Coursera_Capstone_final_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Capstone Project - The Battle of the Neighborhoods (Week 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Applied Data Science Capstone by IBM/Coursera"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Table of Contents"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ul>\n",
    "    <li name=\"Introduction\">Introduction</li>\n",
    "    <li><a>Data Collection from APIs</a></li>\n",
    "    <li><a>Data Cleaning</a></li>\n",
    "    <li><a>Methodolgy</a></li>\n",
    "    <li><a>Analysis</a></li>\n",
    "    <li><a>Results and Discussion</a></li>\n",
    "    <li><a>Conclusion</a></li>\n",
    "    \n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The aim of the project is to identify venues in varanasi, India based on their rating and average prices. In this notebook, we will identify various venues in the city of varanasi, India, using Foursquare API and Zomato API, to help visitors select the restaurants that suit them the best.\n",
    "\n",
    "Whenever a user is visiting a city they start looking for places to visit during their stay. They primarily look for places based on the venue ratings across all venues and the average prices such that the locations fits in their budget.\n",
    "\n",
    "Here, we'll identify places that are fit for various individuals based on the information collected from the two APIs and Data Science. Once we have the plot with the venues, any company can launch an application using the same data and suggest users such information."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To begin with, we will take a look at varanasi on the Map using the folium library.\n",
    "\n",
    "We will also fetch the data from two different APIs.\n",
    "\n",
    "### Foursquare API : \n",
    "We will use the Foursquare API to fetch venues in varanasi starting from the middle upto 6 Kilometers in each direction.\n",
    "### Zomato API: \n",
    "The Zomato API provides information about various venues including the complete address, user ratings, price for two people, price range and a lot more."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Varanasi is a city in the northern Indian state of Uttar Pradesh dating to the 11th century B.C. Regarded as the spiritual capital of India, the city draws Hindu pilgrims who bathe in the Ganges River’s sacred waters and perform funeral rites. Along the city's winding streets are some 2,000 temples, including Kashi Vishwanath, the “Golden Temple,” dedicated to the Hindu god Shiva."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> We can use the geopy library to extract the latitude and longitude values of Varanasi but it seems off and thus, we'll directly supply the values in this case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinates of Varanasi are 25.3176, 82.9739.\n"
     ]
    }
   ],
   "source": [
    "VRS_LATITUDE = 25.3176\n",
    "VRS_LONGITUDE = 82.9739\n",
    "print('The geograpical coordinates of Varanasi are {}, {}.'.format(VRS_LATITUDE, VRS_LONGITUDE))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's use the folium library to create a complete map zoomed on varanasi. We'll also plot a marker on the coordinates we just identified above. This would give us a relatively good look at the center point we will be considering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f3da0eadfd0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import folium\n",
    "varanasi_map = folium.Map(location = [VRS_LATITUDE, VRS_LONGITUDE], zoom_start = 13)\n",
    "folium.Marker([VRS_LATITUDE, VRS_LONGITUDE]).add_to(varanasi_map)\n",
    "varanasi_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Foursquare API\n",
    "We begin by fetching a total of all venues in varanasi upto a range of 6 Kilometers using the Foursquare API. The Foursquare API has the explore API which allows us to find venue recommendations within a given radius from the given coordinates. We will use this API to find all the venues we need."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "FOURSQUARE_CLIENT_ID = 'GMUUC2GUMFOORGUE1X1RP5TDHGBFHG05QV0RBE5G3DIWIMVG'\n",
    "FOURSQUARE_CLIENT_SECRET = 'AKKTWEFY02L5UQCS0P2KKNHOLPQQT1AZWPQMIWSO0AMJ2EI0'\n",
    "RADIUS = 6000 # 4 Km\n",
    "NO_OF_VENUES = 100\n",
    "VERSION = '20190612' # Current date"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "We define the get_category_type method to get the correct category for each venue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_category_type(row):\n",
    "    try:\n",
    "        categories_list = row['categories']\n",
    "    except:\n",
    "        categories_list = row['venue.categories']\n",
    "        \n",
    "    if len(categories_list) == 0:\n",
    "        return None\n",
    "    else:\n",
    "        return categories_list[0]['name']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll call the API over and over till we get all venues from the API within the given distance. The maximum venues this API can fetch is 41, so we will fetch all venues by iteratively calling this API and increasing the offset each time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total 45 venues fetched within a total radius of 6.0 Km\n",
      "\n",
      "Total 45 venues fetched\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors\n",
    "\n",
    "from pandas.io.json import json_normalize\n",
    "import requests\n",
    "\n",
    "pd.set_option('display.max_rows', None)\n",
    "\n",
    "offset = 0\n",
    "total_venues = 0\n",
    "foursquare_venues = pd.DataFrame(columns = ['name', 'categories', 'lat', 'lng'])\n",
    "\n",
    "while (True):\n",
    "    url = ('https://api.foursquare.com/v2/venues/explore?client_id={}'\n",
    "           '&client_secret={}&v={}&ll={},{}&radius={}&limit={}&offset={}').format(FOURSQUARE_CLIENT_ID, \n",
    "                                                                        FOURSQUARE_CLIENT_SECRET, \n",
    "                                                                        VERSION, \n",
    "                                                                        VRS_LATITUDE, \n",
    "                                                                        VRS_LONGITUDE,\n",
    "                                                                        RADIUS,\n",
    "                                                                        NO_OF_VENUES,\n",
    "                                                                        offset)\n",
    "    result = requests.get(url).json()\n",
    "    venues_fetched = len(result['response']['groups'][0]['items'])\n",
    "    total_venues = total_venues + venues_fetched\n",
    "    print(\"Total {} venues fetched within a total radius of {} Km\".format(venues_fetched, RADIUS/1000))\n",
    "\n",
    "    venues = result['response']['groups'][0]['items']\n",
    "    venues = json_normalize(venues)\n",
    "\n",
    "    # Filter the columns\n",
    "    filtered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']\n",
    "    venues = venues.loc[:, filtered_columns]\n",
    "\n",
    "    # Filter the category for each row\n",
    "    venues['venue.categories'] = venues.apply(get_category_type, axis = 1)\n",
    "\n",
    "    # Clean all column names\n",
    "    venues.columns = [col.split(\".\")[-1] for col in venues.columns]\n",
    "    foursquare_venues = pd.concat([foursquare_venues, venues], axis = 0, sort = False)\n",
    "    \n",
    "    if (venues_fetched < 100):\n",
    "        break\n",
    "    else:\n",
    "        offset = offset + 100\n",
    "\n",
    "foursquare_venues = foursquare_venues.reset_index(drop = True)\n",
    "print(\"\\nTotal {} venues fetched\".format(total_venues))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Zomato API"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Zomato API allows using its search API to search for any given venue based on certain search filters such as query, latitude, longitude and more. Zomato also requires a Zomato user key which can be accessed with a developer account.\n",
    "\n",
    "We'll use the name, lat, and lng values of various venues fetched from Foursquare API to use the search API and get more information regarding each venue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fetching data for venue: 1\n",
      "Fetching data for venue: 2\n",
      "Fetching data for venue: 3\n",
      "Fetching data for venue: 4\n",
      "Fetching data for venue: 5\n",
      "Fetching data for venue: 6\n",
      "Fetching data for venue: 7\n",
      "Fetching data for venue: 8\n",
      "Fetching data for venue: 9\n",
      "Fetching data for venue: 10\n",
      "Fetching data for venue: 11\n",
      "Fetching data for venue: 12\n",
      "Fetching data for venue: 13\n",
      "Fetching data for venue: 14\n",
      "Fetching data for venue: 15\n",
      "Fetching data for venue: 16\n",
      "Fetching data for venue: 17\n",
      "Fetching data for venue: 18\n",
      "Fetching data for venue: 19\n",
      "Fetching data for venue: 20\n",
      "Fetching data for venue: 21\n",
      "Fetching data for venue: 22\n",
      "Fetching data for venue: 23\n",
      "Fetching data for venue: 24\n",
      "Fetching data for venue: 25\n",
      "Fetching data for venue: 26\n",
      "Fetching data for venue: 27\n",
      "Fetching data for venue: 28\n",
      "Fetching data for venue: 29\n",
      "Fetching data for venue: 30\n",
      "Fetching data for venue: 31\n",
      "Fetching data for venue: 32\n",
      "Fetching data for venue: 33\n",
      "Fetching data for venue: 34\n",
      "Fetching data for venue: 35\n",
      "Fetching data for venue: 36\n",
      "Fetching data for venue: 37\n",
      "Fetching data for venue: 38\n",
      "Fetching data for venue: 39\n",
      "Fetching data for venue: 40\n",
      "Fetching data for venue: 41\n",
      "Fetching data for venue: 42\n",
      "Fetching data for venue: 43\n",
      "Fetching data for venue: 44\n",
      "Fetching data for venue: 45\n"
     ]
    }
   ],
   "source": [
    "headers = {'user-key': 'b3a1c26ed20422bfaae7ada558744e1f'}\n",
    "venues_information = []\n",
    "\n",
    "for index, row in foursquare_venues.iterrows():\n",
    "    print(\"Fetching data for venue: {}\".format(index + 1))\n",
    "    venue = []\n",
    "    url = ('https://developers.zomato.com/api/v2.1/search?q={}' + \n",
    "          '&start=0&count=1&lat={}&lon={}&sort=real_distance').format(row['name'], row['lat'], row['lng'])\n",
    "    result = requests.get(url, headers = headers).json()\n",
    "    if (len(result['restaurants']) > 0):\n",
    "        venue.append(result['restaurants'][0]['restaurant']['name'])\n",
    "        venue.append(result['restaurants'][0]['restaurant']['location']['latitude'])\n",
    "        venue.append(result['restaurants'][0]['restaurant']['location']['longitude'])\n",
    "        venue.append(result['restaurants'][0]['restaurant']['average_cost_for_two'])\n",
    "        venue.append(result['restaurants'][0]['restaurant']['price_range'])\n",
    "        venue.append(result['restaurants'][0]['restaurant']['user_rating']['aggregate_rating'])\n",
    "        venue.append(result['restaurants'][0]['restaurant']['location']['address'])\n",
    "        venues_information.append(venue)\n",
    "    else:\n",
    "        venues_information.append(np.zeros(6))\n",
    "    \n",
    "zomato_venues = pd.DataFrame(venues_information, \n",
    "                                  columns = ['venue', 'latitude', \n",
    "                                             'longitude', 'price_for_two', \n",
    "                                             'price_range', 'rating', 'address'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_for_two</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Hotel Dolphin International</td>\n",
       "      <td>25.2995300290</td>\n",
       "      <td>82.9995642040</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>B 20/48, Near Jain Mandir, Bhelupur, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Punjab  Grill House</td>\n",
       "      <td>25.3094922309</td>\n",
       "      <td>83.0045169219</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Near Church Crossing, Luxa Road, Godaulia, Var...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>25.3093913007</td>\n",
       "      <td>83.0059475452</td>\n",
       "      <td>150.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>D-37/49, Godaulia, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Dawat</td>\n",
       "      <td>25.3096328663</td>\n",
       "      <td>83.0053490773</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Hotel Ganges Grand, Godowlia Crossing, Godauli...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>UBQ by Barbeque Nation</td>\n",
       "      <td>25.3356311000</td>\n",
       "      <td>82.9776407000</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>JHV Mall, 4th, The Mall Rd, Near Ramada Hotel,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Dolphin Restaurant</td>\n",
       "      <td>25.3078649107</td>\n",
       "      <td>83.0099621415</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>D 16/30 Manmandir Ghat, Dashwamedh Road, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>The Siwon Lassi Shop</td>\n",
       "      <td>25.3114830000</td>\n",
       "      <td>83.0111220000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Tripura Bhairwi Road, Nepali Kapda, Dashaswmed...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Sushi Cafe &amp; Continental Restaurant</td>\n",
       "      <td>25.3053200000</td>\n",
       "      <td>83.0084490000</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>D-32, 13-14, Bangali Tola Road, Bangali Tola, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Sol Bar - Hotel Surya</td>\n",
       "      <td>25.3387057134</td>\n",
       "      <td>82.9798902199</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894327489</td>\n",
       "      <td>83.0061403289</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Taste Of Banaras</td>\n",
       "      <td>25.2885273000</td>\n",
       "      <td>83.0059593000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Assi Ghat, Shivala, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>Di Great Dhaba</td>\n",
       "      <td>25.3131530000</td>\n",
       "      <td>82.9977900000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>D 56/49, Aurangabad, Sigra, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>Eatery Resturant</td>\n",
       "      <td>25.2959460000</td>\n",
       "      <td>83.0056740000</td>\n",
       "      <td>450.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>B 3/284, Shivala Near Chet Singh Fort, Shivala...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894327489</td>\n",
       "      <td>83.0061403289</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>Chowk - The Gateway Hotel</td>\n",
       "      <td>25.3354363817</td>\n",
       "      <td>82.9867000133</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Nadesar Palace Grounds, Nadesar, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3031804464</td>\n",
       "      <td>83.0075159669</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>Open Hand Shop &amp; Cafe</td>\n",
       "      <td>25.2879591583</td>\n",
       "      <td>83.0044683069</td>\n",
       "      <td>450.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>Banarasi Handi</td>\n",
       "      <td>25.3249433000</td>\n",
       "      <td>83.0007119000</td>\n",
       "      <td>250.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Near Dalim School, Ramktora, Pradeep Hotel Roa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>Tandoor Singh</td>\n",
       "      <td>25.3223340000</td>\n",
       "      <td>82.9924570000</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>K62/32, Saptasnagar, Maidagin, Nadesar, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>B-4 Cafe &amp; Rooftop Restaurant</td>\n",
       "      <td>25.2971040000</td>\n",
       "      <td>83.0069830000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>B4/30, Near Junna Akhada, Hanuman Ghat, Bangal...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161400000</td>\n",
       "      <td>82.9855700000</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>The Belgian Waffle Co</td>\n",
       "      <td>25.2996620000</td>\n",
       "      <td>83.0011150000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>Beside Kerala Cafe, Bhelupura Chauraha\\nVaranasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.2915700000</td>\n",
       "      <td>82.9990000000</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9, Ground Floor, IP Vijaya Mall, Bhelupur, Var...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>Aangan- Hotel Hindustan International</td>\n",
       "      <td>25.3238407392</td>\n",
       "      <td>82.9944224283</td>\n",
       "      <td>850.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Hindustan International, C21/3 Maldahiya...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>Ocean - The Rivatas</td>\n",
       "      <td>25.3376363495</td>\n",
       "      <td>82.9796293750</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Rivatas, The Mall Road, Cantonment, Nadesar, V...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>Mangi Ferra Cafe - Hotel Surya</td>\n",
       "      <td>25.3386272310</td>\n",
       "      <td>82.9800092429</td>\n",
       "      <td>800.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>Chestnuts</td>\n",
       "      <td>25.2936387000</td>\n",
       "      <td>83.0022554000</td>\n",
       "      <td>450.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Anandbagh, Bhelupur, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>Hotel The Westinn</td>\n",
       "      <td>25.3386737000</td>\n",
       "      <td>82.9804077000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>S20/52-2A-1 The Mall Road, Cantonment, Varuna ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3031804464</td>\n",
       "      <td>83.0075159669</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>Salt &amp; Pepper</td>\n",
       "      <td>25.2941138038</td>\n",
       "      <td>83.0048179999</td>\n",
       "      <td>600.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>Near Anandmayi Hospital, Bhelupur, Varanasi, A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>Shiva Cafe &amp; German Bakery</td>\n",
       "      <td>25.3081530000</td>\n",
       "      <td>83.0099640000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>D 26/4, BHU Road, Himalaya Lodge, Dashaswmedh ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>Coral Brown</td>\n",
       "      <td>25.3185789380</td>\n",
       "      <td>82.9906686768</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>C 19/115-A-116S, Near Sigra Thana, Sigra, Vara...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>Mr. Dosa &amp; Mrs. Chutney</td>\n",
       "      <td>25.2930430000</td>\n",
       "      <td>83.0027720000</td>\n",
       "      <td>150.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Ravindrapuri Road, Near Anandbagh, Bhelupur, V...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>Sunrise Rooftop Restaurant - Palace on Step</td>\n",
       "      <td>25.3052142930</td>\n",
       "      <td>83.0093579739</td>\n",
       "      <td>600.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Rana Mahal, Ghat Banagali Tola, Godaulia, Vara...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161400000</td>\n",
       "      <td>82.9855700000</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>Benaras Kothi</td>\n",
       "      <td>25.3371010000</td>\n",
       "      <td>82.9765470000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>Budhbihar Colony, Cantt, Nadesar, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>Amrapali Restaurant</td>\n",
       "      <td>25.3099080000</td>\n",
       "      <td>82.9899610000</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>D 58/9, Hotel Siddharth, Sigra, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3031804464</td>\n",
       "      <td>83.0075159669</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>Dolphin Restaurant</td>\n",
       "      <td>25.3078649107</td>\n",
       "      <td>83.0099621415</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>D 16/30 Manmandir Ghat, Dashwamedh Road, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>The Oakwood Bar - Radisson Hotel</td>\n",
       "      <td>25.3382905746</td>\n",
       "      <td>82.9799502343</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>Radisson Hotel, The Mall Road, Nadesar, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>Dolphin Restaurant</td>\n",
       "      <td>25.3078649107</td>\n",
       "      <td>83.0099621415</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>D 16/30 Manmandir Ghat, Dashwamedh Road, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>Sunrise Rooftop Restaurant - Palace on Step</td>\n",
       "      <td>25.3052142930</td>\n",
       "      <td>83.0093579739</td>\n",
       "      <td>600.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Rana Mahal, Ghat Banagali Tola, Godaulia, Vara...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>Crystal Food Mania</td>\n",
       "      <td>25.2831359873</td>\n",
       "      <td>82.9794389382</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>Below Red Bull Gym, Newada, Sunderpur, Varanasi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>Punjab  Grill House</td>\n",
       "      <td>25.3094922309</td>\n",
       "      <td>83.0045169219</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Near Church Crossing, Luxa Road, Godaulia, Var...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          venue       latitude      longitude  \\\n",
       "0                   Hotel Dolphin International  25.2995300290  82.9995642040   \n",
       "1                           Punjab  Grill House  25.3094922309  83.0045169219   \n",
       "2                            Kashi Chat Bhandar  25.3093913007  83.0059475452   \n",
       "3                                         Dawat  25.3096328663  83.0053490773   \n",
       "4                        UBQ by Barbeque Nation  25.3356311000  82.9776407000   \n",
       "5                                             0              0              0   \n",
       "6                            Dolphin Restaurant  25.3078649107  83.0099621415   \n",
       "7                          The Siwon Lassi Shop  25.3114830000  83.0111220000   \n",
       "8           Sushi Cafe & Continental Restaurant  25.3053200000  83.0084490000   \n",
       "9                         Sol Bar - Hotel Surya  25.3387057134  82.9798902199   \n",
       "10                        Pizzeria Vaatika Cafe  25.2894327489  83.0061403289   \n",
       "11                             Taste Of Banaras  25.2885273000  83.0059593000   \n",
       "12                               Di Great Dhaba  25.3131530000  82.9977900000   \n",
       "13                             Eatery Resturant  25.2959460000  83.0056740000   \n",
       "14                        Pizzeria Vaatika Cafe  25.2894327489  83.0061403289   \n",
       "15                    Chowk - The Gateway Hotel  25.3354363817  82.9867000133   \n",
       "16                           Brown Bread Bakery  25.3031804464  83.0075159669   \n",
       "17                        Open Hand Shop & Cafe  25.2879591583  83.0044683069   \n",
       "18                               Banarasi Handi  25.3249433000  83.0007119000   \n",
       "19                                Tandoor Singh  25.3223340000  82.9924570000   \n",
       "20                B-4 Cafe & Rooftop Restaurant  25.2971040000  83.0069830000   \n",
       "21                               Domino's Pizza  25.3161400000  82.9855700000   \n",
       "22                        The Belgian Waffle Co  25.2996620000  83.0011150000   \n",
       "23                               Domino's Pizza  25.2915700000  82.9990000000   \n",
       "24        Aangan- Hotel Hindustan International  25.3238407392  82.9944224283   \n",
       "25                          Ocean - The Rivatas  25.3376363495  82.9796293750   \n",
       "26               Mangi Ferra Cafe - Hotel Surya  25.3386272310  82.9800092429   \n",
       "27                                    Chestnuts  25.2936387000  83.0022554000   \n",
       "28                            Hotel The Westinn  25.3386737000  82.9804077000   \n",
       "29                           Brown Bread Bakery  25.3031804464  83.0075159669   \n",
       "30                                Salt & Pepper  25.2941138038  83.0048179999   \n",
       "31                   Shiva Cafe & German Bakery  25.3081530000  83.0099640000   \n",
       "32                                  Coral Brown  25.3185789380  82.9906686768   \n",
       "33                      Mr. Dosa & Mrs. Chutney  25.2930430000  83.0027720000   \n",
       "34  Sunrise Rooftop Restaurant - Palace on Step  25.3052142930  83.0093579739   \n",
       "35                               Domino's Pizza  25.3161400000  82.9855700000   \n",
       "36                                Benaras Kothi  25.3371010000  82.9765470000   \n",
       "37                          Amrapali Restaurant  25.3099080000  82.9899610000   \n",
       "38                           Brown Bread Bakery  25.3031804464  83.0075159669   \n",
       "39                           Dolphin Restaurant  25.3078649107  83.0099621415   \n",
       "40             The Oakwood Bar - Radisson Hotel  25.3382905746  82.9799502343   \n",
       "41                           Dolphin Restaurant  25.3078649107  83.0099621415   \n",
       "42  Sunrise Rooftop Restaurant - Palace on Step  25.3052142930  83.0093579739   \n",
       "43                           Crystal Food Mania  25.2831359873  82.9794389382   \n",
       "44                          Punjab  Grill House  25.3094922309  83.0045169219   \n",
       "\n",
       "    price_for_two  price_range rating  \\\n",
       "0           500.0          3.0    3.8   \n",
       "1           300.0          2.0    2.9   \n",
       "2           150.0          1.0    4.7   \n",
       "3          1200.0          4.0    3.0   \n",
       "4           400.0          2.0    3.1   \n",
       "5             0.0          0.0      0   \n",
       "6           700.0          3.0    3.7   \n",
       "7           100.0          1.0    3.6   \n",
       "8           400.0          2.0    3.4   \n",
       "9          1500.0          4.0    3.6   \n",
       "10          700.0          3.0    4.2   \n",
       "11          300.0          2.0      0   \n",
       "12          300.0          2.0      0   \n",
       "13          450.0          2.0    3.1   \n",
       "14          700.0          3.0    4.2   \n",
       "15         2000.0          4.0    4.0   \n",
       "16          500.0          3.0    3.2   \n",
       "17          450.0          2.0    4.2   \n",
       "18          250.0          2.0    3.6   \n",
       "19          400.0          2.0      0   \n",
       "20          300.0          2.0    3.0   \n",
       "21          400.0          2.0    3.9   \n",
       "22          300.0          2.0    4.2   \n",
       "23          400.0          2.0    4.0   \n",
       "24          850.0          3.0    3.6   \n",
       "25         1800.0          4.0    3.6   \n",
       "26          800.0          3.0    3.9   \n",
       "27          450.0          2.0    3.0   \n",
       "28          500.0          3.0    3.5   \n",
       "29          500.0          3.0    3.2   \n",
       "30          600.0          3.0    2.7   \n",
       "31          500.0          3.0    3.3   \n",
       "32          400.0          2.0    3.8   \n",
       "33          150.0          1.0    3.6   \n",
       "34          600.0          3.0      0   \n",
       "35          400.0          2.0    3.9   \n",
       "36          500.0          3.0    3.3   \n",
       "37          500.0          3.0      0   \n",
       "38          500.0          3.0    3.2   \n",
       "39          700.0          3.0    3.7   \n",
       "40         1000.0          4.0    3.3   \n",
       "41          700.0          3.0    3.7   \n",
       "42          600.0          3.0      0   \n",
       "43          400.0          2.0    3.5   \n",
       "44          300.0          2.0    2.9   \n",
       "\n",
       "                                              address  \n",
       "0       B 20/48, Near Jain Mandir, Bhelupur, Varanasi  \n",
       "1   Near Church Crossing, Luxa Road, Godaulia, Var...  \n",
       "2                         D-37/49, Godaulia, Varanasi  \n",
       "3   Hotel Ganges Grand, Godowlia Crossing, Godauli...  \n",
       "4   JHV Mall, 4th, The Mall Rd, Near Ramada Hotel,...  \n",
       "5                                                None  \n",
       "6   D 16/30 Manmandir Ghat, Dashwamedh Road, Varanasi  \n",
       "7   Tripura Bhairwi Road, Nepali Kapda, Dashaswmed...  \n",
       "8   D-32, 13-14, Bangali Tola Road, Bangali Tola, ...  \n",
       "9   Hotel Surya, 20/51, A-5, The Mall Road, Varuna...  \n",
       "10                              B 1/178 Assi Varanasi  \n",
       "11                       Assi Ghat, Shivala, Varanasi  \n",
       "12               D 56/49, Aurangabad, Sigra, Varanasi  \n",
       "13  B 3/284, Shivala Near Chet Singh Fort, Shivala...  \n",
       "14                              B 1/178 Assi Varanasi  \n",
       "15          Nadesar Palace Grounds, Nadesar, Varanasi  \n",
       "16  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...  \n",
       "17  B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...  \n",
       "18  Near Dalim School, Ramktora, Pradeep Hotel Roa...  \n",
       "19   K62/32, Saptasnagar, Maidagin, Nadesar, Varanasi  \n",
       "20  B4/30, Near Junna Akhada, Hanuman Ghat, Bangal...  \n",
       "21  14, Ground Floor, Cinema Site, IP Mallvaranasi...  \n",
       "22  Beside Kerala Cafe, Bhelupura Chauraha\\nVaranasi   \n",
       "23  9, Ground Floor, IP Vijaya Mall, Bhelupur, Var...  \n",
       "24  Hotel Hindustan International, C21/3 Maldahiya...  \n",
       "25  Rivatas, The Mall Road, Cantonment, Nadesar, V...  \n",
       "26  Hotel Surya, 20/51, A-5, The Mall Road, Varuna...  \n",
       "27                      Anandbagh, Bhelupur, Varanasi  \n",
       "28  S20/52-2A-1 The Mall Road, Cantonment, Varuna ...  \n",
       "29  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...  \n",
       "30  Near Anandmayi Hospital, Bhelupur, Varanasi, A...  \n",
       "31  D 26/4, BHU Road, Himalaya Lodge, Dashaswmedh ...  \n",
       "32  C 19/115-A-116S, Near Sigra Thana, Sigra, Vara...  \n",
       "33  Ravindrapuri Road, Near Anandbagh, Bhelupur, V...  \n",
       "34  Rana Mahal, Ghat Banagali Tola, Godaulia, Vara...  \n",
       "35  14, Ground Floor, Cinema Site, IP Mallvaranasi...  \n",
       "36         Budhbihar Colony, Cantt, Nadesar, Varanasi  \n",
       "37           D 58/9, Hotel Siddharth, Sigra, Varanasi  \n",
       "38  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...  \n",
       "39  D 16/30 Manmandir Ghat, Dashwamedh Road, Varanasi  \n",
       "40   Radisson Hotel, The Mall Road, Nadesar, Varanasi  \n",
       "41  D 16/30 Manmandir Ghat, Dashwamedh Road, Varanasi  \n",
       "42  Rana Mahal, Ghat Banagali Tola, Godaulia, Vara...  \n",
       "43    Below Red Bull Gym, Newada, Sunderpur, Varanasi  \n",
       "44  Near Church Crossing, Luxa Road, Godaulia, Var...  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zomato_venues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data from multiple resources might not always align. Thus, it is important to combine the data retrieved from multiple resources properly.\n",
    "\n",
    "We'll first plot the two data points on the map. We'll then try to combine data points that have their latitude and longitude values very close to one another. From the remaining selected venues, we will inspect the venues to ensure that any remaining mismatched venues are also removed from the final dataset of venues before we begin any analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We will first plot the Foursquare data on the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
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  "lineJoin": "round",
  "opacity": 1.0,
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</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f3d8d329978>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "varanasi_map = folium.Map(location = [VRS_LATITUDE, VRS_LONGITUDE], zoom_start = 13)\n",
    "\n",
    "for name, latitude, longitude in zip(foursquare_venues['name'], foursquare_venues['lat'], foursquare_venues['lng']):\n",
    "    label = '{}'.format(name)\n",
    "    label = folium.Popup(label, parse_html = True)\n",
    "    folium.CircleMarker(\n",
    "        [latitude, longitude],\n",
    "        radius = 5,\n",
    "        popup = label,\n",
    "        color = 'green',\n",
    "        fill = True,\n",
    "        fill_color = '#3186cc',\n",
    "        fill_opacity = 0.7,\n",
    "        parse_html = False).add_to(varanasi_map)  \n",
    "\n",
    "#chandigarh_map.save(\"maps/Venues by Foursquare.html\")\n",
    "varanasi_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## We will also plot the Zomato data on the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f3d8caa8320>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "VRS_LATITUDE = 25.3176\n",
    "VRS_LONGITUDE = 82.9739\n",
    "varanasi_map = folium.Map(location = [VRS_LATITUDE, VRS_LONGITUDE], zoom_start = 13)\n",
    "\n",
    "for venue, address, latitude, longitude in zip(zomato_venues['venue'], zomato_venues['address'], \n",
    "                                               zomato_venues['latitude'], zomato_venues['longitude']):\n",
    "    label = '{}, {}'.format(name, address)\n",
    "    label = folium.Popup(label, parse_html = True)\n",
    "    folium.CircleMarker(\n",
    "        [float(latitude),float(longitude)],\n",
    "        radius = 5,\n",
    "        popup = label,\n",
    "        color = 'red',\n",
    "        fill = True,\n",
    "        fill_color = '#cc3535',\n",
    "        fill_opacity = 0.7,\n",
    "        parse_html = False).add_to(varanasi_map)  \n",
    "varanasi_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combining the dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To combine the two datasets, I'll have to check that the latitude and longitude values of each corresponding venue match. Thus, I'll round both the latitude and longitude values upto 4 decimal places. Then, I'll calculate the difference between the corresponding latitude and longitude values and see if the difference is less than 0.0004 which should ideally mean that the two locations are same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "foursquare_venues['lat'] = foursquare_venues['lat'].apply(lambda lat: round(float(lat), 4))\n",
    "foursquare_venues['lng'] = foursquare_venues['lng'].apply(lambda lng: round(float(lng), 4))\n",
    "zomato_venues['latitude'] = zomato_venues['latitude'].apply(lambda lat: round(float(lat), 4))\n",
    "zomato_venues['longitude'] = zomato_venues['longitude'].apply(lambda lng: round(float(lng), 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = pd.concat([foursquare_venues, zomato_venues], axis = 1)\n",
    "dataset['lat_diff'] = dataset['latitude'] - dataset['lat']\n",
    "dataset['lng_diff'] = dataset['longitude'] - dataset['lng']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>categories</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_for_two</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "      <th>lat_diff</th>\n",
       "      <th>lng_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Stops Hostel Varanasi</td>\n",
       "      <td>Hostel</td>\n",
       "      <td>25.2995</td>\n",
       "      <td>82.9997</td>\n",
       "      <td>Hotel Dolphin International</td>\n",
       "      <td>25.2995</td>\n",
       "      <td>82.9996</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>B 20/48, Near Jain Mandir, Bhelupur, Varanasi</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>25.3095</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>25.3094</td>\n",
       "      <td>83.0059</td>\n",
       "      <td>150.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>D-37/49, Godaulia, Varanasi</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>JHV Mall</td>\n",
       "      <td>Shopping Mall</td>\n",
       "      <td>25.3357</td>\n",
       "      <td>82.9777</td>\n",
       "      <td>UBQ by Barbeque Nation</td>\n",
       "      <td>25.3356</td>\n",
       "      <td>82.9776</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>JHV Mall, 4th, The Mall Rd, Near Ramada Hotel,...</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Hotel Surya</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>25.3388</td>\n",
       "      <td>82.9800</td>\n",
       "      <td>Sol Bar - Hotel Surya</td>\n",
       "      <td>25.3387</td>\n",
       "      <td>82.9799</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Pizzeria Vaatika Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0062</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Assi Ghat</td>\n",
       "      <td>Temple</td>\n",
       "      <td>25.2888</td>\n",
       "      <td>83.0062</td>\n",
       "      <td>Taste Of Banaras</td>\n",
       "      <td>25.2885</td>\n",
       "      <td>83.0060</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Assi Ghat, Shivala, Varanasi</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Ashish Cafe</td>\n",
       "      <td>Café</td>\n",
       "      <td>25.2897</td>\n",
       "      <td>83.0060</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Open Hand Café &amp; Shop</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>Open Hand Shop &amp; Cafe</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>450.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>25.3160</td>\n",
       "      <td>82.9860</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161</td>\n",
       "      <td>82.9856</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.0004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Kerala Cafe</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>25.3000</td>\n",
       "      <td>83.0012</td>\n",
       "      <td>The Belgian Waffle Co</td>\n",
       "      <td>25.2997</td>\n",
       "      <td>83.0011</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>Beside Kerala Cafe, Bhelupura Chauraha\\nVaranasi</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Hotel Rivatas by Ideal</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>25.3378</td>\n",
       "      <td>82.9799</td>\n",
       "      <td>Ocean - The Rivatas</td>\n",
       "      <td>25.3376</td>\n",
       "      <td>82.9796</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Rivatas, The Mall Road, Cantonment, Nadesar, V...</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>-0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Radisson Hotel</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>25.3386</td>\n",
       "      <td>82.9807</td>\n",
       "      <td>Hotel The Westinn</td>\n",
       "      <td>25.3387</td>\n",
       "      <td>82.9804</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>S20/52-2A-1 The Mall Road, Cantonment, Varuna ...</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>Brown Bread Bakery Varanasi</td>\n",
       "      <td>Café</td>\n",
       "      <td>25.3034</td>\n",
       "      <td>83.0072</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3032</td>\n",
       "      <td>83.0075</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>Madhur Milan Cafe</td>\n",
       "      <td>Asian Restaurant</td>\n",
       "      <td>25.3083</td>\n",
       "      <td>83.0096</td>\n",
       "      <td>Shiva Cafe &amp; German Bakery</td>\n",
       "      <td>25.3082</td>\n",
       "      <td>83.0100</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>D 26/4, BHU Road, Himalaya Lodge, Dashaswmedh ...</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>0.0004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>Ramada Plaza JHV Hotel Varanasi</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>25.3369</td>\n",
       "      <td>82.9764</td>\n",
       "      <td>Benaras Kothi</td>\n",
       "      <td>25.3371</td>\n",
       "      <td>82.9765</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>Budhbihar Colony, Cantt, Nadesar, Varanasi</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>Hotel Siddharth</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>25.3099</td>\n",
       "      <td>82.9901</td>\n",
       "      <td>Amrapali Restaurant</td>\n",
       "      <td>25.3099</td>\n",
       "      <td>82.9900</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>D 58/9, Hotel Siddharth, Sigra, Varanasi</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>Monalisa Cafe</td>\n",
       "      <td>Café</td>\n",
       "      <td>25.3034</td>\n",
       "      <td>83.0072</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3032</td>\n",
       "      <td>83.0075</td>\n",
       "      <td>500.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>0.0003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>Dharbhanga Ghat</td>\n",
       "      <td>River</td>\n",
       "      <td>25.3054</td>\n",
       "      <td>83.0095</td>\n",
       "      <td>Sunrise Rooftop Restaurant - Palace on Step</td>\n",
       "      <td>25.3052</td>\n",
       "      <td>83.0094</td>\n",
       "      <td>600.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Rana Mahal, Ghat Banagali Tola, Godaulia, Vara...</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               name         categories      lat      lng  \\\n",
       "0             Stops Hostel Varanasi             Hostel  25.2995  82.9997   \n",
       "1                Kashi Chat Bhandar  Indian Restaurant  25.3095  83.0061   \n",
       "2                          JHV Mall      Shopping Mall  25.3357  82.9777   \n",
       "3                       Hotel Surya              Hotel  25.3388  82.9800   \n",
       "4             Pizzeria Vaatika Café        Pizza Place  25.2894  83.0062   \n",
       "5                         Assi Ghat             Temple  25.2888  83.0062   \n",
       "6                       Ashish Cafe               Café  25.2897  83.0060   \n",
       "7             Open Hand Café & Shop        Coffee Shop  25.2880  83.0045   \n",
       "8                    Domino's Pizza        Pizza Place  25.3160  82.9860   \n",
       "9                       Kerala Cafe  Indian Restaurant  25.3000  83.0012   \n",
       "10           Hotel Rivatas by Ideal              Hotel  25.3378  82.9799   \n",
       "11                   Radisson Hotel              Hotel  25.3386  82.9807   \n",
       "12      Brown Bread Bakery Varanasi               Café  25.3034  83.0072   \n",
       "13                Madhur Milan Cafe   Asian Restaurant  25.3083  83.0096   \n",
       "14  Ramada Plaza JHV Hotel Varanasi              Hotel  25.3369  82.9764   \n",
       "15                  Hotel Siddharth              Hotel  25.3099  82.9901   \n",
       "16                    Monalisa Cafe               Café  25.3034  83.0072   \n",
       "17                  Dharbhanga Ghat              River  25.3054  83.0095   \n",
       "\n",
       "                                          venue  latitude  longitude  \\\n",
       "0                   Hotel Dolphin International   25.2995    82.9996   \n",
       "1                            Kashi Chat Bhandar   25.3094    83.0059   \n",
       "2                        UBQ by Barbeque Nation   25.3356    82.9776   \n",
       "3                         Sol Bar - Hotel Surya   25.3387    82.9799   \n",
       "4                         Pizzeria Vaatika Cafe   25.2894    83.0061   \n",
       "5                              Taste Of Banaras   25.2885    83.0060   \n",
       "6                         Pizzeria Vaatika Cafe   25.2894    83.0061   \n",
       "7                         Open Hand Shop & Cafe   25.2880    83.0045   \n",
       "8                                Domino's Pizza   25.3161    82.9856   \n",
       "9                         The Belgian Waffle Co   25.2997    83.0011   \n",
       "10                          Ocean - The Rivatas   25.3376    82.9796   \n",
       "11                            Hotel The Westinn   25.3387    82.9804   \n",
       "12                           Brown Bread Bakery   25.3032    83.0075   \n",
       "13                   Shiva Cafe & German Bakery   25.3082    83.0100   \n",
       "14                                Benaras Kothi   25.3371    82.9765   \n",
       "15                          Amrapali Restaurant   25.3099    82.9900   \n",
       "16                           Brown Bread Bakery   25.3032    83.0075   \n",
       "17  Sunrise Rooftop Restaurant - Palace on Step   25.3052    83.0094   \n",
       "\n",
       "    price_for_two  price_range rating  \\\n",
       "0           500.0          3.0    3.8   \n",
       "1           150.0          1.0    4.7   \n",
       "2           400.0          2.0    3.1   \n",
       "3          1500.0          4.0    3.6   \n",
       "4           700.0          3.0    4.2   \n",
       "5           300.0          2.0      0   \n",
       "6           700.0          3.0    4.2   \n",
       "7           450.0          2.0    4.2   \n",
       "8           400.0          2.0    3.9   \n",
       "9           300.0          2.0    4.2   \n",
       "10         1800.0          4.0    3.6   \n",
       "11          500.0          3.0    3.5   \n",
       "12          500.0          3.0    3.2   \n",
       "13          500.0          3.0    3.3   \n",
       "14          500.0          3.0    3.3   \n",
       "15          500.0          3.0      0   \n",
       "16          500.0          3.0    3.2   \n",
       "17          600.0          3.0      0   \n",
       "\n",
       "                                              address  lat_diff  lng_diff  \n",
       "0       B 20/48, Near Jain Mandir, Bhelupur, Varanasi    0.0000   -0.0001  \n",
       "1                         D-37/49, Godaulia, Varanasi   -0.0001   -0.0002  \n",
       "2   JHV Mall, 4th, The Mall Rd, Near Ramada Hotel,...   -0.0001   -0.0001  \n",
       "3   Hotel Surya, 20/51, A-5, The Mall Road, Varuna...   -0.0001   -0.0001  \n",
       "4                               B 1/178 Assi Varanasi    0.0000   -0.0001  \n",
       "5                        Assi Ghat, Shivala, Varanasi   -0.0003   -0.0002  \n",
       "6                               B 1/178 Assi Varanasi   -0.0003    0.0001  \n",
       "7   B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...    0.0000    0.0000  \n",
       "8   14, Ground Floor, Cinema Site, IP Mallvaranasi...    0.0001   -0.0004  \n",
       "9   Beside Kerala Cafe, Bhelupura Chauraha\\nVaranasi    -0.0003   -0.0001  \n",
       "10  Rivatas, The Mall Road, Cantonment, Nadesar, V...   -0.0002   -0.0003  \n",
       "11  S20/52-2A-1 The Mall Road, Cantonment, Varuna ...    0.0001   -0.0003  \n",
       "12  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...   -0.0002    0.0003  \n",
       "13  D 26/4, BHU Road, Himalaya Lodge, Dashaswmedh ...   -0.0001    0.0004  \n",
       "14         Budhbihar Colony, Cantt, Nadesar, Varanasi    0.0002    0.0001  \n",
       "15           D 58/9, Hotel Siddharth, Sigra, Varanasi    0.0000   -0.0001  \n",
       "16  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...   -0.0002    0.0003  \n",
       "17  Rana Mahal, Ghat Banagali Tola, Godaulia, Vara...   -0.0002   -0.0001  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_venues = dataset[(abs(dataset['lat_diff']) <= 0.0004) & (abs(dataset['lng_diff']) <= 0.0004)].reset_index(drop = True)\n",
    "selected_venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_venues = selected_venues.drop([0, 2, 5, 6, 9,11,13,14,15,16]).reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>categories</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_for_two</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "      <th>lat_diff</th>\n",
       "      <th>lng_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>25.3095</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>25.3094</td>\n",
       "      <td>83.0059</td>\n",
       "      <td>150.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>D-37/49, Godaulia, Varanasi</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Hotel Surya</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>25.3388</td>\n",
       "      <td>82.9800</td>\n",
       "      <td>Sol Bar - Hotel Surya</td>\n",
       "      <td>25.3387</td>\n",
       "      <td>82.9799</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Pizzeria Vaatika Café</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0062</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>700.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Open Hand Café &amp; Shop</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>Open Hand Shop &amp; Cafe</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>450.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>25.3160</td>\n",
       "      <td>82.9860</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161</td>\n",
       "      <td>82.9856</td>\n",
       "      <td>400.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>-0.0004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name         categories      lat      lng  \\\n",
       "0     Kashi Chat Bhandar  Indian Restaurant  25.3095  83.0061   \n",
       "1            Hotel Surya              Hotel  25.3388  82.9800   \n",
       "2  Pizzeria Vaatika Café        Pizza Place  25.2894  83.0062   \n",
       "3  Open Hand Café & Shop        Coffee Shop  25.2880  83.0045   \n",
       "4         Domino's Pizza        Pizza Place  25.3160  82.9860   \n",
       "\n",
       "                   venue  latitude  longitude  price_for_two  price_range  \\\n",
       "0     Kashi Chat Bhandar   25.3094    83.0059          150.0          1.0   \n",
       "1  Sol Bar - Hotel Surya   25.3387    82.9799         1500.0          4.0   \n",
       "2  Pizzeria Vaatika Cafe   25.2894    83.0061          700.0          3.0   \n",
       "3  Open Hand Shop & Cafe   25.2880    83.0045          450.0          2.0   \n",
       "4         Domino's Pizza   25.3161    82.9856          400.0          2.0   \n",
       "\n",
       "  rating                                            address  lat_diff  \\\n",
       "0    4.7                        D-37/49, Godaulia, Varanasi   -0.0001   \n",
       "1    3.6  Hotel Surya, 20/51, A-5, The Mall Road, Varuna...   -0.0001   \n",
       "2    4.2                              B 1/178 Assi Varanasi    0.0000   \n",
       "3    4.2  B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...    0.0000   \n",
       "4    3.9  14, Ground Floor, Cinema Site, IP Mallvaranasi...    0.0001   \n",
       "\n",
       "   lng_diff  \n",
       "0   -0.0002  \n",
       "1   -0.0001  \n",
       "2   -0.0001  \n",
       "3    0.0000  \n",
       "4   -0.0004  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_venues.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we'll now select the venue name from Zomato API. I'll also get the average price per person by dividing the column price_for_two by 2 and removing this column from the dataset along with other unnecessary columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_venues['average_price'] = selected_venues['price_for_two']/2\n",
    "selected_venues = selected_venues.drop(columns = ['name', 'lat', 'lng', 'lat_diff', 'lng_diff', 'price_for_two'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the final dataset that is left with us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>categories</th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "      <th>average_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>25.3094</td>\n",
       "      <td>83.0059</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>D-37/49, Godaulia, Varanasi</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Sol Bar - Hotel Surya</td>\n",
       "      <td>25.3387</td>\n",
       "      <td>82.9799</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "      <td>750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Open Hand Shop &amp; Cafe</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...</td>\n",
       "      <td>225.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161</td>\n",
       "      <td>82.9856</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          categories                  venue  latitude  longitude  price_range  \\\n",
       "0  Indian Restaurant     Kashi Chat Bhandar   25.3094    83.0059          1.0   \n",
       "1              Hotel  Sol Bar - Hotel Surya   25.3387    82.9799          4.0   \n",
       "2        Pizza Place  Pizzeria Vaatika Cafe   25.2894    83.0061          3.0   \n",
       "3        Coffee Shop  Open Hand Shop & Cafe   25.2880    83.0045          2.0   \n",
       "4        Pizza Place         Domino's Pizza   25.3161    82.9856          2.0   \n",
       "\n",
       "  rating                                            address  average_price  \n",
       "0    4.7                        D-37/49, Godaulia, Varanasi           75.0  \n",
       "1    3.6  Hotel Surya, 20/51, A-5, The Mall Road, Varuna...          750.0  \n",
       "2    4.2                              B 1/178 Assi Varanasi          350.0  \n",
       "3    4.2  B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...          225.0  \n",
       "4    3.9  14, Ground Floor, Cinema Site, IP Mallvaranasi...          200.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "selected_venues.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'll drop the venues which have 0.0 rating as it means it's not been rated yet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total venues available: 7\n"
     ]
    }
   ],
   "source": [
    "selected_venues = selected_venues[selected_venues['rating'] != 0.0]\n",
    "print(\"Total venues available: {}\".format(selected_venues.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Methodology"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This project aims at identifying the venues in varanasi based on their rating and average costs. This would enable any visitor to identify the venues he/she wants to visit based on their rating and cost preference.\n",
    "\n",
    "As a first step, we retrieved the data from two APIs (Foursquare and Zomato). We extract venue information from the center of varanasi, upto a distance of 6 Km. The latitude and longitude values are then used to fetch venue rating and price from Zomato.\n",
    "\n",
    "Secondly, we then explored the data retrieved from the two APIs on the map and identified the top category types. The data from the two sources is carefully combined based on the name, latitude and longitude values from the two sources. The final dataset would include the rating and price values for each venue.\n",
    "\n",
    "Next, we'll analyse the data that we created based on the ratings and price of each venue. We'll identify places where many venues are located so that any visitor can go to one place and enjoy the option to choose amongst many venue options. We'll also explore areas that are high rated and those that are low rated while also plotting the map of high and low priced venues. Lastly, we'll cluster the venues based on the available information of each venue. This will allow us to clearly identify which venues can be recommended and with what characteristics.\n",
    "\n",
    "Finally, we'll discuss and conclude which venues to be explored based on visitor requirement of rating and cost."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The complete dataset is now in its final form.\n",
    "\n",
    "We will inspect these venues based on their rating. The rating of a venue are based on user reviews and belongs to a range from 1 to 5. We'll also analyse the venues based on their price per person as well as the price range."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categories"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have various types of venues in the final dataset. We will take a look at the venues and check which are the majority venue categories in the list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 5 artists>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "venue_distribution = selected_venues['categories'].value_counts()\n",
    "colors = cm.rainbow(np.linspace(0, 1, len(venue_distribution.index)))\n",
    "plt.figure(figsize = (16, 12))\n",
    "plt.xticks(rotation = 90)\n",
    "plt.xlabel(\"Venue category\", fontsize = 16)\n",
    "plt.ylabel(\"Count\", fontsize = 16)\n",
    "plt.title(\"Count of venues of each category\", fontsize = 20)\n",
    "plt.bar(venue_distribution.index, venue_distribution.values, color = colors)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see the majority venues are Hotel and Pizza Places. So, if as a tourist, you're looking for Hotel and Pizza Places, you're in luck."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Rating\n",
    "\n",
    "Rating of a venue is an important factor on which a visitor decides whether it is worth it to visit the place. To cater to this, we will first see what is the average rating for all the venues in the city. Next, we will plot the venues on the map and color code them.\n",
    "\n",
    "We'll first identify the various rating values and plot them as a bar plot with their counts to see the most common rating."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Count of venues with given rating')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "selected_venues['rating'] = selected_venues['rating'].astype(float)\n",
    "rating = selected_venues['rating'].value_counts().sort_index()\n",
    "plt.figure(figsize = (20, 12))\n",
    "plt.bar(rating.index, rating.values, color = cm.rainbow(np.linspace(0, 1, len(rating.index))))\n",
    "plt.xlabel(\"Rating\", fontsize = 16)\n",
    "plt.ylabel(\"Count\", fontsize = 16)\n",
    "plt.title(\"Count of venues with given rating\", fontsize = 16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the plot above, it is clear that majority venues have their rating close to 3.5 and 4.\n",
    "\n",
    "Let's create bins for various ratings and plot them in different colors on the map. The ratings will be divided between 4 bins:\n",
    "\n",
    ">1 to 2 \n",
    "\n",
    ">2 to 3\n",
    "\n",
    ">3 to 4\n",
    "\n",
    ">4 to 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "bins = [1.0, 2.0, 3.0, 4.0, 5.0]\n",
    "labels = ['Low', 'Okay', 'Good', 'Very good']\n",
    "selected_venues['rating_bin'] = pd.cut(selected_venues['rating'].astype(float), bins = bins, labels = labels, include_lowest = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we will plot the venues on the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
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            var popup_0ce8bef22c8b4faeadee429a11ff00de = L.popup({maxWidth: '300'});

            
                var html_c8877872337c47b98a563a53aee8ef44 = $('<div id="html_c8877872337c47b98a563a53aee8ef44" style="width: 100.0%; height: 100.0%;">Sol Bar - Hotel Surya, Hotel Surya, 20/51, A-5, The Mall Road, Varuna Bridge, Nadesar, Varanasi</div>')[0];
                popup_0ce8bef22c8b4faeadee429a11ff00de.setContent(html_c8877872337c47b98a563a53aee8ef44);
            

            marker_6d2edfb51a6e4b03809420e3ed8ee719.bindPopup(popup_0ce8bef22c8b4faeadee429a11ff00de);

            
        
    

            var marker_4683e57c8a9143bc8e528c20e61a0784 = L.marker(
                [25.2894,83.0061],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_c905104ff18f4b079dbbf2909c16f753);
            
    

                var icon_6106115af8124c439f7e0e5bf5c69bba = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'darkgreen',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_4683e57c8a9143bc8e528c20e61a0784.setIcon(icon_6106115af8124c439f7e0e5bf5c69bba);
            
    
            var popup_8858d94aaa6049e1a7c1a9e36bc0cc5e = L.popup({maxWidth: '300'});

            
                var html_6d999ef39cfb4eeda172cc4ca31d55ee = $('<div id="html_6d999ef39cfb4eeda172cc4ca31d55ee" style="width: 100.0%; height: 100.0%;">Pizzeria Vaatika Cafe, B 1/178 Assi Varanasi</div>')[0];
                popup_8858d94aaa6049e1a7c1a9e36bc0cc5e.setContent(html_6d999ef39cfb4eeda172cc4ca31d55ee);
            

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            var marker_157a61cecaa547ec99b7febc640ac8ab = L.marker(
                [25.288,83.0045],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_c905104ff18f4b079dbbf2909c16f753);
            
    

                var icon_270f34ecceec4a1e8f71c0fb0c649713 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'darkgreen',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_157a61cecaa547ec99b7febc640ac8ab.setIcon(icon_270f34ecceec4a1e8f71c0fb0c649713);
            
    
            var popup_438ece02aa6342dc8a5eec25650211e6 = L.popup({maxWidth: '300'});

            
                var html_8815fb494b944405871c75031d2ac0d2 = $('<div id="html_8815fb494b944405871c75031d2ac0d2" style="width: 100.0%; height: 100.0%;">Open Hand Shop &amp; Cafe, B1/128-3, Dumraun Bagh Colony, Assi Ghat, Varanasi</div>')[0];
                popup_438ece02aa6342dc8a5eec25650211e6.setContent(html_8815fb494b944405871c75031d2ac0d2);
            

            marker_157a61cecaa547ec99b7febc640ac8ab.bindPopup(popup_438ece02aa6342dc8a5eec25650211e6);

            
        
    

            var marker_a77285c7e3ab4344beb11f31ed08db19 = L.marker(
                [25.3161,82.9856],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_c905104ff18f4b079dbbf2909c16f753);
            
    

                var icon_4ce961e119a6450ca03c60dc4e9fe5f0 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_a77285c7e3ab4344beb11f31ed08db19.setIcon(icon_4ce961e119a6450ca03c60dc4e9fe5f0);
            
    
            var popup_0e0e85c773394143819581007cb9fb7d = L.popup({maxWidth: '300'});

            
                var html_7979010c35b64e719ba4326250fd8b04 = $('<div id="html_7979010c35b64e719ba4326250fd8b04" style="width: 100.0%; height: 100.0%;">Domino&#39;s Pizza, 14, Ground Floor, Cinema Site, IP Mallvaranasi, Shastri Nagar, Sigra, Chetganj, Varanasi</div>')[0];
                popup_0e0e85c773394143819581007cb9fb7d.setContent(html_7979010c35b64e719ba4326250fd8b04);
            

            marker_a77285c7e3ab4344beb11f31ed08db19.bindPopup(popup_0e0e85c773394143819581007cb9fb7d);

            
        
    

            var marker_04cae360b6d148d1b36d3f27bfe600c1 = L.marker(
                [25.3376,82.9796],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_c905104ff18f4b079dbbf2909c16f753);
            
    

                var icon_d2afce371bb047ffbecad6198fc31bdf = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_04cae360b6d148d1b36d3f27bfe600c1.setIcon(icon_d2afce371bb047ffbecad6198fc31bdf);
            
    
            var popup_ee6d6cea78644a6a92699a60d3532b56 = L.popup({maxWidth: '300'});

            
                var html_b2d48c50966c4953b14998fb66976ef5 = $('<div id="html_b2d48c50966c4953b14998fb66976ef5" style="width: 100.0%; height: 100.0%;">Ocean - The Rivatas, Rivatas, The Mall Road, Cantonment, Nadesar, Varanasi</div>')[0];
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            var marker_00c5cb8dae72424189d6464f257ec6a7 = L.marker(
                [25.3032,83.0075],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_c905104ff18f4b079dbbf2909c16f753);
            
    

                var icon_b88d9d2b224147a599683ed9a329fd57 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_00c5cb8dae72424189d6464f257ec6a7.setIcon(icon_b88d9d2b224147a599683ed9a329fd57);
            
    
            var popup_b17ff5bffefa41c1b5523254cf65e9b1 = L.popup({maxWidth: '300'});

            
                var html_68e7db6cdd7048a9ad4a7b1a99a8ef39 = $('<div id="html_68e7db6cdd7048a9ad4a7b1a99a8ef39" style="width: 100.0%; height: 100.0%;">Brown Bread Bakery, D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat, Varanasi</div>')[0];
                popup_b17ff5bffefa41c1b5523254cf65e9b1.setContent(html_68e7db6cdd7048a9ad4a7b1a99a8ef39);
            

            marker_00c5cb8dae72424189d6464f257ec6a7.bindPopup(popup_b17ff5bffefa41c1b5523254cf65e9b1);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f3da0666d30>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color_map = {'Low': 'red', 'Okay': 'orange', 'Good': 'green', 'Very good': 'darkgreen'}\n",
    "\n",
    "varanasi_map = folium.Map(location = [VRS_LATITUDE, VRS_LONGITUDE], zoom_start = 13)\n",
    "\n",
    "for name, address, latitude, longitude, rating_bin in zip(selected_venues['venue'], \n",
    "                                                          selected_venues['address'], \n",
    "                                                          selected_venues['latitude'], \n",
    "                                                          selected_venues['longitude'], \n",
    "                                                          selected_venues['rating_bin']):\n",
    "    label = '{}, {}'.format(name, address)\n",
    "    label = folium.Popup(label, parse_html = True)\n",
    "    folium.Marker(\n",
    "        [latitude, longitude],\n",
    "        icon = folium.Icon(color = color_map[rating_bin]),\n",
    "        popup = label).add_to(varanasi_map)  \n",
    "varanasi_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">Users might also be interested in going to a place that fits in their budget. I'll use the price_range column to plot the venues on a map. We'll represent the venues with lower price in green and move towards red as the price increases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS = false; L_NO_TOUCH = false; L_DISABLE_3D = false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.js"></script>
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
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    <link rel="stylesheet" href="https://rawgit.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css"/>
    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
    
            <style> #map_5309627c29ed4ecface976a4e5a6b78e {
                position : relative;
                width : 100.0%;
                height: 100.0%;
                left: 0.0%;
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                }
            </style>
        
</head>
<body>    
    
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</body>
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            var map_5309627c29ed4ecface976a4e5a6b78e = L.map(
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                                  {center: [25.3176,82.9739],
                                  zoom: 13,
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                                  layers: [],
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                                  crs: L.CRS.EPSG3857
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                'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
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  "attribution": null,
  "detectRetina": false,
  "maxZoom": 18,
  "minZoom": 1,
  "noWrap": false,
  "subdomains": "abc"
}
                ).addTo(map_5309627c29ed4ecface976a4e5a6b78e);
        
    

            var marker_21b1fef5251a4726a79f51c00ba71684 = L.marker(
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                {
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                )
                .addTo(map_5309627c29ed4ecface976a4e5a6b78e);
            
    

                var icon_117bbfb129a1460c8ff54f8f87f5ddce = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
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                var html_1b02d034b3e64e319531671669215592 = $('<div id="html_1b02d034b3e64e319531671669215592" style="width: 100.0%; height: 100.0%;">Sol Bar - Hotel Surya, Hotel Surya, 20/51, A-5, The Mall Road, Varuna Bridge, Nadesar, Varanasi</div>')[0];
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            var marker_9afb030cf1914c2dae29b85945d47ac5 = L.marker(
                [25.2894,83.0061],
                {
                    icon: new L.Icon.Default()
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                )
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                var icon_7eb56e4f0cbf46f48f9dd6a7c8adb9d5 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
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                var html_2193a54114594fc9a251515abf006db1 = $('<div id="html_2193a54114594fc9a251515abf006db1" style="width: 100.0%; height: 100.0%;">Pizzeria Vaatika Cafe, B 1/178 Assi Varanasi</div>')[0];
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            var marker_eeb616ff08194c99b0b6c48b14101ccc = L.marker(
                [25.288,83.0045],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_5309627c29ed4ecface976a4e5a6b78e);
            
    

                var icon_1741c8c66ac745f88a1b89161251bb65 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'darkgreen',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_eeb616ff08194c99b0b6c48b14101ccc.setIcon(icon_1741c8c66ac745f88a1b89161251bb65);
            
    
            var popup_b69bdcdceb1f46b68b8a89c6c97615a5 = L.popup({maxWidth: '300'});

            
                var html_95f49dc91b2041ecaed2916585fb8b3a = $('<div id="html_95f49dc91b2041ecaed2916585fb8b3a" style="width: 100.0%; height: 100.0%;">Open Hand Shop &amp; Cafe, B1/128-3, Dumraun Bagh Colony, Assi Ghat, Varanasi</div>')[0];
                popup_b69bdcdceb1f46b68b8a89c6c97615a5.setContent(html_95f49dc91b2041ecaed2916585fb8b3a);
            

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            var marker_90e91bd6f28c43c9bf3f78e52038d1b4 = L.marker(
                [25.3161,82.9856],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_5309627c29ed4ecface976a4e5a6b78e);
            
    

                var icon_a0f19ea01e3543889d3865de516d0e91 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'darkgreen',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_90e91bd6f28c43c9bf3f78e52038d1b4.setIcon(icon_a0f19ea01e3543889d3865de516d0e91);
            
    
            var popup_637948457ff14887a080357f089550d3 = L.popup({maxWidth: '300'});

            
                var html_e8b4ed4239a845a2ae31cda4234f37da = $('<div id="html_e8b4ed4239a845a2ae31cda4234f37da" style="width: 100.0%; height: 100.0%;">Domino&#39;s Pizza, 14, Ground Floor, Cinema Site, IP Mallvaranasi, Shastri Nagar, Sigra, Chetganj, Varanasi</div>')[0];
                popup_637948457ff14887a080357f089550d3.setContent(html_e8b4ed4239a845a2ae31cda4234f37da);
            

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            var marker_ca55ffb6056a405f8f078648b93e6cd4 = L.marker(
                [25.3376,82.9796],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_5309627c29ed4ecface976a4e5a6b78e);
            
    

                var icon_b508fdeec6ab4ab187d32919be817949 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'red',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_ca55ffb6056a405f8f078648b93e6cd4.setIcon(icon_b508fdeec6ab4ab187d32919be817949);
            
    
            var popup_8e73318881f84476ae2247dabd4f2f86 = L.popup({maxWidth: '300'});

            
                var html_1717c7f727e847c59186dcc844076674 = $('<div id="html_1717c7f727e847c59186dcc844076674" style="width: 100.0%; height: 100.0%;">Ocean - The Rivatas, Rivatas, The Mall Road, Cantonment, Nadesar, Varanasi</div>')[0];
                popup_8e73318881f84476ae2247dabd4f2f86.setContent(html_1717c7f727e847c59186dcc844076674);
            

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            var marker_a780021771ec4968b2b75997ac81ac62 = L.marker(
                [25.3032,83.0075],
                {
                    icon: new L.Icon.Default()
                    }
                )
                .addTo(map_5309627c29ed4ecface976a4e5a6b78e);
            
    

                var icon_29052cf957c541b38ebc5687fc37cb32 = L.AwesomeMarkers.icon({
                    icon: 'info-sign',
                    iconColor: 'white',
                    markerColor: 'orange',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_a780021771ec4968b2b75997ac81ac62.setIcon(icon_29052cf957c541b38ebc5687fc37cb32);
            
    
            var popup_d412bf71f0554bd386d42ee538543a2b = L.popup({maxWidth: '300'});

            
                var html_7061522a9fc946e1828c264629e7e751 = $('<div id="html_7061522a9fc946e1828c264629e7e751" style="width: 100.0%; height: 100.0%;">Brown Bread Bakery, D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat, Varanasi</div>')[0];
                popup_d412bf71f0554bd386d42ee538543a2b.setContent(html_7061522a9fc946e1828c264629e7e751);
            

            marker_a780021771ec4968b2b75997ac81ac62.bindPopup(popup_d412bf71f0554bd386d42ee538543a2b);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f3d86d96c18>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color_map = {'1.0': 'green', '2.0': 'darkgreen', '3.0': 'orange', '4.0': 'red'}\n",
    "\n",
    "varanasi_map = folium.Map(location = [VRS_LATITUDE, VRS_LONGITUDE], zoom_start = 13)\n",
    "\n",
    "for name, address, latitude, longitude, price_range in zip(selected_venues['venue'], \n",
    "                                                           selected_venues['address'], \n",
    "                                                           selected_venues['latitude'], \n",
    "                                                           selected_venues['longitude'], \n",
    "                                                           selected_venues['price_range'].astype(str)):\n",
    "    label = '{}, {}'.format(name, address)\n",
    "    label = folium.Popup(label, parse_html = True)\n",
    "    folium.Marker(\n",
    "        [latitude, longitude],\n",
    "        icon = folium.Icon(color = color_map[price_range]),\n",
    "        popup = label).add_to(varanasi_map)  \n",
    "varanasi_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> As shown in map \"Ocean - The Rivatas, Rivatas, The Mall Road, Cantonment, Nadesar, Varanasi\" is very costly.\n",
    "\n",
    "> As shown in map \"Kashi Chat Bhandar, D-37/49, Godaulia, Varanasi\" is least expensive."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Clustering\n",
    "We will now cluster all these venues based on their price range, location and more to identify similar venues and the relationship amongst them. We'll cluster the venues into two separate groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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",
       "    }\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>cluster_labels</th>\n",
       "      <th>categories</th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "      <th>average_price</th>\n",
       "      <th>rating_bin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>25.3094</td>\n",
       "      <td>83.0059</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>D-37/49, Godaulia, Varanasi</td>\n",
       "      <td>75.0</td>\n",
       "      <td>Very good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Sol Bar - Hotel Surya</td>\n",
       "      <td>25.3387</td>\n",
       "      <td>82.9799</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "      <td>750.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Very good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Open Hand Shop &amp; Cafe</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...</td>\n",
       "      <td>225.0</td>\n",
       "      <td>Very good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161</td>\n",
       "      <td>82.9856</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "      <td>200.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Ocean - The Rivatas</td>\n",
       "      <td>25.3376</td>\n",
       "      <td>82.9796</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Rivatas, The Mall Road, Cantonment, Nadesar, V...</td>\n",
       "      <td>900.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3032</td>\n",
       "      <td>83.0075</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "      <td>250.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cluster_labels         categories                  venue  latitude  \\\n",
       "0               0  Indian Restaurant     Kashi Chat Bhandar   25.3094   \n",
       "1               1              Hotel  Sol Bar - Hotel Surya   25.3387   \n",
       "2               0        Pizza Place  Pizzeria Vaatika Cafe   25.2894   \n",
       "3               0        Coffee Shop  Open Hand Shop & Cafe   25.2880   \n",
       "4               0        Pizza Place         Domino's Pizza   25.3161   \n",
       "5               1              Hotel    Ocean - The Rivatas   25.3376   \n",
       "6               0               Café     Brown Bread Bakery   25.3032   \n",
       "\n",
       "   longitude  price_range  rating  \\\n",
       "0    83.0059          1.0     4.7   \n",
       "1    82.9799          4.0     3.6   \n",
       "2    83.0061          3.0     4.2   \n",
       "3    83.0045          2.0     4.2   \n",
       "4    82.9856          2.0     3.9   \n",
       "5    82.9796          4.0     3.6   \n",
       "6    83.0075          3.0     3.2   \n",
       "\n",
       "                                             address  average_price rating_bin  \n",
       "0                        D-37/49, Godaulia, Varanasi           75.0  Very good  \n",
       "1  Hotel Surya, 20/51, A-5, The Mall Road, Varuna...          750.0       Good  \n",
       "2                              B 1/178 Assi Varanasi          350.0  Very good  \n",
       "3  B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...          225.0  Very good  \n",
       "4  14, Ground Floor, Cinema Site, IP Mallvaranasi...          200.0       Good  \n",
       "5  Rivatas, The Mall Road, Cantonment, Nadesar, V...          900.0       Good  \n",
       "6  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...          250.0       Good  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "NO_OF_CLUSTERS = 2\n",
    "\n",
    "clustering = selected_venues.drop(['venue', 'address', 'rating_bin', 'categories'], 1)\n",
    "kMeans = KMeans(n_clusters = NO_OF_CLUSTERS, random_state = 0).fit(clustering)\n",
    "selected_venues.insert(0, 'cluster_labels', kMeans.labels_)\n",
    "selected_venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
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            circle_marker_812e5ef8cbe244c6ae466d558f8f10bb.bindPopup(popup_0d71724b68a1457e861ef88463b46122);

            
        
    
            var circle_marker_7cdfe501c3bd4dca97f2c75aa6811457 = L.circleMarker(
                [25.33815,82.97975],
                {
  "bubblingMouseEvents": true,
  "color": "red",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "red",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 10,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_6fdcc55f65e54fe999b6c76111973c2f);
            
    
            var popup_66aa1ec2997d4561a5848eac2d6e001a = L.popup({maxWidth: '300'});

            
                var html_6a9852faae00432d8a5253a7c28c41ca = $('<div id="html_6a9852faae00432d8a5253a7c28c41ca" style="width: 100.0%; height: 100.0%;">Cluster: 1</div>')[0];
                popup_66aa1ec2997d4561a5848eac2d6e001a.setContent(html_6a9852faae00432d8a5253a7c28c41ca);
            

            circle_marker_7cdfe501c3bd4dca97f2c75aa6811457.bindPopup(popup_66aa1ec2997d4561a5848eac2d6e001a);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f3d845494e0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "varanasi_map = folium.Map(location = [VRS_LATITUDE, VRS_LONGITUDE], zoom_start = 13)\n",
    "color_map = { 0: 'green', 1: 'red'}\n",
    "\n",
    "# add venues to the map\n",
    "markers_colors = []\n",
    "for venue, address, cluster, latitude, longitude in zip(selected_venues['venue'], \n",
    "                                                        selected_venues['address'], \n",
    "                                                        selected_venues['cluster_labels'], \n",
    "                                                        selected_venues['latitude'], \n",
    "                                                        selected_venues['longitude']):\n",
    "    label = folium.Popup(str(venue) + ', ' + str(address), parse_html = True)\n",
    "    folium.CircleMarker(\n",
    "        [float(latitude), float(longitude)],\n",
    "        radius = 5,\n",
    "        popup = label,\n",
    "        color = color_map[cluster],\n",
    "        fill = True,\n",
    "        fill_color = color_map[cluster],\n",
    "        fill_opacity = 0.7).add_to(varanasi_map)\n",
    "\n",
    "# add cluster centers to the map\n",
    "for index, cluster in enumerate(kMeans.cluster_centers_):\n",
    "    latitude = cluster[0]\n",
    "    longitude = cluster[1]\n",
    "    label = folium.Popup(\"Cluster: \" + str(index), parse_html = True)\n",
    "    folium.CircleMarker(\n",
    "        [float(latitude), float(longitude)],\n",
    "        radius = 10,\n",
    "        popup = label,\n",
    "        color = color_map[index],\n",
    "        fill = True,\n",
    "        fill_color = color_map[index],\n",
    "        fill_opacity = 0.7).add_to(varanasi_map)\n",
    "\n",
    "varanasi_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Here is 2 clusters on is in Red colour.\n",
    "\n",
    "> Other Clusters in Green Colour."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'll also check the venues of the two clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster 0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cluster_labels</th>\n",
       "      <th>categories</th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "      <th>average_price</th>\n",
       "      <th>rating_bin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Kashi Chat Bhandar</td>\n",
       "      <td>25.3094</td>\n",
       "      <td>83.0059</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>D-37/49, Godaulia, Varanasi</td>\n",
       "      <td>75.0</td>\n",
       "      <td>Very good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Pizzeria Vaatika Cafe</td>\n",
       "      <td>25.2894</td>\n",
       "      <td>83.0061</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B 1/178 Assi Varanasi</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Very good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Open Hand Shop &amp; Cafe</td>\n",
       "      <td>25.2880</td>\n",
       "      <td>83.0045</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...</td>\n",
       "      <td>225.0</td>\n",
       "      <td>Very good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Domino's Pizza</td>\n",
       "      <td>25.3161</td>\n",
       "      <td>82.9856</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14, Ground Floor, Cinema Site, IP Mallvaranasi...</td>\n",
       "      <td>200.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Brown Bread Bakery</td>\n",
       "      <td>25.3032</td>\n",
       "      <td>83.0075</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...</td>\n",
       "      <td>250.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cluster_labels         categories                  venue  latitude  \\\n",
       "0               0  Indian Restaurant     Kashi Chat Bhandar   25.3094   \n",
       "1               0        Pizza Place  Pizzeria Vaatika Cafe   25.2894   \n",
       "2               0        Coffee Shop  Open Hand Shop & Cafe   25.2880   \n",
       "3               0        Pizza Place         Domino's Pizza   25.3161   \n",
       "4               0               Café     Brown Bread Bakery   25.3032   \n",
       "\n",
       "   longitude  price_range  rating  \\\n",
       "0    83.0059          1.0     4.7   \n",
       "1    83.0061          3.0     4.2   \n",
       "2    83.0045          2.0     4.2   \n",
       "3    82.9856          2.0     3.9   \n",
       "4    83.0075          3.0     3.2   \n",
       "\n",
       "                                             address  average_price rating_bin  \n",
       "0                        D-37/49, Godaulia, Varanasi           75.0  Very good  \n",
       "1                              B 1/178 Assi Varanasi          350.0  Very good  \n",
       "2  B1/128-3, Dumraun Bagh Colony, Assi Ghat, Vara...          225.0  Very good  \n",
       "3  14, Ground Floor, Cinema Site, IP Mallvaranasi...          200.0       Good  \n",
       "4  D 25/42 Ganga Mahal, Bangali Tola, Pandey Ghat...          250.0       Good  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = selected_venues[selected_venues['cluster_labels'] == 0]\n",
    "print(\"Cluster 0\")\n",
    "result.head(10).reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These venues for cluster 0 have mean price range of 2.20 and rating spread around 4.04\n"
     ]
    }
   ],
   "source": [
    "print(\"These venues for cluster 0 have mean price range of {:.02f} and rating spread around {:.02f}\".\n",
    "      format(result['price_range'].mean(), result['rating'].astype(float).mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clusters 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster 1\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cluster_labels</th>\n",
       "      <th>categories</th>\n",
       "      <th>venue</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>price_range</th>\n",
       "      <th>rating</th>\n",
       "      <th>address</th>\n",
       "      <th>average_price</th>\n",
       "      <th>rating_bin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Sol Bar - Hotel Surya</td>\n",
       "      <td>25.3387</td>\n",
       "      <td>82.9799</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Hotel Surya, 20/51, A-5, The Mall Road, Varuna...</td>\n",
       "      <td>750.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Ocean - The Rivatas</td>\n",
       "      <td>25.3376</td>\n",
       "      <td>82.9796</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Rivatas, The Mall Road, Cantonment, Nadesar, V...</td>\n",
       "      <td>900.0</td>\n",
       "      <td>Good</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cluster_labels categories                  venue  latitude  longitude  \\\n",
       "0               1      Hotel  Sol Bar - Hotel Surya   25.3387    82.9799   \n",
       "1               1      Hotel    Ocean - The Rivatas   25.3376    82.9796   \n",
       "\n",
       "   price_range  rating                                            address  \\\n",
       "0          4.0     3.6  Hotel Surya, 20/51, A-5, The Mall Road, Varuna...   \n",
       "1          4.0     3.6  Rivatas, The Mall Road, Cantonment, Nadesar, V...   \n",
       "\n",
       "   average_price rating_bin  \n",
       "0          750.0       Good  \n",
       "1          900.0       Good  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = selected_venues[selected_venues['cluster_labels'] == 1]\n",
    "print(\"Cluster 1\")\n",
    "result.head(10).reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These venues for cluster 1 have mean price range of 4.00 and rating spread around 3.60\n"
     ]
    }
   ],
   "source": [
    "print(\"These venues for cluster 1 have mean price range of {:.02f} and rating spread around {:.02f}\".\n",
    "      format(result['price_range'].mean(), result['rating'].astype(float).mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result and Discussion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on our analysis above, we can draw a number of conclusions that will be useful to aid any visitor visiting the city of varanasi, India.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After collecting data from the Foursquare and Zomato APIs, we got a list of 41 different venues. However, not all venues from the two APIs were identical. Hence, we had to inspect their latitude and longitude values as well as names to combine them and remove all the outliers. This resulted in a total venue count of 16."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We identified that from the total set of venues, majority of them were Hotel and Pizza Places."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, through clusters we identified that there are many venues which are relatively lower priced but have an average rating of 3.57. On the other hand, there are few venues which are high priced and have average rating of 4.0."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A company can use this information to build up an online website/mobile application, to provide users with up to date information about various venues in the city based on the search criteria (name, rating and price)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The purpose of this project was to explore the places that a person visiting to varanasi . The venues have been identified using Foursquare and Zomato API and have been plotted on the map. The map reveals that there are so many places where one can visit during his stay in varanasi. Based on the visitor's venue rating and price requirements, he/she can choose the places."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
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