contains(\"Not assigned\")].reset_index(drop=True)\n",
    "df_tor1=df_tor1.groupby(['Postal Code','Borough'],as_index=False).agg(lambda x: \", \".join(x))\n",
    "for index, row in df_tor1.iterrows():\n",
    "    if row[\"Neighborhood\"] == \"Not assigned\":\n",
    "        row[\"Neighborhood\"] = row[\"Borough\"]\n",
    "        \n",
    "df_tor1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also fetched the coordinate data for all the neighborhoods in Toronto using the csv file and put it into a dataframe. Next, we combine both the dataframes i.e. adding the coordinate data to the original dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(103, 5)\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Malvern, Rouge</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge Hill, Port Union, Highland Creek</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood, Morningside, West Hill</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M1G</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Woburn</td>\n",
       "      <td>43.770992</td>\n",
       "      <td>-79.216917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M1H</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cedarbrae</td>\n",
       "      <td>43.773136</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code      Borough                            Neighborhood   Latitude  \\\n",
       "0         M1B  Scarborough                          Malvern, Rouge  43.806686   \n",
       "1         M1C  Scarborough  Rouge Hill, Port Union, Highland Creek  43.784535   \n",
       "2         M1E  Scarborough       Guildwood, Morningside, West Hill  43.763573   \n",
       "3         M1G  Scarborough                                  Woburn  43.770992   \n",
       "4         M1H  Scarborough                               Cedarbrae  43.773136   \n",
       "\n",
       "   Longitude  \n",
       "0 -79.194353  \n",
       "1 -79.160497  \n",
       "2 -79.188711  \n",
       "3 -79.216917  \n",
       "4 -79.239476  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.read_csv(\"Geospatial_Coordinates.csv\")\n",
    "df_tor2=pd.merge(left=df_tor1, right=df2 ,on='Postal Code')\n",
    "print(df_tor2.shape)\n",
    "df_tor2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we filter only boroughs that contain the word Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Scarborough' 'North York' 'East York' 'East Toronto' 'Central Toronto'\n",
      " 'Downtown Toronto' 'York' 'West Toronto' 'Mississauga' 'Etobicoke']\n"
     ]
    }
   ],
   "source": [
    "print(df_tor2.Borough.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(39, 5)\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4K</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Danforth West, Riverdale</td>\n",
       "      <td>43.679557</td>\n",
       "      <td>-79.352188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M4L</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>India Bazaar, The Beaches West</td>\n",
       "      <td>43.668999</td>\n",
       "      <td>-79.315572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4M</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>Studio District</td>\n",
       "      <td>43.659526</td>\n",
       "      <td>-79.340923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M4N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code          Borough                    Neighborhood   Latitude  \\\n",
       "0         M4E     East Toronto                     The Beaches  43.676357   \n",
       "1         M4K     East Toronto    The Danforth West, Riverdale  43.679557   \n",
       "2         M4L     East Toronto  India Bazaar, The Beaches West  43.668999   \n",
       "3         M4M     East Toronto                 Studio District  43.659526   \n",
       "4         M4N  Central Toronto                   Lawrence Park  43.728020   \n",
       "\n",
       "   Longitude  \n",
       "0 -79.293031  \n",
       "1 -79.352188  \n",
       "2 -79.315572  \n",
       "3 -79.340923  \n",
       "4 -79.388790  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "borough_with_toronto=['East Toronto','Central Toronto','Downtown Toronto', 'West Toronto']\n",
    "df_tor3 = df_tor2[df_tor2['Borough'].isin(borough_with_toronto)].reset_index(drop=True)\n",
    "print(df_tor3.shape)\n",
    "df_tor3.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use geopy library to get the latitude and longitude values of Toronto. In order to define an instance of the geocoder, we need to define a user_agent. We will name our agent to_explorer, as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Toronto are 43.6534817, -79.3839347.\n"
     ]
    }
   ],
   "source": [
    "address = 'Toronto'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"to_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We then use the python folium library to visualize geographic details of Toronto and its boroughs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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      ],
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       "<folium.folium.Map at 0x20987806c08>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "map_toronto = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, borough, neighborhood in zip(df_tor3['Latitude'], df_tor3['Longitude'], df_tor3['Borough'], df_tor3['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).add_to(map_toronto)  \n",
    "    \n",
    "map_toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 New York data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Firstly, let's load the data nedeed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('newyork_data.json') as json_data:\n",
    "    newyork_data = json.load(json_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "neighborhoods_data = newyork_data['features']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next task is essentially transforming this data of nested Python dictionaries into a pandas dataframe. So let's start by creating an empty dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define the dataframe columns\n",
    "column_names = ['Borough', 'Neighborhood', 'Latitude', 'Longitude'] \n",
    "\n",
    "# instantiate the dataframe\n",
    "neighborhoods = pd.DataFrame(columns=column_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then let's loop through the data and fill the dataframe one row at a time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "for data in neighborhoods_data:\n",
    "    borough = neighborhood_name = data['properties']['borough'] \n",
    "    neighborhood_name = data['properties']['name']\n",
    "        \n",
    "    neighborhood_latlon = data['geometry']['coordinates']\n",
    "    neighborhood_lat = neighborhood_latlon[1]\n",
    "    neighborhood_lon = neighborhood_latlon[0]\n",
    "    \n",
    "    neighborhoods = neighborhoods.append({'Borough': borough,\n",
    "                                          'Neighborhood': neighborhood_name,\n",
    "                                          'Latitude': neighborhood_lat,\n",
    "                                          'Longitude': neighborhood_lon}, ignore_index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quickly examine the resulting dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Bronx</td>\n",
       "      <td>Wakefield</td>\n",
       "      <td>40.894705</td>\n",
       "      <td>-73.847201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bronx</td>\n",
       "      <td>Co-op City</td>\n",
       "      <td>40.874294</td>\n",
       "      <td>-73.829939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bronx</td>\n",
       "      <td>Eastchester</td>\n",
       "      <td>40.887556</td>\n",
       "      <td>-73.827806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bronx</td>\n",
       "      <td>Fieldston</td>\n",
       "      <td>40.895437</td>\n",
       "      <td>-73.905643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bronx</td>\n",
       "      <td>Riverdale</td>\n",
       "      <td>40.890834</td>\n",
       "      <td>-73.912585</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Borough Neighborhood   Latitude  Longitude\n",
       "0   Bronx    Wakefield  40.894705 -73.847201\n",
       "1   Bronx   Co-op City  40.874294 -73.829939\n",
       "2   Bronx  Eastchester  40.887556 -73.827806\n",
       "3   Bronx    Fieldston  40.895437 -73.905643\n",
       "4   Bronx    Riverdale  40.890834 -73.912585"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neighborhoods.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, for our purpose, let's slice the original dataframe and create a new dataframe of the Manhattan data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>Neighborhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.910660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chinatown</td>\n",
       "      <td>40.715618</td>\n",
       "      <td>-73.994279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Washington Heights</td>\n",
       "      <td>40.851903</td>\n",
       "      <td>-73.936900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Inwood</td>\n",
       "      <td>40.867684</td>\n",
       "      <td>-73.921210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hamilton Heights</td>\n",
       "      <td>40.823604</td>\n",
       "      <td>-73.949688</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Borough        Neighborhood   Latitude  Longitude\n",
       "0  Manhattan         Marble Hill  40.876551 -73.910660\n",
       "1  Manhattan           Chinatown  40.715618 -73.994279\n",
       "2  Manhattan  Washington Heights  40.851903 -73.936900\n",
       "3  Manhattan              Inwood  40.867684 -73.921210\n",
       "4  Manhattan    Hamilton Heights  40.823604 -73.949688"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "manhattan_data = neighborhoods[neighborhoods['Borough'] == 'Manhattan'].reset_index(drop=True)\n",
    "manhattan_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get the geographical coordinates of Manhattan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Manhattan are 40.7896239, -73.9598939.\n"
     ]
    }
   ],
   "source": [
    "address = 'Manhattan, NY'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"ny_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Manhattan are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize Manhattan the neighborhoods in it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x209879eab08>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Manhattan using latitude and longitude values\n",
    "map_manhattan = folium.Map(location=[latitude, longitude], zoom_start=11)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, label in zip(manhattan_data['Latitude'], manhattan_data['Longitude'], manhattan_data['Neighborhood']):\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_manhattan)  \n",
    "    \n",
    "map_manhattan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.3 Toronto's areas analysis "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are going to start utilizing the Foursquare API to explore the neighborhoods and segment them. Firstly we define Foursquare Credentials and Version. Secondly let's get the top 50 venues that are in the selected Toronto borough s within a radius of 500 meters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your credentails:\n",
      "CLIENT_ID: QJB2JS4JPRGFMR1NB0PLBJ2LCBSPMVK40TWCI5XTWI1ZXOJE\n",
      "CLIENT_SECRET:5EH3OXJI0WRHMLHFSCUWXLGBEBRSZ4H0XXKZWOEU0CWMSCMT\n"
     ]
    }
   ],
   "source": [
    "CLIENT_ID = 'QJB2JS4JPRGFMR1NB0PLBJ2LCBSPMVK40TWCI5XTWI1ZXOJE' # your Foursquare ID\n",
    "CLIENT_SECRET = '5EH3OXJI0WRHMLHFSCUWXLGBEBRSZ4H0XXKZWOEU0CWMSCMT' # 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": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "radius = 500\n",
    "LIMIT = 50\n",
    "\n",
    "venues = []\n",
    "\n",
    "for lat, long, post, borough, neighborhood in zip(df_tor3['Latitude'], df_tor3['Longitude'], df_tor3['Postal Code'], df_tor3['Borough'], df_tor3['Neighborhood']):\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",
    "        long,\n",
    "        radius, \n",
    "        LIMIT)\n",
    "    \n",
    "    results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n",
    "    \n",
    "    for venue in results:\n",
    "        venues.append((\n",
    "            post, \n",
    "            borough,\n",
    "            neighborhood,\n",
    "            lat, \n",
    "            long, \n",
    "            venue['venue']['name'], \n",
    "            venue['venue']['location']['lat'], \n",
    "            venue['venue']['location']['lng'],  \n",
    "            venue['venue']['categories'][0]['name']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1196, 9)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>BoroughLatitude</th>\n",
       "      <th>BoroughLongitude</th>\n",
       "      <th>VenueName</th>\n",
       "      <th>VenueLatitude</th>\n",
       "      <th>VenueLongitude</th>\n",
       "      <th>VenueCategory</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>Glen Manor Ravine</td>\n",
       "      <td>43.676821</td>\n",
       "      <td>-79.293942</td>\n",
       "      <td>Trail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>The Big Carrot Natural Food Market</td>\n",
       "      <td>43.678879</td>\n",
       "      <td>-79.297734</td>\n",
       "      <td>Health Food Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>Grover Pub and Grub</td>\n",
       "      <td>43.679181</td>\n",
       "      <td>-79.297215</td>\n",
       "      <td>Pub</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4E</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>Upper Beaches</td>\n",
       "      <td>43.680563</td>\n",
       "      <td>-79.292869</td>\n",
       "      <td>Neighborhood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M4K</td>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Danforth West, Riverdale</td>\n",
       "      <td>43.679557</td>\n",
       "      <td>-79.352188</td>\n",
       "      <td>MenEssentials</td>\n",
       "      <td>43.677820</td>\n",
       "      <td>-79.351265</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code       Borough                  Neighborhood  BoroughLatitude  \\\n",
       "0         M4E  East Toronto                   The Beaches        43.676357   \n",
       "1         M4E  East Toronto                   The Beaches        43.676357   \n",
       "2         M4E  East Toronto                   The Beaches        43.676357   \n",
       "3         M4E  East Toronto                   The Beaches        43.676357   \n",
       "4         M4K  East Toronto  The Danforth West, Riverdale        43.679557   \n",
       "\n",
       "   BoroughLongitude                           VenueName  VenueLatitude  \\\n",
       "0        -79.293031                   Glen Manor Ravine      43.676821   \n",
       "1        -79.293031  The Big Carrot Natural Food Market      43.678879   \n",
       "2        -79.293031                 Grover Pub and Grub      43.679181   \n",
       "3        -79.293031                       Upper Beaches      43.680563   \n",
       "4        -79.352188                       MenEssentials      43.677820   \n",
       "\n",
       "   VenueLongitude      VenueCategory  \n",
       "0      -79.293942              Trail  \n",
       "1      -79.297734  Health Food Store  \n",
       "2      -79.297215                Pub  \n",
       "3      -79.292869       Neighborhood  \n",
       "4      -79.351265     Cosmetics Shop  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert the venues list into a new DataFrame\n",
    "venues_df = pd.DataFrame(venues)\n",
    "\n",
    "# define the column names\n",
    "venues_df.columns = ['Postal Code', 'Borough', 'Neighborhood', 'BoroughLatitude', 'BoroughLongitude', 'VenueName', 'VenueLatitude', 'VenueLongitude', 'VenueCategory']\n",
    "\n",
    "print(venues_df.shape)\n",
    "venues_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use One Hot Encoding, use the neighborhood to group data, and find out the top ten venues present in each neighborhood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Berczy Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pharmacy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Office</td>\n",
       "      <td>Pet Store</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Climbing Gym</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Skate Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Auto Workshop</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Comic Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Plane</td>\n",
       "      <td>Sculpture Garden</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Airport Gate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Comic Shop</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Poke Place</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                                        Berczy Park           Coffee Shop   \n",
       "1       Brockton, Parkdale Village, Exhibition Place                  Café   \n",
       "2  Business reply mail Processing Centre, South C...    Light Rail Station   \n",
       "3  CN Tower, King and Spadina, Railway Lands, Har...       Airport Service   \n",
       "4                                 Central Bay Street           Coffee Shop   \n",
       "\n",
       "   2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                 Bakery           Cheese Shop          Cocktail Bar   \n",
       "1  Performing Arts Venue                Bakery           Coffee Shop   \n",
       "2             Skate Park           Pizza Place        Farmers Market   \n",
       "3         Airport Lounge      Airport Terminal         Boat or Ferry   \n",
       "4         Sandwich Place       Bubble Tea Shop                  Café   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0        Farmers Market              Beer Bar    Seafood Restaurant   \n",
       "1        Breakfast Spot                Office             Pet Store   \n",
       "2         Auto Workshop                   Spa         Burrito Place   \n",
       "3              Boutique       Harbor / Marina                 Plane   \n",
       "4    Italian Restaurant            Comic Shop           Salad Place   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0            Restaurant                  Café               Pharmacy  \n",
       "1     Convenience Store          Climbing Gym             Restaurant  \n",
       "2            Restaurant  Gym / Fitness Center             Comic Shop  \n",
       "3      Sculpture Garden   Rental Car Location           Airport Gate  \n",
       "4          Burger Joint            Poke Place            Pizza Place  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "Toronto_onehot = pd.get_dummies(venues_df[['VenueCategory']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "Toronto_onehot['Neighborhood'] = venues_df['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [Toronto_onehot.columns[-1]] \n",
    "for i in range(0,Toronto_onehot.shape[1]-1):\n",
    "    fixed_columns.append(Toronto_onehot.columns[i])\n",
    "Toronto_onehot = Toronto_onehot[fixed_columns]\n",
    "\n",
    "# Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category\n",
    "Toronto_grouped = Toronto_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "\n",
    "# Now let's create the new dataframe and display the top 10 venues for each PostalCode\n",
    "num_top_venues = 10\n",
    "\n",
    "# write a function to sort the venues in descending order\n",
    "def return_most_common_venues(row, num_top_venues):\n",
    "    row_categories = row.iloc[1:]\n",
    "    row_categories_sorted = row_categories.sort_values(ascending=False)   \n",
    "    return row_categories_sorted.index.values[0:num_top_venues]\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for ind in np.arange(num_top_venues):\n",
    "    try:\n",
    "        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n",
    "    except:\n",
    "        columns.append('{}th Most Common Venue'.format(ind+1))\n",
    "\n",
    "# create a new dataframe\n",
    "Toronto_venues_sorted = pd.DataFrame(columns=columns)\n",
    "Toronto_venues_sorted['Neighborhood'] = Toronto_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(Toronto_grouped.shape[0]):\n",
    "    Toronto_venues_sorted.iloc[ind, 1:] = return_most_common_venues(Toronto_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "Toronto_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.4 Manhattan areas analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, let's get the top 50 venues that are in the New York Manhattan borough within a radius of 500 meters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "radius = 500\n",
    "LIMIT = 50\n",
    "\n",
    "venues1 = []\n",
    "\n",
    "for lat, long, borough, neighborhood in zip(manhattan_data['Latitude'], manhattan_data['Longitude'], manhattan_data['Borough'], manhattan_data['Neighborhood']):\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",
    "        long,\n",
    "        radius, \n",
    "        LIMIT)\n",
    "    \n",
    "    \n",
    "    results = requests.get(url,'none').json()[\"response\"]['groups'][0]['items']\n",
    "    \n",
    "    for venue in results:\n",
    "        venues1.append((\n",
    "            post, \n",
    "            borough,\n",
    "            neighborhood,\n",
    "            lat, \n",
    "            long, \n",
    "            venue['venue']['name'], \n",
    "            venue['venue']['location']['lat'], \n",
    "            venue['venue']['location']['lng'],  \n",
    "            venue['venue']['categories'][0]['name']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1887, 9)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>BoroughLatitude</th>\n",
       "      <th>BoroughLongitude</th>\n",
       "      <th>VenueName</th>\n",
       "      <th>VenueLatitude</th>\n",
       "      <th>VenueLongitude</th>\n",
       "      <th>VenueCategory</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.91066</td>\n",
       "      <td>Arturo's</td>\n",
       "      <td>40.874412</td>\n",
       "      <td>-73.910271</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.91066</td>\n",
       "      <td>Bikram Yoga</td>\n",
       "      <td>40.876844</td>\n",
       "      <td>-73.906204</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.91066</td>\n",
       "      <td>Tibbett Diner</td>\n",
       "      <td>40.880404</td>\n",
       "      <td>-73.908937</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.91066</td>\n",
       "      <td>Starbucks</td>\n",
       "      <td>40.877531</td>\n",
       "      <td>-73.905582</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M7Y</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.91066</td>\n",
       "      <td>Dunkin'</td>\n",
       "      <td>40.877136</td>\n",
       "      <td>-73.906666</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code    Borough Neighborhood  BoroughLatitude  BoroughLongitude  \\\n",
       "0         M7Y  Manhattan  Marble Hill        40.876551         -73.91066   \n",
       "1         M7Y  Manhattan  Marble Hill        40.876551         -73.91066   \n",
       "2         M7Y  Manhattan  Marble Hill        40.876551         -73.91066   \n",
       "3         M7Y  Manhattan  Marble Hill        40.876551         -73.91066   \n",
       "4         M7Y  Manhattan  Marble Hill        40.876551         -73.91066   \n",
       "\n",
       "       VenueName  VenueLatitude  VenueLongitude VenueCategory  \n",
       "0       Arturo's      40.874412      -73.910271   Pizza Place  \n",
       "1    Bikram Yoga      40.876844      -73.906204   Yoga Studio  \n",
       "2  Tibbett Diner      40.880404      -73.908937         Diner  \n",
       "3      Starbucks      40.877531      -73.905582   Coffee Shop  \n",
       "4        Dunkin'      40.877136      -73.906666    Donut Shop  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert the venues list into a new DataFrame\n",
    "venues_df1 = pd.DataFrame(venues1)\n",
    "\n",
    "# define the column names\n",
    "venues_df1.columns = ['Postal Code','Borough', 'Neighborhood', 'BoroughLatitude', 'BoroughLongitude', 'VenueName', 'VenueLatitude', 'VenueLongitude', 'VenueCategory']\n",
    "\n",
    "print(venues_df1.shape)\n",
    "venues_df1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use One Hot Encoding, use the neighborhood to group data, and find out the top ten venues present in each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Battery Park City</td>\n",
       "      <td>Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Memorial Site</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Food Court</td>\n",
       "      <td>Plaza</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Carnegie Hill</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Central Harlem</td>\n",
       "      <td>African Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Chelsea</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Cupcake Shop</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Liquor Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Chinatown</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Neighborhood 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "0  Battery Park City                  Park           Coffee Shop   \n",
       "1      Carnegie Hill           Pizza Place  Gym / Fitness Center   \n",
       "2     Central Harlem    African Restaurant           Pizza Place   \n",
       "3            Chelsea           Coffee Shop   American Restaurant   \n",
       "4          Chinatown    Chinese Restaurant   American Restaurant   \n",
       "\n",
       "  3rd Most Common Venue 4th Most Common Venue 5th Most Common Venue  \\\n",
       "0         Memorial Site          Gourmet Shop            Food Court   \n",
       "1           Coffee Shop             Bookstore                Bakery   \n",
       "2    Seafood Restaurant        Cosmetics Shop   American Restaurant   \n",
       "3    Italian Restaurant    Seafood Restaurant                 Hotel   \n",
       "4        Ice Cream Shop              Boutique      Greek Restaurant   \n",
       "\n",
       "  6th Most Common Venue 7th Most Common Venue 8th Most Common Venue  \\\n",
       "0                 Plaza                 Hotel                   Gym   \n",
       "1                   Gym    Italian Restaurant     French Restaurant   \n",
       "2                   Bar   Fried Chicken Joint     French Restaurant   \n",
       "3        Ice Cream Shop     French Restaurant          Cupcake Shop   \n",
       "4       Bubble Tea Shop    Salon / Barbershop        Sandwich Place   \n",
       "\n",
       "       9th Most Common Venue 10th Most Common Venue  \n",
       "0              Shopping Mall          Boat or Ferry  \n",
       "1                       Café            Yoga Studio  \n",
       "2         Chinese Restaurant              Bookstore  \n",
       "3  Middle Eastern Restaurant           Liquor Store  \n",
       "4                        Spa       Asian Restaurant  "
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "Manhattan_onehot = pd.get_dummies(venues_df1[['VenueCategory']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "Manhattan_onehot['Neighborhood'] = venues_df1['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [Manhattan_onehot.columns[-1]] \n",
    "for i in range(0,Manhattan_onehot.shape[1]-1):\n",
    "    fixed_columns.append(Manhattan_onehot.columns[i])\n",
    "Manhattan_onehot = Manhattan_onehot[fixed_columns]\n",
    "\n",
    "# Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category\n",
    "Manhattan_grouped = Manhattan_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "\n",
    "# Now let's create the new dataframe and display the top 10 venues for each PostalCode\n",
    "num_top_venues = 10\n",
    "\n",
    "# write a function to sort the venues in descending order\n",
    "def return_most_common_venues(row, num_top_venues):\n",
    "    row_categories = row.iloc[1:]\n",
    "    row_categories_sorted = row_categories.sort_values(ascending=False)   \n",
    "    return row_categories_sorted.index.values[0:num_top_venues]\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for ind in np.arange(num_top_venues):\n",
    "    try:\n",
    "        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n",
    "    except:\n",
    "        columns.append('{}th Most Common Venue'.format(ind+1))\n",
    "\n",
    "# create a new dataframe\n",
    "Manhattan_venues_sorted = pd.DataFrame(columns=columns)\n",
    "Manhattan_venues_sorted['Neighborhood'] = Manhattan_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(Manhattan_grouped.shape[0]):\n",
    "    Manhattan_venues_sorted.iloc[ind, 1:] = return_most_common_venues(Manhattan_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "Manhattan_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.5 Cluster Neighborhood"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's aggregate the two dataframe in a singol one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(39, 11) (40, 11) (79, 11)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>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>Berczy Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pharmacy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Office</td>\n",
       "      <td>Pet Store</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Climbing Gym</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Skate Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Auto Workshop</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Comic Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Plane</td>\n",
       "      <td>Sculpture Garden</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Airport Gate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Comic Shop</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Poke Place</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                                        Berczy Park           Coffee Shop   \n",
       "1       Brockton, Parkdale Village, Exhibition Place                  Café   \n",
       "2  Business reply mail Processing Centre, South C...    Light Rail Station   \n",
       "3  CN Tower, King and Spadina, Railway Lands, Har...       Airport Service   \n",
       "4                                 Central Bay Street           Coffee Shop   \n",
       "\n",
       "   2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                 Bakery           Cheese Shop          Cocktail Bar   \n",
       "1  Performing Arts Venue                Bakery           Coffee Shop   \n",
       "2             Skate Park           Pizza Place        Farmers Market   \n",
       "3         Airport Lounge      Airport Terminal         Boat or Ferry   \n",
       "4         Sandwich Place       Bubble Tea Shop                  Café   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0        Farmers Market              Beer Bar    Seafood Restaurant   \n",
       "1        Breakfast Spot                Office             Pet Store   \n",
       "2         Auto Workshop                   Spa         Burrito Place   \n",
       "3              Boutique       Harbor / Marina                 Plane   \n",
       "4    Italian Restaurant            Comic Shop           Salad Place   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0            Restaurant                  Café               Pharmacy  \n",
       "1     Convenience Store          Climbing Gym             Restaurant  \n",
       "2            Restaurant  Gym / Fitness Center             Comic Shop  \n",
       "3      Sculpture Garden   Rental Car Location           Airport Gate  \n",
       "4          Burger Joint            Poke Place            Pizza Place  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neigh_df=pd.merge(Toronto_venues_sorted, Manhattan_venues_sorted, how='outer')\n",
    "print(Toronto_venues_sorted1.shape, Manhattan_venues_sorted1.shape, neigh_df.shape)\n",
    "neigh_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have some common venue categories in the neighborhoods. We use the unsupervised learning K-means algorithm to cluster the neighborhoods. K-Means algorithm is one of the most common method for clustering in unsupervised learning. Let's run k-means to cluster the neighborhood into 5 clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Yoga Studio</th>\n",
       "      <th>Airport</th>\n",
       "      <th>Airport Food Court</th>\n",
       "      <th>Airport Gate</th>\n",
       "      <th>Airport Lounge</th>\n",
       "      <th>Airport Service</th>\n",
       "      <th>Airport Terminal</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Antique Shop</th>\n",
       "      <th>Aquarium</th>\n",
       "      <th>Art Gallery</th>\n",
       "      <th>Art Museum</th>\n",
       "      <th>Arts &amp; Crafts Store</th>\n",
       "      <th>Asian Restaurant</th>\n",
       "      <th>Auto Workshop</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Baby Store</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bakery</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Bar</th>\n",
       "      <th>Baseball Stadium</th>\n",
       "      <th>Basketball Stadium</th>\n",
       "      <th>Beach</th>\n",
       "      <th>Beer Bar</th>\n",
       "      <th>Beer Store</th>\n",
       "      <th>Belgian Restaurant</th>\n",
       "      <th>Bistro</th>\n",
       "      <th>Boat or Ferry</th>\n",
       "      <th>Bookstore</th>\n",
       "      <th>Boutique</th>\n",
       "      <th>Brazilian Restaurant</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Bubble Tea Shop</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Burrito Place</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Butcher</th>\n",
       "      <th>Café</th>\n",
       "      <th>Cajun / Creole Restaurant</th>\n",
       "      <th>Camera Store</th>\n",
       "      <th>Candy Store</th>\n",
       "      <th>Caribbean Restaurant</th>\n",
       "      <th>Cheese Shop</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Chocolate Shop</th>\n",
       "      <th>Climbing Gym</th>\n",
       "      <th>Clothing Store</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Arts Building</th>\n",
       "      <th>College Auditorium</th>\n",
       "      <th>College Cafeteria</th>\n",
       "      <th>College Gym</th>\n",
       "      <th>College Rec Center</th>\n",
       "      <th>Colombian Restaurant</th>\n",
       "      <th>Comfort Food Restaurant</th>\n",
       "      <th>Comic Shop</th>\n",
       "      <th>Concert Hall</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>Dance Studio</th>\n",
       "      <th>Deli / Bodega</th>\n",
       "      <th>Department Store</th>\n",
       "      <th>Dessert Shop</th>\n",
       "      <th>Diner</th>\n",
       "      <th>Discount Store</th>\n",
       "      <th>Distribution Center</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>Ethiopian Restaurant</th>\n",
       "      <th>Event Space</th>\n",
       "      <th>Falafel Restaurant</th>\n",
       "      <th>Farmers Market</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Filipino Restaurant</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 &amp; Drink Shop</th>\n",
       "      <th>Food Court</th>\n",
       "      <th>Food Truck</th>\n",
       "      <th>Fountain</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>General Travel</th>\n",
       "      <th>Gift Shop</th>\n",
       "      <th>Gluten-free Restaurant</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>Harbor / Marina</th>\n",
       "      <th>Health &amp; Beauty Service</th>\n",
       "      <th>Health Food Store</th>\n",
       "      <th>Historic Site</th>\n",
       "      <th>History Museum</th>\n",
       "      <th>Hobby Shop</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>IT Services</th>\n",
       "      <th>Ice Cream Shop</th>\n",
       "      <th>Indian Restaurant</th>\n",
       "      <th>Indie Movie Theater</th>\n",
       "      <th>Indoor Play Area</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>Juice Bar</th>\n",
       "      <th>Korean Restaurant</th>\n",
       "      <th>Lake</th>\n",
       "      <th>Latin American Restaurant</th>\n",
       "      <th>Light Rail Station</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Lounge</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>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Modern European Restaurant</th>\n",
       "      <th>Molecular Gastronomy Restaurant</th>\n",
       "      <th>Monument / Landmark</th>\n",
       "      <th>Movie Theater</th>\n",
       "      <th>Museum</th>\n",
       "      <th>Music Venue</th>\n",
       "      <th>New American Restaurant</th>\n",
       "      <th>Nightclub</th>\n",
       "      <th>Noodle House</th>\n",
       "      <th>Office</th>\n",
       "      <th>Organic Grocery</th>\n",
       "      <th>Park</th>\n",
       "      <th>Performing Arts Venue</th>\n",
       "      <th>Pet Store</th>\n",
       "      <th>Pharmacy</th>\n",
       "      <th>Pizza Place</th>\n",
       "      <th>Plane</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Poke Place</th>\n",
       "      <th>Pub</th>\n",
       "      <th>Ramen Restaurant</th>\n",
       "      <th>Record Shop</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Roof Deck</th>\n",
       "      <th>Sake Bar</th>\n",
       "      <th>Salad Place</th>\n",
       "      <th>Salon / Barbershop</th>\n",
       "      <th>Sandwich Place</th>\n",
       "      <th>Scenic Lookout</th>\n",
       "      <th>Sculpture Garden</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shoe Store</th>\n",
       "      <th>Shopping Mall</th>\n",
       "      <th>Skate Park</th>\n",
       "      <th>Skating Rink</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>Smoothie Shop</th>\n",
       "      <th>Snack Place</th>\n",
       "      <th>South American Restaurant</th>\n",
       "      <th>Southern / Soul Food Restaurant</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Speakeasy</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Sports Bar</th>\n",
       "      <th>Stadium</th>\n",
       "      <th>Stationery Store</th>\n",
       "      <th>Steakhouse</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Tailor Shop</th>\n",
       "      <th>Taiwanese Restaurant</th>\n",
       "      <th>Tanning Salon</th>\n",
       "      <th>Tea Room</th>\n",
       "      <th>Tennis Court</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</th>\n",
       "      <th>Theme Restaurant</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Trail</th>\n",
       "      <th>Train Station</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Game Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wine Shop</th>\n",
       "      <th>Accessories Store</th>\n",
       "      <th>Adult Boutique</th>\n",
       "      <th>Afghan Restaurant</th>\n",
       "      <th>African Restaurant</th>\n",
       "      <th>Argentinian Restaurant</th>\n",
       "      <th>Athletics &amp; Sports</th>\n",
       "      <th>Auditorium</th>\n",
       "      <th>Australian Restaurant</th>\n",
       "      <th>Austrian Restaurant</th>\n",
       "      <th>Baseball Field</th>\n",
       "      <th>Beer Garden</th>\n",
       "      <th>Big Box Store</th>\n",
       "      <th>Bike Rental / Bike Share</th>\n",
       "      <th>Bike Shop</th>\n",
       "      <th>Bike Trail</th>\n",
       "      <th>Board Shop</th>\n",
       "      <th>Boxing Gym</th>\n",
       "      <th>Bridal Shop</th>\n",
       "      <th>Bridge</th>\n",
       "      <th>Building</th>\n",
       "      <th>Bus Station</th>\n",
       "      <th>Cafeteria</th>\n",
       "      <th>Caucasian Restaurant</th>\n",
       "      <th>Circus</th>\n",
       "      <th>Club House</th>\n",
       "      <th>College Academic Building</th>\n",
       "      <th>College Bookstore</th>\n",
       "      <th>College Theater</th>\n",
       "      <th>Comedy Club</th>\n",
       "      <th>Community Center</th>\n",
       "      <th>Cooking School</th>\n",
       "      <th>Cycle Studio</th>\n",
       "      <th>Czech Restaurant</th>\n",
       "      <th>Daycare</th>\n",
       "      <th>Design Studio</th>\n",
       "      <th>Doctor's Office</th>\n",
       "      <th>Drugstore</th>\n",
       "      <th>Dry Cleaner</th>\n",
       "      <th>Duty-free Shop</th>\n",
       "      <th>Egyptian Restaurant</th>\n",
       "      <th>Empanada Restaurant</th>\n",
       "      <th>English Restaurant</th>\n",
       "      <th>Exhibit</th>\n",
       "      <th>Food Stand</th>\n",
       "      <th>German Restaurant</th>\n",
       "      <th>Gym Pool</th>\n",
       "      <th>Hardware Store</th>\n",
       "      <th>Hawaiian Restaurant</th>\n",
       "      <th>Heliport</th>\n",
       "      <th>Himalayan Restaurant</th>\n",
       "      <th>Hostel</th>\n",
       "      <th>Hot Dog Joint</th>\n",
       "      <th>Hotel Bar</th>\n",
       "      <th>Hotpot Restaurant</th>\n",
       "      <th>Indie Theater</th>\n",
       "      <th>Irish Pub</th>\n",
       "      <th>Israeli Restaurant</th>\n",
       "      <th>Japanese Curry Restaurant</th>\n",
       "      <th>Jewish Restaurant</th>\n",
       "      <th>Karaoke Bar</th>\n",
       "      <th>Kids Store</th>\n",
       "      <th>Leather Goods Store</th>\n",
       "      <th>Library</th>\n",
       "      <th>Lingerie Store</th>\n",
       "      <th>Malay Restaurant</th>\n",
       "      <th>Medical Center</th>\n",
       "      <th>Memorial Site</th>\n",
       "      <th>Mini Golf</th>\n",
       "      <th>Mobile Phone Shop</th>\n",
       "      <th>Moroccan Restaurant</th>\n",
       "      <th>Music School</th>\n",
       "      <th>Nail Salon</th>\n",
       "      <th>Newsstand</th>\n",
       "      <th>Opera House</th>\n",
       "      <th>Optical Shop</th>\n",
       "      <th>Outdoor Sculpture</th>\n",
       "      <th>Outdoors &amp; Recreation</th>\n",
       "      <th>Paella Restaurant</th>\n",
       "      <th>Paper / Office Supplies Store</th>\n",
       "      <th>Pedestrian Plaza</th>\n",
       "      <th>Persian Restaurant</th>\n",
       "      <th>Peruvian Restaurant</th>\n",
       "      <th>Pet Café</th>\n",
       "      <th>Pet Service</th>\n",
       "      <th>Physical Therapist</th>\n",
       "      <th>Pie Shop</th>\n",
       "      <th>Pilates Studio</th>\n",
       "      <th>Pool</th>\n",
       "      <th>Public Art</th>\n",
       "      <th>Residential Building (Apartment / Condo)</th>\n",
       "      <th>Rock Club</th>\n",
       "      <th>Scandinavian Restaurant</th>\n",
       "      <th>School</th>\n",
       "      <th>Shanghai Restaurant</th>\n",
       "      <th>Shipping Store</th>\n",
       "      <th>Soccer Field</th>\n",
       "      <th>Soup Place</th>\n",
       "      <th>Spanish Restaurant</th>\n",
       "      <th>Sports Club</th>\n",
       "      <th>Supplement Shop</th>\n",
       "      <th>Swiss Restaurant</th>\n",
       "      <th>Szechuan Restaurant</th>\n",
       "      <th>Taco Place</th>\n",
       "      <th>Tapas Restaurant</th>\n",
       "      <th>Tennis Stadium</th>\n",
       "      <th>Thrift / Vintage Store</th>\n",
       "      <th>Tiki Bar</th>\n",
       "      <th>Tourist Information Center</th>\n",
       "      <th>Turkish Restaurant</th>\n",
       "      <th>Udon Restaurant</th>\n",
       "      <th>Veterinarian</th>\n",
       "      <th>Video Store</th>\n",
       "      <th>Volleyball Court</th>\n",
       "      <th>Waterfront</th>\n",
       "      <th>Whisky Bar</th>\n",
       "      <th>Wings Joint</th>\n",
       "      <th>Women's Store</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.1875</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood  Yoga Studio  Airport  \\\n",
       "0                                        Berczy Park         0.00   0.0000   \n",
       "1       Brockton, Parkdale Village, Exhibition Place         0.00   0.0000   \n",
       "2  Business reply mail Processing Centre, South C...         0.00   0.0000   \n",
       "3  CN Tower, King and Spadina, Railway Lands, Har...         0.00   0.0625   \n",
       "4                                 Central Bay Street         0.02   0.0000   \n",
       "\n",
       "   Airport Food Court  Airport Gate  Airport Lounge  Airport Service  \\\n",
       "0              0.0000        0.0000           0.000           0.0000   \n",
       "1              0.0000        0.0000           0.000           0.0000   \n",
       "2              0.0000        0.0000           0.000           0.0000   \n",
       "3              0.0625        0.0625           0.125           0.1875   \n",
       "4              0.0000        0.0000           0.000           0.0000   \n",
       "\n",
       "   Airport Terminal  American Restaurant  Antique Shop  Aquarium  Art Gallery  \\\n",
       "0             0.000                  0.0           0.0       0.0         0.02   \n",
       "1             0.000                  0.0           0.0       0.0         0.00   \n",
       "2             0.000                  0.0           0.0       0.0         0.00   \n",
       "3             0.125                  0.0           0.0       0.0         0.00   \n",
       "4             0.000                  0.0           0.0       0.0         0.00   \n",
       "\n",
       "   Art Museum  Arts & Crafts Store  Asian Restaurant  Auto Workshop  \\\n",
       "0        0.00                  0.0               0.0         0.0000   \n",
       "1        0.00                  0.0               0.0         0.0000   \n",
       "2        0.00                  0.0               0.0         0.0625   \n",
       "3        0.00                  0.0               0.0         0.0000   \n",
       "4        0.02                  0.0               0.0         0.0000   \n",
       "\n",
       "   BBQ Joint  Baby Store  Bagel Shop  Bakery  Bank   Bar  Baseball Stadium  \\\n",
       "0        0.0         0.0        0.02    0.04   0.0  0.00               0.0   \n",
       "1        0.0         0.0        0.00    0.08   0.0  0.04               0.0   \n",
       "2        0.0         0.0        0.00    0.00   0.0  0.00               0.0   \n",
       "3        0.0         0.0        0.00    0.00   0.0  0.00               0.0   \n",
       "4        0.0         0.0        0.00    0.00   0.0  0.02               0.0   \n",
       "\n",
       "   Basketball Stadium  Beach  Beer Bar  Beer Store  Belgian Restaurant  \\\n",
       "0                0.02   0.02      0.04         0.0                 0.0   \n",
       "1                0.00   0.00      0.00         0.0                 0.0   \n",
       "2                0.00   0.00      0.00         0.0                 0.0   \n",
       "3                0.00   0.00      0.00         0.0                 0.0   \n",
       "4                0.00   0.00      0.00         0.0                 0.0   \n",
       "\n",
       "   Bistro  Boat or Ferry  Bookstore  Boutique  Brazilian Restaurant  \\\n",
       "0    0.02         0.0000        0.0    0.0000                   0.0   \n",
       "1    0.00         0.0000        0.0    0.0000                   0.0   \n",
       "2    0.00         0.0000        0.0    0.0000                   0.0   \n",
       "3    0.00         0.0625        0.0    0.0625                   0.0   \n",
       "4    0.00         0.0000        0.0    0.0000                   0.0   \n",
       "\n",
       "   Breakfast Spot  Brewery  Bubble Tea Shop  Burger Joint  Burrito Place  \\\n",
       "0            0.02   0.0000             0.00          0.00         0.0000   \n",
       "1            0.08   0.0000             0.00          0.00         0.0400   \n",
       "2            0.00   0.0625             0.00          0.00         0.0625   \n",
       "3            0.00   0.0000             0.00          0.00         0.0000   \n",
       "4            0.00   0.0000             0.04          0.02         0.0000   \n",
       "\n",
       "   Bus Line  Butcher  Café  Cajun / Creole Restaurant  Camera Store  \\\n",
       "0       0.0      0.0  0.04                        0.0           0.0   \n",
       "1       0.0      0.0  0.12                        0.0           0.0   \n",
       "2       0.0      0.0  0.00                        0.0           0.0   \n",
       "3       0.0      0.0  0.00                        0.0           0.0   \n",
       "4       0.0      0.0  0.04                        0.0           0.0   \n",
       "\n",
       "   Candy Store  Caribbean Restaurant  Cheese Shop  Chinese Restaurant  \\\n",
       "0          0.0                   0.0         0.04                 0.0   \n",
       "1          0.0                   0.0         0.00                 0.0   \n",
       "2          0.0                   0.0         0.00                 0.0   \n",
       "3          0.0                   0.0         0.00                 0.0   \n",
       "4          0.0                   0.0         0.00                 0.0   \n",
       "\n",
       "   Chocolate Shop  Climbing Gym  Clothing Store  Cocktail Bar  Coffee Shop  \\\n",
       "0             0.0          0.00             0.0          0.04         0.08   \n",
       "1             0.0          0.04             0.0          0.00         0.08   \n",
       "2             0.0          0.00             0.0          0.00         0.00   \n",
       "3             0.0          0.00             0.0          0.00         0.00   \n",
       "4             0.0          0.00             0.0          0.00         0.16   \n",
       "\n",
       "   College Arts Building  College Auditorium  College Cafeteria  College Gym  \\\n",
       "0                    0.0                 0.0                0.0          0.0   \n",
       "1                    0.0                 0.0                0.0          0.0   \n",
       "2                    0.0                 0.0                0.0          0.0   \n",
       "3                    0.0                 0.0                0.0          0.0   \n",
       "4                    0.0                 0.0                0.0          0.0   \n",
       "\n",
       "   College Rec Center  Colombian Restaurant  Comfort Food Restaurant  \\\n",
       "0                 0.0                   0.0                     0.02   \n",
       "1                 0.0                   0.0                     0.00   \n",
       "2                 0.0                   0.0                     0.00   \n",
       "3                 0.0                   0.0                     0.00   \n",
       "4                 0.0                   0.0                     0.00   \n",
       "\n",
       "   Comic Shop  Concert Hall  Convenience Store  Cosmetics Shop  \\\n",
       "0      0.0000          0.02               0.00             0.0   \n",
       "1      0.0000          0.00               0.04             0.0   \n",
       "2      0.0625          0.00               0.00             0.0   \n",
       "3      0.0000          0.00               0.00             0.0   \n",
       "4      0.0200          0.00               0.00             0.0   \n",
       "\n",
       "   Coworking Space  Creperie  Cuban Restaurant  Cupcake Shop  Dance Studio  \\\n",
       "0              0.0      0.02               0.0           0.0           0.0   \n",
       "1              0.0      0.00               0.0           0.0           0.0   \n",
       "2              0.0      0.00               0.0           0.0           0.0   \n",
       "3              0.0      0.00               0.0           0.0           0.0   \n",
       "4              0.0      0.00               0.0           0.0           0.0   \n",
       "\n",
       "   Deli / Bodega  Department Store  Dessert Shop  Diner  Discount Store  \\\n",
       "0            0.0              0.02          0.00   0.00            0.00   \n",
       "1            0.0              0.00          0.00   0.00            0.00   \n",
       "2            0.0              0.00          0.00   0.00            0.00   \n",
       "3            0.0              0.00          0.00   0.00            0.00   \n",
       "4            0.0              0.02          0.02   0.02            0.02   \n",
       "\n",
       "   Distribution Center  Dog Run  Doner Restaurant  Donut Shop  \\\n",
       "0                  0.0      0.0               0.0        0.00   \n",
       "1                  0.0      0.0               0.0        0.00   \n",
       "2                  0.0      0.0               0.0        0.00   \n",
       "3                  0.0      0.0               0.0        0.00   \n",
       "4                  0.0      0.0               0.0        0.02   \n",
       "\n",
       "   Dumpling Restaurant  Eastern European Restaurant  Electronics 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",
       "   Ethiopian Restaurant  Event Space  Falafel Restaurant  Farmers Market  \\\n",
       "0                   0.0          0.0                0.00          0.0400   \n",
       "1                   0.0          0.0                0.00          0.0000   \n",
       "2                   0.0          0.0                0.00          0.0625   \n",
       "3                   0.0          0.0                0.00          0.0000   \n",
       "4                   0.0          0.0                0.02          0.0000   \n",
       "\n",
       "   Fast Food Restaurant  Filipino Restaurant  Fish & Chips Shop  Fish Market  \\\n",
       "0                0.0000                  0.0                0.0         0.02   \n",
       "1                0.0000                  0.0                0.0         0.00   \n",
       "2                0.0625                  0.0                0.0         0.00   \n",
       "3                0.0000                  0.0                0.0         0.00   \n",
       "4                0.0000                  0.0                0.0         0.00   \n",
       "\n",
       "   Flea Market  Flower Shop  Food & Drink Shop  Food Court  Food Truck  \\\n",
       "0          0.0          0.0                0.0         0.0         0.0   \n",
       "1          0.0          0.0                0.0         0.0         0.0   \n",
       "2          0.0          0.0                0.0         0.0         0.0   \n",
       "3          0.0          0.0                0.0         0.0         0.0   \n",
       "4          0.0          0.0                0.0         0.0         0.0   \n",
       "\n",
       "   Fountain  French Restaurant  Fried Chicken Joint  Frozen Yogurt Shop  \\\n",
       "0      0.02               0.02                  0.0                 0.0   \n",
       "1      0.00               0.00                  0.0                 0.0   \n",
       "2      0.00               0.00                  0.0                 0.0   \n",
       "3      0.00               0.00                  0.0                 0.0   \n",
       "4      0.00               0.02                  0.0                 0.0   \n",
       "\n",
       "   Fruit & Vegetable Store  Furniture / Home Store  Gaming Cafe  Garden  \\\n",
       "0                      0.0                    0.00          0.0  0.0000   \n",
       "1                      0.0                    0.04          0.0  0.0000   \n",
       "2                      0.0                    0.00          0.0  0.0625   \n",
       "3                      0.0                    0.00          0.0  0.0000   \n",
       "4                      0.0                    0.02          0.0  0.0000   \n",
       "\n",
       "   Garden Center  Gas Station  Gastropub  Gay Bar  General Entertainment  \\\n",
       "0         0.0000          0.0       0.00      0.0                    0.0   \n",
       "1         0.0000          0.0       0.00      0.0                    0.0   \n",
       "2         0.0625          0.0       0.00      0.0                    0.0   \n",
       "3         0.0000          0.0       0.00      0.0                    0.0   \n",
       "4         0.0000          0.0       0.02      0.0                    0.0   \n",
       "\n",
       "   General Travel  Gift Shop  Gluten-free Restaurant  Gourmet Shop  \\\n",
       "0             0.0        0.0                     0.0          0.02   \n",
       "1             0.0        0.0                     0.0          0.00   \n",
       "2             0.0        0.0                     0.0          0.00   \n",
       "3             0.0        0.0                     0.0          0.00   \n",
       "4             0.0        0.0                     0.0          0.00   \n",
       "\n",
       "   Greek Restaurant  Grocery Store   Gym  Gym / Fitness Center  \\\n",
       "0              0.02           0.02  0.02                0.0000   \n",
       "1              0.00           0.04  0.04                0.0000   \n",
       "2              0.00           0.00  0.00                0.0625   \n",
       "3              0.00           0.00  0.00                0.0000   \n",
       "4              0.00           0.00  0.00                0.0200   \n",
       "\n",
       "   Harbor / Marina  Health & Beauty Service  Health Food Store  Historic Site  \\\n",
       "0           0.0000                      0.0                0.0            0.0   \n",
       "1           0.0000                      0.0                0.0            0.0   \n",
       "2           0.0000                      0.0                0.0            0.0   \n",
       "3           0.0625                      0.0                0.0            0.0   \n",
       "4           0.0000                      0.0                0.0            0.0   \n",
       "\n",
       "   History Museum  Hobby Shop  Hotel  IT Services  Ice Cream Shop  \\\n",
       "0             0.0         0.0   0.02          0.0            0.00   \n",
       "1             0.0         0.0   0.00          0.0            0.00   \n",
       "2             0.0         0.0   0.00          0.0            0.00   \n",
       "3             0.0         0.0   0.00          0.0            0.00   \n",
       "4             0.0         0.0   0.02          0.0            0.02   \n",
       "\n",
       "   Indian Restaurant  Indie Movie Theater  Indoor Play Area  Intersection  \\\n",
       "0               0.00                  0.0               0.0          0.00   \n",
       "1               0.00                  0.0               0.0          0.04   \n",
       "2               0.00                  0.0               0.0          0.00   \n",
       "3               0.00                  0.0               0.0          0.00   \n",
       "4               0.02                  0.0               0.0          0.00   \n",
       "\n",
       "   Italian Restaurant  Japanese Restaurant  Jazz Club  Jewelry Store  \\\n",
       "0                0.02                 0.02       0.02            0.0   \n",
       "1                0.04                 0.00       0.00            0.0   \n",
       "2                0.00                 0.00       0.00            0.0   \n",
       "3                0.00                 0.00       0.00            0.0   \n",
       "4                0.04                 0.02       0.00            0.0   \n",
       "\n",
       "   Juice Bar  Korean Restaurant  Lake  Latin American Restaurant  \\\n",
       "0        0.0                0.0   0.0                        0.0   \n",
       "1        0.0                0.0   0.0                        0.0   \n",
       "2        0.0                0.0   0.0                        0.0   \n",
       "3        0.0                0.0   0.0                        0.0   \n",
       "4        0.0                0.0   0.0                        0.0   \n",
       "\n",
       "   Light Rail Station  Liquor Store  Lounge  Market  Martial Arts Dojo  \\\n",
       "0               0.000          0.02     0.0     0.0                0.0   \n",
       "1               0.000          0.00     0.0     0.0                0.0   \n",
       "2               0.125          0.00     0.0     0.0                0.0   \n",
       "3               0.000          0.00     0.0     0.0                0.0   \n",
       "4               0.000          0.00     0.0     0.0                0.0   \n",
       "\n",
       "   Massage Studio  Mediterranean Restaurant  Men's Store  Mexican Restaurant  \\\n",
       "0             0.0                       0.0          0.0                 0.0   \n",
       "1             0.0                       0.0          0.0                 0.0   \n",
       "2             0.0                       0.0          0.0                 0.0   \n",
       "3             0.0                       0.0          0.0                 0.0   \n",
       "4             0.0                       0.0          0.0                 0.0   \n",
       "\n",
       "   Middle Eastern Restaurant  Miscellaneous Shop  Modern European Restaurant  \\\n",
       "0                       0.00                0.00                        0.00   \n",
       "1                       0.00                0.00                        0.00   \n",
       "2                       0.00                0.00                        0.00   \n",
       "3                       0.00                0.00                        0.00   \n",
       "4                       0.02                0.02                        0.02   \n",
       "\n",
       "   Molecular Gastronomy Restaurant  Monument / Landmark  Movie Theater  \\\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",
       "   Museum  Music Venue  New American Restaurant  Nightclub  Noodle House  \\\n",
       "0    0.02          0.0                     0.00       0.00           0.0   \n",
       "1    0.00          0.0                     0.00       0.04           0.0   \n",
       "2    0.00          0.0                     0.00       0.00           0.0   \n",
       "3    0.00          0.0                     0.00       0.00           0.0   \n",
       "4    0.00          0.0                     0.02       0.00           0.0   \n",
       "\n",
       "   Office  Organic Grocery    Park  Performing Arts Venue  Pet Store  \\\n",
       "0    0.00              0.0  0.0200                   0.00       0.00   \n",
       "1    0.04              0.0  0.0000                   0.08       0.04   \n",
       "2    0.00              0.0  0.0625                   0.00       0.00   \n",
       "3    0.00              0.0  0.0000                   0.00       0.00   \n",
       "4    0.02              0.0  0.0200                   0.00       0.00   \n",
       "\n",
       "   Pharmacy  Pizza Place   Plane  Playground  Plaza  Poke Place  Pub  \\\n",
       "0      0.02       0.0000  0.0000         0.0    0.0        0.00  0.0   \n",
       "1      0.00       0.0000  0.0000         0.0    0.0        0.00  0.0   \n",
       "2      0.00       0.0625  0.0000         0.0    0.0        0.00  0.0   \n",
       "3      0.00       0.0000  0.0625         0.0    0.0        0.00  0.0   \n",
       "4      0.00       0.0200  0.0000         0.0    0.0        0.02  0.0   \n",
       "\n",
       "   Ramen Restaurant  Record Shop  Rental Car Location  Restaurant  Roof Deck  \\\n",
       "0               0.0          0.0               0.0000      0.0400        0.0   \n",
       "1               0.0          0.0               0.0000      0.0400        0.0   \n",
       "2               0.0          0.0               0.0000      0.0625        0.0   \n",
       "3               0.0          0.0               0.0625      0.0000        0.0   \n",
       "4               0.0          0.0               0.0000      0.0000        0.0   \n",
       "\n",
       "   Sake Bar  Salad Place  Salon / Barbershop  Sandwich Place  Scenic Lookout  \\\n",
       "0       0.0         0.00                 0.0            0.00             0.0   \n",
       "1       0.0         0.00                 0.0            0.00             0.0   \n",
       "2       0.0         0.00                 0.0            0.00             0.0   \n",
       "3       0.0         0.00                 0.0            0.00             0.0   \n",
       "4       0.0         0.02                 0.0            0.06             0.0   \n",
       "\n",
       "   Sculpture Garden  Seafood Restaurant  Shoe Store  Shopping Mall  \\\n",
       "0            0.0000                0.04         0.0            0.0   \n",
       "1            0.0000                0.00         0.0            0.0   \n",
       "2            0.0000                0.00         0.0            0.0   \n",
       "3            0.0625                0.00         0.0            0.0   \n",
       "4            0.0000                0.02         0.0            0.0   \n",
       "\n",
       "   Skate Park  Skating Rink  Smoke Shop  Smoothie Shop  Snack Place  \\\n",
       "0      0.0000           0.0         0.0            0.0          0.0   \n",
       "1      0.0000           0.0         0.0            0.0          0.0   \n",
       "2      0.0625           0.0         0.0            0.0          0.0   \n",
       "3      0.0000           0.0         0.0            0.0          0.0   \n",
       "4      0.0000           0.0         0.0            0.0          0.0   \n",
       "\n",
       "   South American Restaurant  Southern / Soul Food Restaurant     Spa  \\\n",
       "0                        0.0                              0.0  0.0000   \n",
       "1                        0.0                              0.0  0.0000   \n",
       "2                        0.0                              0.0  0.0625   \n",
       "3                        0.0                              0.0  0.0000   \n",
       "4                        0.0                              0.0  0.0200   \n",
       "\n",
       "   Speakeasy  Sporting Goods Shop  Sports Bar  Stadium  Stationery Store  \\\n",
       "0        0.0                  0.0         0.0     0.00               0.0   \n",
       "1        0.0                  0.0         0.0     0.04               0.0   \n",
       "2        0.0                  0.0         0.0     0.00               0.0   \n",
       "3        0.0                  0.0         0.0     0.00               0.0   \n",
       "4        0.0                  0.0         0.0     0.00               0.0   \n",
       "\n",
       "   Steakhouse  Supermarket  Sushi Restaurant  Swim School  Tailor Shop  \\\n",
       "0        0.02          0.0              0.02          0.0         0.02   \n",
       "1        0.00          0.0              0.00          0.0         0.00   \n",
       "2        0.00          0.0              0.00          0.0         0.00   \n",
       "3        0.00          0.0              0.00          0.0         0.00   \n",
       "4        0.00          0.0              0.02          0.0         0.00   \n",
       "\n",
       "   Taiwanese Restaurant  Tanning Salon  Tea Room  Tennis Court  \\\n",
       "0                   0.0            0.0       0.0           0.0   \n",
       "1                   0.0            0.0       0.0           0.0   \n",
       "2                   0.0            0.0       0.0           0.0   \n",
       "3                   0.0            0.0       0.0           0.0   \n",
       "4                   0.0            0.0       0.0           0.0   \n",
       "\n",
       "   Thai Restaurant  Theater  Theme Restaurant  Toy / Game Store  Trail  \\\n",
       "0             0.02      0.0               0.0               0.0    0.0   \n",
       "1             0.00      0.0               0.0               0.0    0.0   \n",
       "2             0.00      0.0               0.0               0.0    0.0   \n",
       "3             0.00      0.0               0.0               0.0    0.0   \n",
       "4             0.00      0.0               0.0               0.0    0.0   \n",
       "\n",
       "   Train Station  Vegetarian / Vegan Restaurant  Video Game Store  \\\n",
       "0            0.0                           0.02               0.0   \n",
       "1            0.0                           0.00               0.0   \n",
       "2            0.0                           0.00               0.0   \n",
       "3            0.0                           0.00               0.0   \n",
       "4            0.0                           0.02               0.0   \n",
       "\n",
       "   Vietnamese Restaurant  Wine Bar  Wine Shop  Accessories Store  \\\n",
       "0                    0.0      0.00        0.0                NaN   \n",
       "1                    0.0      0.00        0.0                NaN   \n",
       "2                    0.0      0.00        0.0                NaN   \n",
       "3                    0.0      0.00        0.0                NaN   \n",
       "4                    0.0      0.02        0.0                NaN   \n",
       "\n",
       "   Adult Boutique  Afghan Restaurant  African Restaurant  \\\n",
       "0             NaN                NaN                 NaN   \n",
       "1             NaN                NaN                 NaN   \n",
       "2             NaN                NaN                 NaN   \n",
       "3             NaN                NaN                 NaN   \n",
       "4             NaN                NaN                 NaN   \n",
       "\n",
       "   Argentinian Restaurant  Athletics & Sports  Auditorium  \\\n",
       "0                     NaN                 NaN         NaN   \n",
       "1                     NaN                 NaN         NaN   \n",
       "2                     NaN                 NaN         NaN   \n",
       "3                     NaN                 NaN         NaN   \n",
       "4                     NaN                 NaN         NaN   \n",
       "\n",
       "   Australian Restaurant  Austrian Restaurant  Baseball Field  Beer Garden  \\\n",
       "0                    NaN                  NaN             NaN          NaN   \n",
       "1                    NaN                  NaN             NaN          NaN   \n",
       "2                    NaN                  NaN             NaN          NaN   \n",
       "3                    NaN                  NaN             NaN          NaN   \n",
       "4                    NaN                  NaN             NaN          NaN   \n",
       "\n",
       "   Big Box Store  Bike Rental / Bike Share  Bike Shop  Bike Trail  Board Shop  \\\n",
       "0            NaN                       NaN        NaN         NaN         NaN   \n",
       "1            NaN                       NaN        NaN         NaN         NaN   \n",
       "2            NaN                       NaN        NaN         NaN         NaN   \n",
       "3            NaN                       NaN        NaN         NaN         NaN   \n",
       "4            NaN                       NaN        NaN         NaN         NaN   \n",
       "\n",
       "   Boxing Gym  Bridal Shop  Bridge  Building  Bus Station  Cafeteria  \\\n",
       "0         NaN          NaN     NaN       NaN          NaN        NaN   \n",
       "1         NaN          NaN     NaN       NaN          NaN        NaN   \n",
       "2         NaN          NaN     NaN       NaN          NaN        NaN   \n",
       "3         NaN          NaN     NaN       NaN          NaN        NaN   \n",
       "4         NaN          NaN     NaN       NaN          NaN        NaN   \n",
       "\n",
       "   Caucasian Restaurant  Circus  Club House  College Academic Building  \\\n",
       "0                   NaN     NaN         NaN                        NaN   \n",
       "1                   NaN     NaN         NaN                        NaN   \n",
       "2                   NaN     NaN         NaN                        NaN   \n",
       "3                   NaN     NaN         NaN                        NaN   \n",
       "4                   NaN     NaN         NaN                        NaN   \n",
       "\n",
       "   College Bookstore  College Theater  Comedy Club  Community Center  \\\n",
       "0                NaN              NaN          NaN               NaN   \n",
       "1                NaN              NaN          NaN               NaN   \n",
       "2                NaN              NaN          NaN               NaN   \n",
       "3                NaN              NaN          NaN               NaN   \n",
       "4                NaN              NaN          NaN               NaN   \n",
       "\n",
       "   Cooking School  Cycle Studio  Czech Restaurant  Daycare  Design Studio  \\\n",
       "0             NaN           NaN               NaN      NaN            NaN   \n",
       "1             NaN           NaN               NaN      NaN            NaN   \n",
       "2             NaN           NaN               NaN      NaN            NaN   \n",
       "3             NaN           NaN               NaN      NaN            NaN   \n",
       "4             NaN           NaN               NaN      NaN            NaN   \n",
       "\n",
       "   Doctor's Office  Drugstore  Dry Cleaner  Duty-free Shop  \\\n",
       "0              NaN        NaN          NaN             NaN   \n",
       "1              NaN        NaN          NaN             NaN   \n",
       "2              NaN        NaN          NaN             NaN   \n",
       "3              NaN        NaN          NaN             NaN   \n",
       "4              NaN        NaN          NaN             NaN   \n",
       "\n",
       "   Egyptian Restaurant  Empanada Restaurant  English Restaurant  Exhibit  \\\n",
       "0                  NaN                  NaN                 NaN      NaN   \n",
       "1                  NaN                  NaN                 NaN      NaN   \n",
       "2                  NaN                  NaN                 NaN      NaN   \n",
       "3                  NaN                  NaN                 NaN      NaN   \n",
       "4                  NaN                  NaN                 NaN      NaN   \n",
       "\n",
       "   Food Stand  German Restaurant  Gym Pool  Hardware Store  \\\n",
       "0         NaN                NaN       NaN             NaN   \n",
       "1         NaN                NaN       NaN             NaN   \n",
       "2         NaN                NaN       NaN             NaN   \n",
       "3         NaN                NaN       NaN             NaN   \n",
       "4         NaN                NaN       NaN             NaN   \n",
       "\n",
       "   Hawaiian Restaurant  Heliport  Himalayan Restaurant  Hostel  Hot Dog Joint  \\\n",
       "0                  NaN       NaN                   NaN     NaN            NaN   \n",
       "1                  NaN       NaN                   NaN     NaN            NaN   \n",
       "2                  NaN       NaN                   NaN     NaN            NaN   \n",
       "3                  NaN       NaN                   NaN     NaN            NaN   \n",
       "4                  NaN       NaN                   NaN     NaN            NaN   \n",
       "\n",
       "   Hotel Bar  Hotpot Restaurant  Indie Theater  Irish Pub  Israeli Restaurant  \\\n",
       "0        NaN                NaN            NaN        NaN                 NaN   \n",
       "1        NaN                NaN            NaN        NaN                 NaN   \n",
       "2        NaN                NaN            NaN        NaN                 NaN   \n",
       "3        NaN                NaN            NaN        NaN                 NaN   \n",
       "4        NaN                NaN            NaN        NaN                 NaN   \n",
       "\n",
       "   Japanese Curry Restaurant  Jewish Restaurant  Karaoke Bar  Kids Store  \\\n",
       "0                        NaN                NaN          NaN         NaN   \n",
       "1                        NaN                NaN          NaN         NaN   \n",
       "2                        NaN                NaN          NaN         NaN   \n",
       "3                        NaN                NaN          NaN         NaN   \n",
       "4                        NaN                NaN          NaN         NaN   \n",
       "\n",
       "   Leather Goods Store  Library  Lingerie Store  Malay Restaurant  \\\n",
       "0                  NaN      NaN             NaN               NaN   \n",
       "1                  NaN      NaN             NaN               NaN   \n",
       "2                  NaN      NaN             NaN               NaN   \n",
       "3                  NaN      NaN             NaN               NaN   \n",
       "4                  NaN      NaN             NaN               NaN   \n",
       "\n",
       "   Medical Center  Memorial Site  Mini Golf  Mobile Phone Shop  \\\n",
       "0             NaN            NaN        NaN                NaN   \n",
       "1             NaN            NaN        NaN                NaN   \n",
       "2             NaN            NaN        NaN                NaN   \n",
       "3             NaN            NaN        NaN                NaN   \n",
       "4             NaN            NaN        NaN                NaN   \n",
       "\n",
       "   Moroccan Restaurant  Music School  Nail Salon  Newsstand  Opera House  \\\n",
       "0                  NaN           NaN         NaN        NaN          NaN   \n",
       "1                  NaN           NaN         NaN        NaN          NaN   \n",
       "2                  NaN           NaN         NaN        NaN          NaN   \n",
       "3                  NaN           NaN         NaN        NaN          NaN   \n",
       "4                  NaN           NaN         NaN        NaN          NaN   \n",
       "\n",
       "   Optical Shop  Outdoor Sculpture  Outdoors & Recreation  Paella Restaurant  \\\n",
       "0           NaN                NaN                    NaN                NaN   \n",
       "1           NaN                NaN                    NaN                NaN   \n",
       "2           NaN                NaN                    NaN                NaN   \n",
       "3           NaN                NaN                    NaN                NaN   \n",
       "4           NaN                NaN                    NaN                NaN   \n",
       "\n",
       "   Paper / Office Supplies Store  Pedestrian Plaza  Persian Restaurant  \\\n",
       "0                            NaN               NaN                 NaN   \n",
       "1                            NaN               NaN                 NaN   \n",
       "2                            NaN               NaN                 NaN   \n",
       "3                            NaN               NaN                 NaN   \n",
       "4                            NaN               NaN                 NaN   \n",
       "\n",
       "   Peruvian Restaurant  Pet Café  Pet Service  Physical Therapist  Pie Shop  \\\n",
       "0                  NaN       NaN          NaN                 NaN       NaN   \n",
       "1                  NaN       NaN          NaN                 NaN       NaN   \n",
       "2                  NaN       NaN          NaN                 NaN       NaN   \n",
       "3                  NaN       NaN          NaN                 NaN       NaN   \n",
       "4                  NaN       NaN          NaN                 NaN       NaN   \n",
       "\n",
       "   Pilates Studio  Pool  Public Art  Residential Building (Apartment / Condo)  \\\n",
       "0             NaN   NaN         NaN                                       NaN   \n",
       "1             NaN   NaN         NaN                                       NaN   \n",
       "2             NaN   NaN         NaN                                       NaN   \n",
       "3             NaN   NaN         NaN                                       NaN   \n",
       "4             NaN   NaN         NaN                                       NaN   \n",
       "\n",
       "   Rock Club  Scandinavian Restaurant  School  Shanghai Restaurant  \\\n",
       "0        NaN                      NaN     NaN                  NaN   \n",
       "1        NaN                      NaN     NaN                  NaN   \n",
       "2        NaN                      NaN     NaN                  NaN   \n",
       "3        NaN                      NaN     NaN                  NaN   \n",
       "4        NaN                      NaN     NaN                  NaN   \n",
       "\n",
       "   Shipping Store  Soccer Field  Soup Place  Spanish Restaurant  Sports Club  \\\n",
       "0             NaN           NaN         NaN                 NaN          NaN   \n",
       "1             NaN           NaN         NaN                 NaN          NaN   \n",
       "2             NaN           NaN         NaN                 NaN          NaN   \n",
       "3             NaN           NaN         NaN                 NaN          NaN   \n",
       "4             NaN           NaN         NaN                 NaN          NaN   \n",
       "\n",
       "   Supplement Shop  Swiss Restaurant  Szechuan Restaurant  Taco Place  \\\n",
       "0              NaN               NaN                  NaN         NaN   \n",
       "1              NaN               NaN                  NaN         NaN   \n",
       "2              NaN               NaN                  NaN         NaN   \n",
       "3              NaN               NaN                  NaN         NaN   \n",
       "4              NaN               NaN                  NaN         NaN   \n",
       "\n",
       "   Tapas Restaurant  Tennis Stadium  Thrift / Vintage Store  Tiki Bar  \\\n",
       "0               NaN             NaN                     NaN       NaN   \n",
       "1               NaN             NaN                     NaN       NaN   \n",
       "2               NaN             NaN                     NaN       NaN   \n",
       "3               NaN             NaN                     NaN       NaN   \n",
       "4               NaN             NaN                     NaN       NaN   \n",
       "\n",
       "   Tourist Information Center  Turkish Restaurant  Udon Restaurant  \\\n",
       "0                         NaN                 NaN              NaN   \n",
       "1                         NaN                 NaN              NaN   \n",
       "2                         NaN                 NaN              NaN   \n",
       "3                         NaN                 NaN              NaN   \n",
       "4                         NaN                 NaN              NaN   \n",
       "\n",
       "   Veterinarian  Video Store  Volleyball Court  Waterfront  Whisky Bar  \\\n",
       "0           NaN          NaN               NaN         NaN         NaN   \n",
       "1           NaN          NaN               NaN         NaN         NaN   \n",
       "2           NaN          NaN               NaN         NaN         NaN   \n",
       "3           NaN          NaN               NaN         NaN         NaN   \n",
       "4           NaN          NaN               NaN         NaN         NaN   \n",
       "\n",
       "   Wings Joint  Women's Store  \n",
       "0          NaN            NaN  \n",
       "1          NaN            NaN  \n",
       "2          NaN            NaN  \n",
       "3          NaN            NaN  \n",
       "4          NaN            NaN  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#aggregating the two dataframe\n",
    "neigh_grouped=pd.merge(Toronto_grouped, Manhattan_grouped, how='outer').reset_index(drop=True)\n",
    "neigh_grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4, 4, 4, 4, 0, 4, 4, 0, 0, 0])"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 5\n",
    "\n",
    "neigh_grouped_clustering = neigh_grouped.drop('Neighborhood', 1).fillna(0)\n",
    "\n",
    "# run k-means clustering\n",
    "kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(neigh_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "kmeans.labels_[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tor4=df_tor3.drop(['Postal Code'],axis=1)\n",
    "df_tor4['City']='Toronto'\n",
    "df_man=manhattan_data\n",
    "df_man['City']='New York'\n",
    "neigh_merged=pd.merge(df_tor4, df_man, how='outer').reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add clustering labels\n",
    "neigh_merged['Cluster Labels'] = kmeans.labels_\n",
    "#merge the data\n",
    "final=pd.merge(left=neigh_merged, right=neigh_df ,on=['Neighborhood'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the final result in the following table: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "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>Neighborhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>City</th>\n",
       "      <th>Cluster Labels</th>\n",
       "      <th>1st Most Common Venue</th>\n",
       "      <th>2nd Most Common Venue</th>\n",
       "      <th>3rd Most Common Venue</th>\n",
       "      <th>4th Most Common Venue</th>\n",
       "      <th>5th Most Common Venue</th>\n",
       "      <th>6th Most Common Venue</th>\n",
       "      <th>7th Most Common Venue</th>\n",
       "      <th>8th Most Common Venue</th>\n",
       "      <th>9th Most Common Venue</th>\n",
       "      <th>10th Most Common Venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Beaches</td>\n",
       "      <td>43.676357</td>\n",
       "      <td>-79.293031</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Health Food Store</td>\n",
       "      <td>Wine Shop</td>\n",
       "      <td>Cupcake Shop</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>The Danforth West, Riverdale</td>\n",
       "      <td>43.679557</td>\n",
       "      <td>-79.352188</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Café</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>India Bazaar, The Beaches West</td>\n",
       "      <td>43.668999</td>\n",
       "      <td>-79.315572</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Fish &amp; Chips Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Pub</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>Studio District</td>\n",
       "      <td>43.659526</td>\n",
       "      <td>-79.340923</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Cheese Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Park</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>43.715383</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Sporting Goods Shop</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "      <td>43.704324</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>43.689574</td>\n",
       "      <td>-79.383160</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Tennis Court</td>\n",
       "      <td>Cuban Restaurant</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Summerhill West, Rathnelly, South Hill, Forest...</td>\n",
       "      <td>43.686412</td>\n",
       "      <td>-79.400049</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bagel Shop</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Sports Bar</td>\n",
       "      <td>Bank</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Rosedale</td>\n",
       "      <td>43.679563</td>\n",
       "      <td>-79.377529</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Cuban Restaurant</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town, Cabbagetown</td>\n",
       "      <td>43.667967</td>\n",
       "      <td>-79.367675</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Park</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Church and Wellesley</td>\n",
       "      <td>43.665860</td>\n",
       "      <td>-79.383160</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>2</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Men's Store</td>\n",
       "      <td>Gay Bar</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Hobby Shop</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Regent Park, Harbourfront</td>\n",
       "      <td>43.654260</td>\n",
       "      <td>-79.360636</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Park</td>\n",
       "      <td>Café</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Theater</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Health Food Store</td>\n",
       "      <td>Historic Site</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Garden District, Ryerson</td>\n",
       "      <td>43.657162</td>\n",
       "      <td>-79.378937</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Ramen Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Theater</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Tea Room</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>St. James Town</td>\n",
       "      <td>43.651494</td>\n",
       "      <td>-79.375418</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Café</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Creperie</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Berczy Park</td>\n",
       "      <td>43.644771</td>\n",
       "      <td>-79.373306</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pharmacy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Central Bay Street</td>\n",
       "      <td>43.657952</td>\n",
       "      <td>-79.387383</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Comic Shop</td>\n",
       "      <td>Salad Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Poke Place</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Richmond, Adelaide, King</td>\n",
       "      <td>43.650571</td>\n",
       "      <td>-79.384568</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Concert Hall</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Smoke Shop</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Harbourfront East, Union Station, Toronto Islands</td>\n",
       "      <td>43.640816</td>\n",
       "      <td>-79.381752</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Aquarium</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Park</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Plaza</td>\n",
       "      <td>Brewery</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bistro</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Toronto Dominion Centre, Design Exchange</td>\n",
       "      <td>43.647177</td>\n",
       "      <td>-79.381576</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>2</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Bar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Commerce Court, Victoria Hotel</td>\n",
       "      <td>43.648198</td>\n",
       "      <td>-79.379817</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Café</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Roselawn</td>\n",
       "      <td>43.711695</td>\n",
       "      <td>-79.416936</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Wine Shop</td>\n",
       "      <td>Cupcake Shop</td>\n",
       "      <td>Dumpling Restaurant</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Forest Hill North &amp; West, Forest Hill Road Park</td>\n",
       "      <td>43.696948</td>\n",
       "      <td>-79.411307</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Jewelry Store</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Cuban Restaurant</td>\n",
       "      <td>Doner Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Distribution Center</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.672710</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Pub</td>\n",
       "      <td>History Museum</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>University of Toronto, Harbord</td>\n",
       "      <td>43.662696</td>\n",
       "      <td>-79.400049</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Bank</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Kensington Market, Chinatown, Grange Park</td>\n",
       "      <td>43.653206</td>\n",
       "      <td>-79.400049</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>2</td>\n",
       "      <td>Café</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "      <td>Caribbean Restaurant</td>\n",
       "      <td>Cheese Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>CN Tower, King and Spadina, Railway Lands, Har...</td>\n",
       "      <td>43.628947</td>\n",
       "      <td>-79.394420</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>1</td>\n",
       "      <td>Airport Service</td>\n",
       "      <td>Airport Lounge</td>\n",
       "      <td>Airport Terminal</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Plane</td>\n",
       "      <td>Sculpture Garden</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Airport Gate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Stn A PO Boxes</td>\n",
       "      <td>43.646435</td>\n",
       "      <td>-79.374846</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Cheese Shop</td>\n",
       "      <td>Creperie</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>First Canadian Place, Underground city</td>\n",
       "      <td>43.648429</td>\n",
       "      <td>-79.382280</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Tea Room</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Christie</td>\n",
       "      <td>43.669542</td>\n",
       "      <td>-79.422564</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Café</td>\n",
       "      <td>Park</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Baby Store</td>\n",
       "      <td>Candy Store</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Nightclub</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Dufferin, Dovercourt Village</td>\n",
       "      <td>43.669005</td>\n",
       "      <td>-79.442259</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Bank</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Music Venue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Little Portugal, Trinity</td>\n",
       "      <td>43.647927</td>\n",
       "      <td>-79.419750</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Men's Store</td>\n",
       "      <td>Gift Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Brockton, Parkdale Village, Exhibition Place</td>\n",
       "      <td>43.636847</td>\n",
       "      <td>-79.428191</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Office</td>\n",
       "      <td>Pet Store</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Climbing Gym</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>High Park, The Junction South</td>\n",
       "      <td>43.661608</td>\n",
       "      <td>-79.464763</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Flea Market</td>\n",
       "      <td>Park</td>\n",
       "      <td>Gastropub</td>\n",
       "      <td>Cajun / Creole Restaurant</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Parkdale, Roncesvalles</td>\n",
       "      <td>43.648960</td>\n",
       "      <td>-79.456325</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Gift Shop</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Cuban Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Dog Run</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Eastern European Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>West Toronto</td>\n",
       "      <td>Runnymede, Swansea</td>\n",
       "      <td>43.651571</td>\n",
       "      <td>-79.484450</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>South American Restaurant</td>\n",
       "      <td>Smoothie Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Downtown Toronto</td>\n",
       "      <td>Queen's Park, Ontario Provincial Government</td>\n",
       "      <td>43.662301</td>\n",
       "      <td>-79.389494</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Diner</td>\n",
       "      <td>College Cafeteria</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>Smoothie Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Park</td>\n",
       "      <td>College Auditorium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>East Toronto</td>\n",
       "      <td>Business reply mail Processing Centre, South C...</td>\n",
       "      <td>43.662744</td>\n",
       "      <td>-79.321558</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>4</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Skate Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Auto Workshop</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Burrito Place</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Comic Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Marble Hill</td>\n",
       "      <td>40.876551</td>\n",
       "      <td>-73.910660</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Kids Store</td>\n",
       "      <td>Steakhouse</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Miscellaneous Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chinatown</td>\n",
       "      <td>40.715618</td>\n",
       "      <td>-73.994279</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Washington Heights</td>\n",
       "      <td>40.851903</td>\n",
       "      <td>-73.936900</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Mobile Phone Shop</td>\n",
       "      <td>Wine Shop</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>New American Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Tapas Restaurant</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Inwood</td>\n",
       "      <td>40.867684</td>\n",
       "      <td>-73.921210</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Park</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Lounge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hamilton Heights</td>\n",
       "      <td>40.823604</td>\n",
       "      <td>-73.949688</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>School</td>\n",
       "      <td>Caribbean Restaurant</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Manhattanville</td>\n",
       "      <td>40.816934</td>\n",
       "      <td>-73.957385</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Ramen Restaurant</td>\n",
       "      <td>Bike Trail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Central Harlem</td>\n",
       "      <td>40.815976</td>\n",
       "      <td>-73.943211</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>African Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.792249</td>\n",
       "      <td>-73.944182</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Latin American Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>New American Restaurant</td>\n",
       "      <td>Beer Bar</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Taco Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper East Side</td>\n",
       "      <td>40.775639</td>\n",
       "      <td>-73.960508</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Art Gallery</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Yorkville</td>\n",
       "      <td>40.775930</td>\n",
       "      <td>-73.947118</td>\n",
       "      <td>New York</td>\n",
       "      <td>0</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Wine Shop</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lenox Hill</td>\n",
       "      <td>40.768113</td>\n",
       "      <td>-73.958860</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Turkish Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Paper / Office Supplies Store</td>\n",
       "      <td>French Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Roosevelt Island</td>\n",
       "      <td>40.762160</td>\n",
       "      <td>-73.949168</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Dry Cleaner</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Bridge</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Soccer Field</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>School</td>\n",
       "      <td>Sandwich Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.787658</td>\n",
       "      <td>-73.977059</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Mediterranean Restaurant</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Bar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lincoln Square</td>\n",
       "      <td>40.773529</td>\n",
       "      <td>-73.985338</td>\n",
       "      <td>New York</td>\n",
       "      <td>0</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "      <td>Theater</td>\n",
       "      <td>Concert Hall</td>\n",
       "      <td>Plaza</td>\n",
       "      <td>Indie Movie Theater</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Café</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Mediterranean Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Clinton</td>\n",
       "      <td>40.759101</td>\n",
       "      <td>-73.996119</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Theater</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Wine Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Lounge</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Comedy Club</td>\n",
       "      <td>Health Food Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Midtown</td>\n",
       "      <td>40.754691</td>\n",
       "      <td>-73.981669</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Theater</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Tailor Shop</td>\n",
       "      <td>Sporting Goods Shop</td>\n",
       "      <td>Food Stand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Murray Hill</td>\n",
       "      <td>40.748303</td>\n",
       "      <td>-73.978332</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Jewish Restaurant</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Mediterranean Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Bagel Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>40.744035</td>\n",
       "      <td>-74.003116</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Cupcake Shop</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Liquor Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Greenwich Village</td>\n",
       "      <td>40.726933</td>\n",
       "      <td>-73.999914</td>\n",
       "      <td>New York</td>\n",
       "      <td>0</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Electronics Store</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Optical Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Village</td>\n",
       "      <td>40.727847</td>\n",
       "      <td>-73.982226</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Korean Restaurant</td>\n",
       "      <td>Vegetarian / Vegan Restaurant</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Wine Bar</td>\n",
       "      <td>Cheese Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lower East Side</td>\n",
       "      <td>40.717807</td>\n",
       "      <td>-73.980890</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Café</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Art Gallery</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Ramen Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Tribeca</td>\n",
       "      <td>40.721522</td>\n",
       "      <td>-74.010683</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Wine Bar</td>\n",
       "      <td>Café</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Men's Store</td>\n",
       "      <td>Scenic Lookout</td>\n",
       "      <td>Greek Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Steakhouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Little Italy</td>\n",
       "      <td>40.719324</td>\n",
       "      <td>-73.997305</td>\n",
       "      <td>New York</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Wine Bar</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Mediterranean Restaurant</td>\n",
       "      <td>Newsstand</td>\n",
       "      <td>Jewelry Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Soho</td>\n",
       "      <td>40.722184</td>\n",
       "      <td>-74.000657</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Mediterranean Restaurant</td>\n",
       "      <td>Women's Store</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Salon / Barbershop</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Men's Store</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>West Village</td>\n",
       "      <td>40.734434</td>\n",
       "      <td>-74.006180</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Wine Bar</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Chinese Restaurant</td>\n",
       "      <td>New American Restaurant</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Taco Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Manhattan Valley</td>\n",
       "      <td>40.797307</td>\n",
       "      <td>-73.964286</td>\n",
       "      <td>New York</td>\n",
       "      <td>0</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Hawaiian Restaurant</td>\n",
       "      <td>Health Food Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Morningside Heights</td>\n",
       "      <td>40.808000</td>\n",
       "      <td>-73.963896</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>College Cafeteria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Gramercy</td>\n",
       "      <td>40.737210</td>\n",
       "      <td>-73.981376</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Bagel Shop</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Park</td>\n",
       "      <td>Thrift / Vintage Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>American Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Battery Park City</td>\n",
       "      <td>40.711932</td>\n",
       "      <td>-74.016869</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Memorial Site</td>\n",
       "      <td>Gourmet Shop</td>\n",
       "      <td>Food Court</td>\n",
       "      <td>Plaza</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>Boat or Ferry</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Financial District</td>\n",
       "      <td>40.707107</td>\n",
       "      <td>-74.010665</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Falafel Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Food Truck</td>\n",
       "      <td>Food Court</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Carnegie Hill</td>\n",
       "      <td>40.782683</td>\n",
       "      <td>-73.953256</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Noho</td>\n",
       "      <td>40.723259</td>\n",
       "      <td>-73.988434</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Rock Club</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Boutique</td>\n",
       "      <td>Bookstore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Civic Center</td>\n",
       "      <td>40.715229</td>\n",
       "      <td>-74.005415</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Park</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Spa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Midtown South</td>\n",
       "      <td>40.748510</td>\n",
       "      <td>-73.988713</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Korean Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Cosmetics Shop</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Bookstore</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Sutton Place</td>\n",
       "      <td>40.760280</td>\n",
       "      <td>-73.963556</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Beer Garden</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Gym</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Turtle Bay</td>\n",
       "      <td>40.752042</td>\n",
       "      <td>-73.967708</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Karaoke Bar</td>\n",
       "      <td>Wine Bar</td>\n",
       "      <td>Seafood Restaurant</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Food Truck</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Tudor City</td>\n",
       "      <td>40.746917</td>\n",
       "      <td>-73.971219</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Café</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Thai Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Vietnamese Restaurant</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Spanish Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Stuyvesant Town</td>\n",
       "      <td>40.731000</td>\n",
       "      <td>-73.974052</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Park</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Fountain</td>\n",
       "      <td>Baseball Field</td>\n",
       "      <td>Bistro</td>\n",
       "      <td>Cocktail Bar</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Harbor / Marina</td>\n",
       "      <td>Gas Station</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Flatiron</td>\n",
       "      <td>40.739673</td>\n",
       "      <td>-73.990947</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Japanese Restaurant</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>New American Restaurant</td>\n",
       "      <td>Spa</td>\n",
       "      <td>Sporting Goods Shop</td>\n",
       "      <td>Furniture / Home Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hudson Yards</td>\n",
       "      <td>40.756658</td>\n",
       "      <td>-74.000111</td>\n",
       "      <td>New York</td>\n",
       "      <td>4</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Café</td>\n",
       "      <td>Park</td>\n",
       "      <td>Lounge</td>\n",
       "      <td>Dog Run</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Borough                                       Neighborhood  \\\n",
       "0       East Toronto                                        The Beaches   \n",
       "1       East Toronto                       The Danforth West, Riverdale   \n",
       "2       East Toronto                     India Bazaar, The Beaches West   \n",
       "3       East Toronto                                    Studio District   \n",
       "4    Central Toronto                                      Lawrence Park   \n",
       "5    Central Toronto                                   Davisville North   \n",
       "6    Central Toronto                  North Toronto West, Lawrence Park   \n",
       "7    Central Toronto                                         Davisville   \n",
       "8    Central Toronto                        Moore Park, Summerhill East   \n",
       "9    Central Toronto  Summerhill West, Rathnelly, South Hill, Forest...   \n",
       "10  Downtown Toronto                                           Rosedale   \n",
       "11  Downtown Toronto                        St. James Town, Cabbagetown   \n",
       "12  Downtown Toronto                               Church and Wellesley   \n",
       "13  Downtown Toronto                          Regent Park, Harbourfront   \n",
       "14  Downtown Toronto                           Garden District, Ryerson   \n",
       "15  Downtown Toronto                                     St. James Town   \n",
       "16  Downtown Toronto                                        Berczy Park   \n",
       "17  Downtown Toronto                                 Central Bay Street   \n",
       "18  Downtown Toronto                           Richmond, Adelaide, King   \n",
       "19  Downtown Toronto  Harbourfront East, Union Station, Toronto Islands   \n",
       "20  Downtown Toronto           Toronto Dominion Centre, Design Exchange   \n",
       "21  Downtown Toronto                     Commerce Court, Victoria Hotel   \n",
       "22   Central Toronto                                           Roselawn   \n",
       "23   Central Toronto    Forest Hill North & West, Forest Hill Road Park   \n",
       "24   Central Toronto                The Annex, North Midtown, Yorkville   \n",
       "25  Downtown Toronto                     University of Toronto, Harbord   \n",
       "26  Downtown Toronto          Kensington Market, Chinatown, Grange Park   \n",
       "27  Downtown Toronto  CN Tower, King and Spadina, Railway Lands, Har...   \n",
       "28  Downtown Toronto                                     Stn A PO Boxes   \n",
       "29  Downtown Toronto             First Canadian Place, Underground city   \n",
       "30  Downtown Toronto                                           Christie   \n",
       "31      West Toronto                       Dufferin, Dovercourt Village   \n",
       "32      West Toronto                           Little Portugal, Trinity   \n",
       "33      West Toronto       Brockton, Parkdale Village, Exhibition Place   \n",
       "34      West Toronto                      High Park, The Junction South   \n",
       "35      West Toronto                             Parkdale, Roncesvalles   \n",
       "36      West Toronto                                 Runnymede, Swansea   \n",
       "37  Downtown Toronto        Queen's Park, Ontario Provincial Government   \n",
       "38      East Toronto  Business reply mail Processing Centre, South C...   \n",
       "39         Manhattan                                        Marble Hill   \n",
       "40         Manhattan                                          Chinatown   \n",
       "41         Manhattan                                 Washington Heights   \n",
       "42         Manhattan                                             Inwood   \n",
       "43         Manhattan                                   Hamilton Heights   \n",
       "44         Manhattan                                     Manhattanville   \n",
       "45         Manhattan                                     Central Harlem   \n",
       "46         Manhattan                                        East Harlem   \n",
       "47         Manhattan                                    Upper East Side   \n",
       "48         Manhattan                                          Yorkville   \n",
       "49         Manhattan                                         Lenox Hill   \n",
       "50         Manhattan                                   Roosevelt Island   \n",
       "51         Manhattan                                    Upper West Side   \n",
       "52         Manhattan                                     Lincoln Square   \n",
       "53         Manhattan                                            Clinton   \n",
       "54         Manhattan                                            Midtown   \n",
       "55         Manhattan                                        Murray Hill   \n",
       "56         Manhattan                                            Chelsea   \n",
       "57         Manhattan                                  Greenwich Village   \n",
       "58         Manhattan                                       East Village   \n",
       "59         Manhattan                                    Lower East Side   \n",
       "60         Manhattan                                            Tribeca   \n",
       "61         Manhattan                                       Little Italy   \n",
       "62         Manhattan                                               Soho   \n",
       "63         Manhattan                                       West Village   \n",
       "64         Manhattan                                   Manhattan Valley   \n",
       "65         Manhattan                                Morningside Heights   \n",
       "66         Manhattan                                           Gramercy   \n",
       "67         Manhattan                                  Battery Park City   \n",
       "68         Manhattan                                 Financial District   \n",
       "69         Manhattan                                      Carnegie Hill   \n",
       "70         Manhattan                                               Noho   \n",
       "71         Manhattan                                       Civic Center   \n",
       "72         Manhattan                                      Midtown South   \n",
       "73         Manhattan                                       Sutton Place   \n",
       "74         Manhattan                                         Turtle Bay   \n",
       "75         Manhattan                                         Tudor City   \n",
       "76         Manhattan                                    Stuyvesant Town   \n",
       "77         Manhattan                                           Flatiron   \n",
       "78         Manhattan                                       Hudson Yards   \n",
       "\n",
       "     Latitude  Longitude      City  Cluster Labels  1st Most Common Venue  \\\n",
       "0   43.676357 -79.293031   Toronto               4                  Trail   \n",
       "1   43.679557 -79.352188   Toronto               4       Greek Restaurant   \n",
       "2   43.668999 -79.315572   Toronto               4                   Park   \n",
       "3   43.659526 -79.340923   Toronto               4                   Café   \n",
       "4   43.728020 -79.388790   Toronto               0                   Park   \n",
       "5   43.712751 -79.390197   Toronto               4                   Park   \n",
       "6   43.715383 -79.405678   Toronto               4            Coffee Shop   \n",
       "7   43.704324 -79.388790   Toronto               0            Pizza Place   \n",
       "8   43.689574 -79.383160   Toronto               0             Restaurant   \n",
       "9   43.686412 -79.400049   Toronto               0                    Pub   \n",
       "10  43.679563 -79.377529   Toronto               4                   Park   \n",
       "11  43.667967 -79.367675   Toronto               0            Coffee Shop   \n",
       "12  43.665860 -79.383160   Toronto               2       Sushi Restaurant   \n",
       "13  43.654260 -79.360636   Toronto               0            Coffee Shop   \n",
       "14  43.657162 -79.378937   Toronto               4            Coffee Shop   \n",
       "15  43.651494 -79.375418   Toronto               4                   Café   \n",
       "16  43.644771 -79.373306   Toronto               4            Coffee Shop   \n",
       "17  43.657952 -79.387383   Toronto               4            Coffee Shop   \n",
       "18  43.650571 -79.384568   Toronto               3            Coffee Shop   \n",
       "19  43.640816 -79.381752   Toronto               4               Aquarium   \n",
       "20  43.647177 -79.381576   Toronto               2            Coffee Shop   \n",
       "21  43.648198 -79.379817   Toronto               4                   Café   \n",
       "22  43.711695 -79.416936   Toronto               4                 Garden   \n",
       "23  43.696948 -79.411307   Toronto               0          Jewelry Store   \n",
       "24  43.672710 -79.405678   Toronto               0                   Café   \n",
       "25  43.662696 -79.400049   Toronto               0                   Café   \n",
       "26  43.653206 -79.400049   Toronto               2                   Café   \n",
       "27  43.628947 -79.394420   Toronto               1        Airport Service   \n",
       "28  43.646435 -79.374846   Toronto               0                   Café   \n",
       "29  43.648429 -79.382280   Toronto               4            Coffee Shop   \n",
       "30  43.669542 -79.422564   Toronto               0          Grocery Store   \n",
       "31  43.669005 -79.442259   Toronto               4               Pharmacy   \n",
       "32  43.647927 -79.419750   Toronto               4                    Bar   \n",
       "33  43.636847 -79.428191   Toronto               0                   Café   \n",
       "34  43.661608 -79.464763   Toronto               0     Mexican Restaurant   \n",
       "35  43.648960 -79.456325   Toronto               4              Gift Shop   \n",
       "36  43.651571 -79.484450   Toronto               4            Coffee Shop   \n",
       "37  43.662301 -79.389494   Toronto               0            Coffee Shop   \n",
       "38  43.662744 -79.321558   Toronto               4     Light Rail Station   \n",
       "39  40.876551 -73.910660  New York               4                    Gym   \n",
       "40  40.715618 -73.994279  New York               4     Chinese Restaurant   \n",
       "41  40.851903 -73.936900  New York               4                   Café   \n",
       "42  40.867684 -73.921210  New York               4     Mexican Restaurant   \n",
       "43  40.823604 -73.949688  New York               4            Coffee Shop   \n",
       "44  40.816934 -73.957385  New York               4            Coffee Shop   \n",
       "45  40.815976 -73.943211  New York               4     African Restaurant   \n",
       "46  40.792249 -73.944182  New York               4     Mexican Restaurant   \n",
       "47  40.775639 -73.960508  New York               4     Italian Restaurant   \n",
       "48  40.775930 -73.947118  New York               0     Italian Restaurant   \n",
       "49  40.768113 -73.958860  New York               4           Burger Joint   \n",
       "50  40.762160 -73.949168  New York               4                   Park   \n",
       "51  40.787658 -73.977059  New York               4     Italian Restaurant   \n",
       "52  40.773529 -73.985338  New York               0  Performing Arts Venue   \n",
       "53  40.759101 -73.996119  New York               4                Theater   \n",
       "54  40.754691 -73.981669  New York               4         Clothing Store   \n",
       "55  40.748303 -73.978332  New York               4    Japanese Restaurant   \n",
       "56  40.744035 -74.003116  New York               4            Coffee Shop   \n",
       "57  40.726933 -73.999914  New York               0     Italian Restaurant   \n",
       "58  40.727847 -73.982226  New York               4                    Bar   \n",
       "59  40.717807 -73.980890  New York               4                   Café   \n",
       "60  40.721522 -74.010683  New York               4                   Park   \n",
       "61  40.719324 -73.997305  New York               0                   Café   \n",
       "62  40.722184 -74.000657  New York               4         Clothing Store   \n",
       "63  40.734434 -74.006180  New York               4     Italian Restaurant   \n",
       "64  40.797307 -73.964286  New York               0                    Bar   \n",
       "65  40.808000 -73.963896  New York               4                   Park   \n",
       "66  40.737210 -73.981376  New York               4             Bagel Shop   \n",
       "67  40.711932 -74.016869  New York               4                   Park   \n",
       "68  40.707107 -74.010665  New York               4            Coffee Shop   \n",
       "69  40.782683 -73.953256  New York               4            Pizza Place   \n",
       "70  40.723259 -73.988434  New York               4            Coffee Shop   \n",
       "71  40.715229 -74.005415  New York               4   Gym / Fitness Center   \n",
       "72  40.748510 -73.988713  New York               4      Korean Restaurant   \n",
       "73  40.760280 -73.963556  New York               4     Italian Restaurant   \n",
       "74  40.752042 -73.967708  New York               4                   Park   \n",
       "75  40.746917 -73.971219  New York               4                   Park   \n",
       "76  40.731000 -73.974052  New York               4                   Park   \n",
       "77  40.739673 -73.990947  New York               4    American Restaurant   \n",
       "78  40.756658 -74.000111  New York               4   Gym / Fitness Center   \n",
       "\n",
       "            2nd Most Common Venue  3rd Most Common Venue  \\\n",
       "0                             Pub      Health Food Store   \n",
       "1              Italian Restaurant            Coffee Shop   \n",
       "2               Fish & Chips Shop         Sandwich Place   \n",
       "3                     Coffee Shop              Gastropub   \n",
       "4                     Swim School               Bus Line   \n",
       "5                           Hotel         Breakfast Spot   \n",
       "6                  Clothing Store            Yoga Studio   \n",
       "7                  Sandwich Place           Dessert Shop   \n",
       "8                            Park                  Trail   \n",
       "9                     Coffee Shop             Bagel Shop   \n",
       "10                     Playground                  Trail   \n",
       "11                           Café            Pizza Place   \n",
       "12                    Coffee Shop    Japanese Restaurant   \n",
       "13                            Pub                 Bakery   \n",
       "14                           Café         Clothing Store   \n",
       "15                 Cosmetics Shop            Coffee Shop   \n",
       "16                         Bakery            Cheese Shop   \n",
       "17                 Sandwich Place        Bubble Tea Shop   \n",
       "18                     Steakhouse                   Café   \n",
       "19                    Coffee Shop                   Park   \n",
       "20                           Café             Restaurant   \n",
       "21                          Hotel            Coffee Shop   \n",
       "22                      Wine Shop           Cupcake Shop   \n",
       "23                          Trail       Sushi Restaurant   \n",
       "24                 Sandwich Place            Coffee Shop   \n",
       "25                     Restaurant         Sandwich Place   \n",
       "26  Vegetarian / Vegan Restaurant     Mexican Restaurant   \n",
       "27                 Airport Lounge       Airport Terminal   \n",
       "28                     Restaurant         Farmers Market   \n",
       "29                           Café             Restaurant   \n",
       "30                           Café                   Park   \n",
       "31                         Bakery                    Gym   \n",
       "32                    Coffee Shop  Vietnamese Restaurant   \n",
       "33          Performing Arts Venue                 Bakery   \n",
       "34                           Café        Thai Restaurant   \n",
       "35                 Breakfast Spot       Cuban Restaurant   \n",
       "36                           Café     Italian Restaurant   \n",
       "37                          Diner      College Cafeteria   \n",
       "38                     Skate Park            Pizza Place   \n",
       "39                    Coffee Shop             Kids Store   \n",
       "40            American Restaurant         Ice Cream Shop   \n",
       "41                    Coffee Shop      Mobile Phone Shop   \n",
       "42                           Café             Restaurant   \n",
       "43                           Café            Pizza Place   \n",
       "44                  Deli / Bodega       Sushi Restaurant   \n",
       "45                    Pizza Place     Seafood Restaurant   \n",
       "46                Thai Restaurant                 Bakery   \n",
       "47                         Bakery      French Restaurant   \n",
       "48                            Gym            Coffee Shop   \n",
       "49           Gym / Fitness Center                    Gym   \n",
       "50                    Pizza Place            Dry Cleaner   \n",
       "51                    Coffee Shop         Ice Cream Shop   \n",
       "52                        Theater           Concert Hall   \n",
       "53           Gym / Fitness Center              Wine Shop   \n",
       "54                         Bakery                  Hotel   \n",
       "55              Jewish Restaurant         Sandwich Place   \n",
       "56            American Restaurant     Italian Restaurant   \n",
       "57               Sushi Restaurant                   Café   \n",
       "58                    Pizza Place  Vietnamese Restaurant   \n",
       "59             Chinese Restaurant           Cocktail Bar   \n",
       "60                       Wine Bar                   Café   \n",
       "61                    Coffee Shop         Ice Cream Shop   \n",
       "62       Mediterranean Restaurant          Women's Store   \n",
       "63                   Cocktail Bar               Wine Bar   \n",
       "64                    Yoga Studio            Pizza Place   \n",
       "65                      Bookstore            Coffee Shop   \n",
       "66                 Ice Cream Shop            Pizza Place   \n",
       "67                    Coffee Shop          Memorial Site   \n",
       "68                    Pizza Place   Gym / Fitness Center   \n",
       "69           Gym / Fitness Center            Coffee Shop   \n",
       "70             Italian Restaurant     Mexican Restaurant   \n",
       "71                    Coffee Shop           Cocktail Bar   \n",
       "72                    Coffee Shop         Cosmetics Shop   \n",
       "73                    Yoga Studio            Beer Garden   \n",
       "74                    Coffee Shop       Sushi Restaurant   \n",
       "75                  Deli / Bodega                   Café   \n",
       "76                            Bar               Fountain   \n",
       "77                    Yoga Studio    Japanese Restaurant   \n",
       "78            American Restaurant     Italian Restaurant   \n",
       "\n",
       "            4th Most Common Venue      5th Most Common Venue  \\\n",
       "0                       Wine Shop               Cupcake Shop   \n",
       "1          Furniture / Home Store                 Restaurant   \n",
       "2              Light Rail Station         Italian Restaurant   \n",
       "3                         Brewery                     Bakery   \n",
       "4                    Dance Studio                 Donut Shop   \n",
       "5            Gym / Fitness Center             Sandwich Place   \n",
       "6              Mexican Restaurant                      Diner   \n",
       "7                Sushi Restaurant                Coffee Shop   \n",
       "8                    Tennis Court           Cuban Restaurant   \n",
       "9                     Supermarket                 Sports Bar   \n",
       "10               Cuban Restaurant                 Donut Shop   \n",
       "11             Chinese Restaurant                 Restaurant   \n",
       "12                    Yoga Studio                Men's Store   \n",
       "13                           Park                       Café   \n",
       "14             Italian Restaurant           Ramen Restaurant   \n",
       "15                       Creperie                      Hotel   \n",
       "16                   Cocktail Bar             Farmers Market   \n",
       "17                           Café         Italian Restaurant   \n",
       "18                          Hotel               Concert Hall   \n",
       "19                           Café                      Hotel   \n",
       "20             Seafood Restaurant                      Hotel   \n",
       "21                            Gym                 Restaurant   \n",
       "22            Dumpling Restaurant                 Donut Shop   \n",
       "23                           Park                     Garden   \n",
       "24                    Pizza Place           Asian Restaurant   \n",
       "25                            Bar                     Bakery   \n",
       "26                    Coffee Shop               Dessert Shop   \n",
       "27                  Boat or Ferry                   Boutique   \n",
       "28             Seafood Restaurant                Coffee Shop   \n",
       "29                          Hotel                 Steakhouse   \n",
       "30             Italian Restaurant                      Diner   \n",
       "31                  Grocery Store                       Bank   \n",
       "32  Vegetarian / Vegan Restaurant           Asian Restaurant   \n",
       "33                    Coffee Shop             Breakfast Spot   \n",
       "34             Italian Restaurant                Flea Market   \n",
       "35             Italian Restaurant                    Dog Run   \n",
       "36                    Pizza Place                        Pub   \n",
       "37                       Beer Bar              Smoothie Shop   \n",
       "38                 Farmers Market              Auto Workshop   \n",
       "39                     Steakhouse              Shopping Mall   \n",
       "40                       Boutique           Greek Restaurant   \n",
       "41                      Wine Shop                     Bakery   \n",
       "42                    Pizza Place                       Park   \n",
       "43             Mexican Restaurant              Deli / Bodega   \n",
       "44             Seafood Restaurant                        Bar   \n",
       "45                 Cosmetics Shop        American Restaurant   \n",
       "46                  Deli / Bodega  Latin American Restaurant   \n",
       "47               Sushi Restaurant        American Restaurant   \n",
       "48                  Deli / Bodega           Sushi Restaurant   \n",
       "49             Turkish Restaurant            Thai Restaurant   \n",
       "50                    Supermarket                     Bridge   \n",
       "51  Vegetarian / Vegan Restaurant                     Bakery   \n",
       "52                          Plaza        Indie Movie Theater   \n",
       "53                            Gym                      Hotel   \n",
       "54                      Bookstore                Coffee Shop   \n",
       "55                   Burger Joint   Mediterranean Restaurant   \n",
       "56             Seafood Restaurant                      Hotel   \n",
       "57                 Ice Cream Shop               Gourmet Shop   \n",
       "58                         Bakery               Dessert Shop   \n",
       "59            Japanese Restaurant                Art Gallery   \n",
       "60            American Restaurant                        Spa   \n",
       "61                 Sandwich Place                     Bakery   \n",
       "62                         Bakery         Salon / Barbershop   \n",
       "63            American Restaurant         Chinese Restaurant   \n",
       "64                            Spa         Mexican Restaurant   \n",
       "65            American Restaurant              Deli / Bodega   \n",
       "66             Italian Restaurant               Cocktail Bar   \n",
       "67                   Gourmet Shop                 Food Court   \n",
       "68                   Cocktail Bar         Falafel Restaurant   \n",
       "69                      Bookstore                     Bakery   \n",
       "70                      Rock Club              Grocery Store   \n",
       "71                    Yoga Studio                       Park   \n",
       "72            Japanese Restaurant                      Hotel   \n",
       "73                  Grocery Store     Furniture / Home Store   \n",
       "74              French Restaurant         Italian Restaurant   \n",
       "75             Mexican Restaurant            Thai Restaurant   \n",
       "76                 Baseball Field                     Bistro   \n",
       "77                   Cycle Studio                Coffee Shop   \n",
       "78                          Hotel                Coffee Shop   \n",
       "\n",
       "        6th Most Common Venue          7th Most Common Venue  \\\n",
       "0                  Donut Shop               Doner Restaurant   \n",
       "1              Ice Cream Shop                 Cosmetics Shop   \n",
       "2               Burrito Place                   Liquor Store   \n",
       "3         American Restaurant                    Yoga Studio   \n",
       "4            Doner Restaurant                        Dog Run   \n",
       "5            Department Store              Food & Drink Shop   \n",
       "6          Salon / Barbershop                            Spa   \n",
       "7          Italian Restaurant                           Café   \n",
       "8            Doner Restaurant                        Dog Run   \n",
       "9                        Bank                     Restaurant   \n",
       "10           Doner Restaurant                        Dog Run   \n",
       "11                        Pub                         Bakery   \n",
       "12                    Gay Bar                     Restaurant   \n",
       "13             Breakfast Spot                        Theater   \n",
       "14                  Bookstore                 Cosmetics Shop   \n",
       "15                  Gastropub             Seafood Restaurant   \n",
       "16                   Beer Bar             Seafood Restaurant   \n",
       "17                 Comic Shop                    Salad Place   \n",
       "18        American Restaurant                     Restaurant   \n",
       "19                      Plaza                        Brewery   \n",
       "20        Japanese Restaurant                       Beer Bar   \n",
       "21        American Restaurant             Seafood Restaurant   \n",
       "22           Doner Restaurant                        Dog Run   \n",
       "23           Cuban Restaurant               Doner Restaurant   \n",
       "24  Middle Eastern Restaurant                    Flower Shop   \n",
       "25                  Bookstore            Japanese Restaurant   \n",
       "26               Burger Joint                            Bar   \n",
       "27            Harbor / Marina                          Plane   \n",
       "28                   Beer Bar                    Cheese Shop   \n",
       "29              Deli / Bodega                       Tea Room   \n",
       "30                 Baby Store                    Candy Store   \n",
       "31                        Bar      Middle Eastern Restaurant   \n",
       "32                 Restaurant                           Café   \n",
       "33                     Office                      Pet Store   \n",
       "34                       Park                      Gastropub   \n",
       "35                        Bar                   Dessert Shop   \n",
       "36           Sushi Restaurant                    Yoga Studio   \n",
       "37             Sandwich Place                  Burrito Place   \n",
       "38                        Spa                  Burrito Place   \n",
       "39         Seafood Restaurant                 Sandwich Place   \n",
       "40            Bubble Tea Shop             Salon / Barbershop   \n",
       "41    New American Restaurant                           Park   \n",
       "42                     Bakery             Chinese Restaurant   \n",
       "43               Cocktail Bar                         School   \n",
       "44         Mexican Restaurant             Italian Restaurant   \n",
       "45                        Bar            Fried Chicken Joint   \n",
       "46             Sandwich Place        New American Restaurant   \n",
       "47       Gym / Fitness Center                    Art Gallery   \n",
       "48                  Wine Shop             Mexican Restaurant   \n",
       "49         Italian Restaurant                   Cycle Studio   \n",
       "50            Bubble Tea Shop                   Soccer Field   \n",
       "51            Thai Restaurant       Mediterranean Restaurant   \n",
       "52               Cycle Studio                           Café   \n",
       "53        American Restaurant                         Lounge   \n",
       "54                    Theater                   Cycle Studio   \n",
       "55                Coffee Shop                          Hotel   \n",
       "56             Ice Cream Shop              French Restaurant   \n",
       "57          French Restaurant              Electronics Store   \n",
       "58          Korean Restaurant  Vegetarian / Vegan Restaurant   \n",
       "59                Pizza Place                         Bakery   \n",
       "60                Men's Store                 Scenic Lookout   \n",
       "61                   Wine Bar             Salon / Barbershop   \n",
       "62               Dessert Shop                    Men's Store   \n",
       "63    New American Restaurant                   Gourmet Shop   \n",
       "64            Thai Restaurant                    Coffee Shop   \n",
       "65               Burger Joint                 Sandwich Place   \n",
       "66                       Park         Thrift / Vintage Store   \n",
       "67                      Plaza                          Hotel   \n",
       "68                        Gym                 Farmers Market   \n",
       "69                        Gym             Italian Restaurant   \n",
       "70          French Restaurant                    Pizza Place   \n",
       "71          French Restaurant               Sushi Restaurant   \n",
       "72             Clothing Store                   Dessert Shop   \n",
       "73           Department Store           Gym / Fitness Center   \n",
       "74                Karaoke Bar                       Wine Bar   \n",
       "75                Coffee Shop          Vietnamese Restaurant   \n",
       "76               Cocktail Bar                    Coffee Shop   \n",
       "77             Clothing Store        New American Restaurant   \n",
       "78                        Gym                           Café   \n",
       "\n",
       "          8th Most Common Venue          9th Most Common Venue  \\\n",
       "0                       Dog Run            Distribution Center   \n",
       "1                       Brewery                Bubble Tea Shop   \n",
       "2                    Restaurant                 Ice Cream Shop   \n",
       "3             Convenience Store                 Sandwich Place   \n",
       "4           Distribution Center                 Discount Store   \n",
       "5              Doner Restaurant                        Dog Run   \n",
       "6                    Restaurant            Sporting Goods Shop   \n",
       "7                           Gym                        Brewery   \n",
       "8           Distribution Center                 Discount Store   \n",
       "9                   Pizza Place                   Liquor Store   \n",
       "10          Distribution Center                 Discount Store   \n",
       "11                         Park             Italian Restaurant   \n",
       "12                   Hobby Shop            Distribution Center   \n",
       "13         Gym / Fitness Center              Health Food Store   \n",
       "14                      Theater           Fast Food Restaurant   \n",
       "15               Farmers Market                     Restaurant   \n",
       "16                   Restaurant                           Café   \n",
       "17                 Burger Joint                     Poke Place   \n",
       "18                Burrito Place                     Smoke Shop   \n",
       "19                   Restaurant                         Bistro   \n",
       "20                  Pizza Place           Gym / Fitness Center   \n",
       "21                     Beer Bar                  Deli / Bodega   \n",
       "22          Distribution Center                 Discount Store   \n",
       "23                      Dog Run            Distribution Center   \n",
       "24                          Pub                 History Museum   \n",
       "25                  Yoga Studio                            Pub   \n",
       "26        Vietnamese Restaurant           Caribbean Restaurant   \n",
       "27             Sculpture Garden            Rental Car Location   \n",
       "28                     Creperie                   Cocktail Bar   \n",
       "29          American Restaurant                            Gym   \n",
       "30                   Restaurant                      Nightclub   \n",
       "31                         Café                    Supermarket   \n",
       "32                  Men's Store                      Gift Shop   \n",
       "33            Convenience Store                   Climbing Gym   \n",
       "34    Cajun / Creole Restaurant                          Diner   \n",
       "35  Eastern European Restaurant                     Restaurant   \n",
       "36           Falafel Restaurant      South American Restaurant   \n",
       "37                         Café                           Park   \n",
       "38                   Restaurant           Gym / Fitness Center   \n",
       "39                  Pizza Place                       Pharmacy   \n",
       "40               Sandwich Place                            Spa   \n",
       "41             Tapas Restaurant                  Deli / Bodega   \n",
       "42                Deli / Bodega            American Restaurant   \n",
       "43         Caribbean Restaurant             Chinese Restaurant   \n",
       "44                     Boutique               Ramen Restaurant   \n",
       "45            French Restaurant             Chinese Restaurant   \n",
       "46                     Beer Bar              French Restaurant   \n",
       "47                        Hotel                    Pizza Place   \n",
       "48                         Park                          Diner   \n",
       "49                 Cocktail Bar  Paper / Office Supplies Store   \n",
       "50                     Bus Line                         School   \n",
       "51            Indian Restaurant             Seafood Restaurant   \n",
       "52                          Gym           Gym / Fitness Center   \n",
       "53                 Cocktail Bar                    Comedy Club   \n",
       "54                  Tailor Shop            Sporting Goods Shop   \n",
       "55         Gym / Fitness Center                            Gym   \n",
       "56                 Cupcake Shop      Middle Eastern Restaurant   \n",
       "57               Clothing Store                   Optical Shop   \n",
       "58               Ice Cream Shop                       Wine Bar   \n",
       "59             Ramen Restaurant                    Coffee Shop   \n",
       "60             Greek Restaurant                          Hotel   \n",
       "61     Mediterranean Restaurant                      Newsstand   \n",
       "62                     Boutique         Furniture / Home Store   \n",
       "63                  Coffee Shop                         Garden   \n",
       "64           Italian Restaurant            Hawaiian Restaurant   \n",
       "65                  Pizza Place                 Farmers Market   \n",
       "66                  Coffee Shop                          Hotel   \n",
       "67                          Gym                  Shopping Mall   \n",
       "68           Seafood Restaurant                     Food Truck   \n",
       "69            French Restaurant                           Café   \n",
       "70               Ice Cream Shop                       Boutique   \n",
       "71                       Bakery                            Gym   \n",
       "72                   Restaurant                      Bookstore   \n",
       "73                  Coffee Shop                            Bar   \n",
       "74           Seafood Restaurant                 Farmers Market   \n",
       "75                          Gym               Sushi Restaurant   \n",
       "76         Gym / Fitness Center                Harbor / Marina   \n",
       "77                          Spa            Sporting Goods Shop   \n",
       "78                         Park                         Lounge   \n",
       "\n",
       "      10th Most Common Venue  \n",
       "0             Discount Store  \n",
       "1                       Café  \n",
       "2                        Pub  \n",
       "3                Cheese Shop  \n",
       "4                      Diner  \n",
       "5        Distribution Center  \n",
       "6       Fast Food Restaurant  \n",
       "7                      Diner  \n",
       "8                      Diner  \n",
       "9           Sushi Restaurant  \n",
       "10                     Diner  \n",
       "11       Japanese Restaurant  \n",
       "12                 Bookstore  \n",
       "13             Historic Site  \n",
       "14                  Tea Room  \n",
       "15                 Bookstore  \n",
       "16                  Pharmacy  \n",
       "17               Pizza Place  \n",
       "18        Seafood Restaurant  \n",
       "19            Ice Cream Shop  \n",
       "20                       Bar  \n",
       "21       Japanese Restaurant  \n",
       "22                     Diner  \n",
       "23            Discount Store  \n",
       "24                Donut Shop  \n",
       "25                      Bank  \n",
       "26               Cheese Shop  \n",
       "27              Airport Gate  \n",
       "28        Italian Restaurant  \n",
       "29        Seafood Restaurant  \n",
       "30               Coffee Shop  \n",
       "31               Music Venue  \n",
       "32        Italian Restaurant  \n",
       "33                Restaurant  \n",
       "34            Discount Store  \n",
       "35                 Bookstore  \n",
       "36             Smoothie Shop  \n",
       "37        College Auditorium  \n",
       "38                Comic Shop  \n",
       "39        Miscellaneous Shop  \n",
       "40          Asian Restaurant  \n",
       "41            Ice Cream Shop  \n",
       "42                    Lounge  \n",
       "43          Sushi Restaurant  \n",
       "44                Bike Trail  \n",
       "45                 Bookstore  \n",
       "46                Taco Place  \n",
       "47               Yoga Studio  \n",
       "48                 Bookstore  \n",
       "49         French Restaurant  \n",
       "50            Sandwich Place  \n",
       "51                       Bar  \n",
       "52  Mediterranean Restaurant  \n",
       "53         Health Food Store  \n",
       "54                Food Stand  \n",
       "55                Bagel Shop  \n",
       "56              Liquor Store  \n",
       "57               Pizza Place  \n",
       "58               Cheese Shop  \n",
       "59            Sandwich Place  \n",
       "60                Steakhouse  \n",
       "61             Jewelry Store  \n",
       "62        Italian Restaurant  \n",
       "63                Taco Place  \n",
       "64         Health Food Store  \n",
       "65         College Cafeteria  \n",
       "66       American Restaurant  \n",
       "67             Boat or Ferry  \n",
       "68                Food Court  \n",
       "69               Yoga Studio  \n",
       "70                 Bookstore  \n",
       "71                       Spa  \n",
       "72       Fried Chicken Joint  \n",
       "73                       Gym  \n",
       "74                Food Truck  \n",
       "75        Spanish Restaurant  \n",
       "76               Gas Station  \n",
       "77    Furniture / Home Store  \n",
       "78                   Dog Run  "
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Results: Visualizing the resulting Clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use the matplotlib and folium packages to visualize the clusters on a map of both cities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "n1=neigh_merged.loc[neigh_merged['City']=='Toronto']\n",
    "n2=neigh_merged.loc[neigh_merged['City']=='New York']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
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                [43.6969476,-79.41130720000001],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_2fa64d22090440de8e0b038ad08aa33f = L.popup({maxWidth: '300'});

            
                var html_263bcb674dde4ec98665ec9375ab1de1 = $('<div id="html_263bcb674dde4ec98665ec9375ab1de1" style="width: 100.0%; height: 100.0%;">Forest Hill North &amp; West, Forest Hill Road Park Cluster 0</div>')[0];
                popup_2fa64d22090440de8e0b038ad08aa33f.setContent(html_263bcb674dde4ec98665ec9375ab1de1);
            

            circle_marker_c8106ebb934d4f5883cc64107989dfe2.bindPopup(popup_2fa64d22090440de8e0b038ad08aa33f);

            
        
    
            var circle_marker_d442cda4c0f146329ad26831cc0dc4e2 = L.circleMarker(
                [43.6727097,-79.40567840000001],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_4bbd0520f1e449fe839acf7509a16e80 = L.popup({maxWidth: '300'});

            
                var html_62e59ef02e8e4ad78369316286b55c20 = $('<div id="html_62e59ef02e8e4ad78369316286b55c20" style="width: 100.0%; height: 100.0%;">The Annex, North Midtown, Yorkville Cluster 0</div>')[0];
                popup_4bbd0520f1e449fe839acf7509a16e80.setContent(html_62e59ef02e8e4ad78369316286b55c20);
            

            circle_marker_d442cda4c0f146329ad26831cc0dc4e2.bindPopup(popup_4bbd0520f1e449fe839acf7509a16e80);

            
        
    
            var circle_marker_b65cc88addf247c08efa8660eb181a27 = L.circleMarker(
                [43.6626956,-79.4000493],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_92d416578a27449ea8f84e89a9b9a5c9 = L.popup({maxWidth: '300'});

            
                var html_4dfe83c90e2e4838bc8bf41b6e85885a = $('<div id="html_4dfe83c90e2e4838bc8bf41b6e85885a" style="width: 100.0%; height: 100.0%;">University of Toronto, Harbord Cluster 0</div>')[0];
                popup_92d416578a27449ea8f84e89a9b9a5c9.setContent(html_4dfe83c90e2e4838bc8bf41b6e85885a);
            

            circle_marker_b65cc88addf247c08efa8660eb181a27.bindPopup(popup_92d416578a27449ea8f84e89a9b9a5c9);

            
        
    
            var circle_marker_f116b8cac5c64e21a1df523dea28938a = L.circleMarker(
                [43.6532057,-79.4000493],
                {
  "bubblingMouseEvents": true,
  "color": "#00b5eb",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#00b5eb",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_d6a900c46cbd4e2f969e3fab0acef6dc = L.popup({maxWidth: '300'});

            
                var html_04f6d4ed9fc2490794d91e41446ecfe1 = $('<div id="html_04f6d4ed9fc2490794d91e41446ecfe1" style="width: 100.0%; height: 100.0%;">Kensington Market, Chinatown, Grange Park Cluster 2</div>')[0];
                popup_d6a900c46cbd4e2f969e3fab0acef6dc.setContent(html_04f6d4ed9fc2490794d91e41446ecfe1);
            

            circle_marker_f116b8cac5c64e21a1df523dea28938a.bindPopup(popup_d6a900c46cbd4e2f969e3fab0acef6dc);

            
        
    
            var circle_marker_ce6dba3026ef4183aaca883a7b10c9b7 = L.circleMarker(
                [43.6289467,-79.3944199],
                {
  "bubblingMouseEvents": true,
  "color": "#8000ff",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#8000ff",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_0c6b7093aa2447b48b60f7faaab1d10f = L.popup({maxWidth: '300'});

            
                var html_eedd90486d0248388afe39634ba217a5 = $('<div id="html_eedd90486d0248388afe39634ba217a5" style="width: 100.0%; height: 100.0%;">CN Tower, King and Spadina, Railway Lands, Harbourfront West, Bathurst Quay, South Niagara, Island airport Cluster 1</div>')[0];
                popup_0c6b7093aa2447b48b60f7faaab1d10f.setContent(html_eedd90486d0248388afe39634ba217a5);
            

            circle_marker_ce6dba3026ef4183aaca883a7b10c9b7.bindPopup(popup_0c6b7093aa2447b48b60f7faaab1d10f);

            
        
    
            var circle_marker_0dbddbfabf4b480ebb47b62481b74f2b = L.circleMarker(
                [43.6464352,-79.37484599999999],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_502ece61ac104561aed7216c168f23a0 = L.popup({maxWidth: '300'});

            
                var html_559417287cc74c6483ae05a3b1a68a20 = $('<div id="html_559417287cc74c6483ae05a3b1a68a20" style="width: 100.0%; height: 100.0%;">Stn A PO Boxes Cluster 0</div>')[0];
                popup_502ece61ac104561aed7216c168f23a0.setContent(html_559417287cc74c6483ae05a3b1a68a20);
            

            circle_marker_0dbddbfabf4b480ebb47b62481b74f2b.bindPopup(popup_502ece61ac104561aed7216c168f23a0);

            
        
    
            var circle_marker_95df1e9f9d3f4cb58cafd32cbfd41732 = L.circleMarker(
                [43.6484292,-79.3822802],
                {
  "bubblingMouseEvents": true,
  "color": "#ffb360",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ffb360",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_333b2038d34643ada44dfb392e7b0ff1 = L.popup({maxWidth: '300'});

            
                var html_57895fcdfc304fdfb27022f93d354fac = $('<div id="html_57895fcdfc304fdfb27022f93d354fac" style="width: 100.0%; height: 100.0%;">First Canadian Place, Underground city Cluster 4</div>')[0];
                popup_333b2038d34643ada44dfb392e7b0ff1.setContent(html_57895fcdfc304fdfb27022f93d354fac);
            

            circle_marker_95df1e9f9d3f4cb58cafd32cbfd41732.bindPopup(popup_333b2038d34643ada44dfb392e7b0ff1);

            
        
    
            var circle_marker_ff8d73236b7a4068b1692c72865c7b4a = L.circleMarker(
                [43.669542,-79.4225637],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_72ad9f92f4de495f962220ac1074aa12 = L.popup({maxWidth: '300'});

            
                var html_4a0cd6c0020f4cec8598c0ce728ced90 = $('<div id="html_4a0cd6c0020f4cec8598c0ce728ced90" style="width: 100.0%; height: 100.0%;">Christie Cluster 0</div>')[0];
                popup_72ad9f92f4de495f962220ac1074aa12.setContent(html_4a0cd6c0020f4cec8598c0ce728ced90);
            

            circle_marker_ff8d73236b7a4068b1692c72865c7b4a.bindPopup(popup_72ad9f92f4de495f962220ac1074aa12);

            
        
    
            var circle_marker_6a1a8939592c416096f745d2ef41af17 = L.circleMarker(
                [43.66900510000001,-79.4422593],
                {
  "bubblingMouseEvents": true,
  "color": "#ffb360",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ffb360",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_bd257f51dd67437da0fe545c38c183b6 = L.popup({maxWidth: '300'});

            
                var html_a6c6f04b96b442e589b2632f8c3a037b = $('<div id="html_a6c6f04b96b442e589b2632f8c3a037b" style="width: 100.0%; height: 100.0%;">Dufferin, Dovercourt Village Cluster 4</div>')[0];
                popup_bd257f51dd67437da0fe545c38c183b6.setContent(html_a6c6f04b96b442e589b2632f8c3a037b);
            

            circle_marker_6a1a8939592c416096f745d2ef41af17.bindPopup(popup_bd257f51dd67437da0fe545c38c183b6);

            
        
    
            var circle_marker_64675ba221cd4d33b96a45f6cb03f17c = L.circleMarker(
                [43.647926700000006,-79.4197497],
                {
  "bubblingMouseEvents": true,
  "color": "#ffb360",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ffb360",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_15d8487ef74240eeb0478509e66cd3e2 = L.popup({maxWidth: '300'});

            
                var html_adfdc10da0574878b0ebe7607705043f = $('<div id="html_adfdc10da0574878b0ebe7607705043f" style="width: 100.0%; height: 100.0%;">Little Portugal, Trinity Cluster 4</div>')[0];
                popup_15d8487ef74240eeb0478509e66cd3e2.setContent(html_adfdc10da0574878b0ebe7607705043f);
            

            circle_marker_64675ba221cd4d33b96a45f6cb03f17c.bindPopup(popup_15d8487ef74240eeb0478509e66cd3e2);

            
        
    
            var circle_marker_a6ef921fb6df48e8a39d4ce1b4b28d5d = L.circleMarker(
                [43.6368472,-79.42819140000002],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_c78403bcc43c4efebfd5b802c010fa11 = L.popup({maxWidth: '300'});

            
                var html_8f85e588cf2443ad846a974f2adc2aef = $('<div id="html_8f85e588cf2443ad846a974f2adc2aef" style="width: 100.0%; height: 100.0%;">Brockton, Parkdale Village, Exhibition Place Cluster 0</div>')[0];
                popup_c78403bcc43c4efebfd5b802c010fa11.setContent(html_8f85e588cf2443ad846a974f2adc2aef);
            

            circle_marker_a6ef921fb6df48e8a39d4ce1b4b28d5d.bindPopup(popup_c78403bcc43c4efebfd5b802c010fa11);

            
        
    
            var circle_marker_b61dea4d6a294ba7b6e36c7d1d816d67 = L.circleMarker(
                [43.6616083,-79.46476329999999],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_0089acd0e60e46579572a0b33b927640 = L.popup({maxWidth: '300'});

            
                var html_67e13a60a7794e0e9eea347e33e7f1d4 = $('<div id="html_67e13a60a7794e0e9eea347e33e7f1d4" style="width: 100.0%; height: 100.0%;">High Park, The Junction South Cluster 0</div>')[0];
                popup_0089acd0e60e46579572a0b33b927640.setContent(html_67e13a60a7794e0e9eea347e33e7f1d4);
            

            circle_marker_b61dea4d6a294ba7b6e36c7d1d816d67.bindPopup(popup_0089acd0e60e46579572a0b33b927640);

            
        
    
            var circle_marker_e3943f9184ce4458a18f5333ed130b14 = L.circleMarker(
                [43.6489597,-79.456325],
                {
  "bubblingMouseEvents": true,
  "color": "#ffb360",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ffb360",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_54c374af7a4d4a3880c517b7be976998 = L.popup({maxWidth: '300'});

            
                var html_0cb41a5e988744fa9154fbc1212056ae = $('<div id="html_0cb41a5e988744fa9154fbc1212056ae" style="width: 100.0%; height: 100.0%;">Parkdale, Roncesvalles Cluster 4</div>')[0];
                popup_54c374af7a4d4a3880c517b7be976998.setContent(html_0cb41a5e988744fa9154fbc1212056ae);
            

            circle_marker_e3943f9184ce4458a18f5333ed130b14.bindPopup(popup_54c374af7a4d4a3880c517b7be976998);

            
        
    
            var circle_marker_bf7b166ebc794aeeb0bfcd23f96bbdda = L.circleMarker(
                [43.6515706,-79.4844499],
                {
  "bubblingMouseEvents": true,
  "color": "#ffb360",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ffb360",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_5436cd8344154cee9cb86420f71c3e0c = L.popup({maxWidth: '300'});

            
                var html_002d23ef8ebe48859c31ca096d515835 = $('<div id="html_002d23ef8ebe48859c31ca096d515835" style="width: 100.0%; height: 100.0%;">Runnymede, Swansea Cluster 4</div>')[0];
                popup_5436cd8344154cee9cb86420f71c3e0c.setContent(html_002d23ef8ebe48859c31ca096d515835);
            

            circle_marker_bf7b166ebc794aeeb0bfcd23f96bbdda.bindPopup(popup_5436cd8344154cee9cb86420f71c3e0c);

            
        
    
            var circle_marker_7cab831ed59541ca8d5f9e44d9fd67f3 = L.circleMarker(
                [43.6623015,-79.3894938],
                {
  "bubblingMouseEvents": true,
  "color": "#ff0000",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ff0000",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_812293c1f08843208217e9e57286da6a = L.popup({maxWidth: '300'});

            
                var html_4a682e9a552c493e9479b81ffc3f061d = $('<div id="html_4a682e9a552c493e9479b81ffc3f061d" style="width: 100.0%; height: 100.0%;">Queen&#39;s Park, Ontario Provincial Government Cluster 0</div>')[0];
                popup_812293c1f08843208217e9e57286da6a.setContent(html_4a682e9a552c493e9479b81ffc3f061d);
            

            circle_marker_7cab831ed59541ca8d5f9e44d9fd67f3.bindPopup(popup_812293c1f08843208217e9e57286da6a);

            
        
    
            var circle_marker_38e2d257f07f482fa56d1173f2860191 = L.circleMarker(
                [43.6627439,-79.321558],
                {
  "bubblingMouseEvents": true,
  "color": "#ffb360",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#ffb360",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_dfcd94ba91414ff19f4566ecee7ac203);
            
    
            var popup_cc3b21b217cd4283bdc000189f186659 = L.popup({maxWidth: '300'});

            
                var html_9bf10602259d44f6ae4f73cc0be05e3a = $('<div id="html_9bf10602259d44f6ae4f73cc0be05e3a" style="width: 100.0%; height: 100.0%;">Business reply mail Processing Centre, South Central Letter Processing Plant Toronto Cluster 4</div>')[0];
                popup_cc3b21b217cd4283bdc000189f186659.setContent(html_9bf10602259d44f6ae4f73cc0be05e3a);
            

            circle_marker_38e2d257f07f482fa56d1173f2860191.bindPopup(popup_cc3b21b217cd4283bdc000189f186659);

            
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2098afb1f08>"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map\n",
    "address = 'Toronto'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"to_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "map_clusters1 = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
    "\n",
    "# set color scheme for the clusters\n",
    "x = np.arange(kclusters)\n",
    "ys = [i+x+(i*x)**2 for i in range(kclusters)]\n",
    "colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\n",
    "rainbow = [colors.rgb2hex(i) for i in colors_array]\n",
    "\n",
    "# add markers to the map\n",
    "markers_colors = []\n",
    "for lat, lon, poi, cluster in zip(n1['Latitude'], n1['Longitude'], \n",
    "                                  n1['Neighborhood'], \n",
    "                                  n1['Cluster Labels']):\n",
    "    label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lon],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color=rainbow[cluster-1],\n",
    "        fill=True,\n",
    "        fill_color=rainbow[cluster-1],\n",
    "        fill_opacity=0.7).add_to(map_clusters1)\n",
    "       \n",
    "map_clusters1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
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            var popup_cf801c9f6e6a4a75a4228cb97b2798db = L.popup({maxWidth: '300'});

            
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            circle_marker_f1940688b6b9415fbb0e17674f404ac7.bindPopup(popup_cf801c9f6e6a4a75a4228cb97b2798db);

            
        
    
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            var popup_3e1c273eb3c24c86b7407bf24fa9bc22 = L.popup({maxWidth: '300'});

            
                var html_fc898d75846945c0ae4c88ed59922a4e = $('<div id="html_fc898d75846945c0ae4c88ed59922a4e" style="width: 100.0%; height: 100.0%;">Turtle Bay Cluster 4</div>')[0];
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                var html_78e1a6f9aeb74e25ad55477da14dd6a6 = $('<div id="html_78e1a6f9aeb74e25ad55477da14dd6a6" style="width: 100.0%; height: 100.0%;">Tudor City Cluster 4</div>')[0];
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            circle_marker_eb88967029d14708b7feb45650b07009.bindPopup(popup_a0f2d64145f44cd397879d8f2c1e582e);

            
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2098afd1548>"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "address = 'Manhattan, NY'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"ny_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "map_clusters2 = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
    "\n",
    "# set color scheme for the clusters\n",
    "x = np.arange(kclusters)\n",
    "ys = [i+x+(i*x)**2 for i in range(kclusters)]\n",
    "colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\n",
    "rainbow = [colors.rgb2hex(i) for i in colors_array]\n",
    "\n",
    "# add markers to the map\n",
    "markers_colors = []\n",
    "for lat, lon, poi, cluster in zip(n2['Latitude'], n2['Longitude'], \n",
    "                                  n2['Neighborhood'], \n",
    "                                  n2['Cluster Labels']):\n",
    "    label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)\n",
    "    folium.CircleMarker(\n",
    "        [lat, lon],\n",
    "        radius=5,\n",
    "        popup=label,\n",
    "        color=rainbow[cluster-1],\n",
    "        fill=True,\n",
    "        fill_color=rainbow[cluster-1],\n",
    "        fill_opacity=0.7).add_to(map_clusters2)\n",
    "       \n",
    "map_clusters2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Discussion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The aim of this analysis was to find out similar neighborhoods for a person relocating in New York city.\n",
    "The maps above show us that if your friend want to move from a neighborhood in Toronto to a neighborhood in Manhattan, he has to choose the neighborhood with the same color displayed if he want to find the same kind of venues of his living zone. Consequently he’s lucky if he live in an orange or red zone of the map above in Toronto."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The scope of the analysis has been achieved. However the model created can easily be replicated again and again with data from other cities by using the Foursquare API. This show us the potentiality of Data Science in real life problems"
   ]
  }
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