Zomato.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "79c99c1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0ff173e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "zmt = pd.read_csv(r\"C:\\Users\\User\\Documents\\Pradeep documents\\Internship\\Zomato\\zomato.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fe8c7702",
   "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>url</th>\n",
       "      <th>address</th>\n",
       "      <th>name</th>\n",
       "      <th>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>phone</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>dish_liked</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>approx_cost(for two people)</th>\n",
       "      <th>reviews_list</th>\n",
       "      <th>menu_item</th>\n",
       "      <th>listed_in(type)</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://www.zomato.com/bangalore/jalsa-banasha...</td>\n",
       "      <td>942, 21st Main Road, 2nd Stage, Banashankari, ...</td>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>775</td>\n",
       "      <td>080 42297555\\r\\n+91 9743772233</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Pasta, Lunch Buffet, Masala Papad, Paneer Laja...</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  A beautiful place to ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.zomato.com/bangalore/spice-elephan...</td>\n",
       "      <td>2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...</td>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>787</td>\n",
       "      <td>080 41714161</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Momos, Lunch Buffet, Chocolate Nirvana, Thai G...</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Had been here for din...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.zomato.com/SanchurroBangalore?cont...</td>\n",
       "      <td>1112, Next to KIMS Medical College, 17th Cross...</td>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>918</td>\n",
       "      <td>+91 9663487993</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Churros, Cannelloni, Minestrone Soup, Hot Choc...</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>[('Rated 3.0', \"RATED\\n  Ambience is not that ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.zomato.com/bangalore/addhuri-udupi...</td>\n",
       "      <td>1st Floor, Annakuteera, 3rd Stage, Banashankar...</td>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7/5</td>\n",
       "      <td>88</td>\n",
       "      <td>+91 9620009302</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>Masala Dosa</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>[('Rated 4.0', \"RATED\\n  Great food and proper...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://www.zomato.com/bangalore/grand-village...</td>\n",
       "      <td>10, 3rd Floor, Lakshmi Associates, Gandhi Baza...</td>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>166</td>\n",
       "      <td>+91 8026612447\\r\\n+91 9901210005</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Panipuri, Gol Gappe</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Very good restaurant ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51712</th>\n",
       "      <td>https://www.zomato.com/bangalore/best-brews-fo...</td>\n",
       "      <td>Four Points by Sheraton Bengaluru, 43/3, White...</td>\n",
       "      <td>Best Brews - Four Points by Sheraton Bengaluru...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.6 /5</td>\n",
       "      <td>27</td>\n",
       "      <td>080 40301477</td>\n",
       "      <td>Whitefield</td>\n",
       "      <td>Bar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Continental</td>\n",
       "      <td>1,500</td>\n",
       "      <td>[('Rated 5.0', \"RATED\\n  Food and service are ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Pubs and bars</td>\n",
       "      <td>Whitefield</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51713</th>\n",
       "      <td>https://www.zomato.com/bangalore/vinod-bar-and...</td>\n",
       "      <td>Number 10, Garudachar Palya, Mahadevapura, Whi...</td>\n",
       "      <td>Vinod Bar And Restaurant</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>+91 8197675843</td>\n",
       "      <td>Whitefield</td>\n",
       "      <td>Bar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Finger Food</td>\n",
       "      <td>600</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>Pubs and bars</td>\n",
       "      <td>Whitefield</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51714</th>\n",
       "      <td>https://www.zomato.com/bangalore/plunge-sherat...</td>\n",
       "      <td>Sheraton Grand Bengaluru Whitefield Hotel &amp; Co...</td>\n",
       "      <td>Plunge - Sheraton Grand Bengaluru Whitefield H...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Whitefield</td>\n",
       "      <td>Bar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Finger Food</td>\n",
       "      <td>2,000</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>Pubs and bars</td>\n",
       "      <td>Whitefield</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51715</th>\n",
       "      <td>https://www.zomato.com/bangalore/chime-sherato...</td>\n",
       "      <td>Sheraton Grand Bengaluru Whitefield Hotel &amp; Co...</td>\n",
       "      <td>Chime - Sheraton Grand Bengaluru Whitefield Ho...</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.3 /5</td>\n",
       "      <td>236</td>\n",
       "      <td>080 49652769</td>\n",
       "      <td>ITPL Main Road, Whitefield</td>\n",
       "      <td>Bar</td>\n",
       "      <td>Cocktails, Pizza, Buttermilk</td>\n",
       "      <td>Finger Food</td>\n",
       "      <td>2,500</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Nice and friendly pla...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Pubs and bars</td>\n",
       "      <td>Whitefield</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51716</th>\n",
       "      <td>https://www.zomato.com/bangalore/the-nest-the-...</td>\n",
       "      <td>ITPL Main Road, KIADB Export Promotion Industr...</td>\n",
       "      <td>The Nest - The Den Bengaluru</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.4 /5</td>\n",
       "      <td>13</td>\n",
       "      <td>+91 8071117272</td>\n",
       "      <td>ITPL Main Road, Whitefield</td>\n",
       "      <td>Bar, Casual Dining</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Finger Food, North Indian, Continental</td>\n",
       "      <td>1,500</td>\n",
       "      <td>[('Rated 5.0', 'RATED\\n  Great ambience , look...</td>\n",
       "      <td>[]</td>\n",
       "      <td>Pubs and bars</td>\n",
       "      <td>Whitefield</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>51717 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     url  \\\n",
       "0      https://www.zomato.com/bangalore/jalsa-banasha...   \n",
       "1      https://www.zomato.com/bangalore/spice-elephan...   \n",
       "2      https://www.zomato.com/SanchurroBangalore?cont...   \n",
       "3      https://www.zomato.com/bangalore/addhuri-udupi...   \n",
       "4      https://www.zomato.com/bangalore/grand-village...   \n",
       "...                                                  ...   \n",
       "51712  https://www.zomato.com/bangalore/best-brews-fo...   \n",
       "51713  https://www.zomato.com/bangalore/vinod-bar-and...   \n",
       "51714  https://www.zomato.com/bangalore/plunge-sherat...   \n",
       "51715  https://www.zomato.com/bangalore/chime-sherato...   \n",
       "51716  https://www.zomato.com/bangalore/the-nest-the-...   \n",
       "\n",
       "                                                 address  \\\n",
       "0      942, 21st Main Road, 2nd Stage, Banashankari, ...   \n",
       "1      2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...   \n",
       "2      1112, Next to KIMS Medical College, 17th Cross...   \n",
       "3      1st Floor, Annakuteera, 3rd Stage, Banashankar...   \n",
       "4      10, 3rd Floor, Lakshmi Associates, Gandhi Baza...   \n",
       "...                                                  ...   \n",
       "51712  Four Points by Sheraton Bengaluru, 43/3, White...   \n",
       "51713  Number 10, Garudachar Palya, Mahadevapura, Whi...   \n",
       "51714  Sheraton Grand Bengaluru Whitefield Hotel & Co...   \n",
       "51715  Sheraton Grand Bengaluru Whitefield Hotel & Co...   \n",
       "51716  ITPL Main Road, KIADB Export Promotion Industr...   \n",
       "\n",
       "                                                    name online_order  \\\n",
       "0                                                  Jalsa          Yes   \n",
       "1                                         Spice Elephant          Yes   \n",
       "2                                        San Churro Cafe          Yes   \n",
       "3                                  Addhuri Udupi Bhojana           No   \n",
       "4                                          Grand Village           No   \n",
       "...                                                  ...          ...   \n",
       "51712  Best Brews - Four Points by Sheraton Bengaluru...           No   \n",
       "51713                           Vinod Bar And Restaurant           No   \n",
       "51714  Plunge - Sheraton Grand Bengaluru Whitefield H...           No   \n",
       "51715  Chime - Sheraton Grand Bengaluru Whitefield Ho...           No   \n",
       "51716                       The Nest - The Den Bengaluru           No   \n",
       "\n",
       "      book_table    rate  votes                             phone  \\\n",
       "0            Yes   4.1/5    775    080 42297555\\r\\n+91 9743772233   \n",
       "1             No   4.1/5    787                      080 41714161   \n",
       "2             No   3.8/5    918                    +91 9663487993   \n",
       "3             No   3.7/5     88                    +91 9620009302   \n",
       "4             No   3.8/5    166  +91 8026612447\\r\\n+91 9901210005   \n",
       "...          ...     ...    ...                               ...   \n",
       "51712         No  3.6 /5     27                      080 40301477   \n",
       "51713         No     NaN      0                    +91 8197675843   \n",
       "51714         No     NaN      0                               NaN   \n",
       "51715        Yes  4.3 /5    236                      080 49652769   \n",
       "51716         No  3.4 /5     13                    +91 8071117272   \n",
       "\n",
       "                         location            rest_type  \\\n",
       "0                    Banashankari        Casual Dining   \n",
       "1                    Banashankari        Casual Dining   \n",
       "2                    Banashankari  Cafe, Casual Dining   \n",
       "3                    Banashankari          Quick Bites   \n",
       "4                    Basavanagudi        Casual Dining   \n",
       "...                           ...                  ...   \n",
       "51712                  Whitefield                  Bar   \n",
       "51713                  Whitefield                  Bar   \n",
       "51714                  Whitefield                  Bar   \n",
       "51715  ITPL Main Road, Whitefield                  Bar   \n",
       "51716  ITPL Main Road, Whitefield   Bar, Casual Dining   \n",
       "\n",
       "                                              dish_liked  \\\n",
       "0      Pasta, Lunch Buffet, Masala Papad, Paneer Laja...   \n",
       "1      Momos, Lunch Buffet, Chocolate Nirvana, Thai G...   \n",
       "2      Churros, Cannelloni, Minestrone Soup, Hot Choc...   \n",
       "3                                            Masala Dosa   \n",
       "4                                    Panipuri, Gol Gappe   \n",
       "...                                                  ...   \n",
       "51712                                                NaN   \n",
       "51713                                                NaN   \n",
       "51714                                                NaN   \n",
       "51715                       Cocktails, Pizza, Buttermilk   \n",
       "51716                                                NaN   \n",
       "\n",
       "                                     cuisines approx_cost(for two people)  \\\n",
       "0              North Indian, Mughlai, Chinese                         800   \n",
       "1                 Chinese, North Indian, Thai                         800   \n",
       "2                      Cafe, Mexican, Italian                         800   \n",
       "3                  South Indian, North Indian                         300   \n",
       "4                    North Indian, Rajasthani                         600   \n",
       "...                                       ...                         ...   \n",
       "51712                             Continental                       1,500   \n",
       "51713                             Finger Food                         600   \n",
       "51714                             Finger Food                       2,000   \n",
       "51715                             Finger Food                       2,500   \n",
       "51716  Finger Food, North Indian, Continental                       1,500   \n",
       "\n",
       "                                            reviews_list menu_item  \\\n",
       "0      [('Rated 4.0', 'RATED\\n  A beautiful place to ...        []   \n",
       "1      [('Rated 4.0', 'RATED\\n  Had been here for din...        []   \n",
       "2      [('Rated 3.0', \"RATED\\n  Ambience is not that ...        []   \n",
       "3      [('Rated 4.0', \"RATED\\n  Great food and proper...        []   \n",
       "4      [('Rated 4.0', 'RATED\\n  Very good restaurant ...        []   \n",
       "...                                                  ...       ...   \n",
       "51712  [('Rated 5.0', \"RATED\\n  Food and service are ...        []   \n",
       "51713                                                 []        []   \n",
       "51714                                                 []        []   \n",
       "51715  [('Rated 4.0', 'RATED\\n  Nice and friendly pla...        []   \n",
       "51716  [('Rated 5.0', 'RATED\\n  Great ambience , look...        []   \n",
       "\n",
       "      listed_in(type) listed_in(city)  \n",
       "0              Buffet    Banashankari  \n",
       "1              Buffet    Banashankari  \n",
       "2              Buffet    Banashankari  \n",
       "3              Buffet    Banashankari  \n",
       "4              Buffet    Banashankari  \n",
       "...               ...             ...  \n",
       "51712   Pubs and bars      Whitefield  \n",
       "51713   Pubs and bars      Whitefield  \n",
       "51714   Pubs and bars      Whitefield  \n",
       "51715   Pubs and bars      Whitefield  \n",
       "51716   Pubs and bars      Whitefield  \n",
       "\n",
       "[51717 rows x 17 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6fd7baab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 51717 entries, 0 to 51716\n",
      "Data columns (total 17 columns):\n",
      " #   Column                       Non-Null Count  Dtype \n",
      "---  ------                       --------------  ----- \n",
      " 0   url                          51717 non-null  object\n",
      " 1   address                      51717 non-null  object\n",
      " 2   name                         51717 non-null  object\n",
      " 3   online_order                 51717 non-null  object\n",
      " 4   book_table                   51717 non-null  object\n",
      " 5   rate                         43942 non-null  object\n",
      " 6   votes                        51717 non-null  int64 \n",
      " 7   phone                        50509 non-null  object\n",
      " 8   location                     51696 non-null  object\n",
      " 9   rest_type                    51490 non-null  object\n",
      " 10  dish_liked                   23639 non-null  object\n",
      " 11  cuisines                     51672 non-null  object\n",
      " 12  approx_cost(for two people)  51371 non-null  object\n",
      " 13  reviews_list                 51717 non-null  object\n",
      " 14  menu_item                    51717 non-null  object\n",
      " 15  listed_in(type)              51717 non-null  object\n",
      " 16  listed_in(city)              51717 non-null  object\n",
      "dtypes: int64(1), object(16)\n",
      "memory usage: 6.7+ MB\n"
     ]
    }
   ],
   "source": [
    "zmt.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6a16f67e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(51717, 17)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d515555c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['url', 'address', 'name', 'online_order', 'book_table', 'rate', 'votes',\n",
       "       'phone', 'location', 'rest_type', 'dish_liked', 'cuisines',\n",
       "       'approx_cost(for two people)', 'reviews_list', 'menu_item',\n",
       "       'listed_in(type)', 'listed_in(city)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "422377c0",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>approx_cost(for two people)</th>\n",
       "      <th>listed_in(type)</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1/5</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7/5</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8/5</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table   rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes  4.1/5    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No  4.1/5    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No  3.8/5    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No  3.7/5     88  Banashankari   \n",
       "4          Grand Village           No         No  3.8/5    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines  \\\n",
       "0        Casual Dining  North Indian, Mughlai, Chinese   \n",
       "1        Casual Dining     Chinese, North Indian, Thai   \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian   \n",
       "3          Quick Bites      South Indian, North Indian   \n",
       "4        Casual Dining        North Indian, Rajasthani   \n",
       "\n",
       "  approx_cost(for two people) listed_in(type) listed_in(city)  \n",
       "0                         800          Buffet    Banashankari  \n",
       "1                         800          Buffet    Banashankari  \n",
       "2                         800          Buffet    Banashankari  \n",
       "3                         300          Buffet    Banashankari  \n",
       "4                         600          Buffet    Banashankari  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt = zmt.drop([\"url\",\"address\",\"phone\",\"dish_liked\",\"menu_item\",\"reviews_list\"],axis=1)\n",
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "952ecc33",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 51717 entries, 0 to 51716\n",
      "Data columns (total 11 columns):\n",
      " #   Column                       Non-Null Count  Dtype \n",
      "---  ------                       --------------  ----- \n",
      " 0   name                         51717 non-null  object\n",
      " 1   online_order                 51717 non-null  object\n",
      " 2   book_table                   51717 non-null  object\n",
      " 3   rate                         43942 non-null  object\n",
      " 4   votes                        51717 non-null  int64 \n",
      " 5   location                     51696 non-null  object\n",
      " 6   rest_type                    51490 non-null  object\n",
      " 7   cuisines                     51672 non-null  object\n",
      " 8   approx_cost(for two people)  51371 non-null  object\n",
      " 9   listed_in(type)              51717 non-null  object\n",
      " 10  listed_in(city)              51717 non-null  object\n",
      "dtypes: int64(1), object(10)\n",
      "memory usage: 4.3+ MB\n"
     ]
    }
   ],
   "source": [
    "zmt.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6adc7e30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(51609, 11)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dropping duplicates\n",
    "zmt.drop_duplicates(inplace=True)\n",
    "zmt.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ea329caf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['4.1/5', '3.8/5', '3.7/5', '3.6/5', '4.6/5', '4.0/5', '4.2/5',\n",
       "       '3.9/5', '3.1/5', '3.0/5', '3.2/5', '3.3/5', '2.8/5', '4.4/5',\n",
       "       '4.3/5', 'NEW', '2.9/5', '3.5/5', nan, '2.6/5', '3.8 /5', '3.4/5',\n",
       "       '4.5/5', '2.5/5', '2.7/5', '4.7/5', '2.4/5', '2.2/5', '2.3/5',\n",
       "       '3.4 /5', '-', '3.6 /5', '4.8/5', '3.9 /5', '4.2 /5', '4.0 /5',\n",
       "       '4.1 /5', '3.7 /5', '3.1 /5', '2.9 /5', '3.3 /5', '2.8 /5',\n",
       "       '3.5 /5', '2.7 /5', '2.5 /5', '3.2 /5', '2.6 /5', '4.5 /5',\n",
       "       '4.3 /5', '4.4 /5', '4.9/5', '2.1/5', '2.0/5', '1.8/5', '4.6 /5',\n",
       "       '4.9 /5', '3.0 /5', '4.8 /5', '2.3 /5', '4.7 /5', '2.4 /5',\n",
       "       '2.1 /5', '2.2 /5', '2.0 /5', '1.8 /5'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cleaning rate column\n",
    "zmt[\"rate\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c976ab8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4.1\n",
       "1    4.1\n",
       "2    3.8\n",
       "3    3.7\n",
       "4    3.8\n",
       "Name: rate, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def handlerate(value):\n",
    "    if(value==\"NEW\" or value==\"-\"):\n",
    "        return np.nan\n",
    "    else:\n",
    "        value = str(value).split(\"/\")\n",
    "        value = value[0]\n",
    "        return float(value)\n",
    "    \n",
    "zmt[\"rate\"] = zmt[\"rate\"].apply(handlerate)\n",
    "zmt[\"rate\"].head()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "df2efc11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10019"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.rate.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5e9098fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "zmt[\"rate\"].fillna(zmt[\"rate\"].mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9d1b6067",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.rate.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ba981230",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51609 entries, 0 to 51716\n",
      "Data columns (total 11 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   name                         51609 non-null  object \n",
      " 1   online_order                 51609 non-null  object \n",
      " 2   book_table                   51609 non-null  object \n",
      " 3   rate                         51609 non-null  float64\n",
      " 4   votes                        51609 non-null  int64  \n",
      " 5   location                     51588 non-null  object \n",
      " 6   rest_type                    51382 non-null  object \n",
      " 7   cuisines                     51564 non-null  object \n",
      " 8   approx_cost(for two people)  51265 non-null  object \n",
      " 9   listed_in(type)              51609 non-null  object \n",
      " 10  listed_in(city)              51609 non-null  object \n",
      "dtypes: float64(1), int64(1), object(9)\n",
      "memory usage: 4.7+ MB\n"
     ]
    }
   ],
   "source": [
    "zmt.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b56683d3",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>approx_cost(for two people)</th>\n",
       "      <th>listed_in(type)</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines  \\\n",
       "0        Casual Dining  North Indian, Mughlai, Chinese   \n",
       "1        Casual Dining     Chinese, North Indian, Thai   \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian   \n",
       "3          Quick Bites      South Indian, North Indian   \n",
       "4        Casual Dining        North Indian, Rajasthani   \n",
       "\n",
       "  approx_cost(for two people) listed_in(type) listed_in(city)  \n",
       "0                         800          Buffet    Banashankari  \n",
       "1                         800          Buffet    Banashankari  \n",
       "2                         800          Buffet    Banashankari  \n",
       "3                         300          Buffet    Banashankari  \n",
       "4                         600          Buffet    Banashankari  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dropping null values\n",
    "\n",
    "zmt.dropna(inplace=True)\n",
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "11f3078d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51042 entries, 0 to 51716\n",
      "Data columns (total 11 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   name                         51042 non-null  object \n",
      " 1   online_order                 51042 non-null  object \n",
      " 2   book_table                   51042 non-null  object \n",
      " 3   rate                         51042 non-null  float64\n",
      " 4   votes                        51042 non-null  int64  \n",
      " 5   location                     51042 non-null  object \n",
      " 6   rest_type                    51042 non-null  object \n",
      " 7   cuisines                     51042 non-null  object \n",
      " 8   approx_cost(for two people)  51042 non-null  object \n",
      " 9   listed_in(type)              51042 non-null  object \n",
      " 10  listed_in(city)              51042 non-null  object \n",
      "dtypes: float64(1), int64(1), object(9)\n",
      "memory usage: 4.7+ MB\n"
     ]
    }
   ],
   "source": [
    "zmt.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b6f943d4",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "      <th>listed_in(city)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines Cost2plates    Type  \\\n",
       "0        Casual Dining  North Indian, Mughlai, Chinese         800  Buffet   \n",
       "1        Casual Dining     Chinese, North Indian, Thai         800  Buffet   \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian         800  Buffet   \n",
       "3          Quick Bites      South Indian, North Indian         300  Buffet   \n",
       "4        Casual Dining        North Indian, Rajasthani         600  Buffet   \n",
       "\n",
       "  listed_in(city)  \n",
       "0    Banashankari  \n",
       "1    Banashankari  \n",
       "2    Banashankari  \n",
       "3    Banashankari  \n",
       "4    Banashankari  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renaming columns\n",
    "\n",
    "zmt.rename(columns={\"approx_cost(for two people)\":\"Cost2plates\",\"listed_in(type)\":\"Type\"}, inplace=True)\n",
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a6e60a7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Banashankari', 'Basavanagudi', 'Mysore Road', 'Jayanagar',\n",
       "       'Kumaraswamy Layout', 'Rajarajeshwari Nagar', 'Vijay Nagar',\n",
       "       'Uttarahalli', 'JP Nagar', 'South Bangalore', 'City Market',\n",
       "       'Nagarbhavi', 'Bannerghatta Road', 'BTM', 'Kanakapura Road',\n",
       "       'Bommanahalli', 'CV Raman Nagar', 'Electronic City', 'HSR',\n",
       "       'Marathahalli', 'Wilson Garden', 'Shanti Nagar',\n",
       "       'Koramangala 5th Block', 'Koramangala 8th Block', 'Richmond Road',\n",
       "       'Koramangala 7th Block', 'Jalahalli', 'Koramangala 4th Block',\n",
       "       'Bellandur', 'Sarjapur Road', 'Whitefield', 'East Bangalore',\n",
       "       'Old Airport Road', 'Indiranagar', 'Koramangala 1st Block',\n",
       "       'Frazer Town', 'RT Nagar', 'MG Road', 'Brigade Road',\n",
       "       'Lavelle Road', 'Church Street', 'Ulsoor', 'Residency Road',\n",
       "       'Shivajinagar', 'Infantry Road', 'St. Marks Road',\n",
       "       'Cunningham Road', 'Race Course Road', 'Commercial Street',\n",
       "       'Vasanth Nagar', 'HBR Layout', 'Domlur', 'Ejipura',\n",
       "       'Jeevan Bhima Nagar', 'Old Madras Road', 'Malleshwaram',\n",
       "       'Seshadripuram', 'Kammanahalli', 'Koramangala 6th Block',\n",
       "       'Majestic', 'Langford Town', 'Central Bangalore', 'Sanjay Nagar',\n",
       "       'Brookefield', 'ITPL Main Road, Whitefield',\n",
       "       'Varthur Main Road, Whitefield', 'KR Puram',\n",
       "       'Koramangala 2nd Block', 'Koramangala 3rd Block', 'Koramangala',\n",
       "       'Hosur Road', 'Rajajinagar', 'Banaswadi', 'North Bangalore',\n",
       "       'Nagawara', 'Hennur', 'Kalyan Nagar', 'New BEL Road', 'Jakkur',\n",
       "       'Rammurthy Nagar', 'Thippasandra', 'Kaggadasapura', 'Hebbal',\n",
       "       'Kengeri', 'Sankey Road', 'Sadashiv Nagar', 'Basaveshwara Nagar',\n",
       "       'Yeshwantpur', 'West Bangalore', 'Magadi Road', 'Yelahanka',\n",
       "       'Sahakara Nagar', 'Peenya'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt[\"location\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2681115b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Banashankari', 'Bannerghatta Road', 'Basavanagudi', 'Bellandur',\n",
       "       'Brigade Road', 'Brookefield', 'BTM', 'Church Street',\n",
       "       'Electronic City', 'Frazer Town', 'HSR', 'Indiranagar',\n",
       "       'Jayanagar', 'JP Nagar', 'Kalyan Nagar', 'Kammanahalli',\n",
       "       'Koramangala 4th Block', 'Koramangala 5th Block',\n",
       "       'Koramangala 6th Block', 'Koramangala 7th Block', 'Lavelle Road',\n",
       "       'Malleshwaram', 'Marathahalli', 'MG Road', 'New BEL Road',\n",
       "       'Old Airport Road', 'Rajajinagar', 'Residency Road',\n",
       "       'Sarjapur Road', 'Whitefield'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt[\"listed_in(city)\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98df105e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# keeping only one location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c3b1bc1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "zmt = zmt.drop([\"listed_in(city)\"],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "971fb74e",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines Cost2plates    Type  \n",
       "0        Casual Dining  North Indian, Mughlai, Chinese         800  Buffet  \n",
       "1        Casual Dining     Chinese, North Indian, Thai         800  Buffet  \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian         800  Buffet  \n",
       "3          Quick Bites      South Indian, North Indian         300  Buffet  \n",
       "4        Casual Dining        North Indian, Rajasthani         600  Buffet  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b47ac0ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['800', '300', '600', '700', '550', '500', '450', '650', '400',\n",
       "       '900', '200', '750', '150', '850', '100', '1,200', '350', '250',\n",
       "       '950', '1,000', '1,500', '1,300', '199', '80', '1,100', '160',\n",
       "       '1,600', '230', '130', '50', '190', '1,700', '1,400', '180',\n",
       "       '1,350', '2,200', '2,000', '1,800', '1,900', '330', '2,500',\n",
       "       '2,100', '3,000', '2,800', '3,400', '40', '1,250', '3,500',\n",
       "       '4,000', '2,400', '2,600', '120', '1,450', '469', '70', '3,200',\n",
       "       '60', '560', '240', '360', '6,000', '1,050', '2,300', '4,100',\n",
       "       '5,000', '3,700', '1,650', '2,700', '4,500', '140'], dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt[\"Cost2plates\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a7d83280",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 800.,  300.,  600.,  700.,  550.,  500.,  450.,  650.,  400.,\n",
       "        900.,  200.,  750.,  150.,  850.,  100., 1200.,  350.,  250.,\n",
       "        950., 1000., 1500., 1300.,  199.,   80., 1100.,  160., 1600.,\n",
       "        230.,  130.,   50.,  190., 1700., 1400.,  180., 1350., 2200.,\n",
       "       2000., 1800., 1900.,  330., 2500., 2100., 3000., 2800., 3400.,\n",
       "         40., 1250., 3500., 4000., 2400., 2600.,  120., 1450.,  469.,\n",
       "         70., 3200.,   60.,  560.,  240.,  360., 6000., 1050., 2300.,\n",
       "       4100., 5000., 3700., 1650., 2700., 4500.,  140.])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# removing ',' from Cost2plates column\n",
    "\n",
    "def handlecomma(value):\n",
    "    value = str(value)\n",
    "    if ',' in value:\n",
    "        value = value.replace(',','')\n",
    "        return float(value)\n",
    "    else:\n",
    "        return float(value)\n",
    "    \n",
    "zmt['Cost2plates'] = zmt['Cost2plates'].apply(handlecomma)\n",
    "zmt['Cost2plates'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ab64350f",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Cafe, Casual Dining</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "             rest_type                        cuisines  Cost2plates    Type  \n",
       "0        Casual Dining  North Indian, Mughlai, Chinese        800.0  Buffet  \n",
       "1        Casual Dining     Chinese, North Indian, Thai        800.0  Buffet  \n",
       "2  Cafe, Casual Dining          Cafe, Mexican, Italian        800.0  Buffet  \n",
       "3          Quick Bites      South Indian, North Indian        300.0  Buffet  \n",
       "4        Casual Dining        North Indian, Rajasthani        600.0  Buffet  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "68eb88a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Quick Bites                   19010\n",
       "Casual Dining                 10253\n",
       "Cafe                           3682\n",
       "Delivery                       2574\n",
       "Dessert Parlor                 2242\n",
       "                              ...  \n",
       "Dessert Parlor, Kiosk             2\n",
       "Food Court, Beverage Shop         2\n",
       "Dessert Parlor, Food Court        2\n",
       "Quick Bites, Kiosk                1\n",
       "Sweet Shop, Dessert Parlor        1\n",
       "Name: rest_type, Length: 93, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cleaning rest_type column\n",
    "\n",
    "zmt[\"rest_type\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e9460bcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Quick Bites                   19010\n",
       "Casual Dining                 10253\n",
       "Cafe                           3682\n",
       "Delivery                       2574\n",
       "Dessert Parlor                 2242\n",
       "                              ...  \n",
       "Dessert Parlor, Kiosk             2\n",
       "Food Court, Beverage Shop         2\n",
       "Dessert Parlor, Food Court        2\n",
       "Quick Bites, Kiosk                1\n",
       "Sweet Shop, Dessert Parlor        1\n",
       "Name: rest_type, Length: 93, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rest_type = zmt[\"rest_type\"].value_counts(ascending = False)\n",
    "rest_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6232c22b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Beverage Shop                 863\n",
       "Bar                           686\n",
       "Food Court                    616\n",
       "Sweet Shop                    468\n",
       "Bar, Casual Dining            411\n",
       "                             ... \n",
       "Dessert Parlor, Kiosk           2\n",
       "Food Court, Beverage Shop       2\n",
       "Dessert Parlor, Food Court      2\n",
       "Quick Bites, Kiosk              1\n",
       "Sweet Shop, Dessert Parlor      1\n",
       "Name: rest_type, Length: 85, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rest_type_lessthan1000 = rest_type[rest_type<1000]\n",
    "rest_type_lessthan1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8a08f489",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Quick Bites           19010\n",
       "Casual Dining         10253\n",
       "others                 9003\n",
       "Cafe                   3682\n",
       "Delivery               2574\n",
       "Dessert Parlor         2242\n",
       "Takeaway, Delivery     2008\n",
       "Bakery                 1140\n",
       "Casual Dining, Bar     1130\n",
       "Name: rest_type, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replacing lessthan 1000 to others\n",
    "\n",
    "def handle_rest_type(value):\n",
    "    if value in rest_type_lessthan1000:\n",
    "        return 'others'\n",
    "    else:\n",
    "        return value\n",
    "    \n",
    "zmt['rest_type'] = zmt['rest_type'].apply(handle_rest_type)\n",
    "zmt['rest_type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fbfa3547",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>others</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "       rest_type                        cuisines  Cost2plates    Type  \n",
       "0  Casual Dining  North Indian, Mughlai, Chinese        800.0  Buffet  \n",
       "1  Casual Dining     Chinese, North Indian, Thai        800.0  Buffet  \n",
       "2         others          Cafe, Mexican, Italian        800.0  Buffet  \n",
       "3    Quick Bites      South Indian, North Indian        300.0  Buffet  \n",
       "4  Casual Dining        North Indian, Rajasthani        600.0  Buffet  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1adf6613",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BTM                      5056\n",
       "HSR                      2494\n",
       "Koramangala 5th Block    2479\n",
       "JP Nagar                 2218\n",
       "Whitefield               2105\n",
       "                         ... \n",
       "West Bangalore              6\n",
       "Yelahanka                   5\n",
       "Jakkur                      3\n",
       "Rajarajeshwari Nagar        2\n",
       "Peenya                      1\n",
       "Name: location, Length: 93, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cleaning location column\n",
    "\n",
    "zmt['location'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "38fe6451",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BTM                      5056\n",
       "HSR                      2494\n",
       "Koramangala 5th Block    2479\n",
       "JP Nagar                 2218\n",
       "Whitefield               2105\n",
       "                         ... \n",
       "West Bangalore              6\n",
       "Yelahanka                   5\n",
       "Jakkur                      3\n",
       "Rajarajeshwari Nagar        2\n",
       "Peenya                      1\n",
       "Name: location, Length: 93, dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "location = zmt[\"location\"].value_counts(ascending = False)\n",
    "location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4ff0f383",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Koramangala 8th Block            294\n",
       "Vasanth Nagar                    293\n",
       "Jeevan Bhima Nagar               268\n",
       "Wilson Garden                    246\n",
       "Bommanahalli                     236\n",
       "Koramangala 3rd Block            215\n",
       "Thippasandra                     191\n",
       "Kumaraswamy Layout               191\n",
       "Nagawara                         187\n",
       "Basaveshwara Nagar               187\n",
       "Seshadripuram                    165\n",
       "Hennur                           159\n",
       "Majestic                         155\n",
       "HBR Layout                       153\n",
       "Infantry Road                    150\n",
       "Race Course Road                 139\n",
       "City Market                      122\n",
       "Yeshwantpur                      119\n",
       "ITPL Main Road, Whitefield       113\n",
       "Varthur Main Road, Whitefield    109\n",
       "South Bangalore                  107\n",
       "Koramangala 2nd Block            102\n",
       "Kaggadasapura                    101\n",
       "Hosur Road                        98\n",
       "CV Raman Nagar                    89\n",
       "Vijay Nagar                       78\n",
       "RT Nagar                          78\n",
       "Sanjay Nagar                      76\n",
       "Sadashiv Nagar                    63\n",
       "Sahakara Nagar                    53\n",
       "Koramangala                       48\n",
       "East Bangalore                    43\n",
       "Jalahalli                         38\n",
       "Magadi Road                       34\n",
       "Rammurthy Nagar                   32\n",
       "Langford Town                     27\n",
       "Sankey Road                       27\n",
       "Old Madras Road                   22\n",
       "Mysore Road                       22\n",
       "Kanakapura Road                   19\n",
       "KR Puram                          18\n",
       "Uttarahalli                       17\n",
       "Hebbal                            14\n",
       "North Bangalore                   14\n",
       "Nagarbhavi                         9\n",
       "Kengeri                            8\n",
       "Central Bangalore                  8\n",
       "West Bangalore                     6\n",
       "Yelahanka                          5\n",
       "Jakkur                             3\n",
       "Rajarajeshwari Nagar               2\n",
       "Peenya                             1\n",
       "Name: location, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "location_lessthan300 = location[location<300]\n",
    "location_lessthan300"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "a5247d7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BTM                      5056\n",
       "others                   4954\n",
       "HSR                      2494\n",
       "Koramangala 5th Block    2479\n",
       "JP Nagar                 2218\n",
       "Whitefield               2105\n",
       "Indiranagar              2026\n",
       "Jayanagar                1916\n",
       "Marathahalli             1805\n",
       "Bannerghatta Road        1609\n",
       "Bellandur                1268\n",
       "Electronic City          1246\n",
       "Koramangala 1st Block    1236\n",
       "Brigade Road             1210\n",
       "Koramangala 7th Block    1174\n",
       "Koramangala 6th Block    1127\n",
       "Sarjapur Road            1047\n",
       "Koramangala 4th Block    1017\n",
       "Ulsoor                   1011\n",
       "Banashankari              902\n",
       "MG Road                   893\n",
       "Kalyan Nagar              841\n",
       "Richmond Road             803\n",
       "Malleshwaram              721\n",
       "Frazer Town               714\n",
       "Basavanagudi              684\n",
       "Residency Road            671\n",
       "Brookefield               656\n",
       "New BEL Road              644\n",
       "Banaswadi                 640\n",
       "Kammanahalli              639\n",
       "Rajajinagar               591\n",
       "Church Street             566\n",
       "Lavelle Road              518\n",
       "Shanti Nagar              508\n",
       "Shivajinagar              498\n",
       "Cunningham Road           490\n",
       "Domlur                    482\n",
       "Old Airport Road          437\n",
       "Ejipura                   433\n",
       "Commercial Street         370\n",
       "St. Marks Road            343\n",
       "Name: location, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replacing lessthan 300 location to others\n",
    "\n",
    "def handle_location(value):\n",
    "    if value in location_lessthan300:\n",
    "        return 'others'\n",
    "    else:\n",
    "        return value\n",
    "    \n",
    "zmt['location'] = zmt['location'].apply(handle_location)\n",
    "zmt['location'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f402a4cd",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Chinese, North Indian, Thai</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>others</td>\n",
       "      <td>Cafe, Mexican, Italian</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "       rest_type                        cuisines  Cost2plates    Type  \n",
       "0  Casual Dining  North Indian, Mughlai, Chinese        800.0  Buffet  \n",
       "1  Casual Dining     Chinese, North Indian, Thai        800.0  Buffet  \n",
       "2         others          Cafe, Mexican, Italian        800.0  Buffet  \n",
       "3    Quick Bites      South Indian, North Indian        300.0  Buffet  \n",
       "4  Casual Dining        North Indian, Rajasthani        600.0  Buffet  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "6d8a9d0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "North Indian                                2852\n",
       "North Indian, Chinese                       2351\n",
       "South Indian                                1820\n",
       "Biryani                                      903\n",
       "Bakery, Desserts                             898\n",
       "                                            ... \n",
       "North Indian, Chinese, Oriya, Mithai           1\n",
       "Beverages, Burger                              1\n",
       "North Indian, Mughlai, Lucknowi                1\n",
       "Continental, Thai, North Indian, Chinese       1\n",
       "North Indian, Chinese, Arabian, Momos          1\n",
       "Name: cuisines, Length: 2704, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt['cuisines'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "d120ca53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "North Indian                                2852\n",
       "North Indian, Chinese                       2351\n",
       "South Indian                                1820\n",
       "Biryani                                      903\n",
       "Bakery, Desserts                             898\n",
       "                                            ... \n",
       "North Indian, Chinese, Oriya, Mithai           1\n",
       "Beverages, Burger                              1\n",
       "North Indian, Mughlai, Lucknowi                1\n",
       "Continental, Thai, North Indian, Chinese       1\n",
       "North Indian, Chinese, Arabian, Momos          1\n",
       "Name: cuisines, Length: 2704, dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cuisiens = zmt['cuisines'].value_counts(ascending=False)\n",
    "cuisiens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "750e027d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "North Indian, Continental, Chinese          97\n",
       "Juices                                      94\n",
       "Fast Food, North Indian                     93\n",
       "Bengali, North Indian                       93\n",
       "Beverages, Juices                           90\n",
       "                                            ..\n",
       "North Indian, Chinese, Oriya, Mithai         1\n",
       "Beverages, Burger                            1\n",
       "North Indian, Mughlai, Lucknowi              1\n",
       "Continental, Thai, North Indian, Chinese     1\n",
       "North Indian, Chinese, Arabian, Momos        1\n",
       "Name: cuisines, Length: 2635, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cuisiens_lessthan100 = cuisiens[cuisiens<100]\n",
    "cuisiens_lessthan100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "5c35b228",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "others                                 26159\n",
       "North Indian                            2852\n",
       "North Indian, Chinese                   2351\n",
       "South Indian                            1820\n",
       "Biryani                                  903\n",
       "                                       ...  \n",
       "South Indian, Chinese, North Indian      105\n",
       "North Indian, Mughlai, Chinese           104\n",
       "South Indian, Fast Food                  104\n",
       "Italian, Pizza                           102\n",
       "North Indian, Chinese, Seafood           102\n",
       "Name: cuisines, Length: 70, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replacing lessthan100 cuisiens to others\n",
    "\n",
    "def handle_cuisiens(value):\n",
    "    if value in cuisiens_lessthan100:\n",
    "        return 'others'\n",
    "    else:\n",
    "        return value\n",
    "    \n",
    "zmt['cuisines'] = zmt['cuisines'].apply(handle_cuisiens)\n",
    "zmt['cuisines'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "249265cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['North Indian, Mughlai, Chinese', 'Chinese, North Indian, Thai',\n",
       "       'Cafe, Mexican, Italian', ...,\n",
       "       'North Indian, Street Food, Biryani', 'Chinese, Mughlai',\n",
       "       'North Indian, Chinese, Arabian, Momos'], dtype=object)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt['cuisines'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "cb4016a3",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>rate</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>Cost2plates</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jalsa</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>North Indian, Mughlai, Chinese</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>others</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>others</td>\n",
       "      <td>others</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Grand Village</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>others</td>\n",
       "      <td>600.0</td>\n",
       "      <td>Buffet</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name online_order book_table  rate  votes      location  \\\n",
       "0                  Jalsa          Yes        Yes   4.1    775  Banashankari   \n",
       "1         Spice Elephant          Yes         No   4.1    787  Banashankari   \n",
       "2        San Churro Cafe          Yes         No   3.8    918  Banashankari   \n",
       "3  Addhuri Udupi Bhojana           No         No   3.7     88  Banashankari   \n",
       "4          Grand Village           No         No   3.8    166  Basavanagudi   \n",
       "\n",
       "       rest_type                        cuisines  Cost2plates    Type  \n",
       "0  Casual Dining  North Indian, Mughlai, Chinese        800.0  Buffet  \n",
       "1  Casual Dining                          others        800.0  Buffet  \n",
       "2         others                          others        800.0  Buffet  \n",
       "3    Quick Bites      South Indian, North Indian        300.0  Buffet  \n",
       "4  Casual Dining                          others        600.0  Buffet  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "3173505b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Delivery              25579\n",
       "Dine-out              17562\n",
       "Desserts               3559\n",
       "Cafes                  1703\n",
       "Drinks & nightlife     1084\n",
       "Buffet                  869\n",
       "Pubs and bars           686\n",
       "Name: Type, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zmt['Type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b1b85998",
   "metadata": {},
   "outputs": [],
   "source": [
    "zmt.to_excel(\"zomato_1.xlsx\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0014e321",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2be7d67c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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