Battle-of-Neighbour.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Battle of Neighborhood 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "### This project is to take a glimpse at different neighborhoods of Providence,RI and Hartford,CT. Both cities are capital cities of their states and are major cities between New York City and Boston in East Coast.\n",
    "\n",
    "### Travelers from inside and outside of New England area who want to dicide where to visit and business owners may be interested in the project.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data \n",
    "\n",
    "### I organized two data sets of zipcode and neighborhoods with latitude and longtude for each city from multiple online sources"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Methodology\n",
    "\n",
    "### Basic skills from week 3 lab\n",
    "### Majorly relied on Foursquare API to retrieve all venues of each neighborhoods, then group by each neighborhoods and to count how many venues before filter top 10 most common venue types of each neighborhoods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Data where you describe the data that will be used to solve the problem and the source of the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the required library\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>Zipcode</th>\n",
       "      <th>Neighborhoods</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2906</td>\n",
       "      <td>Blackstone</td>\n",
       "      <td>41.846388</td>\n",
       "      <td>-71.385406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2904</td>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2906</td>\n",
       "      <td>College Hill</td>\n",
       "      <td>41.830157</td>\n",
       "      <td>-71.403219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2903</td>\n",
       "      <td>Downtown</td>\n",
       "      <td>41.822533</td>\n",
       "      <td>-71.415094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2908</td>\n",
       "      <td>Elmhurst</td>\n",
       "      <td>41.840911</td>\n",
       "      <td>-71.438842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Zipcode Neighborhoods   Latitude  Longitude\n",
       "0     2906    Blackstone  41.846388 -71.385406\n",
       "1     2904       Charles  41.812104 -71.429089\n",
       "2     2906  College Hill  41.830157 -71.403219\n",
       "3     2903      Downtown  41.822533 -71.415094\n",
       "4     2908      Elmhurst  41.840911 -71.438842"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load data of Providence,RI\n",
    "df_pvd=pd.read_excel(\"pvd.xlsx\")\n",
    "df_pvd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add '0' before '2' of each zipcode\n",
    "df_pvd['Zipcode']='0'+ df_pvd['Zipcode'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zipcode</th>\n",
       "      <th>Neighborhoods</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02906</td>\n",
       "      <td>Blackstone</td>\n",
       "      <td>41.846388</td>\n",
       "      <td>-71.385406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02904</td>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>02906</td>\n",
       "      <td>College Hill</td>\n",
       "      <td>41.830157</td>\n",
       "      <td>-71.403219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02903</td>\n",
       "      <td>Downtown</td>\n",
       "      <td>41.822533</td>\n",
       "      <td>-71.415094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>02908</td>\n",
       "      <td>Elmhurst</td>\n",
       "      <td>41.840911</td>\n",
       "      <td>-71.438842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Zipcode Neighborhoods   Latitude  Longitude\n",
       "0   02906    Blackstone  41.846388 -71.385406\n",
       "1   02904       Charles  41.812104 -71.429089\n",
       "2   02906  College Hill  41.830157 -71.403219\n",
       "3   02903      Downtown  41.822533 -71.415094\n",
       "4   02908      Elmhurst  41.840911 -71.438842"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pvd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30, 4)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pvd.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Zipcode</th>\n",
       "      <th>Neighborhoods</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6105</td>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6106</td>\n",
       "      <td>Barry Square</td>\n",
       "      <td>41.747158</td>\n",
       "      <td>-72.683114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6114</td>\n",
       "      <td>Barry Square</td>\n",
       "      <td>41.747158</td>\n",
       "      <td>-72.683114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6106</td>\n",
       "      <td>Behind The Rocks</td>\n",
       "      <td>41.745071</td>\n",
       "      <td>-72.700849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6112</td>\n",
       "      <td>Blue Hills</td>\n",
       "      <td>41.812877</td>\n",
       "      <td>-72.697593</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Zipcode     Neighborhoods   Latitude  Longitude\n",
       "0     6105       Asylum Hill  41.773149 -72.694937\n",
       "1     6106      Barry Square  41.747158 -72.683114\n",
       "2     6114      Barry Square  41.747158 -72.683114\n",
       "3     6106  Behind The Rocks  41.745071 -72.700849\n",
       "4     6112        Blue Hills  41.812877 -72.697593"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load data of Hartford,CT\n",
    "df_bdl=pd.read_excel(\"bdl.xlsx\")\n",
    "df_bdl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add '0' before '6' of each zipcode\n",
    "df_bdl['Zipcode']='0'+ df_bdl['Zipcode'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>Zipcode</th>\n",
       "      <th>Neighborhoods</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06105</td>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>06106</td>\n",
       "      <td>Barry Square</td>\n",
       "      <td>41.747158</td>\n",
       "      <td>-72.683114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06114</td>\n",
       "      <td>Barry Square</td>\n",
       "      <td>41.747158</td>\n",
       "      <td>-72.683114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06106</td>\n",
       "      <td>Behind The Rocks</td>\n",
       "      <td>41.745071</td>\n",
       "      <td>-72.700849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06112</td>\n",
       "      <td>Blue Hills</td>\n",
       "      <td>41.812877</td>\n",
       "      <td>-72.697593</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Zipcode     Neighborhoods   Latitude  Longitude\n",
       "0   06105       Asylum Hill  41.773149 -72.694937\n",
       "1   06106      Barry Square  41.747158 -72.683114\n",
       "2   06114      Barry Square  41.747158 -72.683114\n",
       "3   06106  Behind The Rocks  41.745071 -72.700849\n",
       "4   06112        Blue Hills  41.812877 -72.697593"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_bdl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25, 4)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_bdl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import mapping libraries\n",
    "from geopy.geocoders import Nominatim\n",
    "import folium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Libraries imported.\n"
     ]
    }
   ],
   "source": [
    "# Importing libraries\n",
    "import numpy as np # library to handle data in a vectorized manner\n",
    "\n",
    "import pandas as pd # library for data analsysis\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)\n",
    "\n",
    "import json # library to handle JSON files\n",
    "\n",
    "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",
    "import folium # map rendering library\n",
    "\n",
    "print('Libraries imported.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "My credentails:\n",
      "CLIENT_ID: FD5IPVIXWPQA0FVEOHMZPM0MXPQIHKDQPO20JMZMCK1EA2LN\n",
      "CLIENT_SECRET:SXF5QRXJ4T1UVTLZFOXXSTVBXA54FMAOE1PMI0CP5X2IKAP0\n"
     ]
    }
   ],
   "source": [
    "# Working with Foursquare\n",
    "CLIENT_ID = 'FD5IPVIXWPQA0FVEOHMZPM0MXPQIHKDQPO20JMZMCK1EA2LN' # your Foursquare ID\n",
    "CLIENT_SECRET = 'SXF5QRXJ4T1UVTLZFOXXSTVBXA54FMAOE1PMI0CP5X2IKAP0' # your Foursquare Secret\n",
    "VERSION = '20181224' # Foursquare API version\n",
    "\n",
    "print('My credentails:')\n",
    "print('CLIENT_ID: ' + CLIENT_ID)\n",
    "print('CLIENT_SECRET:' + CLIENT_SECRET)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getNearbyVenues(names, latitudes, longitudes, radius=500):\n",
    "    \n",
    "    venues_list=[]\n",
    "    for name, lat, lng in zip(names, latitudes, longitudes):\n",
    "        \n",
    "            \n",
    "        # create the API request URL\n",
    "        url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit=100'.format(\n",
    "            CLIENT_ID, \n",
    "            CLIENT_SECRET, \n",
    "            VERSION, \n",
    "            lat, \n",
    "            lng, \n",
    "            radius)\n",
    "            \n",
    "        # make the GET request\n",
    "        results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n",
    "        \n",
    "        # return only relevant information for each nearby venue\n",
    "        venues_list.append([(\n",
    "            name, \n",
    "            lat, \n",
    "            lng, \n",
    "            v['venue']['name'], \n",
    "            v['venue']['location']['lat'], \n",
    "            v['venue']['location']['lng'],  \n",
    "            v['venue']['categories'][0]['name']) for v in results])\n",
    "\n",
    "    nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])\n",
    "    nearby_venues.columns = ['Neighborhood', \n",
    "                  'Neighborhood Latitude', \n",
    "                  'Neighborhood Longitude', \n",
    "                  'Venue', \n",
    "                  'Venue Latitude', \n",
    "                  'Venue Longitude', \n",
    "                  'Venue Category']\n",
    "    \n",
    "    return(nearby_venues)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "pvd_venues=getNearbyVenues(df_pvd['Neighborhoods'], df_pvd['Latitude'], df_pvd['Longitude'])\n",
    "bdl_venues=getNearbyVenues(df_bdl['Neighborhoods'], df_bdl['Latitude'], df_bdl['Longitude'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "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>Neighborhood</th>\n",
       "      <th>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "      <td>Armory Park</td>\n",
       "      <td>41.812957</td>\n",
       "      <td>-71.431897</td>\n",
       "      <td>Plaza</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "      <td>Hudson Street Delicatessen</td>\n",
       "      <td>41.813256</td>\n",
       "      <td>-71.434625</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "      <td>Family Dollar</td>\n",
       "      <td>41.813362</td>\n",
       "      <td>-71.427587</td>\n",
       "      <td>Discount Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "      <td>Tropical Liquors</td>\n",
       "      <td>41.812774</td>\n",
       "      <td>-71.429217</td>\n",
       "      <td>Liquor Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Charles</td>\n",
       "      <td>41.812104</td>\n",
       "      <td>-71.429089</td>\n",
       "      <td>John's NY System</td>\n",
       "      <td>41.812643</td>\n",
       "      <td>-71.429725</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Neighborhood  Neighborhood Latitude  Neighborhood Longitude  \\\n",
       "0      Charles              41.812104              -71.429089   \n",
       "1      Charles              41.812104              -71.429089   \n",
       "2      Charles              41.812104              -71.429089   \n",
       "3      Charles              41.812104              -71.429089   \n",
       "4      Charles              41.812104              -71.429089   \n",
       "\n",
       "                        Venue  Venue Latitude  Venue Longitude  Venue Category  \n",
       "0                 Armory Park       41.812957       -71.431897           Plaza  \n",
       "1  Hudson Street Delicatessen       41.813256       -71.434625   Deli / Bodega  \n",
       "2               Family Dollar       41.813362       -71.427587  Discount Store  \n",
       "3            Tropical Liquors       41.812774       -71.429217    Liquor Store  \n",
       "4            John's NY System       41.812643       -71.429725  Breakfast Spot  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pvd_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "      <td>Au Bon Pain</td>\n",
       "      <td>41.773804</td>\n",
       "      <td>-72.699015</td>\n",
       "      <td>Café</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "      <td>Sigourney Square Park</td>\n",
       "      <td>41.775729</td>\n",
       "      <td>-72.693938</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "      <td>Saint Francis Main Cafeteria</td>\n",
       "      <td>41.774191</td>\n",
       "      <td>-72.698254</td>\n",
       "      <td>Café</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "      <td>Women's Auxiliary Gift Shop</td>\n",
       "      <td>41.773952</td>\n",
       "      <td>-72.698893</td>\n",
       "      <td>Gift Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>41.773149</td>\n",
       "      <td>-72.694937</td>\n",
       "      <td>Saint Francis Fitness Center</td>\n",
       "      <td>41.773976</td>\n",
       "      <td>-72.700199</td>\n",
       "      <td>Gym</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Neighborhood  Neighborhood Latitude  Neighborhood Longitude  \\\n",
       "0  Asylum Hill              41.773149              -72.694937   \n",
       "1  Asylum Hill              41.773149              -72.694937   \n",
       "2  Asylum Hill              41.773149              -72.694937   \n",
       "3  Asylum Hill              41.773149              -72.694937   \n",
       "4  Asylum Hill              41.773149              -72.694937   \n",
       "\n",
       "                          Venue  Venue Latitude  Venue Longitude  \\\n",
       "0                   Au Bon Pain       41.773804       -72.699015   \n",
       "1         Sigourney Square Park       41.775729       -72.693938   \n",
       "2  Saint Francis Main Cafeteria       41.774191       -72.698254   \n",
       "3   Women's Auxiliary Gift Shop       41.773952       -72.698893   \n",
       "4  Saint Francis Fitness Center       41.773976       -72.700199   \n",
       "\n",
       "  Venue Category  \n",
       "0           Café  \n",
       "1           Park  \n",
       "2           Café  \n",
       "3      Gift Shop  \n",
       "4            Gym  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bdl_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(512, 7)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pvd_venues.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(460, 7)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bdl_venues.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neighborhood</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Charles</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>College Hill</th>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Downtown</th>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elmhurst</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elmwood</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Federal Hill</th>\n",
       "      <td>118</td>\n",
       "      <td>118</td>\n",
       "      <td>118</td>\n",
       "      <td>118</td>\n",
       "      <td>118</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fox Point</th>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hartford</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hope (Summit)</th>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lower South Providence</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manton</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mount Hope</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mount Pleasant</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Olneyville</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reservoir</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Silver Lake</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smith Hill</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Elmwood</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Valley</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Neighborhood Latitude  Neighborhood Longitude  Venue  \\\n",
       "Neighborhood                                                                   \n",
       "Charles                                    10                      10     10   \n",
       "College Hill                               50                      50     50   \n",
       "Downtown                                   72                      72     72   \n",
       "Elmhurst                                    5                       5      5   \n",
       "Elmwood                                     4                       4      4   \n",
       "Federal Hill                              118                     118    118   \n",
       "Fox Point                                  72                      72     72   \n",
       "Hartford                                    7                       7      7   \n",
       "Hope (Summit)                              42                      42     42   \n",
       "Lower South Providence                      2                       2      2   \n",
       "Manton                                     14                      14     14   \n",
       "Mount Hope                                 18                      18     18   \n",
       "Mount Pleasant                             10                      10     10   \n",
       "Olneyville                                  7                       7      7   \n",
       "Reservoir                                  14                      14     14   \n",
       "Silver Lake                                11                      11     11   \n",
       "Smith Hill                                 26                      26     26   \n",
       "South Elmwood                              22                      22     22   \n",
       "Valley                                      8                       8      8   \n",
       "\n",
       "                        Venue Latitude  Venue Longitude  Venue Category  \n",
       "Neighborhood                                                             \n",
       "Charles                             10               10              10  \n",
       "College Hill                        50               50              50  \n",
       "Downtown                            72               72              72  \n",
       "Elmhurst                             5                5               5  \n",
       "Elmwood                              4                4               4  \n",
       "Federal Hill                       118              118             118  \n",
       "Fox Point                           72               72              72  \n",
       "Hartford                             7                7               7  \n",
       "Hope (Summit)                       42               42              42  \n",
       "Lower South Providence               2                2               2  \n",
       "Manton                              14               14              14  \n",
       "Mount Hope                          18               18              18  \n",
       "Mount Pleasant                      10               10              10  \n",
       "Olneyville                           7                7               7  \n",
       "Reservoir                           14               14              14  \n",
       "Silver Lake                         11               11              11  \n",
       "Smith Hill                          26               26              26  \n",
       "South Elmwood                       22               22              22  \n",
       "Valley                               8                8               8  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of venues of each \n",
    "pvd_venues.groupby('Neighborhood').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood Latitude</th>\n",
       "      <th>Neighborhood Longitude</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Venue Latitude</th>\n",
       "      <th>Venue Longitude</th>\n",
       "      <th>Venue Category</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neighborhood</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Asylum Hill</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barry Square</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Behind The Rocks</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blue Hills</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clay Arsenal</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Downtown</th>\n",
       "      <td>188</td>\n",
       "      <td>188</td>\n",
       "      <td>188</td>\n",
       "      <td>188</td>\n",
       "      <td>188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frog Hollow</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North East</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Meadows</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parkville</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sheldon Charter Oak</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South End</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Green</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Meadows</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South West</th>\n",
       "      <td>112</td>\n",
       "      <td>112</td>\n",
       "      <td>112</td>\n",
       "      <td>112</td>\n",
       "      <td>112</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Upper Albany</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West End</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Neighborhood Latitude  Neighborhood Longitude  Venue  \\\n",
       "Neighborhood                                                                \n",
       "Asylum Hill                              6                       6      6   \n",
       "Barry Square                            10                      10     10   \n",
       "Behind The Rocks                         2                       2      2   \n",
       "Blue Hills                               8                       8      8   \n",
       "Clay Arsenal                             8                       8      8   \n",
       "Downtown                               188                     188    188   \n",
       "Frog Hollow                              6                       6      6   \n",
       "North East                              22                      22     22   \n",
       "North Meadows                           13                      13     13   \n",
       "Parkville                               14                      14     14   \n",
       "Sheldon Charter Oak                      8                       8      8   \n",
       "South End                               10                      10     10   \n",
       "South Green                             28                      28     28   \n",
       "South Meadows                           13                      13     13   \n",
       "South West                             112                     112    112   \n",
       "Upper Albany                             8                       8      8   \n",
       "West End                                 4                       4      4   \n",
       "\n",
       "                     Venue Latitude  Venue Longitude  Venue Category  \n",
       "Neighborhood                                                          \n",
       "Asylum Hill                       6                6               6  \n",
       "Barry Square                     10               10              10  \n",
       "Behind The Rocks                  2                2               2  \n",
       "Blue Hills                        8                8               8  \n",
       "Clay Arsenal                      8                8               8  \n",
       "Downtown                        188              188             188  \n",
       "Frog Hollow                       6                6               6  \n",
       "North East                       22               22              22  \n",
       "North Meadows                    13               13              13  \n",
       "Parkville                        14               14              14  \n",
       "Sheldon Charter Oak               8                8               8  \n",
       "South End                        10               10              10  \n",
       "South Green                      28               28              28  \n",
       "South Meadows                    13               13              13  \n",
       "South West                      112              112             112  \n",
       "Upper Albany                      8                8               8  \n",
       "West End                          4                4               4  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bdl_venues.groupby('Neighborhood').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Art Gallery</th>\n",
       "      <th>Asian Restaurant</th>\n",
       "      <th>Automotive Shop</th>\n",
       "      <th>BBQ Joint</th>\n",
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       "      <th>Brewery</th>\n",
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       "      <th>Café</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Chocolate Shop</th>\n",
       "      <th>Clothing Store</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Bookstore</th>\n",
       "      <th>College Gym</th>\n",
       "      <th>Concert Hall</th>\n",
       "      <th>Convenience Store</th>\n",
       "      <th>Cosmetics Shop</th>\n",
       "      <th>Creperie</th>\n",
       "      <th>Dance Studio</th>\n",
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       "      <th>Department Store</th>\n",
       "      <th>Dessert Shop</th>\n",
       "      <th>Diner</th>\n",
       "      <th>Discount Store</th>\n",
       "      <th>Dive Bar</th>\n",
       "      <th>Donut Shop</th>\n",
       "      <th>Exhibit</th>\n",
       "      <th>Farmers Market</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Fish Market</th>\n",
       "      <th>Food</th>\n",
       "      <th>Food Truck</th>\n",
       "      <th>French Restaurant</th>\n",
       "      <th>Fried Chicken Joint</th>\n",
       "      <th>Frozen Yogurt Shop</th>\n",
       "      <th>Gas Station</th>\n",
       "      <th>Gastropub</th>\n",
       "      <th>Gay Bar</th>\n",
       "      <th>Gift Shop</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>Hardware Store</th>\n",
       "      <th>Hockey Arena</th>\n",
       "      <th>Hookah Bar</th>\n",
       "      <th>Hot Dog Joint</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>Ice Cream Shop</th>\n",
       "      <th>Indian Restaurant</th>\n",
       "      <th>Indie Movie Theater</th>\n",
       "      <th>Italian Restaurant</th>\n",
       "      <th>Japanese Restaurant</th>\n",
       "      <th>Jewelry Store</th>\n",
       "      <th>Karaoke Bar</th>\n",
       "      <th>Korean Restaurant</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Lounge</th>\n",
       "      <th>Mediterranean Restaurant</th>\n",
       "      <th>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Movie Theater</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>Outdoor Supply Store</th>\n",
       "      <th>Park</th>\n",
       "      <th>Performing Arts Venue</th>\n",
       "      <th>Perfume Shop</th>\n",
       "      <th>Pet Store</th>\n",
       "      <th>Pharmacy</th>\n",
       "      <th>Pizza Place</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Pool</th>\n",
       "      <th>Public Art</th>\n",
       "      <th>Record Shop</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Salon / Barbershop</th>\n",
       "      <th>Sandwich Place</th>\n",
       "      <th>Scenic Lookout</th>\n",
       "      <th>Science Museum</th>\n",
       "      <th>Sculpture Garden</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shipping Store</th>\n",
       "      <th>Skating Rink</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>South American Restaurant</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Spanish Restaurant</th>\n",
       "      <th>Speakeasy</th>\n",
       "      <th>Sports Bar</th>\n",
       "      <th>Steakhouse</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Taco Place</th>\n",
       "      <th>Tea Room</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</th>\n",
       "      <th>Thrift / Vintage Store</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wine Shop</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "    <tr>\n",
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      ],
      "text/plain": [
       "  Neighborhood  American Restaurant  Art Gallery  Asian Restaurant  \\\n",
       "0      Charles                    0            0                 0   \n",
       "1      Charles                    0            0                 0   \n",
       "2      Charles                    0            0                 0   \n",
       "3      Charles                    0            0                 0   \n",
       "4      Charles                    0            0                 0   \n",
       "\n",
       "   Automotive Shop  BBQ Joint  Bagel Shop  Bakery  Bar  Beer Garden  Bistro  \\\n",
       "0                0          0           0       0    0            0       0   \n",
       "1                0          0           0       0    0            0       0   \n",
       "2                0          0           0       0    0            0       0   \n",
       "3                0          0           0       0    0            0       0   \n",
       "4                0          0           0       0    0            0       0   \n",
       "\n",
       "   Bookstore  Breakfast Spot  Brewery  Bubble Tea Shop  Burger Joint  Café  \\\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               1        0                0             0     0   \n",
       "\n",
       "   Chinese Restaurant  Chocolate Shop  Clothing Store  Cocktail Bar  \\\n",
       "0                   0               0               0             0   \n",
       "1                   0               0               0             0   \n",
       "2                   0               0               0             0   \n",
       "3                   0               0               0             0   \n",
       "4                   0               0               0             0   \n",
       "\n",
       "   Coffee Shop  College Bookstore  College Gym  Concert Hall  \\\n",
       "0            0                  0            0             0   \n",
       "1            0                  0            0             0   \n",
       "2            0                  0            0             0   \n",
       "3            0                  0            0             0   \n",
       "4            0                  0            0             0   \n",
       "\n",
       "   Convenience Store  Cosmetics Shop  Creperie  Dance Studio  Deli / Bodega  \\\n",
       "0                  0               0         0             0              0   \n",
       "1                  0               0         0             0              1   \n",
       "2                  0               0         0             0              0   \n",
       "3                  0               0         0             0              0   \n",
       "4                  0               0         0             0              0   \n",
       "\n",
       "   Department Store  Dessert Shop  Diner  Discount Store  Dive Bar  \\\n",
       "0                 0             0      0               0         0   \n",
       "1                 0             0      0               0         0   \n",
       "2                 0             0      0               1         0   \n",
       "3                 0             0      0               0         0   \n",
       "4                 0             0      0               0         0   \n",
       "\n",
       "   Donut Shop  Exhibit  Farmers Market  Fast Food Restaurant  Fish Market  \\\n",
       "0           0        0               0                     0            0   \n",
       "1           0        0               0                     0            0   \n",
       "2           0        0               0                     0            0   \n",
       "3           0        0               0                     0            0   \n",
       "4           0        0               0                     0            0   \n",
       "\n",
       "   Food  Food Truck  French Restaurant  Fried Chicken Joint  \\\n",
       "0     0           0                  0                    0   \n",
       "1     0           0                  0                    0   \n",
       "2     0           0                  0                    0   \n",
       "3     0           0                  0                    0   \n",
       "4     0           0                  0                    0   \n",
       "\n",
       "   Frozen Yogurt Shop  Gas Station  Gastropub  Gay Bar  Gift Shop  \\\n",
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       "1                   0            0          0        0          0   \n",
       "2                   0            0          0        0          0   \n",
       "3                   0            0          0        0          0   \n",
       "4                   0            0          0        0          0   \n",
       "\n",
       "   Gourmet Shop  Greek Restaurant  Grocery Store  Gym  Gym / Fitness Center  \\\n",
       "0             0                 0              0    0                     0   \n",
       "1             0                 0              0    0                     0   \n",
       "2             0                 0              0    0                     0   \n",
       "3             0                 0              0    0                     0   \n",
       "4             0                 0              0    0                     0   \n",
       "\n",
       "   Harbor / Marina  Hardware Store  Hockey Arena  Hookah Bar  Hot Dog Joint  \\\n",
       "0                0               0             0           0              0   \n",
       "1                0               0             0           0              0   \n",
       "2                0               0             0           0              0   \n",
       "3                0               0             0           0              0   \n",
       "4                0               0             0           0              0   \n",
       "\n",
       "   Hotel  Ice Cream Shop  Indian Restaurant  Indie Movie Theater  \\\n",
       "0      0               0                  0                    0   \n",
       "1      0               0                  0                    0   \n",
       "2      0               0                  0                    0   \n",
       "3      0               0                  0                    0   \n",
       "4      0               0                  0                    0   \n",
       "\n",
       "   Italian Restaurant  Japanese Restaurant  Jewelry Store  Karaoke Bar  \\\n",
       "0                   0                    0              0            0   \n",
       "1                   0                    0              0            0   \n",
       "2                   0                    0              0            0   \n",
       "3                   0                    0              0            0   \n",
       "4                   0                    0              0            0   \n",
       "\n",
       "   Korean Restaurant  Liquor Store  Lounge  Mediterranean Restaurant  \\\n",
       "0                  0             0       0                         0   \n",
       "1                  0             0       0                         0   \n",
       "2                  0             0       0                         0   \n",
       "3                  0             1       0                         0   \n",
       "4                  0             0       0                         0   \n",
       "\n",
       "   Mexican Restaurant  Middle Eastern Restaurant  Miscellaneous Shop  \\\n",
       "0                   0                          0                   0   \n",
       "1                   0                          0                   0   \n",
       "2                   0                          0                   0   \n",
       "3                   0                          0                   0   \n",
       "4                   0                          0                   0   \n",
       "\n",
       "   Movie Theater  Music Venue  New American Restaurant  Nightclub  \\\n",
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       "3              0            0                        0          0   \n",
       "4              0            0                        0          0   \n",
       "\n",
       "   Noodle House  Office  Outdoor Supply Store  Park  Performing Arts Venue  \\\n",
       "0             0       0                     0     0                      0   \n",
       "1             0       0                     0     0                      0   \n",
       "2             0       0                     0     0                      0   \n",
       "3             0       0                     0     0                      0   \n",
       "4             0       0                     0     0                      0   \n",
       "\n",
       "   Perfume Shop  Pet Store  Pharmacy  Pizza Place  Playground  Plaza  Pool  \\\n",
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       "3             0          0         0            0           0      0     0   \n",
       "4             0          0         0            0           0      0     0   \n",
       "\n",
       "   Public Art  Record Shop  Rental Car Location  Restaurant  \\\n",
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       "1           0            0                    0           0   \n",
       "2           0            0                    0           0   \n",
       "3           0            0                    0           0   \n",
       "4           0            0                    0           0   \n",
       "\n",
       "   Salon / Barbershop  Sandwich Place  Scenic Lookout  Science Museum  \\\n",
       "0                   0               0               0               0   \n",
       "1                   0               0               0               0   \n",
       "2                   0               0               0               0   \n",
       "3                   0               0               0               0   \n",
       "4                   0               0               0               0   \n",
       "\n",
       "   Sculpture Garden  Seafood Restaurant  Shipping Store  Skating Rink  \\\n",
       "0                 0                   0               0             0   \n",
       "1                 0                   0               0             0   \n",
       "2                 0                   0               0             0   \n",
       "3                 0                   0               0             0   \n",
       "4                 0                   0               0             0   \n",
       "\n",
       "   Smoke Shop  South American Restaurant  Spa  Spanish Restaurant  Speakeasy  \\\n",
       "0           0                          0    0                   0          0   \n",
       "1           0                          0    0                   0          0   \n",
       "2           0                          0    0                   0          0   \n",
       "3           0                          0    0                   0          0   \n",
       "4           0                          0    0                   0          0   \n",
       "\n",
       "   Sports Bar  Steakhouse  Supermarket  Sushi Restaurant  Taco Place  \\\n",
       "0           0           0            0                 0           0   \n",
       "1           0           0            0                 0           0   \n",
       "2           0           0            0                 0           0   \n",
       "3           0           0            0                 0           0   \n",
       "4           0           0            0                 0           0   \n",
       "\n",
       "   Tea Room  Thai Restaurant  Theater  Thrift / Vintage Store  \\\n",
       "0         0                0        0                       0   \n",
       "1         0                0        0                       0   \n",
       "2         0                0        0                       0   \n",
       "3         0                0        0                       0   \n",
       "4         0                0        0                       0   \n",
       "\n",
       "   Vegetarian / Vegan Restaurant  Video Store  Vietnamese Restaurant  \\\n",
       "0                              0            0                      0   \n",
       "1                              0            0                      0   \n",
       "2                              0            0                      0   \n",
       "3                              0            0                      0   \n",
       "4                              0            0                      0   \n",
       "\n",
       "   Wine Bar  Wine Shop  Yoga Studio  \n",
       "0         0          0            0  \n",
       "1         0          0            0  \n",
       "2         0          0            0  \n",
       "3         0          0            0  \n",
       "4         0          0            0  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "pvd_onehot = pd.get_dummies(pvd_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "pvd_onehot['Neighborhood'] = pvd_venues['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [pvd_onehot.columns[-1]] + list(pvd_onehot.columns[:-1])\n",
    "pvd_onehot = pvd_onehot[fixed_columns]\n",
    "\n",
    "pvd_onehot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Art Gallery</th>\n",
       "      <th>Asian Restaurant</th>\n",
       "      <th>Automotive Shop</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bakery</th>\n",
       "      <th>Bar</th>\n",
       "      <th>Beer Garden</th>\n",
       "      <th>Bistro</th>\n",
       "      <th>Bookstore</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Bubble Tea Shop</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Café</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Chocolate Shop</th>\n",
       "      <th>Clothing Store</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Bookstore</th>\n",
       "      <th>College Gym</th>\n",
       "      <th>Concert Hall</th>\n",
       "      <th>Convenience Store</th>\n",
       "      <th>Cosmetics Shop</th>\n",
       "      <th>Creperie</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>Dive Bar</th>\n",
       "      <th>Donut Shop</th>\n",
       "      <th>Exhibit</th>\n",
       "      <th>Farmers Market</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Fish Market</th>\n",
       "      <th>Food</th>\n",
       "      <th>Food Truck</th>\n",
       "      <th>French Restaurant</th>\n",
       "      <th>Fried Chicken Joint</th>\n",
       "      <th>Frozen Yogurt Shop</th>\n",
       "      <th>Gas Station</th>\n",
       "      <th>Gastropub</th>\n",
       "      <th>Gay Bar</th>\n",
       "      <th>Gift Shop</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>Hardware Store</th>\n",
       "      <th>Hockey Arena</th>\n",
       "      <th>Hookah Bar</th>\n",
       "      <th>Hot Dog Joint</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>Ice Cream Shop</th>\n",
       "      <th>Indian Restaurant</th>\n",
       "      <th>Indie Movie Theater</th>\n",
       "      <th>Italian Restaurant</th>\n",
       "      <th>Japanese Restaurant</th>\n",
       "      <th>Jewelry Store</th>\n",
       "      <th>Karaoke Bar</th>\n",
       "      <th>Korean Restaurant</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Lounge</th>\n",
       "      <th>Mediterranean Restaurant</th>\n",
       "      <th>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Movie Theater</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>Outdoor Supply Store</th>\n",
       "      <th>Park</th>\n",
       "      <th>Performing Arts Venue</th>\n",
       "      <th>Perfume Shop</th>\n",
       "      <th>Pet Store</th>\n",
       "      <th>Pharmacy</th>\n",
       "      <th>Pizza Place</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Pool</th>\n",
       "      <th>Public Art</th>\n",
       "      <th>Record Shop</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Salon / Barbershop</th>\n",
       "      <th>Sandwich Place</th>\n",
       "      <th>Scenic Lookout</th>\n",
       "      <th>Science Museum</th>\n",
       "      <th>Sculpture Garden</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shipping Store</th>\n",
       "      <th>Skating Rink</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>South American Restaurant</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Spanish Restaurant</th>\n",
       "      <th>Speakeasy</th>\n",
       "      <th>Sports Bar</th>\n",
       "      <th>Steakhouse</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Taco Place</th>\n",
       "      <th>Tea Room</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</th>\n",
       "      <th>Thrift / Vintage Store</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wine Shop</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Charles</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>College Hill</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.060000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.020000</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>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.040000</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>0.020000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.020000</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Downtown</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.097222</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.013889</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.041667</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.027778</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>0.027778</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.041667</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.041667</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.027778</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>0.041667</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.027778</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>0.013889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.027778</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>0.027778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elmhurst</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Elmwood</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.25</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>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.250000</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>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Neighborhood  American Restaurant  Art Gallery  Asian Restaurant  \\\n",
       "0       Charles             0.000000     0.000000          0.000000   \n",
       "1  College Hill             0.040000     0.020000          0.000000   \n",
       "2      Downtown             0.027778     0.013889          0.013889   \n",
       "3      Elmhurst             0.000000     0.000000          0.000000   \n",
       "4       Elmwood             0.000000     0.000000          0.000000   \n",
       "\n",
       "   Automotive Shop  BBQ Joint  Bagel Shop    Bakery       Bar  Beer Garden  \\\n",
       "0              0.0       0.00        0.00  0.000000  0.000000     0.000000   \n",
       "1              0.0       0.02        0.02  0.000000  0.000000     0.000000   \n",
       "2              0.0       0.00        0.00  0.013889  0.097222     0.013889   \n",
       "3              0.0       0.00        0.00  0.200000  0.000000     0.000000   \n",
       "4              0.0       0.00        0.00  0.000000  0.000000     0.000000   \n",
       "\n",
       "     Bistro  Bookstore  Breakfast Spot   Brewery  Bubble Tea Shop  \\\n",
       "0  0.000000       0.00             0.1  0.000000             0.00   \n",
       "1  0.000000       0.02             0.0  0.000000             0.02   \n",
       "2  0.013889       0.00             0.0  0.013889             0.00   \n",
       "3  0.000000       0.00             0.0  0.000000             0.00   \n",
       "4  0.000000       0.00             0.0  0.000000             0.00   \n",
       "\n",
       "   Burger Joint      Café  Chinese Restaurant  Chocolate Shop  Clothing Store  \\\n",
       "0      0.000000  0.000000                 0.0        0.000000        0.000000   \n",
       "1      0.000000  0.040000                 0.0        0.000000        0.020000   \n",
       "2      0.027778  0.027778                 0.0        0.013889        0.013889   \n",
       "3      0.000000  0.000000                 0.0        0.000000        0.200000   \n",
       "4      0.000000  0.000000                 0.0        0.000000        0.000000   \n",
       "\n",
       "   Cocktail Bar  Coffee Shop  College Bookstore  College Gym  Concert Hall  \\\n",
       "0      0.000000     0.000000           0.000000         0.00      0.000000   \n",
       "1      0.000000     0.060000           0.000000         0.02      0.000000   \n",
       "2      0.027778     0.055556           0.013889         0.00      0.013889   \n",
       "3      0.000000     0.000000           0.000000         0.00      0.000000   \n",
       "4      0.000000     0.000000           0.000000         0.00      0.000000   \n",
       "\n",
       "   Convenience Store  Cosmetics Shop  Creperie  Dance Studio  Deli / Bodega  \\\n",
       "0                0.0             0.0      0.00          0.00       0.100000   \n",
       "1                0.0             0.0      0.02          0.02       0.000000   \n",
       "2                0.0             0.0      0.00          0.00       0.013889   \n",
       "3                0.0             0.0      0.00          0.00       0.000000   \n",
       "4                0.0             0.0      0.00          0.00       0.000000   \n",
       "\n",
       "   Department Store  Dessert Shop  Diner  Discount Store  Dive Bar  \\\n",
       "0          0.000000          0.00   0.00             0.1       0.0   \n",
       "1          0.000000          0.02   0.00             0.0       0.0   \n",
       "2          0.013889          0.00   0.00             0.0       0.0   \n",
       "3          0.000000          0.00   0.00             0.0       0.0   \n",
       "4          0.000000          0.00   0.25             0.0       0.0   \n",
       "\n",
       "   Donut Shop  Exhibit  Farmers Market  Fast Food Restaurant  Fish Market  \\\n",
       "0         0.0      0.0             0.1                   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",
       "   Food  Food Truck  French Restaurant  Fried Chicken Joint  \\\n",
       "0   0.2    0.000000                0.0                  0.0   \n",
       "1   0.0    0.020000                0.0                  0.0   \n",
       "2   0.0    0.027778                0.0                  0.0   \n",
       "3   0.0    0.000000                0.0                  0.0   \n",
       "4   0.0    0.000000                0.0                  0.0   \n",
       "\n",
       "   Frozen Yogurt Shop  Gas Station  Gastropub   Gay Bar  Gift Shop  \\\n",
       "0                0.00          0.0   0.000000  0.000000   0.000000   \n",
       "1                0.02          0.0   0.000000  0.000000   0.020000   \n",
       "2                0.00          0.0   0.013889  0.041667   0.013889   \n",
       "3                0.00          0.0   0.000000  0.000000   0.000000   \n",
       "4                0.00          0.0   0.000000  0.000000   0.000000   \n",
       "\n",
       "   Gourmet Shop  Greek Restaurant  Grocery Store  Gym  Gym / Fitness Center  \\\n",
       "0           0.0          0.000000            0.0  0.0                   0.0   \n",
       "1           0.0          0.020000            0.0  0.0                   0.0   \n",
       "2           0.0          0.027778            0.0  0.0                   0.0   \n",
       "3           0.0          0.000000            0.0  0.0                   0.0   \n",
       "4           0.0          0.000000            0.0  0.0                   0.0   \n",
       "\n",
       "   Harbor / Marina  Hardware Store  Hockey Arena  Hookah Bar  Hot Dog Joint  \\\n",
       "0              0.0             0.0      0.000000        0.00            0.0   \n",
       "1              0.0             0.0      0.000000        0.02            0.0   \n",
       "2              0.0             0.0      0.027778        0.00            0.0   \n",
       "3              0.0             0.0      0.000000        0.00            0.0   \n",
       "4              0.0             0.0      0.000000        0.00            0.0   \n",
       "\n",
       "      Hotel  Ice Cream Shop  Indian Restaurant  Indie Movie Theater  \\\n",
       "0  0.000000            0.00               0.00                 0.00   \n",
       "1  0.000000            0.02               0.02                 0.02   \n",
       "2  0.041667            0.00               0.00                 0.00   \n",
       "3  0.000000            0.00               0.00                 0.00   \n",
       "4  0.000000            0.00               0.00                 0.00   \n",
       "\n",
       "   Italian Restaurant  Japanese Restaurant  Jewelry Store  Karaoke Bar  \\\n",
       "0            0.000000                 0.00           0.00     0.000000   \n",
       "1            0.000000                 0.02           0.02     0.000000   \n",
       "2            0.027778                 0.00           0.00     0.013889   \n",
       "3            0.000000                 0.00           0.00     0.000000   \n",
       "4            0.000000                 0.00           0.00     0.000000   \n",
       "\n",
       "   Korean Restaurant  Liquor Store    Lounge  Mediterranean Restaurant  \\\n",
       "0               0.00          0.10  0.000000                      0.00   \n",
       "1               0.06          0.00  0.000000                      0.02   \n",
       "2               0.00          0.00  0.013889                      0.00   \n",
       "3               0.00          0.20  0.000000                      0.00   \n",
       "4               0.00          0.25  0.000000                      0.00   \n",
       "\n",
       "   Mexican Restaurant  Middle Eastern Restaurant  Miscellaneous Shop  \\\n",
       "0            0.000000                       0.00                0.00   \n",
       "1            0.040000                       0.02                0.02   \n",
       "2            0.013889                       0.00                0.00   \n",
       "3            0.000000                       0.00                0.00   \n",
       "4            0.000000                       0.00                0.00   \n",
       "\n",
       "   Movie Theater  Music Venue  New American Restaurant  Nightclub  \\\n",
       "0            0.0          0.0                 0.000000   0.000000   \n",
       "1            0.0          0.0                 0.000000   0.000000   \n",
       "2            0.0          0.0                 0.041667   0.013889   \n",
       "3            0.0          0.0                 0.000000   0.000000   \n",
       "4            0.0          0.0                 0.000000   0.000000   \n",
       "\n",
       "   Noodle House  Office  Outdoor Supply Store      Park  \\\n",
       "0      0.000000     0.0                   0.0  0.200000   \n",
       "1      0.000000     0.0                   0.0  0.000000   \n",
       "2      0.013889     0.0                   0.0  0.013889   \n",
       "3      0.000000     0.0                   0.0  0.000000   \n",
       "4      0.000000     0.0                   0.0  0.000000   \n",
       "\n",
       "   Performing Arts Venue  Perfume Shop  Pet Store  Pharmacy  Pizza Place  \\\n",
       "0                   0.00           0.0        0.0  0.000000     0.000000   \n",
       "1                   0.02           0.0        0.0  0.020000     0.040000   \n",
       "2                   0.00           0.0        0.0  0.013889     0.027778   \n",
       "3                   0.00           0.0        0.0  0.000000     0.000000   \n",
       "4                   0.00           0.0        0.0  0.000000     0.000000   \n",
       "\n",
       "   Playground  Plaza  Pool  Public Art  Record Shop  Rental Car Location  \\\n",
       "0         0.0    0.1  0.00         0.0          0.0                  0.0   \n",
       "1         0.0    0.0  0.02         0.0          0.0                  0.0   \n",
       "2         0.0    0.0  0.00         0.0          0.0                  0.0   \n",
       "3         0.2    0.0  0.00         0.0          0.0                  0.2   \n",
       "4         0.0    0.0  0.00         0.0          0.0                  0.0   \n",
       "\n",
       "   Restaurant  Salon / Barbershop  Sandwich Place  Scenic Lookout  \\\n",
       "0    0.000000                0.00        0.000000            0.00   \n",
       "1    0.020000                0.02        0.020000            0.02   \n",
       "2    0.041667                0.00        0.027778            0.00   \n",
       "3    0.000000                0.00        0.000000            0.00   \n",
       "4    0.000000                0.00        0.250000            0.00   \n",
       "\n",
       "   Science Museum  Sculpture Garden  Seafood Restaurant  Shipping Store  \\\n",
       "0             0.0               0.0                 0.0            0.00   \n",
       "1             0.0               0.0                 0.0            0.02   \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",
       "   Skating Rink  Smoke Shop  South American Restaurant       Spa  \\\n",
       "0      0.000000         0.0                        0.0  0.000000   \n",
       "1      0.000000         0.0                        0.0  0.000000   \n",
       "2      0.013889         0.0                        0.0  0.013889   \n",
       "3      0.000000         0.0                        0.0  0.000000   \n",
       "4      0.000000         0.0                        0.0  0.000000   \n",
       "\n",
       "   Spanish Restaurant  Speakeasy  Sports Bar  Steakhouse  Supermarket  \\\n",
       "0                 0.0       0.00         0.0    0.000000         0.00   \n",
       "1                 0.0       0.02         0.0    0.000000         0.00   \n",
       "2                 0.0       0.00         0.0    0.027778         0.00   \n",
       "3                 0.0       0.00         0.0    0.000000         0.00   \n",
       "4                 0.0       0.00         0.0    0.000000         0.25   \n",
       "\n",
       "   Sushi Restaurant  Taco Place  Tea Room  Thai Restaurant   Theater  \\\n",
       "0              0.00         0.0      0.00              0.0  0.000000   \n",
       "1              0.02         0.0      0.02              0.0  0.000000   \n",
       "2              0.00         0.0      0.00              0.0  0.027778   \n",
       "3              0.00         0.0      0.00              0.0  0.000000   \n",
       "4              0.00         0.0      0.00              0.0  0.000000   \n",
       "\n",
       "   Thrift / Vintage Store  Vegetarian / Vegan Restaurant  Video Store  \\\n",
       "0                     0.0                           0.00          0.0   \n",
       "1                     0.0                           0.02          0.0   \n",
       "2                     0.0                           0.00          0.0   \n",
       "3                     0.0                           0.00          0.0   \n",
       "4                     0.0                           0.00          0.0   \n",
       "\n",
       "   Vietnamese Restaurant  Wine Bar  Wine Shop  Yoga Studio  \n",
       "0                    0.0  0.000000   0.000000         0.00  \n",
       "1                    0.0  0.000000   0.000000         0.02  \n",
       "2                    0.0  0.013889   0.013889         0.00  \n",
       "3                    0.0  0.000000   0.000000         0.00  \n",
       "4                    0.0  0.000000   0.000000         0.00  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pvd_grouped = pvd_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "pvd_grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Accessories Store</th>\n",
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       "      <th>Art Museum</th>\n",
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       "      <th>Bakery</th>\n",
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       "      <th>Brewery</th>\n",
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       "      <th>Burger Joint</th>\n",
       "      <th>Bus Station</th>\n",
       "      <th>Café</th>\n",
       "      <th>Caribbean Restaurant</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Churrascaria</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Gym</th>\n",
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       "      <th>Convenience Store</th>\n",
       "      <th>Cupcake Shop</th>\n",
       "      <th>Cycle Studio</th>\n",
       "      <th>Deli / Bodega</th>\n",
       "      <th>Dessert Shop</th>\n",
       "      <th>Diner</th>\n",
       "      <th>Discount Store</th>\n",
       "      <th>Donut Shop</th>\n",
       "      <th>Event Space</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Financial or Legal Service</th>\n",
       "      <th>Food</th>\n",
       "      <th>Food &amp; Drink Shop</th>\n",
       "      <th>Food Court</th>\n",
       "      <th>Food Truck</th>\n",
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       "      <th>Furniture / Home Store</th>\n",
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       "      <th>Grocery Store</th>\n",
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       "      <th>Gym / Fitness Center</th>\n",
       "      <th>Hardware Store</th>\n",
       "      <th>Health &amp; Beauty Service</th>\n",
       "      <th>History Museum</th>\n",
       "      <th>Hockey Arena</th>\n",
       "      <th>Hot Dog Joint</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>Hotel Bar</th>\n",
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       "      <th>Insurance Office</th>\n",
       "      <th>Italian Restaurant</th>\n",
       "      <th>Japanese Restaurant</th>\n",
       "      <th>Jewelry Store</th>\n",
       "      <th>Kebab Restaurant</th>\n",
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       "      <th>Latin American Restaurant</th>\n",
       "      <th>Lebanese Restaurant</th>\n",
       "      <th>Lingerie Store</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Mediterranean Restaurant</th>\n",
       "      <th>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Motel</th>\n",
       "      <th>Motorcycle Shop</th>\n",
       "      <th>Movie Theater</th>\n",
       "      <th>Music Store</th>\n",
       "      <th>Nightclub</th>\n",
       "      <th>Optical Shop</th>\n",
       "      <th>Other Nightlife</th>\n",
       "      <th>Park</th>\n",
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       "      <th>Pizza Place</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Pub</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Rental Service</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Rock Club</th>\n",
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       "      <th>Sandwich Place</th>\n",
       "      <th>Science Museum</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shipping Store</th>\n",
       "      <th>Shoe Store</th>\n",
       "      <th>Shopping Mall</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>Smoothie Shop</th>\n",
       "      <th>Snack Place</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Spanish Restaurant</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Stadium</th>\n",
       "      <th>Steakhouse</th>\n",
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       "      <th>Tapas Restaurant</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</th>\n",
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       "      <th>Wine Bar</th>\n",
       "      <th>Wine Shop</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  Neighborhood  Accessories Store  American Restaurant  Art Museum  \\\n",
       "0  Asylum Hill                  0                    0           0   \n",
       "1  Asylum Hill                  0                    0           0   \n",
       "2  Asylum Hill                  0                    0           0   \n",
       "3  Asylum Hill                  0                    0           0   \n",
       "4  Asylum Hill                  0                    0           0   \n",
       "\n",
       "   Arts & Entertainment  Asian Restaurant  Athletics & Sports  BBQ Joint  \\\n",
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       "2                     0                 0                   0          0   \n",
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       "\n",
       "   Bagel Shop  Bakery  Bank  Bar  Baseball Field  Baseball Stadium  Bistro  \\\n",
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       "2            0     1                     0                   0             0   \n",
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       "1                           0                  0             0             0   \n",
       "2                           0                  0             0             0   \n",
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       "3              0             0      0               0           0   \n",
       "4              0             0      0               0           0   \n",
       "\n",
       "   Event Space  Fast Food Restaurant  Financial or Legal Service  Food  \\\n",
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       "1            0                     0                           0     0   \n",
       "2            0                     0                           0     0   \n",
       "3            0                     0                           0     0   \n",
       "4            0                     0                           0     0   \n",
       "\n",
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       "1                  0           0           0                  0   \n",
       "2                  0           0           0                  0   \n",
       "3                  0           0           0                  0   \n",
       "4                  0           0           0                  0   \n",
       "\n",
       "   Furniture / Home Store  Gas Station  Gift Shop  Grocery Store  Gym  \\\n",
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       "1                       0            0          0              0    0   \n",
       "2                       0            0          0              0    0   \n",
       "3                       0            0          1              0    0   \n",
       "4                       0            0          0              0    1   \n",
       "\n",
       "   Gym / Fitness Center  Hardware Store  Health & Beauty Service  \\\n",
       "0                     0               0                        0   \n",
       "1                     0               0                        0   \n",
       "2                     0               0                        0   \n",
       "3                     0               0                        0   \n",
       "4                     0               0                        0   \n",
       "\n",
       "   History Museum  Hockey Arena  Hot Dog Joint  Hotel  Hotel Bar  \\\n",
       "0               0             0              0      0          0   \n",
       "1               0             0              0      0          0   \n",
       "2               0             0              0      0          0   \n",
       "3               0             0              0      0          0   \n",
       "4               0             0              0      0          0   \n",
       "\n",
       "   Ice Cream Shop  Indian Restaurant  Insurance Office  Italian Restaurant  \\\n",
       "0               0                  0                 0                   0   \n",
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       "2               0                  0                 0                   0   \n",
       "3               0                  0                 0                   0   \n",
       "4               0                  0                 0                   0   \n",
       "\n",
       "   Japanese Restaurant  Jewelry Store  Kebab Restaurant  Korean Restaurant  \\\n",
       "0                    0              0                 0                  0   \n",
       "1                    0              0                 0                  0   \n",
       "2                    0              0                 0                  0   \n",
       "3                    0              0                 0                  0   \n",
       "4                    0              0                 0                  0   \n",
       "\n",
       "   Latin American Restaurant  Lebanese Restaurant  Lingerie Store  \\\n",
       "0                          0                    0               0   \n",
       "1                          0                    0               0   \n",
       "2                          0                    0               0   \n",
       "3                          0                    0               0   \n",
       "4                          0                    0               0   \n",
       "\n",
       "   Liquor Store  Mediterranean Restaurant  Mexican Restaurant  \\\n",
       "0             0                         0                   0   \n",
       "1             0                         0                   0   \n",
       "2             0                         0                   0   \n",
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       "\n",
       "   Middle Eastern Restaurant  Miscellaneous Shop  Motel  Motorcycle Shop  \\\n",
       "0                          0                   0      0                0   \n",
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       "2                          0                   0      0                0   \n",
       "3                          0                   0      0                0   \n",
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       "   Movie Theater  Music Store  Nightclub  Optical Shop  Other Nightlife  Park  \\\n",
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       "\n",
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       "\n",
       "   Rental Service  Restaurant  Rock Club  Sake Bar  Sandwich Place  \\\n",
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       "1               0           0          0         0               0   \n",
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       "3               0           0          0         0               0   \n",
       "4               0           0          0         0               0   \n",
       "\n",
       "   Science Museum  Seafood Restaurant  Shipping Store  Shoe Store  \\\n",
       "0               0                   0               0           0   \n",
       "1               0                   0               0           0   \n",
       "2               0                   0               0           0   \n",
       "3               0                   0               0           0   \n",
       "4               0                   0               0           0   \n",
       "\n",
       "   Shopping Mall  Smoke Shop  Smoothie Shop  Snack Place  Spa  \\\n",
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       "3              0           0              0            0    0   \n",
       "4              0           0              0            0    0   \n",
       "\n",
       "   Spanish Restaurant  Sporting Goods Shop  Stadium  Steakhouse  Supermarket  \\\n",
       "0                   0                    0        0           0            0   \n",
       "1                   0                    0        0           0            0   \n",
       "2                   0                    0        0           0            0   \n",
       "3                   0                    0        0           0            0   \n",
       "4                   0                    0        0           0            0   \n",
       "\n",
       "   Tapas Restaurant  Thai Restaurant  Theater  Theme Park Ride / Attraction  \\\n",
       "0                 0                0        0                             0   \n",
       "1                 0                0        0                             0   \n",
       "2                 0                0        0                             0   \n",
       "3                 0                0        0                             0   \n",
       "4                 0                0        0                             0   \n",
       "\n",
       "   Toy / Game Store  Vegetarian / Vegan Restaurant  Video Store  \\\n",
       "0                 0                              0            0   \n",
       "1                 0                              0            0   \n",
       "2                 0                              0            0   \n",
       "3                 0                              0            0   \n",
       "4                 0                              0            0   \n",
       "\n",
       "   Vietnamese Restaurant  Wine Bar  Wine Shop  Yoga Studio  \n",
       "0                      0         0          0            0  \n",
       "1                      0         0          0            0  \n",
       "2                      0         0          0            0  \n",
       "3                      0         0          0            0  \n",
       "4                      0         0          0            0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "bdl_onehot = pd.get_dummies(bdl_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "bdl_onehot['Neighborhood'] = bdl_venues['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [bdl_onehot.columns[-1]] + list(bdl_onehot.columns[:-1])\n",
    "bdl_onehot = bdl_onehot[fixed_columns]\n",
    "\n",
    "bdl_onehot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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",
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       "    .dataframe thead th {\n",
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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>Accessories Store</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>Art Museum</th>\n",
       "      <th>Arts &amp; Entertainment</th>\n",
       "      <th>Asian Restaurant</th>\n",
       "      <th>Athletics &amp; Sports</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bakery</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Bar</th>\n",
       "      <th>Baseball Field</th>\n",
       "      <th>Baseball Stadium</th>\n",
       "      <th>Bistro</th>\n",
       "      <th>Bookstore</th>\n",
       "      <th>Boutique</th>\n",
       "      <th>Bowling Alley</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Bubble Tea Shop</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Bus Station</th>\n",
       "      <th>Café</th>\n",
       "      <th>Caribbean Restaurant</th>\n",
       "      <th>Chinese Restaurant</th>\n",
       "      <th>Churrascaria</th>\n",
       "      <th>Cocktail Bar</th>\n",
       "      <th>Coffee Shop</th>\n",
       "      <th>College Gym</th>\n",
       "      <th>Concert Hall</th>\n",
       "      <th>Construction &amp; Landscaping</th>\n",
       "      <th>Convenience Store</th>\n",
       "      <th>Cupcake Shop</th>\n",
       "      <th>Cycle Studio</th>\n",
       "      <th>Deli / Bodega</th>\n",
       "      <th>Dessert Shop</th>\n",
       "      <th>Diner</th>\n",
       "      <th>Discount Store</th>\n",
       "      <th>Donut Shop</th>\n",
       "      <th>Event Space</th>\n",
       "      <th>Fast Food Restaurant</th>\n",
       "      <th>Financial or Legal Service</th>\n",
       "      <th>Food</th>\n",
       "      <th>Food &amp; Drink Shop</th>\n",
       "      <th>Food Court</th>\n",
       "      <th>Food Truck</th>\n",
       "      <th>French Restaurant</th>\n",
       "      <th>Furniture / Home Store</th>\n",
       "      <th>Gas Station</th>\n",
       "      <th>Gift Shop</th>\n",
       "      <th>Grocery Store</th>\n",
       "      <th>Gym</th>\n",
       "      <th>Gym / Fitness Center</th>\n",
       "      <th>Hardware Store</th>\n",
       "      <th>Health &amp; Beauty Service</th>\n",
       "      <th>History Museum</th>\n",
       "      <th>Hockey Arena</th>\n",
       "      <th>Hot Dog Joint</th>\n",
       "      <th>Hotel</th>\n",
       "      <th>Hotel Bar</th>\n",
       "      <th>Ice Cream Shop</th>\n",
       "      <th>Indian Restaurant</th>\n",
       "      <th>Insurance Office</th>\n",
       "      <th>Italian Restaurant</th>\n",
       "      <th>Japanese Restaurant</th>\n",
       "      <th>Jewelry Store</th>\n",
       "      <th>Kebab Restaurant</th>\n",
       "      <th>Korean Restaurant</th>\n",
       "      <th>Latin American Restaurant</th>\n",
       "      <th>Lebanese Restaurant</th>\n",
       "      <th>Lingerie Store</th>\n",
       "      <th>Liquor Store</th>\n",
       "      <th>Mediterranean Restaurant</th>\n",
       "      <th>Mexican Restaurant</th>\n",
       "      <th>Middle Eastern Restaurant</th>\n",
       "      <th>Miscellaneous Shop</th>\n",
       "      <th>Motel</th>\n",
       "      <th>Motorcycle Shop</th>\n",
       "      <th>Movie Theater</th>\n",
       "      <th>Music Store</th>\n",
       "      <th>Nightclub</th>\n",
       "      <th>Optical Shop</th>\n",
       "      <th>Other Nightlife</th>\n",
       "      <th>Park</th>\n",
       "      <th>Pharmacy</th>\n",
       "      <th>Pizza Place</th>\n",
       "      <th>Playground</th>\n",
       "      <th>Plaza</th>\n",
       "      <th>Pub</th>\n",
       "      <th>Rental Car Location</th>\n",
       "      <th>Rental Service</th>\n",
       "      <th>Restaurant</th>\n",
       "      <th>Rock Club</th>\n",
       "      <th>Sake Bar</th>\n",
       "      <th>Sandwich Place</th>\n",
       "      <th>Science Museum</th>\n",
       "      <th>Seafood Restaurant</th>\n",
       "      <th>Shipping Store</th>\n",
       "      <th>Shoe Store</th>\n",
       "      <th>Shopping Mall</th>\n",
       "      <th>Smoke Shop</th>\n",
       "      <th>Smoothie Shop</th>\n",
       "      <th>Snack Place</th>\n",
       "      <th>Spa</th>\n",
       "      <th>Spanish Restaurant</th>\n",
       "      <th>Sporting Goods Shop</th>\n",
       "      <th>Stadium</th>\n",
       "      <th>Steakhouse</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Tapas Restaurant</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Theater</th>\n",
       "      <th>Theme Park Ride / Attraction</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Video Store</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Wine Bar</th>\n",
       "      <th>Wine Shop</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Asylum Hill</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.166667</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>0.0</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>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.166667</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>0.0</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.166667</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>0.0</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Barry Square</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.0</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>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.2</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</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>0.0</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.0</td>\n",
       "      <td>0.4</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Behind The Rocks</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.0</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>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.000000</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</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>0.0</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.5</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>0.0</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Blue Hills</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.0</td>\n",
       "      <td>0.25</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>0.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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>0.0</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>0.25</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</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>0.0</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>0.0</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>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</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",
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       "    <tr>\n",
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       "      <td>Clay Arsenal</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Neighborhood  Accessories Store  American Restaurant  Art Museum  \\\n",
       "0       Asylum Hill                0.0                  0.0         0.0   \n",
       "1      Barry Square                0.0                  0.0         0.0   \n",
       "2  Behind The Rocks                0.0                  0.0         0.0   \n",
       "3        Blue Hills                0.0                  0.0         0.0   \n",
       "4      Clay Arsenal                0.0                  0.0         0.0   \n",
       "\n",
       "   Arts & Entertainment  Asian Restaurant  Athletics & Sports  BBQ Joint  \\\n",
       "0              0.166667               0.0                 0.0        0.0   \n",
       "1              0.000000               0.0                 0.0        0.0   \n",
       "2              0.000000               0.0                 0.0        0.0   \n",
       "3              0.000000               0.0                 0.0        0.0   \n",
       "4              0.000000               0.0                 0.0        0.0   \n",
       "\n",
       "   Bagel Shop  Bakery  Bank  Bar  Baseball Field  Baseball Stadium  Bistro  \\\n",
       "0         0.0     0.0   0.0  0.0             0.0              0.00     0.0   \n",
       "1         0.0     0.0   0.0  0.0             0.0              0.00     0.0   \n",
       "2         0.0     0.0   0.0  0.0             0.0              0.00     0.0   \n",
       "3         0.0     0.0   0.0  0.0             0.0              0.25     0.0   \n",
       "4         0.0     0.0   0.0  0.0             0.0              0.00     0.0   \n",
       "\n",
       "   Bookstore  Boutique  Bowling Alley  Brewery  Bubble Tea Shop  Burger Joint  \\\n",
       "0        0.0       0.0            0.0      0.0              0.0          0.00   \n",
       "1        0.0       0.0            0.0      0.0              0.0          0.00   \n",
       "2        0.0       0.0            0.0      0.0              0.0          0.00   \n",
       "3        0.0       0.0            0.0      0.0              0.0          0.25   \n",
       "4        0.0       0.0            0.0      0.0              0.0          0.00   \n",
       "\n",
       "   Bus Station      Café  Caribbean Restaurant  Chinese Restaurant  \\\n",
       "0          0.0  0.333333                   0.0                 0.0   \n",
       "1          0.0  0.000000                   0.0                 0.0   \n",
       "2          0.5  0.000000                   0.0                 0.0   \n",
       "3          0.0  0.000000                   0.0                 0.0   \n",
       "4          0.0  0.000000                   0.0                 0.0   \n",
       "\n",
       "   Churrascaria  Cocktail Bar  Coffee Shop  College Gym  Concert Hall  \\\n",
       "0           0.0           0.0          0.0          0.0           0.0   \n",
       "1           0.0           0.0          0.0          0.2           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",
       "   Construction & Landscaping  Convenience Store  Cupcake Shop  Cycle Studio  \\\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",
       "   Deli / Bodega  Dessert Shop  Diner  Discount Store  Donut Shop  \\\n",
       "0            0.0           0.0    0.0            0.00        0.00   \n",
       "1            0.0           0.0    0.0            0.00        0.00   \n",
       "2            0.0           0.0    0.0            0.00        0.00   \n",
       "3            0.0           0.0    0.0            0.00        0.25   \n",
       "4            0.0           0.0    0.0            0.25        0.00   \n",
       "\n",
       "   Event Space  Fast Food Restaurant  Financial or Legal Service  Food  \\\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",
       "   Food & Drink Shop  Food Court  Food Truck  French 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",
       "   Furniture / Home Store  Gas Station  Gift Shop  Grocery Store       Gym  \\\n",
       "0                     0.0          0.0   0.166667           0.00  0.166667   \n",
       "1                     0.0          0.4   0.000000           0.00  0.000000   \n",
       "2                     0.0          0.0   0.000000           0.00  0.000000   \n",
       "3                     0.0          0.0   0.000000           0.00  0.000000   \n",
       "4                     0.0          0.0   0.000000           0.25  0.000000   \n",
       "\n",
       "   Gym / Fitness Center  Hardware Store  Health & Beauty Service  \\\n",
       "0                  0.00             0.0                      0.0   \n",
       "1                  0.00             0.0                      0.0   \n",
       "2                  0.00             0.0                      0.0   \n",
       "3                  0.00             0.0                      0.0   \n",
       "4                  0.25             0.0                      0.0   \n",
       "\n",
       "   History Museum  Hockey Arena  Hot Dog Joint  Hotel  Hotel Bar  \\\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",
       "   Ice Cream Shop  Indian Restaurant  Insurance Office  Italian 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",
       "   Japanese Restaurant  Jewelry Store  Kebab Restaurant  Korean 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",
       "   Latin American Restaurant  Lebanese Restaurant  Lingerie 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",
       "   Liquor Store  Mediterranean Restaurant  Mexican Restaurant  \\\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",
       "   Middle Eastern Restaurant  Miscellaneous Shop  Motel  Motorcycle Shop  \\\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",
       "   Movie Theater  Music Store  Nightclub  Optical Shop  Other Nightlife  \\\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",
       "       Park  Pharmacy  Pizza Place  Playground  Plaza  Pub  \\\n",
       "0  0.166667       0.0          0.0         0.0    0.0  0.0   \n",
       "1  0.000000       0.0          0.0         0.0    0.0  0.0   \n",
       "2  0.000000       0.5          0.0         0.0    0.0  0.0   \n",
       "3  0.000000       0.0          0.0         0.0    0.0  0.0   \n",
       "4  0.000000       0.0          0.0         0.0    0.0  0.0   \n",
       "\n",
       "   Rental Car Location  Rental Service  Restaurant  Rock Club  Sake Bar  \\\n",
       "0                  0.0             0.0         0.0        0.0       0.0   \n",
       "1                  0.0             0.0         0.0        0.4       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",
       "   Sandwich Place  Science Museum  Seafood Restaurant  Shipping Store  \\\n",
       "0            0.00             0.0                 0.0             0.0   \n",
       "1            0.00             0.0                 0.0             0.0   \n",
       "2            0.00             0.0                 0.0             0.0   \n",
       "3            0.25             0.0                 0.0             0.0   \n",
       "4            0.00             0.0                 0.0             0.0   \n",
       "\n",
       "   Shoe Store  Shopping Mall  Smoke Shop  Smoothie Shop  Snack Place  Spa  \\\n",
       "0         0.0            0.0         0.0            0.0          0.0  0.0   \n",
       "1         0.0            0.0         0.0            0.0          0.0  0.0   \n",
       "2         0.0            0.0         0.0            0.0          0.0  0.0   \n",
       "3         0.0            0.0         0.0            0.0          0.0  0.0   \n",
       "4         0.0            0.0         0.0            0.0          0.0  0.0   \n",
       "\n",
       "   Spanish Restaurant  Sporting Goods Shop  Stadium  Steakhouse  Supermarket  \\\n",
       "0                0.00                  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                0.25                  0.0      0.0         0.0          0.0   \n",
       "\n",
       "   Tapas Restaurant  Thai Restaurant  Theater  Theme Park Ride / Attraction  \\\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",
       "   Toy / Game Store  Vegetarian / Vegan Restaurant  Video 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",
       "   Vietnamese Restaurant  Wine Bar  Wine Shop  Yoga Studio  \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  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bdl_grouped = bdl_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "bdl_grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a function for top venus for a neighborhood\n",
    "num_top_venues=10\n",
    "def return_most_common_venues(row, num_top_venues):\n",
    "    row_categories = row.iloc[1:]\n",
    "    row_categories_sorted = row_categories.sort_values(ascending=False)\n",
    "    \n",
    "    return row_categories_sorted.index.values[0:num_top_venues]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Charles</td>\n",
       "      <td>Food</td>\n",
       "      <td>Park</td>\n",
       "      <td>Plaza</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Fish Market</td>\n",
       "      <td>French Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>College Hill</td>\n",
       "      <td>Korean Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Café</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Bubble Tea Shop</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Performing Arts Venue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Downtown</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Gay Bar</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>New American Restaurant</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Hockey Arena</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elmhurst</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Rental Car Location</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Food Truck</td>\n",
       "      <td>Food</td>\n",
       "      <td>Fish Market</td>\n",
       "      <td>Farmers Market</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Elmwood</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>French Restaurant</td>\n",
       "      <td>Food Truck</td>\n",
       "      <td>Food</td>\n",
       "      <td>Fish Market</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Neighborhood 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "0       Charles                  Food                  Park   \n",
       "1  College Hill     Korean Restaurant           Coffee Shop   \n",
       "2      Downtown                   Bar           Coffee Shop   \n",
       "3      Elmhurst            Playground          Liquor Store   \n",
       "4       Elmwood                 Diner        Sandwich Place   \n",
       "\n",
       "  3rd Most Common Venue 4th Most Common Venue    5th Most Common Venue  \\\n",
       "0                 Plaza        Discount Store            Deli / Bodega   \n",
       "1   American Restaurant                  Café       Mexican Restaurant   \n",
       "2               Gay Bar                 Hotel  New American Restaurant   \n",
       "3        Clothing Store   Rental Car Location                   Bakery   \n",
       "4           Supermarket          Liquor Store              Yoga Studio   \n",
       "\n",
       "  6th Most Common Venue 7th Most Common Venue 8th Most Common Venue  \\\n",
       "0        Farmers Market        Breakfast Spot          Liquor Store   \n",
       "1           Pizza Place       Bubble Tea Shop        Ice Cream Shop   \n",
       "2            Restaurant   American Restaurant          Burger Joint   \n",
       "3     French Restaurant            Food Truck                  Food   \n",
       "4  Fast Food Restaurant     French Restaurant            Food Truck   \n",
       "\n",
       "  9th Most Common Venue 10th Most Common Venue  \n",
       "0           Fish Market      French Restaurant  \n",
       "1              Pharmacy  Performing Arts Venue  \n",
       "2          Hockey Arena     Italian Restaurant  \n",
       "3           Fish Market         Farmers Market  \n",
       "4                  Food            Fish Market  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_top_venues = 10\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for ind in np.arange(num_top_venues):\n",
    "    try:\n",
    "        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n",
    "    except:\n",
    "        columns.append('{}th Most Common Venue'.format(ind+1))\n",
    "\n",
    "# create a new dataframe\n",
    "pvd_neighborhoods_venues_sorted = pd.DataFrame(columns=columns)\n",
    "pvd_neighborhoods_venues_sorted['Neighborhood'] = pvd_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(pvd_grouped.shape[0]):\n",
    "    pvd_neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(pvd_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "pvd_neighborhoods_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>Asylum Hill</td>\n",
       "      <td>Café</td>\n",
       "      <td>Arts &amp; Entertainment</td>\n",
       "      <td>Park</td>\n",
       "      <td>Gift Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Financial or Legal Service</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Event Space</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Barry Square</td>\n",
       "      <td>Rock Club</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>College Gym</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Cupcake Shop</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Behind The Rocks</td>\n",
       "      <td>Pharmacy</td>\n",
       "      <td>Bus Station</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Convenience Store</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Blue Hills</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Donut Shop</td>\n",
       "      <td>Burger Joint</td>\n",
       "      <td>Baseball Stadium</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Food Court</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Clay Arsenal</td>\n",
       "      <td>Spanish Restaurant</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Discount Store</td>\n",
       "      <td>Grocery Store</td>\n",
       "      <td>Food Court</td>\n",
       "      <td>Cupcake Shop</td>\n",
       "      <td>Cycle Studio</td>\n",
       "      <td>Deli / Bodega</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Diner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Neighborhood 1st Most Common Venue 2nd Most Common Venue  \\\n",
       "0       Asylum Hill                  Café  Arts & Entertainment   \n",
       "1      Barry Square             Rock Club           Gas Station   \n",
       "2  Behind The Rocks              Pharmacy           Bus Station   \n",
       "3        Blue Hills        Sandwich Place            Donut Shop   \n",
       "4      Clay Arsenal    Spanish Restaurant  Gym / Fitness Center   \n",
       "\n",
       "  3rd Most Common Venue 4th Most Common Venue 5th Most Common Venue  \\\n",
       "0                  Park             Gift Shop                   Gym   \n",
       "1           College Gym           Yoga Studio     Food & Drink Shop   \n",
       "2           Yoga Studio     Convenience Store          Cycle Studio   \n",
       "3          Burger Joint      Baseball Stadium           Yoga Studio   \n",
       "4        Discount Store         Grocery Store            Food Court   \n",
       "\n",
       "  6th Most Common Venue 7th Most Common Venue       8th Most Common Venue  \\\n",
       "0           Yoga Studio            Donut Shop  Financial or Legal Service   \n",
       "1          Cupcake Shop          Cycle Studio               Deli / Bodega   \n",
       "2         Deli / Bodega          Dessert Shop                       Diner   \n",
       "3            Food Court          Cycle Studio               Deli / Bodega   \n",
       "4          Cupcake Shop          Cycle Studio               Deli / Bodega   \n",
       "\n",
       "  9th Most Common Venue 10th Most Common Venue  \n",
       "0  Fast Food Restaurant            Event Space  \n",
       "1          Dessert Shop                  Diner  \n",
       "2        Discount Store             Donut Shop  \n",
       "3          Dessert Shop                  Diner  \n",
       "4          Dessert Shop                  Diner  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_top_venues = 10\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for ind in np.arange(num_top_venues):\n",
    "    try:\n",
    "        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n",
    "    except:\n",
    "        columns.append('{}th Most Common Venue'.format(ind+1))\n",
    "\n",
    "bdl_neighborhoods_venues_sorted = pd.DataFrame(columns=columns)\n",
    "bdl_neighborhoods_venues_sorted['Neighborhood'] = bdl_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(bdl_grouped.shape[0]):\n",
    "    bdl_neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(bdl_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "bdl_neighborhoods_venues_sorted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 1, 4, 0, 0, 0, 0, 3])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 5\n",
    "\n",
    "pvd_grouped_clustering = pvd_grouped.drop('Neighborhood', 1)\n",
    "\n",
    "# run k-means clustering\n",
    "pvd_kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(pvd_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "pvd_kmeans.labels_[0:10] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Length of values does not match length of index",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-52-9b11bd9dccf9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mpvd_merged\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Cluster Labels'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpvd_kmeans\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlabels_\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[1;34m(self, key, value)\u001b[0m\n\u001b[0;32m   3117\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3118\u001b[0m             \u001b[1;31m# set column\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3119\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_set_item\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3120\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3121\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_setitem_slice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m_set_item\u001b[1;34m(self, key, value)\u001b[0m\n\u001b[0;32m   3192\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3193\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_ensure_valid_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3194\u001b[1;33m         \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sanitize_column\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3195\u001b[0m         \u001b[0mNDFrame\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_set_item\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3196\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m_sanitize_column\u001b[1;34m(self, key, value, broadcast)\u001b[0m\n\u001b[0;32m   3389\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3390\u001b[0m             \u001b[1;31m# turn me into an ndarray\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3391\u001b[1;33m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_sanitize_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3392\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mIndex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3393\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\series.py\u001b[0m in \u001b[0;36m_sanitize_index\u001b[1;34m(data, index, copy)\u001b[0m\n\u001b[0;32m   3999\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4000\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 4001\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Length of values does not match length of '\u001b[0m \u001b[1;34m'index'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   4002\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4003\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mABCIndexClass\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Length of values does not match length of index"
     ]
    }
   ],
   "source": [
    "pvd_merged = df_pvd\n",
    "\n",
    "\n",
    "pvd_merged['Cluster Labels'] = pvd_kmeans.labels_\n",
    "\n",
    "\n",
    "pvd_merged = pvd_merged.join(pvd_neighborhoods_venues_sorted.set_index('Neighborhood'), on='Neighborhood')\n",
    "\n",
    "\n",
    "pvd_merged.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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