Zomato_ratings_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2677673a",
   "metadata": {},
   "source": [
    "## ABSTRACT\n",
    "Zomato is one of the best online food delivery apps which gives the users the ratings and the reviews on restaurants all over india.These ratings and the Reviews are considered as one of the most important deciding factors which determine how good a restaurant is.\n",
    "\n",
    "We will therefore use the real time Data set with variuos features a user would look into regarding a restaurant. We will be considering Banglore City in this analysis.\n",
    "\n",
    "Content The basic idea of analyzing the Zomato dataset is to get a fair idea about the factors affecting the establishment of different types of restaurant at different places in Bengaluru, aggregate rating of each restaurant, Bengaluru being one such city has more than 12,000 restaurants with restaurants serving dishes from all over the world.\n",
    "\n",
    "With each day new restaurants opening the industry has’nt been saturated yet and the demand is increasing day by day. Inspite of increasing demand it however has become difficult for new restaurants to compete with established restaurants. Most of them serving the same food. Bengaluru being an IT capital of India. Most of the people here are dependent mainly on the restaurant food as they don’t have time to cook for themselves.\n",
    "\n",
    "With such an overwhelming demand of restaurants it has therefore become important to study the demography of a location. What kind of a food is more popular in a locality. Do the entire locality loves vegetarian food. If yes then is that locality populated by a particular sect of people for eg. Jain, Marwaris, Gujaratis who are mostly vegetarian. These kind of analysis can be done using the data, by studying the factors such as\n",
    "\n",
    "• Location of the restaurant\n",
    "• Approx Price of food\n",
    "• Theme based restaurant or not\n",
    "• Which locality of that city serves that cuisines with maximum number of restaurants\n",
    "• The needs of people who are striving to get the best cuisine of the neighborhood\n",
    "• Is a particular neighborhood famous for its own kind of food.\n",
    "\n",
    "“Just so that you have a good meal the next time you step out”\n",
    "\n",
    "The data is accurate to that available on the zomato website until 15 March 2019. The data was scraped from Zomato in two phase. After going through the structure of the website I found that for each neighborhood there are 6-7 category of restaurants viz. Buffet, Cafes, Delivery, Desserts, Dine-out, Drinks & nightlife, Pubs and bars.\n",
    "\n",
    "Phase I,\n",
    "\n",
    "In Phase I of extraction only the URL, name and address of the restaurant were extracted which were visible on the front page. The URl's for each of the restaurants on the zomato were recorded in the csv file so that later the data can be extracted individually for each restaurant. This made the extraction process easier and reduced the extra load on my machine. The data for each neighborhood and each category can be found here\n",
    "\n",
    "Phase II,\n",
    "\n",
    "In Phase II the recorded data for each restaurant and each category was read and data for each restaurant was scraped individually. 15 variables were scraped in this phase. For each of the neighborhood and for each category their onlineorder, booktable, rate, votes, phone, location, resttype, dishliked, cuisines, approxcost(for two people), reviewslist, menu_item was extracted. See section 5 for more details about the variables.\n",
    "\n",
    "Acknowledgements The data scraped was entirely for educational purposes only. Note that I don’t claim any copyright for the data. All copyrights for the data is owned by Zomato Media Pvt. Ltd..\n",
    "\n",
    "        Source: Kaggle\n",
    "Main Objective:\n",
    "\n",
    "The main agenda of this project is:\n",
    "\n",
    "Perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset.\n",
    "\n",
    "Build an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features\n",
    "\n",
    "DEPLOY the Machine learning model via Flask that can be used to make live predictions of restaurants ratings\n",
    "\n",
    "A step by step guide is attached to this documnet as well as a video explanation of each concpet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6b3a7811",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the neceessary dependencies\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.graph_objs as go\n",
    "import plotly.offline as py\n",
    "import seaborn as sns\n",
    "\n",
    "import matplotlib.ticker as mtick\n",
    "plt.style.use('fivethirtyeight')\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import  ExtraTreesRegressor\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "361ef03d",
   "metadata": {},
   "source": [
    "#Load Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "85bae5f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset shape: (51717, 17)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "  </tbody>\n",
       "</table>\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",
       "                                             address                   name  \\\n",
       "0  942, 21st Main Road, 2nd Stage, Banashankari, ...                  Jalsa   \n",
       "1  2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...         Spice Elephant   \n",
       "2  1112, Next to KIMS Medical College, 17th Cross...        San Churro Cafe   \n",
       "3  1st Floor, Annakuteera, 3rd Stage, Banashankar...  Addhuri Udupi Bhojana   \n",
       "4  10, 3rd Floor, Lakshmi Associates, Gandhi Baza...          Grand Village   \n",
       "\n",
       "  online_order book_table   rate  votes                             phone  \\\n",
       "0          Yes        Yes  4.1/5    775    080 42297555\\r\\n+91 9743772233   \n",
       "1          Yes         No  4.1/5    787                      080 41714161   \n",
       "2          Yes         No  3.8/5    918                    +91 9663487993   \n",
       "3           No         No  3.7/5     88                    +91 9620009302   \n",
       "4           No         No  3.8/5    166  +91 8026612447\\r\\n+91 9901210005   \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",
       "                                          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",
       "                         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",
       "                                        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",
       "  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  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the dataset\n",
    "df = pd.read_csv(r\"C:\\Users\\Admin\\Dropbox\\Zomato_rating_prediction\\Copy of zomato.csv\")\n",
    "print(f'Dataset shape: {df.shape}')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96bf14e4",
   "metadata": {},
   "source": [
    "## Columns description\n",
    "1. url  </B>:  contains the url of the restaurant in the zomato website\n",
    "\n",
    "2. address :  contains the address of the restaurant in Bengaluru\n",
    "\n",
    "3. name : contains the name of the restaurant\n",
    "\n",
    "4. online_order : whether online ordering is available in the restaurant or not\n",
    "\n",
    "5. book_table : table book option available or not\n",
    "\n",
    "6. rate : contains the overall rating of the restaurant out of 5\n",
    "\n",
    "7. votes : contains total number of rating for the restaurant as of the above mentioned date\n",
    "\n",
    "8. phone : contains the phone number of the restaurant\n",
    "\n",
    "9. location : contains the neighborhood in which the restaurant is located\n",
    "\n",
    "10. rest_type : restaurant type\n",
    "\n",
    "11. dish_liked : dishes people liked in the restaurant\n",
    "\n",
    "12. cuisines : food styles, separated by comma\n",
    "\n",
    "13. approx_cost(for two people) : contains the approximate cost of meal for two people\n",
    "\n",
    "14. reviews_list : list of tuples containing reviews for the restaurant, each tuple\n",
    "\n",
    "15. menu_item : contains list of menus available in the restaurant\n",
    "\n",
    "16. listed_in(type) : type of meal\n",
    "\n",
    "17. listed_in(city) : contains the neighborhood in which the restaurant is listed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b9e374a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "url                            object\n",
       "address                        object\n",
       "name                           object\n",
       "online_order                   object\n",
       "book_table                     object\n",
       "rate                           object\n",
       "votes                           int64\n",
       "phone                          object\n",
       "location                       object\n",
       "rest_type                      object\n",
       "dish_liked                     object\n",
       "cuisines                       object\n",
       "approx_cost(for two people)    object\n",
       "reviews_list                   object\n",
       "menu_item                      object\n",
       "listed_in(type)                object\n",
       "listed_in(city)                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c21a2d1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "url                                0\n",
       "address                            0\n",
       "name                               0\n",
       "online_order                       0\n",
       "book_table                         0\n",
       "rate                            7775\n",
       "votes                              0\n",
       "phone                           1208\n",
       "location                          21\n",
       "rest_type                        227\n",
       "dish_liked                     28078\n",
       "cuisines                          45\n",
       "approx_cost(for two people)      346\n",
       "reviews_list                       0\n",
       "menu_item                          0\n",
       "listed_in(type)                    0\n",
       "listed_in(city)                    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking null values\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "168d8657",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Deleting Unnnecessary Columns\n",
    "df=df.drop(['url','phone'],axis=1) #Dropping the column like \"phone\" and \"url\" and saving the new dataset as \"df\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "31b48451",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "43"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for Duplicate values\n",
    "df.duplicated().sum() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "41ccac8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "69a15bf5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "address                        0\n",
       "name                           0\n",
       "online_order                   0\n",
       "book_table                     0\n",
       "rate                           0\n",
       "votes                          0\n",
       "location                       0\n",
       "rest_type                      0\n",
       "dish_liked                     0\n",
       "cuisines                       0\n",
       "approx_cost(for two people)    0\n",
       "reviews_list                   0\n",
       "menu_item                      0\n",
       "listed_in(type)                0\n",
       "listed_in(city)                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Remove the NaN values from the dataset\n",
    "df.dropna(how='any',inplace=True)\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93d5f824",
   "metadata": {},
   "source": [
    "Renaming columes appropriately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8757f19d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['address', 'name', 'online_order', 'book_table', 'rate', 'votes',\n",
       "       '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": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "2b23cfa8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['address', 'name', 'online_order', 'book_table', 'rate', 'votes',\n",
       "       'location', 'rest_type', 'dish_liked', 'cuisines', 'cost',\n",
       "       'reviews_list', 'menu_item', 'type', 'city'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.rename(columns={'approx_cost(for two people)':'cost','listed_in(type)':'type',\n",
    "                                  'listed_in(city)':'city'})\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "fcd49c52",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>dish_liked</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>cost</th>\n",
       "      <th>reviews_list</th>\n",
       "      <th>menu_item</th>\n",
       "      <th>type</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>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>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>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>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>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>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>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>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>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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             address                   name  \\\n",
       "0  942, 21st Main Road, 2nd Stage, Banashankari, ...                  Jalsa   \n",
       "1  2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...         Spice Elephant   \n",
       "2  1112, Next to KIMS Medical College, 17th Cross...        San Churro Cafe   \n",
       "3  1st Floor, Annakuteera, 3rd Stage, Banashankar...  Addhuri Udupi Bhojana   \n",
       "4  10, 3rd Floor, Lakshmi Associates, Gandhi Baza...          Grand Village   \n",
       "\n",
       "  online_order book_table   rate  votes      location            rest_type  \\\n",
       "0          Yes        Yes  4.1/5    775  Banashankari        Casual Dining   \n",
       "1          Yes         No  4.1/5    787  Banashankari        Casual Dining   \n",
       "2          Yes         No  3.8/5    918  Banashankari  Cafe, Casual Dining   \n",
       "3           No         No  3.7/5     88  Banashankari          Quick Bites   \n",
       "4           No         No  3.8/5    166  Basavanagudi        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",
       "                         cuisines cost  \\\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",
       "                                        reviews_list menu_item    type  \\\n",
       "0  [('Rated 4.0', 'RATED\\n  A beautiful place to ...        []  Buffet   \n",
       "1  [('Rated 4.0', 'RATED\\n  Had been here for din...        []  Buffet   \n",
       "2  [('Rated 3.0', \"RATED\\n  Ambience is not that ...        []  Buffet   \n",
       "3  [('Rated 4.0', \"RATED\\n  Great food and proper...        []  Buffet   \n",
       "4  [('Rated 4.0', 'RATED\\n  Very good restaurant ...        []  Buffet   \n",
       "\n",
       "           city  \n",
       "0  Banashankari  \n",
       "1  Banashankari  \n",
       "2  Banashankari  \n",
       "3  Banashankari  \n",
       "4  Banashankari  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57d0e962",
   "metadata": {},
   "source": [
    "## Cleaning the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "dd8563ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['800', '300', '600', '700', '550', '500', '450', '650', '400',\n",
       "       '750', '200', '850', '1,200', '150', '350', '250', '1,500',\n",
       "       '1,300', '1,000', '100', '900', '1,100', '1,600', '950', '230',\n",
       "       '1,700', '1,400', '1,350', '2,200', '2,000', '1,800', '1,900',\n",
       "       '180', '330', '2,500', '2,100', '3,000', '2,800', '3,400', '40',\n",
       "       '1,250', '3,500', '4,000', '2,400', '1,450', '3,200', '6,000',\n",
       "       '1,050', '4,100', '2,300', '120', '2,600', '5,000', '3,700',\n",
       "       '1,650', '2,700', '4,500'], dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['cost'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95c4ffaf",
   "metadata": {},
   "source": [
    "### replacing the \",\" with nothing and converting the results to float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "2ed5feb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['cost'] = df['cost'].apply(lambda x: x.replace(',','')) #Using lambda function to replace ',' from cost\n",
    "df['cost'] = df['cost'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1b9abfa6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 800.  300.  600.  700.  550.  500.  450.  650.  400.  750.  200.  850.\n",
      " 1200.  150.  350.  250. 1500. 1300. 1000.  100.  900. 1100. 1600.  950.\n",
      "  230. 1700. 1400. 1350. 2200. 2000. 1800. 1900.  180.  330. 2500. 2100.\n",
      " 3000. 2800. 3400.   40. 1250. 3500. 4000. 2400. 1450. 3200. 6000. 1050.\n",
      " 4100. 2300.  120. 2600. 5000. 3700. 1650. 2700. 4500.]\n",
      "------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "address          object\n",
       "name             object\n",
       "online_order     object\n",
       "book_table       object\n",
       "rate             object\n",
       "votes             int64\n",
       "location         object\n",
       "rest_type        object\n",
       "dish_liked       object\n",
       "cuisines         object\n",
       "cost            float64\n",
       "reviews_list     object\n",
       "menu_item        object\n",
       "type             object\n",
       "city             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df['cost'].unique())\n",
    "\n",
    "print('---'*10)\n",
    "\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "81013652",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['4.1/5', '3.8/5', '3.7/5', '4.6/5', '4.0/5', '4.2/5', '3.9/5',\n",
       "       '3.0/5', '3.6/5', '2.8/5', '4.4/5', '3.1/5', '4.3/5', '2.6/5',\n",
       "       '3.3/5', '3.5/5', '3.8 /5', '3.2/5', '4.5/5', '2.5/5', '2.9/5',\n",
       "       '3.4/5', '2.7/5', '4.7/5', 'NEW', '2.4/5', '2.2/5', '2.3/5',\n",
       "       '4.8/5', '3.9 /5', '4.2 /5', '4.0 /5', '4.1 /5', '2.9 /5',\n",
       "       '2.7 /5', '2.5 /5', '2.6 /5', '4.5 /5', '4.3 /5', '3.7 /5',\n",
       "       '4.4 /5', '4.9/5', '2.1/5', '2.0/5', '1.8/5', '3.4 /5', '3.6 /5',\n",
       "       '3.3 /5', '4.6 /5', '4.9 /5', '3.2 /5', '3.0 /5', '2.8 /5',\n",
       "       '3.5 /5', '3.1 /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": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Reading uninque values from the Rate column\n",
    "df['rate'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "b0e6e7a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.loc[df.rate !='NEW'] #getting rid of \"NEW\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "1e90b192",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['4.1/5', '3.8/5', '3.7/5', '4.6/5', '4.0/5', '4.2/5', '3.9/5',\n",
       "       '3.0/5', '3.6/5', '2.8/5', '4.4/5', '3.1/5', '4.3/5', '2.6/5',\n",
       "       '3.3/5', '3.5/5', '3.8 /5', '3.2/5', '4.5/5', '2.5/5', '2.9/5',\n",
       "       '3.4/5', '2.7/5', '4.7/5', '2.4/5', '2.2/5', '2.3/5', '4.8/5',\n",
       "       '3.9 /5', '4.2 /5', '4.0 /5', '4.1 /5', '2.9 /5', '2.7 /5',\n",
       "       '2.5 /5', '2.6 /5', '4.5 /5', '4.3 /5', '3.7 /5', '4.4 /5',\n",
       "       '4.9/5', '2.1/5', '2.0/5', '1.8/5', '3.4 /5', '3.6 /5', '3.3 /5',\n",
       "       '4.6 /5', '4.9 /5', '3.2 /5', '3.0 /5', '2.8 /5', '3.5 /5',\n",
       "       '3.1 /5', '4.8 /5', '2.3 /5', '4.7 /5', '2.4 /5', '2.1 /5',\n",
       "       '2.2 /5', '2.0 /5', '1.8 /5'], dtype=object)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rate'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9b2b5e09",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Removing '/5' from Rates\n",
    "\n",
    "df['rate'] = df['rate'].apply(lambda x: x.replace('/5',''))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50af7691",
   "metadata": {},
   "source": [
    "## Visualisations\n",
    "Most famous restaurants chains in Bangaluru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "4089f978",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(17,10))\n",
    "chains=df['name'].value_counts()[:20]\n",
    "sns.barplot(x=chains,y=chains.index,palette='deep')\n",
    "plt.title(\"Most famous restaurants chains in Bangaluru\")\n",
    "plt.xlabel(\"Number of outlets\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e67882f",
   "metadata": {},
   "source": [
    "Whether restaurant offer Table booking or not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "784eec1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "labels": [
          "No",
          "Yes"
         ],
         "marker": {
          "colors": [
           "#F70000",
           "#119326"
          ],
          "line": {
           "color": "#001000",
           "width": 2
          }
         },
         "textinfo": "value",
         "type": "pie",
         "values": [
          17191,
          6057
         ]
        }
       ],
       "layout": {
        "height": 600,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
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           "showlakes": true,
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          "hoverlabel": {
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          "hovermode": "closest",
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           "style": "light"
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           "bgcolor": "#E5ECF6",
           "radialaxis": {
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          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
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           "yaxis": {
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            "gridwidth": 2,
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            "gridwidth": 2,
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            "showbackground": true,
            "ticks": "",
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          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
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          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
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         }
        },
        "title": {
         "text": "Table booking"
        },
        "width": 600
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=df['book_table'].value_counts()\n",
    "colors = ['#F70000', '#119326']\n",
    "\n",
    "trace=go.Pie(labels=x.index,values=x,textinfo=\"value\",\n",
    "            marker=dict(colors=colors, \n",
    "                           line=dict(color='#001000', width=2)))\n",
    "layout=go.Layout(title=\"Table booking\",width=600,height=600)\n",
    "fig=go.Figure(data=[trace],layout=layout)\n",
    "py.iplot(fig, filename='pie_chart_subplots')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47d9be58",
   "metadata": {},
   "source": [
    "### Insight\n",
    "\n",
    "Most of the Restaurants do not offer table booking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75a0c326",
   "metadata": {},
   "source": [
    "Whether Restaurants deliver online or Not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "f74677cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Restaurants delivering Online or not\n",
    "sns.countplot(df['online_order'])\n",
    "fig = plt.gcf()\n",
    "fig.set_size_inches(10,10)\n",
    "plt.title('Whether Restaurants deliver online or Not')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63249b0f",
   "metadata": {},
   "source": [
    "### Insight:\n",
    "\n",
    "Most Restaurants offer option for online order and delivery"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fbee10b",
   "metadata": {},
   "source": [
    "### Rating Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b5952fb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='rate', ylabel='Density'>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#How ratings are distributed\n",
    "plt.figure(figsize=(9,7))\n",
    "\n",
    "sns.distplot(df['rate'],bins=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62a23d36",
   "metadata": {},
   "source": [
    "### Insight\n",
    "\n",
    "We can infer from above that most of the ratings are within 3.5 and 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "df62aff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# #Distribution of the cost Vs ratings in parallel with online order\n",
    "plt.figure(figsize=(10,7))\n",
    "sns.scatterplot(x=\"rate\",y='cost',hue='online_order',data=df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa7665ee",
   "metadata": {},
   "source": [
    "### Count of ratings as between \"1 and 2\", \"2 and 3\", \"3 and 4\", and \"4 and 5\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['4.1', '3.8', '3.7', '4.6', '4.0', '4.2', '3.9', '3.0', '3.6',\n",
       "       '2.8', '4.4', '3.1', '4.3', '2.6', '3.3', '3.5', '3.8 ', '3.2',\n",
       "       '4.5', '2.5', '2.9', '3.4', '2.7', '4.7', '2.4', '2.2', '2.3',\n",
       "       '4.8', '3.9 ', '4.2 ', '4.0 ', '4.1 ', '2.9 ', '2.7 ', '2.5 ',\n",
       "       '2.6 ', '4.5 ', '4.3 ', '3.7 ', '4.4 ', '4.9', '2.1', '2.0', '1.8',\n",
       "       '3.4 ', '3.6 ', '3.3 ', '4.6 ', '4.9 ', '3.2 ', '3.0 ', '2.8 ',\n",
       "       '3.5 ', '3.1 ', '4.8 ', '2.3 ', '4.7 ', '2.4 ', '2.1 ', '2.2 ',\n",
       "       '2.0 ', '1.8 '], dtype=object)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rate'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "00a38ed5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.8'"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rate'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "f665ffc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'4.9 '"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rate'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "0706d426",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['rate']=df['rate'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df['rate']>=1) & (df['rate']<2)).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "8ce24e38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1179"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df['rate']>=2) & (df['rate']<3)).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "44ea3b2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10153"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df['rate']>=3) & (df['rate']<4)).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "7b70b97d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11911"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df['rate']>=4).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f26a2404",
   "metadata": {},
   "source": [
    "#### Plotting the counts with the help of pie chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "2aef199f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slices=[((df['rate']>=1) & (df['rate']<2)).sum(),\n",
    "        ((df['rate']>=2) & (df['rate']<3)).sum(),\n",
    "        ((df['rate']>=3) & (df['rate']<4)).sum(),\n",
    "        (df['rate']>=4).sum()\n",
    "        ]\n",
    "\n",
    "labels=['1<rate<2','2<rate<3','3<rate<4','>4']\n",
    "colors = ['#119326','#F70000','#F7F732']\n",
    "plt.pie(slices,colors=colors, labels=labels, autopct='%1.0f%%', pctdistance=.5, labeldistance=1.2,shadow=True)\n",
    "fig = plt.gcf()\n",
    "plt.title(\"Percentage of Restaurants according to their ratings\")\n",
    "\n",
    "fig.set_size_inches(10,10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdd100e9",
   "metadata": {},
   "source": [
    "## Services Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "4a00e30b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Type of Service')"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Types of Services\n",
    "\n",
    "sns.countplot(df['type']).set_xticklabels(sns.countplot(df['type']).get_xticklabels(), rotation=45, ha=\"right\")\n",
    "fig = plt.gcf()\n",
    "fig.set_size_inches(12,12)\n",
    "plt.title('Type of Service')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3347643b",
   "metadata": {},
   "source": [
    "Here the two main service types are Delivery and Dine-out"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da25632a",
   "metadata": {},
   "source": [
    "### Distribution of Cost of Food for two People"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "f304b663",
   "metadata": {},
   "outputs": [],
   "source": [
    "from plotly.offline import iplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "9d277ff6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "marker": {
          "color": "rgb(113, 10, 100)"
         },
         "name": "accepting online orders",
         "type": "box",
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          "scene": {
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            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
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            "showbackground": true,
            "ticks": "",
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           "yaxis": {
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            "ticks": ""
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           "baxis": {
            "gridcolor": "white",
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            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
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           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
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           "title": {
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         }
        },
        "title": {
         "text": "Box plot of approximate cost"
        },
        "width": 800,
        "yaxis": {
         "title": {
          "text": "Price"
         }
        }
       }
      }
     },
     "metadata": {},
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   ],
   "source": [
    "trace0=go.Box(y=df['cost'],name=\"accepting online orders\",\n",
    "              marker = dict(\n",
    "        color = 'rgb(113, 10, 100)',\n",
    "    ))\n",
    "data=[trace0]\n",
    "layout=go.Layout(title=\"Box plot of approximate cost\",width=800,height=800,yaxis=dict(title=\"Price\"))\n",
    "fig=go.Figure(data=data,layout=layout)\n",
    "py.iplot(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e18254b",
   "metadata": {},
   "source": [
    "#### Distribution of charges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "66f4ed5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "sns.distplot(df['cost'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d98a3656",
   "metadata": {},
   "source": [
    "### Most Liked Dishes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c3601fad",
   "metadata": {},
   "outputs": [],
   "source": [
    "#re=regular expression (use for splitting words)\n",
    "\n",
    "import re\n",
    "\n",
    "df.index=range(df.shape[0])\n",
    "likes=[]\n",
    "for i in range(df.shape[0]):\n",
    "    array_split=re.split(',',df['dish_liked'][i])\n",
    "    for item in array_split:\n",
    "        likes.append(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "5e4061d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.index=range(df.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "a3b7cf65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=23248, step=1)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "b64c24b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Count of Most liked dishes in Bangalore\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       " Pasta              2692\n",
       " Pizza              1915\n",
       " Cocktails          1880\n",
       " Burgers            1736\n",
       " Mocktails          1623\n",
       " Biryani            1307\n",
       " Sandwiches         1287\n",
       "Burgers             1256\n",
       " Coffee             1184\n",
       " Nachos             1170\n",
       " Fish               1116\n",
       " Paratha            1107\n",
       " Salads             1055\n",
       " Chicken Biryani    1004\n",
       "Cocktails            891\n",
       " Fries               876\n",
       " Noodles             854\n",
       " Beer                835\n",
       " Mutton Biryani      832\n",
       " Tea                 819\n",
       "Coffee               801\n",
       " Sandwich            788\n",
       " Butter Chicken      782\n",
       " Thali               770\n",
       "Biryani              749\n",
       "Pizza                747\n",
       " Roti                729\n",
       " Brownie             726\n",
       " Salad               677\n",
       " Hot Chocolate       672\n",
       "dtype: int64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Count of Most liked dishes in Bangalore\")\n",
    "favourite_food = pd.Series(likes).value_counts()\n",
    "favourite_food.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "769fe261",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = favourite_food.nlargest(n=20, keep='first').plot(kind='bar',figsize=(18,10),title = 'Top 30 Favourite Food counts ')\n",
    "\n",
    "for i in ax.patches:\n",
    "    ax.annotate(str(i.get_height()), (i.get_x() * 1.005, i.get_height() * 1.005))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0b557b5",
   "metadata": {},
   "source": [
    "We can infer from the analysis that the 5 most liked dishes are Pasta,Pizza,Cocktails,Burgers,and Mocktails"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e440195",
   "metadata": {},
   "source": [
    "### Restaurant and their counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "bedfeed6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'count')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "rest=df['rest_type'].value_counts()[:20]\n",
    "sns.barplot(rest,rest.index)\n",
    "plt.title(\"Restaurant types\")\n",
    "plt.xlabel(\"count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59161c5b",
   "metadata": {},
   "source": [
    "##### Casual Dining, Quick Bites and Cafe are the 3 most common types of Restaurants in Banglore"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "553d1313",
   "metadata": {},
   "source": [
    "### Most famous Restaurants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "41c5d3d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Number of outlets')"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sE1JVV9Ps47Ah8Oku+zhMWcZ9KRa19zNGtPsY7llaNumSPCDJLiP3ZWnH/iHt08l4by9XSaZxz1KsuR2HFrX3M0bUfy7NDKHJ8H2aJSpvTXJ3MqB9TT9G9yTaIuAhSZ48Iq7XsmSbxA7/Hnt1O/NquJ2NaZYmLo2zaJJ4r0yydkebD6H5SltJqzCXokjSKq79ZoQ/j1uxqVtJ9qbZ62BOkp/SfJB8PM1f4W8A/rPjmxm2AI5IcjbN+vy/AevTzNRYg44PRlV1Y5LTgacnOZTmA/+dNLMt5i/l5Z1Jk1x4SZJTaBIIGwDPo0k4/G2Mc5fZUrxe0OwDspBmw9VH0ExjfyTNa/ZT4N9HdPNKmnX8v6X5ysdraf6avRvNXiKfm4TruDjJa2i+FeGCJEfTjM8abWxPp9l3YdOliOlUmg+ob28/oAzvB/DFqlqc5As0eyssaF+/+wM703y4PaF93Bnr7Uk+D7wPODfJETT/33k2zXgvzZh/h2Z/kc8l2ZlmfIaAF9J8pefMpWizm+NpNgM9OsmJNK/VeVX1s3HOewvN7IV9gBlJjqH5hptH03wYfRH3/lC9JH5GM4bvbJNr59KM+QuBXzC5ichOa9EsIVvU/l64DFiTZhyfQPN74aLl1PfSmpVkRvt4DZqvmt6D5utYfwYc2VH3KzT7Gv0wyY9p9kjZnGZPmh8wCe+pqrokyf7AR4HzksyhWYb1bJqfn/OAJ4847XM075nfJflBW38bmlkfP6LZK2kifZ/evod3As5I8hua3727AcfQfdbFeG1e0f7b8B/AvCS/oNkA+vk0X1W8LJswSxpwJjYkSUuk/Q/rtjQzPZ5F8x/Va2iWsXyoqn7fUf0smr8MPoPmP+wPpvkAfDbwhar61Yjm/wM4sK37CiDAX4GlSmy0m5e+CPgwzX9+30bzAeJbbdmFS9PuEsawJK8XVXVrkl2AT9N8ANmWJin0SpoNK0cmNg6jmf2yA83SjLVorvFw4DNVdf4kXcf3kpwH/D+aZMJzaJYv/Y3mA8+cpYmpqq5N8lKavRpeTfMhEOB7NB+q3kfznnkdzd4si2kSRe+l2X+jm/fTJEteD7yBZo+Ow2k2M13iMa+qv7UzUj5O8wHvuTQJqv+i+fA9WYmND9MsldmNZk+G1YBDaD4UjxXftUl2oNkMdybNNd9J860XB7EM7/OquqndAPjjNLMLnk6zEe+HgM8yedc+0k00X5m6M837aA+aROAlNF8/fNBy6ndZdO6LUTTv1XNp9jL6dudX5lbV/DZJNvy7aXWaRMNLaPZNmZTXtao+luSvNHt6vJrmNTyGZn+hY7lnH47h+kcn2Y3m52smzfvoDJpxeAwTTGy0dgc+1d6/lSYhONzvyN9jE/V6muTnK4A30yTlv9D2s7RtSloJpPvXkkuSJElaGSV5EE2CYF5VdduEV5IGintsSJIkSSuhJOu3+5J0lq0OfIZmac8RPQlMkiaZMzYkSZKklVCSfWi+xvvXNEuTHkKz78XjgHnADlV1y6gNSNKAcI8NSZIkaeV0Os2myTsBD23LLgU+AnzCpIaklYUzNiRJkiRJ0sByjw1JkiRJkjSwTGxIkiRJkqSBZWJDkiRJkiQNLBMbkiRJkiRpYJnYkCRJkiRJA8vEhiRJkiRJGlgmNiRJkiRJ0sAysSFJkiRJkgaWiQ1JkiRJkjSwTGxIkiRJkqSBZWJDkiRJkiQNLBMbkiRJkiRpYJnYkCRJkiRJA8vEhiRJkiRJGlir9zoA9Y/FixdXr2OQJEmSJGksU6dOTedzZ2xIkiRJkqSBZWJDkiRJkiQNLJeiqKuFuzy71yFIkiRJkpaToeOP63UIk8YZG5IkSZIkaWCZ2JAkSZIkSQPLxIYkSZIkSRpYJjZ6JMkjkvw0ycIklyT5fJL7T2L7eyTZbLLakyRJkiSpH5nY6IEkAX4CHFlVQ8DjgCnARyaxmz0AExuSJEmSpJWa34rSG88Ebq2qgwGq6s4k7wAuTXIp8CxgbWAT4Iiq2g8gyXOADwAPAC4BXl1VNyb5OPAi4A7gWJqkyYuAZyR5L/DSts83APcH/gj8R1XdvKIuWJIkSZKk5cHERm88ETi7s6Cqrk/yZ5oxmQ5sCdwG/D7JF4FbgPcCz6qqm5L8D/DOJF8CXgxsWlWVZN2qui7JUcDPq+pHAEmuq6pvto8/DLwW+OKKuFhJkiRJkpYXExu9EaDGKD++qhYDJLkQeBSwLs3SkpOblSzcHzgVuB64FfhWkl8APx+lz83bhMa6NMtejpmka5EkSZIkqWdMbPTGBTTLQ+6W5EHAxsCdNDM1ht1JM04BjquqV4xsLMl2wC7Ay4G30Cw7GWk2sEdVnZdkFjBjWS9CkiRJkqRec/PQ3jgeWDvJfwIkWQ34DE3yYbR9L04Dnpbkse05ayd5XJIpwNSq+iXwdpplLAA3AOt0nL8OcEWSNYC9JvVqJEmSJEnqERMbPVBVRbMvxsuSLAT+QLOc5D1jnHM1MAs4LMl8mkTHpjQJi5+3Zb8F3tGecjjwriTnJtkEeB9wOnAccPHyuC5JkiRJkla0NJ+xJVi8ePHdb4aFuzy7l6FIkiRJkpajoeOP63UIS23q1KnpfO6MDUmSJEmSNLBMbEiSJEmSpIHlUhTdrXMpivrXwoULGRoa6nUYGofj1P8co/7nGPU/x2gwOE79zzHqf45Rf3EpiiRJkiRJWmmY2JAkSZIkSQPLxIYkSZIkSRpYq/c6APWnmZ8+utchaEyX9DoATYjj1P8co/7nGPU/x2gwOE5jmbPvrr0OQdIycMaGJEmSJEkaWCY2JEmSJEnSwDKxIUmSJEmSBlZfJjaS3JlkXsft3ZPU7i+TrLsM5y9KsiDJ/CS/TfKopWhjWpJXLm0Mk6EfYpAkSZIkaTL0ZWIDuKWqpnfcPj4ZjVbV86vqus6yNJbkddi5qp4MzAXeuxRhTAMmLamQZLVexyBJkiRJUq/0a2Kjq3bGxEeTnJrkrCRbJTkmySVJ9mnrzEhyYpIjklyY5GvDiYv2/PXaGQsXJfkKcA6wcZJ3JTmznY3xgQmEcyqwUdvu+kl+3J5/ZpKnteXP6Jh1cm6SdYCPA09vy97RxnJSknPa2w4d1/Hzjmv/UpJZHdexf5LfAS9L8vq23/PaONZu681O8oUkpyT5U5I92+buFcOyjoskSZIkSb3Sr4mNtUYsRZnZcewvVbU9cBIwG9gTeCrwwY462wH/D3gSsAnwki59PB74TlVt2T4eas+bDmydZKdxYtwVOLJ9/HngwKraFngp8K22fF/gzVU1HXg6cAvwbuCkdibKgcBVwLOraitgJvCFcfoddmtV7VhVhwM/qaptq2oL4CLgtR31NgR2BF5Ik9CgSwySJEmSJA2k1XsdwChuaZMB3RzV3i8AplTVDcANSW7t2D/jjKr6E0CSw2g+2P9oRDuXVdVp7ePntLdz2+dTaBIdJ3bp/4QkG9AkJIaXojwL2CzJcJ0HtbMzTgY+m+RQmuTDXzvqDFsD+FKS6cCdwONGue6R5nQ83jzJh4F129iP6Th2ZFXdBVzYxi1JkiRJ0kqjXxMbY7mtvb+r4/Hw8+HrqRHnjHwOcFPH4wAfq6qvT6D/ndtzZ9PMEnknzcyX7avqlhF1P57kF8DzgdOSPKtLe+8ArgS2aNu5tS2/g3vPqFlzjPhnA3tU1XntcpUZHcc6X6P7ZFUkSZIkSRpk/boUZVltl+TR7d4aM4HfjVP/GOA1SaYAJNkoycNGq9wmMN4O/GeShwDHAm8ZPt7OviDJJlW1oKo+AZwFbArcAKzT0dxU4Ip2VsV/AMObgV5GMwvkAUmmAruMEf86wBVJ1gD2Guda6RKDJEmSJEkDqV8TGyP32FjSb0U5lWY/ifOBS4EjxqpcVccC3wdOTbKAZtnKmB/8q+oK4DDgzcDbgG3ajUcvBPZpq709yflJzqPZX+NXwHzgjnajz3cAXwH2TnIazTKUm9r2/wL8oK1/KPcsk+nmfcDpwHHAxWPF3RoZgyRJkiRJAylV3VZpDK4kM4B9q+qFPQ5l4CxevPjuN8PMTx/dy1AkSZKkFWbOvrv2tP+FCxcyNDTU0xg0Nseov0ydOvVe2yz064wNSZIkSZKkcQ3i5qFjqqq5wNwehyFJkiRJklaAlS6xocnR6+l4Gp3T4AaD49T/HKP+5xj1P8doMDhOklZ2LkWRJEmSJEkDy8SGJEmSJEkaWCY2JEmSJEnSwHKPDXX1pqPe2OsQNJaLeh2AJsRx6n+OUf9zjPqfY9QTX33R13sdgiT1DWdsSJIkSZKkgWViQ5IkSZIkDSwTG5IkSZIkaWCZ2BhQSW7sePz8JAuTPDLJAUkuTzKvvX28rbNGko+39c5PckaS5/XuCiRJkiRJWnZuHjrgkuwCfBF4TlX9OQnAgVX16RFVPwRsCGxeVbcl2QB4xoqNVpIkSZKkyWViY4AleTrwTeD5VXXJGPXWBl4PPLqqbgOoqiuBH6yQQCVJkiRJWk5cijK4HgD8FNijqi4ecewdHUtRngs8FvhzVV2/wqOUJEmSJGk5MrExuG4HTgFe2+XYgVU1vb0ds4LjkiRJkiRphTGxMbjuAv4d2DbJe8ap+0fgkUnWWf5hSZIkSZK04pjYGGBVdTPwQmCvJN1mbnTW+zbwhST3B0iyYZJXrZhIJUmSJElaPtw8dMBV1T+T7AqcmOSaMaq+F/gwcGGSW4GbgP1XRIySJEmSJC0vJjYGVFVN6Xj8F+DR7dOfjlL/X8B+7U2SJEmSpJWCS1EkSZIkSdLAMrEhSZIkSZIGlktR1NVXX/T1XoegUSxcuJChoaFeh6FxOE79zzHqf45R/3OMJEn9wBkbkiRJkiRpYJnYkCRJkiRJA8vEhiRJkiRJGljusaGuZr/p8F6HoDGczNm9DkET4Dj1P8eo/zlG/c8xGt+sr7681yFI0krNGRuSJEmSJGlgmdiQJEmSJEkDy8SGJEmSJEkaWCY2xpGkkny34/nqSa5O8vNxzluUZEF7uzDJh5M8YDnENzvJnl3KZwzHmGRWkgMmu29JkiRJknrNxMb4bgI2T7JW+/zZwOUTPHfnqnoSsB3wGOAbyyE+SZIkSZJWWSY2JuZXwAvax68ADhs+kGRKkoPbmRnzk7x05MlVdSOwD7BHkoek8akk57fnzWzbmpFkbpIfJbk4yaFJ0h7bP8mZ7TnfGC7vlGTX9rzfAS/pOHQLcGNb52VtG+clOXFyXh5JkiRJknrDxMbEHA68PMmawJOB0zuOvQ9YXFVPqqonA7/p1kBVXQ9cCgzRJB2mA1sAzwI+lWTDtuqWwNuBzWhmeTytLf9SVW1bVZsDawEv7Gy/je2bwG7A04F/6+h7TlV9un26P/DcqtoCeNGSvQySJEmSJPUXExsTUFXzgWk0szV+OeLws4Avd9S9doymhmdZ7AgcVlV3VtWVwG+BbdtjZ1TVX6vqLmBe2y/AzklOT7IAeCbwxBFtbwpcWlULq6qA740Sw8nA7CSvB1YbI1ZJkiRJkvqeiY2JOwr4NB3LUFoBaryTk6xDk6T4A/ckOLq5rePxncDq7WyMrwB7tnt2fBNYs8u548ZRVfsA7wU2BuYleeh450iSJEmS1K9MbEzcQcAHq2rBiPJjgbcMP0ny4JEnJplCk5g4sp3RcSIwM8lqSdYHdgLOGKPv4STGNW1b9/kWFOBi4NFJNmmfv6JbQ0k2qarTq2p/4BqaBIckSZIkSQPJxMYEtctDPt/l0IeBBw9vyAns3HHshCTn0yQt/gy8sS0/ApgPnEezJ8d+VfX3Mfq+jmaWxgLgSODMLnVuBd4A/KLdPPSyUZr7VLth6fk0CZbzRutXkiRJkqR+t3qvA+h3VTWlS9lcYG77+EZg7y51po3RZgHvam9d222fv6Xj8XtplpCMbGtWx+OjafbaGFVVvWSs45IkSZIkDRJnbEiSJEmSpIFlYkOSJEmSJA0sl6Koq1lffXmvQ9AoFi5cyNDQUK/D0Dgcp/7nGPU/x6j/OUaSpH7gjA1JkiRJkjSwTGxIkiRJkqSBZWJDkiRJkiQNLPfYUFfXHji91yFoFOsB1/Y6CI3Lcep/jlH/c4z636o+Rg9+x7xehyBJwhkbkiRJkiRpgJnYkCRJkiRJA8vEhiRJkiRJGlgmNiZZkjuTzEtyfpIfJlk7yTZJvrCc+luUZL2O5zOS/Hycc9ZN8l/LIx5JkiRJklYkExuT75aqml5VmwP/AvapqrOq6m29DqzDuoCJDUmSJEnSwDOxsXydBDy2cxZFkl+2MzrmJVmcZO8k3+oouzrJ+5NMSXJ8knOSLEiy+5J2nuSAJPt2PD8/yTTg48AmbX+fmqyLlSRJkiRpRfPrXpeTJKsDzwOO7iyvque3x7cGDgaOrKpD2rJHAccAs4FbgRdX1fXtUpPTkhxVVdWluxOS3Nk+ngJcPE547wY2r6rpS3NtkiRJkiT1C2dsTL61kswDzgL+DHx7ZIU2UfFd4JVVtbgtWxP4IfCWqroMCPDRJPOBXwMbARuM0ufO7fKX6cDrJvdyJEmSJEnqX87YmHy3jJwJkaTz8WrA4cAHq+r8jmpfA35SVb9un+8FrA9sXVW3J1kErLmEsdzBvZNXS3q+JEmSJEl9zRkbK97HgflVdfhwQZI3A+tU1cc76k0FrmqTGjsDj1qKvhYBW7V9bAU8ui2/AVhnKdqTJEmSJKmvOGNjxdsXuKBdrgKwf1t2e0fZ14BDgZ8lOQuYx/j7ZnTzY+A/23bPBP4AUFX/SHJykvOBX1XVu5buUiRJkiRJ6i0TG5OsqqZ0KZsLzG0fZ+Rx4KhRmtt+Av1NG6OvW4DnjHLeK8drW5IkSZKkfudSFEmSJEmSNLBMbEiSJEmSpIHlUhR19eB3zOt1CBrFwoULGRoa6nUYGofj1P8co/7nGPU/x0iS1A+csSFJkiRJkgaWiQ1JkiRJkjSwTGxIkiRJkqSB5R4b6urmm1/V6xA0io02gptv7nUUGo/j1P8co/7nGPW/lXGM1l77e70OQZK0hJyxIUmSJEmSBpaJDUmSJEmSNLBMbEiSJEmSpIG1Uic2ktyZZF6SC5Kcl+SdSSblmpN8MMmzlvLcWUkOmGDdaUluaa/jwiRfS3K/JC9K8u6l6V+SJEmSpJXFyr556C1VNR0gycOA7wNTgfcva8NVtf+ytrEELqmq6UlWB34D7FFVPwGOWoExSJIkSZLUd1bqGRudquoq4A3AW9JYM8nBSRYkOTfJznD3bIojk/wsyaVJ3tLO9Dg3yWlJHtLWm51kz/bxoiQfSHJO296mbflD2rbmt+c+uQ3nFuDGts7Lkpzfzig5cZxruAM4BXhsG+eX2jbmddxuSfKMJL/sKFucZO929sdJbZznJNlh8l9pSZIkSZJWnJV9xsa9VNWf2qUoDwNe1ZY9qU1EHJvkcW3VzYEtgTWBPwL/U1VbJjkQ+E/gc12av6aqtkryX8C+wOuADwDnVtUeSZ4JfAeYXlVzOs7bH3huVV2eZN2x4k+yNrBLe84GHdc1vT2+G7AfcEpVPb8t2xo4GDgSuB14dlXdmmQIOAzYZuxXTZIkSZKk/rXKzNjokPZ+R+C7AFV1MXAZMJzYOKGqbqiqq4HFwM/a8gXAtFHa/Ul7f3ZHnc4+fgM8NMnUEeedDMxO8npgtVHa3iTJvLbuL6rqV/e5qCZR8SlgZlXd3pat1/b/yqpaDKwBfDPJAuCHwGaj9CdJkiRJ0kBYpWZsJHkMcCdwFfckOLq5rePxXR3P72L012y4zp0ddbr1Ufd6UrVPkqcALwDmJZleVf8Ycc4lw7MyuknyQOAHwOur6m9t2WrA4cAHq+r8tuo7gCuBLWiSWreO1qYkSZIkSYNglZmxkWR94GvAl6qqgBOBvdpjjwMeCfx+krvt7GMGzXKV60fEtUlVnd5uRnoNsPFS9HMwcHBVndRR9nFgflUd3lE2Fbiiqu4C/oPRZ4hIkiRJkjQQVvYZG2u1SzjWAO6gWZbx2fbYV4Cvtcsy7gBmVdVtyVgTOZbYAcDBSeYDNwN7d6nzqXYZSYDjgfOWpIMkjwL2BB6X5DVt8eto9vm4oL1+aPbl+Arw4yQvA04Ablqiq5EkSZIkqc+kmbwgweLFi+9+M9x886t6GYokSVJPrL3293odwqRbuHAhQ0NDvQ5DY3CM+p9j1F+mTp16rxkJq8xSFEmSJEmStPIxsSFJkiRJkgbWyr7HhpbSyjgNc2XhNLjB4Dj1P8eo/zlG/c8xkiT1A2dsSJIkSZKkgWViQ5IkSZIkDSwTG5IkSZIkaWC5x4a6+v5/7drrEDSGM3sdgCbEcep/jlH/c4z63yCM0Su/cnSvQ5AkLUfO2JAkSZIkSQPLxIYkSZIkSRpYJjYkSZIkSdLAco+NHktyJ7Cgo2iPqlrUo3AkSZIkSRooJjZ675aqmt7rICRJkiRJGkQuRekzSaYkOT7JOUkWJNm949iRSc5OckGSN7RlqyWZneT8tv472vLpSU5LMj/JEUke3Ja/LcmFbfnhvblKSZIkSZImhzM2em+tJPPax5cCLwNeXFXXJ1kPOC3JUVVVwGuq6p9J1gLOTPJjYBqwUVVtDpBk3bat7wBvrarfJvkg8H7g7cC7gUdX1W0ddSVJkiRJGkgmNnrvXktRkqwBfDTJTsBdwEbABsDfgbcleXFbdWNgCPg98JgkXwR+ARybZCqwblX9tq17CPDD9vF84NAkRwJHLsfrkiRJkiRpuXMpSv/ZC1gf2LpNeFwJrJlkBvAsYPuq2gI4F1izqq4FtgDmAm8GvjVO+y8AvgxsDZydxOSWJEmSJGlgmdjoP1OBq6rq9iQ7A4/qKL+2qm5OsinwVIB2ucr9qurHwPuArapqMXBtkqe35/4H8Nsk9wM2rqoTgP2AdYEpK+rCJEmSJEmabP61vv8cCvwsyVnAPODitvxoYJ8k82mWn5zWlm8EHNwmLQD+t73fG/hakrWBPwGvBlYDvtcuVQlwYFVdt3wvR5IkSZKk5cfERo9V1ZQRz68Bth+l+vNGKd+qS7vzaGd1jLDjksQnSZIkSVI/cymKJEmSJEkaWCY2JEmSJEnSwHIpirp65VeO7nUIGsXChQsZGhrqdRgah+PU/xyj/ucY9T/HSJLUD5yxIUmSJEmSBpaJDUmSJEmSNLBMbEiSJEmSpIHlHhvq6tbZ5/Q6BI1iY+DWkx2ffuc49T/HqP85Rv1vUMZozVlb9ToESdJy5IwNSZIkSZI0sExsSJIkSZKkgWViQ5IkSZIkDayeJjaS/F+SC5LMTzIvyVMmqd0b2/tpSc4fp+6sJAdMsN1pSW5pY70wyXeSrLEU8c1IssNSnPe8JGcluSjJxUk+PU79ByT5dRvvzCXtT5IkSZKkftezzUOTbA+8ENiqqm5Lsh5w/17FswQuqarpSVYDjgP+HTh0CduYAdwInDLRE5JsDnwJeEFVXZxkdeAN45y2JbBGVU1fwvgkSZIkSRoIvZyxsSFwTVXdBlBV11TV3wCSLEry0SSntjMUtkpyTJJLkuzT1pmS5Pgk5yRZkGT3sTpLclKS6R3PT07yZOAWmiQDSV6W5Pwk5yU5caz2qupO4Axgo/bcrZP8NsnZbawbtuVva2d3zE9yeJJpwD7AO9qZFE9P8qj2Wua394/s0uV+wEeq6uK2/zuq6ittH7slOT3Jue0MjQ2SPAz4HjC97WeT0WKUJEmSJGlQ9TKxcSywcZI/JPlKkmeMOP6XqtoeOAmYDewJPBX4YHv8VuDFVbUVsDPwmSQZo79vAbMAkjwOeEBVza+qOVU1vKRjf+C5VbUF8KKxgk+yJvAU4Oh2OcoXgT2ramvgIOAjbdV3A1tW1ZOBfapqEfA14MCqml5VJ9HMxPhOW+dQ4AtdutwcOHuUcH4HPLWqtgQOB/arqquA1wEntTM2/jxGjJIkSZIkDaSeJTaq6kZga5rlFFcDc5LM6qhyVHu/ADi9qm6oqquBW5OsCwT4aJL5wK9pZk5sMEaXPwRe2CYhXkOTLBnpZGB2ktcDq43SziZJ5gH/AP5cVfOBx9MkHo5rj70XeERbfz5waJJXAXeM0ub2wPfbx98FdhzjOrp5BHBMkgXAu4AndqkzVoySJEmSJA2knu2xAXcv55gLzG0/lO/NPQmH29r7uzoeDz9fHdgLWB/YuqpuT7IIWHOMvm5OchywO82+GNt0qbNPu4HpC4B5SaZX1T9GVBveY2PDNu4XAZcCF7QzTEZ6AbATzQyQ9yXplnS4Tyhdyi6gSQSd1+XYF4HPVtVRSWYAB3SpkzFilCRJkiRpIPVsxkaSxycZ6iiaDly2BE1MBa5qkxo7A4+awDnfolnmcWZV/bNLTJtU1elVtT9wDbDxaA1V1RU0y0z+F/g9sH67ISpJ1kjyxCT3AzauqhNo9shYF5gC3ACs09HcKcDL28d70SwtGelTwHvaZTQkuV+Sd7bHpgKXt4/3HiXkrjGOdn2SJEmSJA2CXs7YmAJ8sV1WcgfwR8b/lo9OhwI/S3IWMA+4eLwTqursJNcDB49S5VNtsiXA8XSfHdHpSJrZEU+h2QPkC0mm0ryunwP+AHyvLQvNvhrXJfkZ8KN2w9O3Am8DDkryLpplOa/uEvv8JG8HDkuyNs2sjl+0hw8AfpjkcuA04NFdzv9Xkm4xXjDONUqSJEmS1LdS1W3Vw8opycNplr5sWlV39TicvrN48eK73wy3zj6nl6FIkiRNmjVnbdXrEHpq4cKFDA0NjV9RPeMY9T/HqL9MnTr1Xl8c0stvRVmhkvwncDrwfyY1JEmSJElaOfR089AVqaq+A3yn13FIkiRJkqTJs8okNrRkVvUpm/3MaXCDwXHqf45R/3OM+p9jJEnqB6vMUhRJkiRJkrTyMbEhSZIkSZIGlokNSZIkSZI0sNxjQ13NmTOn1yFoDOec49fxDgLHqf85Rv3PMep/kz1GM2fOnNT2JEkrP2dsSJIkSZKkgWViQ5IkSZIkDSwTG5IkSZIkaWCNm9hI8m9JDk9ySZILk/wyyeNWRHCjxDMryZdGlM1Nsk0PYrlxktp5XpKzklyU5OIkn56MdiVJkiRJWtmNmdhIEuAIYG5VbVJVmwHvATaYSONJVlvWAJOs1BucJtkc+BLwqqp6ArA58Kcu9Vbq10GSJEmSpKUx3oyNnYHbq+prwwVVNa+qTkrjU0nOT7IgyUyAJDOSnJDk+8CC9vncJD9qZyMc2iZMSLJ1kt8mOTvJMUk2bMvnJvlokt8C/70kF5TkFW085yf5REf5jR2P90wyu338srbueUlObMtWa6/tzCTzk7xxAv3u1/Z7XpKPt2WbJDm6vb6Tkmza5dT9gI9U1cXt63tHVX2lPX92ks8mOQH4xGjtJdktyelJzk3y6yQbtOUHJDkkybFJFiV5SZJPtnEenWSNJXltJUmSJEnqN+PNAtgcOHuUYy8BpgNbAOsBZw4nBoDtgM2r6tIkM4AtgScCfwNOBp6W5HTgi8DuVXV1mxj5CPCato11q+oZo/Q9M8mOHc8fC5Dk4cAngK2Ba4Fjk+xRVUeOcY37A8+tqsuTrNuWvRZYXFXbJnkAcHKSY6vq0m4NJHkesAfwlKq6OclD2kPfAPapqoVJngJ8BXjmiNM3Bz4zRnyPA55VVXcmOX6U9n4HPLWqKsnraJIl/689fxOaBNVmwKnAS6tqvyRHAC8AxnptJEmSJEnqa8uyvGFH4LCquhO4sp1dsS1wPXDGiCTAGVX1V4Ak84BpwHU0H+qPaydwrAZc0XHOnDH6nlNVbxl+kmRu+3BbmmUzV7flhwI7MfaH95OB2Ul+APykLXsO8OQke7bPpwJDQNfEBvAs4OCquhmgqv6ZZAqwA/DD9voAHjBGHKP5YZvUGKu9RwBz2hkv9x8R56+q6vYkC2he46Pb8gU04yBJkiRJ0sAaL7FxAbDnKMcySjnATSOe39bx+M623wAXVNX2E2xjIsaKqToer3l3YdU+7eyHFwDzkkxv23lrVR2zBP3WiLL7AddV1fRxzr2AZobJeaMcH34dxmrvi8Bnq+qodobMAR3HbgOoqruS3F5Vw3HexbIltiRJkiRJ6rnx9tj4DfCAJK8fLkiybZJnACfSLAlZLcn6NDMjzliCvn8PrJ9k+7bdNZI8ccnCv4/TgWckWa/duPQVwG/bY1cmeUKS+wEv7rieTarq9KraH7gG2Bg4BnjT8B4USR6X5IFj9Hss8Joka7f1H1JV1wOXJnlZW5YkW3Q591PAe9J+00yS+yV558hK47Q3Fbi8fbz32C+RJEmSJEkrjzETG+1f918MPDvN171eQDMb4G8035Yyn2amwW+A/arq7xPtuKr+RTMb5BNJzgPm0Sy1WGpVdQXwv8AJbVznVNVP28PvBn7extq55OVTw5uN0iRrzgO+BVwInNOWf50xZjdU1dHAUcBZ7VKbfdtDewGvba/vAmD3LufOB94OHJbkIuB8YMNRuhqtvQNolqicRJOckSRJkiRplZB7ViZoVbd48eK73wxz5oy1xYkkSdLyMXPmzF6HsNJZuHAhQ0NDvQ5DY3CM+p9j1F+mTp16r20oxluKIkmSJEmS1LdMbEiSJEmSpIHlt2KoK6eB9i+nwQ0Gx6n/OUb9zzHqf46RJKkfOGNDkiRJkiQNLBMbkiRJkiRpYJnYkCRJkiRJA8s9NtTVwl2e3esQNIaFvQ5AE+I49T/HqP85Rv1vomM0dPxxyzUOSdKqyxkbkiRJkiRpYJnYkCRJkiRJA8vEhiRJkiRJGlgmNkaR5M4k85Kcl+ScJDv0QUw3djx+fpKFSR6ZZJ8k/9nL2CRJkiRJ6gU3Dx3dLVU1HSDJc4GPAc+Y6MlJVquqO5e28ySrV9UdoxzbBfgi8Jyq+jPwtaXtR5IkSZKkQeaMjYl5EHAtQJIZSX4+fCDJl5LMah8vSrJ/kt8BL2tnVVyc5HdJvjB8XpIHJjkoyZlJzk2ye1s+K8kPk/wMOLZbIEmeDnwTeEFVXdKWHZBk3/bx3CSfSHJGkj+09UmydpIfJJmfZE6S05Nss3xeLkmSJEmSVgxnbIxurSTzgDWBDYFnTvC8W6tqxyRr0nwD2k5VdWmSwzrq/B/wm6p6TZJ1gTOS/Lo9tj3w5Kr6Z5e2HwD8FJhRVRePEcPqVbVdkucD7weeBfwXcG1VPTnJ5sC8CV6PJEmSJEl9yxkbo7ulqqZX1abArsB3kmQC581p7zcF/lRVl7bPOxMbzwHe3SZO5tIkTx7ZHjtulKQGwO3AKcBrx4nhJ+392cC09vGOwOEAVXU+MH+cNiRJkiRJ6nsmNiagqk4F1gPWB+7g3q/bmiOq39Tej5UECfDSNnEyvaoeWVUXjTi/m7uAfwe2TfKeMerd1t7fyT2zciaSlJEkSZIkaaCY2JiAJJsCqwH/AC4DNkvygCRTgV1GOe1i4DFJprXPZ3YcOwZ46/AMkCRbTjSWqroZeCGwV5LxZm50+h1NUoQkmwFPWoJzJUmSJEnqS+6xMbrhPTagme2wd/stJ39J8gOapRwLgXO7nVxVtyT5L+DoJNcAZ3Qc/hDwOWB+m9xYRJOsmJCq+meSXYET27Yn4ivAIUnmtzHPBxZPtE9JkiRJkvqRiY1RVNVqYxzbD9ivS/m0EUUnVNWmbfLiy8BZbb1bgDd2OX82MHuMfqd0PP4L8Oj26U87ymd0PL6Ge/bYuBV4VVXdmmQT4Hia2SeSJEmSJA0sExvL1+uT7A3cn2aWxNd7GMvawAlJ1qCZgfKmqvpXD+ORJEmSJGmZmdhYjqrqQODAXscBUFU3ANv0Og5JkiRJkiaTiQ11NXT8cb0OQaNYuHAhQ0NDvQ5D43Cc+p9j1P8co/7nGEmS+oHfiiJJkiRJkgaWiQ1JkiRJkjSwTGxIkiRJkqSB5R4b6mrmp4/udQga0yW9DkAT4jj1P8eo/zlGk2XOvrv2OgRJkpYLZ2xIkiRJkqSBZWJDkiRJkiQNLBMbkiRJkiRpYJnYWEpJ7kwyL8n5SX6YZO0x6s5K8qVl6Gtaklva/s5LckqSxy9te5IkSZIkrSxMbCy9W6pqelVtDvwL2GeyGk7SbVPXS9r+tgAOAd4zCf0kie8BSZIkSdLA8kPt5DgJeGyShyQ5Msn8JKclefLIikl2S3J6knOT/DrJBm35AUm+keRY4Dvj9Pcg4Nr2vNWSfCrJmW2/b2zLpyQ5Psk5SRYk2b0tn5bkoiRfAc4BNp68l0GSJEmSpBXLr3tdRu3siucBRwMfAM6tqj2SPJMmQTF9xCm/A55aVZXkdcB+wP9rj20N7FhVt3TpapMk84B1gLWBp7TlrwUWV9W2SR4AnNwmR/4CvLiqrk+yHnBakqPacx4PvLqq/mtZr1+SJEmSpF4ysbH01moTDdDM2Pg2cDrwUoCq+k2ShyaZOuK8RwBzkmwI3B+4tOPYUaMkNaBdigKQZCbwDWBX4DnAk5Ps2dabCgwBfwU+mmQn4C5gI2CDts5lVXXakl+yJEmSJEn9xcTG0rtlONEwLEm61KsRz78IfLaqjkoyAzig49hNE+z7KODg4W6Bt1bVMSNimQWsD2xdVbcnWQSsuYT9SJIkSZLU19xjY3KdCOwF0CYtrqmq60fUmQpc3j7eeyn72RG4pH18DPCmJGu0/T4uyQPbfq5qkxo7A49ayr4kSZIkSepbztiYXAcAByeZD9xM98TFAcAPk1wOnAY8eoJtD++xEZpvYXldW/4tYBpwTjtj5GpgD+BQ4GdJzgLmARcv6cVIkiRJktTvTGwspaqa0qXsn8DuXcpnA7Pbxz8FftqlzgFj9LUIWGuUY3fRfPVrt69/3X6UJjcfrS9JkiRJkgaJS1EkSZIkSdLAMrEhSZIkSZIGlktR1NWcfXftdQgaxcKFCxkaGup1GBqH49T/HKP+5xhJkqSJcMaGJEmSJEkaWCY2JEmSJEnSwDKxIUmSJEmSBpZ7bKirNx31xl6HoLFc1OsANCGOU/9zjPqfYzSur77o670OQZKknnLGhiRJkiRJGlgmNiRJkiRJ0sAysSFJkiRJkgaWiY0+keT/klyQZH6SeUme0uuYJEmSJEnqd24e2geSbA+8ENiqqm5Lsh5w/xXQ72pVdefy7keSJEmSpOXFGRv9YUPgmqq6DaCqrqmqvyVZlOSjSU5NclaSrZIck+SSJPsApPGpJOcnWZBk5jjlM5KckOT7wIJeXbAkSZIkSZPBGRv94Vhg/yR/AH4NzKmq37bH/lJV2yc5EJgNPA1YE7gA+BrwEmA6sAWwHnBmkhOBHUYpB9gO2LyqLl3+lyZJkiRJ0vJjYqMPVNWNSbYGng7sDMxJ8u728FHt/QJgSlXdANyQ5NYk6wI7Aoe1S0quTPJbYNsxyq8HzjCpIUmSJElaGZjY6BNtAmIuMDfJAmDv9tBt7f1dHY+Hn68OZJQmRysHuGnpI5UkSZIkqX+4x0YfSPL4JEMdRdOByyZ4+onAzCSrJVkf2Ak4Y4xySZIkSZJWGs7Y6A9TgC+2S0vuAP4IvIHmm1LGcwSwPXAeUMB+VfX3JKOVb7oc4pckSZIkqSdMbPSBqjqbZrPPkaZ11JlNs3no8PNpHfXe1d4626xRyufSLHmRJEmSJGnguRRFkiRJkiQNLBMbkiRJkiRpYLkURV199UVf73UIGsXChQsZGhoav6J6ynHqf45R/3OMJEnSRDhjQ5IkSZIkDSwTG5IkSZIkaWCZ2JAkSZIkSQPLPTbU1ew3Hd7rEDSGkzm71yFoAhyn/ucY9T/HaHyzvvryXocgSVJPOWNDkiRJkiQNLBMbkiRJkiRpYJnYkCRJkiRJA6vniY0kleS7Hc9XT3J1kp8vQ5u/TLJu+3jREpw3N8nvk8xPcnGSLw23M9mSLEqyIMm89n73jmOnLI8+R/T/wSTPWt79SJIkSZK0PPU8sQHcBGyeZK32+bOBy5elwap6flVdt5Sn71VVTwaeDNwG/HRZYhnHzlU1HdgT+MJwYVXtMLJiktUms+Oq2r+qfj2ZbUqSJEmStKL1Q2ID4FfAC9rHrwAOGz6QZLskpyQ5t71/fFs+K8lPkhydZGGST3acsyjJeu3Tq9uyDZOc2M6QOD/J08cKqKr+BewHPDLJFkmmJTm/o499kxzQPp6b5MC2/YuSbNvGtjDJhydw/Q8Cru1o+8b2fkaSE5J8H1iQ5ENJ/ruj3keSvC3JlCTHJzmnc/ZHG/NFSb6Z5IIkxw4nkJLMTrLnBGKTJEmSJKlv9Uti43Dg5UnWpJkpcXrHsYuBnapqS2B/4KMdx6YDM4EnATOTbDyy4aratn34SuCYdobEFsC88YKqqjuB84BNJ3AN/6qqnYCv0czyeDOwOTAryUNHOeeENlnyW+C9o9TZDvi/qtoM+DawN0CS+wEvBw4FbgVeXFVbATsDn0mS9vwh4MtV9UTgOuClE7gWSZIkSZIGwuq9DgCgquYnmUYzW+OXIw5PBQ5JMgQUsEbHseOrajFAkguBRwF/GaWbM4GDkqwBHFlV8yYYXsavAsBR7f0C4IKquqKN60/AxsA/upyzc1Vdk2QT4Pgkc6vqxhF1zqiqSwGqalGSfyTZEtgAOLeq/tFe00eT7ATcBWzUHge4tONazwamTfB6JEmSJEnqe/0yYwOaxMCn6ViG0voQcEJVbQ7sBqzZcey2jsd3MkaipqpOBHai2b/ju0n+c7yA2n0tngRcBNzBvV+vNUdUH47lrhFx3TVWXG1slwBXApt1OXzTiOffAmYBrwYOasv2AtYHtm5npFzZEd+EXyNJkiRJkgZNPyU2DgI+WFULRpRP5Z7NRGctbeNJHgVcVVXfpFnSsdU49dcAPgb8parm0yQLHpbkoUkeALxwaWPp0tfDgEcDl02g+hHArsC2wDFt2VSaa7s9yc40M1ckSZIkSVrp9c1f76vqr8Dnuxz6JM1SlHcCv1mGLmYA70pyO3AjMNqMjUOT3AY8APg1sHsb3+1JPkiz/8elNHt/LKsTktxJs7zm3VV15XgnVNW/kpwAXNfuAQLNPhs/S3IWzd4hkxGbJEmSJEl9L1XV6xi0BNpNQ88BXlZVCyez7cWLF9/9Zpj9psMns2lJkrSczPrqy3vW98KFCxkaGupZ/5oYx6n/OUb9zzHqL1OnTr3XXpj9tBRF40iyGfBHmk1TJzWpIUmSJEnSIOqbpSgaX1VdCDym13FIkiRJktQvTGyoq15Oa9XYnAY3GByn/ucY9T/HSJIkTYRLUSRJkiRJ0sAysSFJkiRJkgaWiQ1JkiRJkjSw3GNDXV174PReh6BRrAdc2+sgNC7Hqf85Rv1vVR6jB79jXq9DkCRpYDhjQ5IkSZIkDSwTG5IkSZIkaWCZ2JAkSZIkSQPLxMYySHJnknlJzk/ywyRrJ9kmyReWU3+vSbIgyfy2z93b8llJHr48+pQkSZIkqZ+5eeiyuaWqpgMkORTYp6o+C5w12R0leQTwf8BWVbU4yRRg/fbwLOB84G+T3a8kSZIkSf3MGRuT5yTgsUlmJPk5QJJftjM65iVZnGTvJN/qKLs6yfuTTElyfJJz2hkZu3dp/2HADcCNAFV1Y1VdmmRPYBvg0LbNtZLskuTctq2DkjygjWdRkk8kOaO9PXbFvDSSJEmSJC0fJjYmQZLVgecBCzrLq+r57YyO1wKXAUdW1evast2BfwCzgVuBF1fVVsDOwGeSZEQ35wFXApcmOTjJbm0fP6KZIbJX2261bc6sqifRzMp5U0c711fVdsCXgM9NwuVLkiRJktQzJjaWzVpJ5tEkFv4MfHtkhSTrAd8FXllVi9uyNYEfAm+pqsuAAB9NMh/4NbARsEFnO1V1J7ArsCfwB+DAJAd0ienxwKVV9Yf2+SHATh3HD+u4334Jr1eSJEmSpL7iHhvL5u49NoZ1TrRIshpwOPDBqjq/o9rXgJ9U1a/b53vR7JexdVXdnmQRsObIzqqqgDOAM5IcBxwMHDCi2siZHvdpZpTHkiRJkiQNHGdsLF8fB+ZX1eHDBUneDKxTVR/vqDcVuKpNauwMPGpkQ0kenmSrjqLpNMtboNl7Y5328cXAtI79M/4D+G3HeTM77k9dqquSJEmSJKlPOGNj+doXuKBdrgKwf1t2e0fZ14BDgZ8lOQuYR5OcGGkN4NPt17reClwN7NMemw18LcktNMtLXg38sN3748y2j2EPSHI6TVLrFct+iZIkSZIk9Y6JjWVQVVO6lM0F5raPuy0LOWqU5sbc76Ldi+OZoxz7MfDjjqLjgS1HaerLVfWBsfqSJEmSJGlQuBRFkiRJkiQNLGdsrEKqalqvY5AkSZIkaTKZ2FBXD37HvF6HoFEsXLiQoaGhXoehcThO/c8x6n+OkSRJmgiXokiSJEmSpIFlYkOSJEmSJA0sExuSJEmSJGlguceGurr55lf1OgSNYqON4Oabex2FxuM49T/HqP+tjGO09trf63UIkiStdJyxIUmSJEmSBpaJDUmSJEmSNLBMbEiSJEmSpIFlYmMcSf4tyeFJLklyYZJfJnlckhlJfr4C41g3yT+SpH2+fZJK8oj2+dQk/0zSdUxXdLySJEmSJK0IJjbG0CYRjgDmVtUmVbUZ8B5ggxUdS1VdB/wdeEJbtANwbnsP8FTg9Kq6a0XHJkmSJElSr5jYGNvOwO1V9bXhgqqaV1UntU+nJPlRkouTHNoxm2JRkvXax9skmds+PiDJQUnmJvlTkrcNt5vkfW07xyU5LMm+XeI5mXsSGTsAB454fkqSaUlOSnJOe9uh4/yu8UqSJEmSNKhMbIxtc+DsMY5vCbwd2Ax4DPC0CbS5KfBcYDvg/UnWSLIN8NK2vZcA24xy7inck8h4DPDDjro70CQ+rgKeXVVbATOBLyxjvJIkSZIk9S0TG8vmjKr6a7v8Yx4wbQLn/KKqbquqa2iSEBsAOwI/rapbquoG4GejnHsysEOSRwOLqupWmhUzU4CtgTOANYBvJllAk/jYbBnjlSRJkiSpb5nYGNsFNAmD0dzW8fhOYPX28R3c89quOYFzJrQkpKoWAg8GdgNObYvPBl4NXFpVNwLvAK4EtqCZzXH/CcQrSZIkSdJAMrExtt8AD0jy+uGCJNsmecY45y3inoTISyfQz++A3ZKs2c6+eMEYdU8F/pt7Ehun0iwvOaV9PhW4op2V8R/AahPoX5IkSZKkgWRiYwxVVcCLgWe3X/d6AXAA8LdxTv0A8PkkJ9HMjBivnzOBo4DzgJ8AZwGLR6l+MrBxWweaxMZjuCex8RVg7ySnAY8Dbhqvf0mSJEmSBlWaz+7qtSRTqurGJGsDJwJvqKpzVmQMixcvvvvNcPPNr1qRXUuStEpYe+3v9TqESbVw4UKGhoZ6HYbG4Tj1P8eo/zlG/WXq1Kn32s7BPRb6xzeSbEazJ8chKzqpIUmSJEnSIDKx0Seq6pW9jkGSJEmSpEFjYkNdrWxTZVcmToMbDI5T/3OM+p9jJEmSJsLNQyVJkiRJ0sAysSFJkiRJkgaWiQ1JkiRJkjSw3GNDXX3/v3btdQgaw5m9DkAT4jj1P8eo/61sY/TKrxzd6xAkSVrpOGNDkiRJkiQNLBMbkiRJkiRpYJnYkCRJkiRJA8vExgqU5P+SXJBkfpJ5SZ4yRt0Dkuy7IuOTJEmSJGnQuHnoCpJke+CFwFZVdVuS9YD79zgsSZIkSZIGmjM2VpwNgWuq6jaAqrqmqv6WZFGb5CDJNknmdpyzRZLfJFmY5PVtna8keVH7+IgkB7WPX5vkw+3jI5Oc3c4OeUPH8QOHG07y+iSfXQHXLUmSJEnScmNiY8U5Ftg4yR/a5MQzJnDOk4EXANsD+yd5OHAi8PT2+EbAZu3jHYGT2sevqaqtgW2AtyV5KHA48KIka7R1Xg0cvKwXJUmSJElSL5nYWEGq6kZga+ANwNXAnCSzxjntp1V1S1VdA5wAbEeTvHh6ks2AC4Erk2xIk/w4pT3vbUnOA04DNgaGquom4DfAC5NsCqxRVQsm9SIlSZIkSVrB3GNjBaqqO4G5wNwkC4C9gTu4J8G05shT7ttEXZ7kwcCuNLM3HgL8O3BjVd2QZAbwLGD7qrq5Xdoy3O63gPcAF+NsDUmSJEnSSsAZGytIkscnGeoomg5cBiyimckB8NIRp+2eZM12KckM4My2/FTg7TSJjZOAfblnGcpU4No2qbEp8NThxqrqdJoZHK8EDpuM65IkSZIkqZecsbHiTAG+mGRdmlkaf6RZlvIE4NtJ3gOcPuKcM4BfAI8EPlRVf2vLTwKeU1V/THIZzayN4cTG0cA+SeYDv6dZjtLpB8D0qrp2Mi9OkiRJkqReMLGxglTV2cAOXQ6dBDyuS/0Dxmjr28C328e3Aw/sOHYb8LwxQtkROHCM45IkSZIkDQyXoqwikqyb5A/ALVV1fK/jkSRJkiRpMjhjYxVRVdfRZWaIJEmSJEmDzMSGunrlV47udQgaxcKFCxkaGhq/onrKcep/jlH/c4wkSdJEuBRFkiRJkiQNLBMbkiRJkiRpYJnYkCRJkiRJA8s9NtTVrbPP6XUIGsXGwK0nOz79znHqf45R/1sZx2jNWVv1OgRJklY6ztiQJEmSJEkDy8SGJEmSJEkaWCY2JEmSJEnSwFrpEhtJKsl3O56vnuTqJD8f57xtknxhAu3fOElxTkty/ijHHpfkl0n+mOSiJD9IskGSWUm+NMo5v0yy7mTEJkmSJEnSoFgZNw+9Cdg8yVpVdQvwbODy8U6qqrOAs5Z3cONJsibwC+CdVfWztmxnYP2xzquq56+A8CRJkiRJ6isr3YyN1q+AF7SPXwEcNnwgyXZJTklybnv/+LZ8xvCsjiQHJDkoydwkf0rytpEdJJmS5Pgk5yRZkGT3tnxaO8vim0kuSHJskrXaY1snOS/JqcCbR4n9lcCpw0kNgKo6oaqGZ3c8PMnRSRYm+WRHPIuSrDdO/69PcmYbw4+TrL1Ur64kSZIkSX1iZU1sHA68vJ398GTg9I5jFwM7VdWWwP7AR0dpY1PgucB2wPuTrDHi+K3Ai6tqK2Bn4DNJ0h4bAr5cVU8ErgNe2pYfDLytqrYfI/bNgbPHOD4dmAk8CZiZZOMudUbr/ydVtW1VbQFcBLx2jH4kSZIkSep7K+NSFKpqfpJpNLM1fjni8FTgkCRDQAEjExbDflFVtwG3JbkK2AD4a8fxAB9NshNwF7BRWwfg0qqa1z4+G5iWZCqwblX9ti3/LvC8pbi846tqMUCSC4FHAX8ZUec+/bePN0/yYWBdYApwzFL0L0mSJElS31hZZ2wAHAV8mo5lKK0PASdU1ebAbsCao5x/W8fjO7lvEmgvmn0vtq6q6cCVHW11Ozc0iZTxXABsPcbx8eIaq85s4C1V9STgA4x+7ZIkSZIkDYSVObFxEPDBqlowonwq92wmOmsZ2p8KXFVVt7ebez5qrMpVdR2wOMmObdFeo1T9PrBDkuE9Qkiya5InLUOsw9YBrmiX1YzWvyRJkiRJA2OlTWxU1V+r6vNdDn0S+FiSk4HVlqGLQ4FtkpxFkyS4eALnvBr4crt56C3dKrTf5PJC4K3tBqEX0iRgrlqGWIe9j2a/keMmGK8kSZIkSX0tVRNZHaFVweLFi+9+M9w6+5xehiJJ0kppzVlb9TqESbVw4UKGhoZ6HYbG4Tj1P8eo/zlG/WXq1KnpfL7SztiQJEmSJEkrPxMbkiRJkiRpYK2UX/eqZbeyTZVdmTgNbjA4Tv3PMep/jpEkSZoIZ2xIkiRJkqSBZWJDkiRJkiQNLBMbkiRJkiRpYLnHhrqaM2dOr0PQGM45x6/jHQSOU/9zjPrfIIzRzJkzex2CJEmrNGdsSJIkSZKkgWViQ5IkSZIkDSwTG5IkSZIkaWCZ2JigJDeOeD4ryZd6Fc+ySnJAkn17HYckSZIkScvCxMZKJA3HVJIkSZK0yvBD8CRIsluS05Ocm+TXSTZoyw9IckiSY5MsSvKSJJ9MsiDJ0UnWaOstSvLRJKcmOSvJVkmOSXJJkn06+nlXkjOTzE/ygbZsWpKLknwFOAfYuFu9tu7/Jfl9kl8Dj1+hL5IkSZIkScuBiY2JWyvJvOEb8MGOY78DnlpVWwKHA/t1HNsEeAGwO/A94ISqehJwS1s+7C9VtT1wEjAb2BN46nA/SZ4DDAHbAdOBrZPs1J77eOA7bf+P71YvydbAy4EtgZcA2y7j6yFJkiRJUs+t3usABsgtVTV9+EmSWcA27dNHAHOSbAjcH7i047xfVdXtSRYAqwFHt+ULgGkd9Y7qKJ9SVTcANyS5Ncm6wHPa27ltvSk0CYw/A5dV1Wlt+Wj11gGOqKqb2/iH+5MkSZIkaWA5Y2NyfBH4UjsT443Amh3HbgOoqruA26uq2vK7uHdi6baO8ts6yofrBfhYVU1vb4+tqm+3dW7qqD9WvUKSJEmSpJWIiY3JMRW4vH2893Lq4xjgNUmmACTZKMnDlqDeicCLk6yVZB1gt+UUpyRJkiRJK4xLUSbHAcAPk1wOnAY8erI7qKpjkzwBODUJwI3Aq4A7J1Kvqs5JMgeYB1xGs5eHJEmSJEkDLfesjNCqbvHixXe/GebMmdPLUCRJGhgzZ87sdQg9s3DhQoaGhnodhsbhOPU/x6j/OUb9ZerUqel87lIUSZIkSZI0sExsSJIkSZKkgeUeG+pqVZ5W2++cBjcYHKf+5xj1P8dIkiRNhDM2JEmSJEnSwDKxIUmSJEmSBpaJDUmSJEmSNLDcY0NdLdzl2b0OQWNY2OsANCGOU/9zjPrfIIzR0PHH9ToESZJWac7YkCRJkiRJA8vEhiRJkiRJGlgmNiRJkiRJ0sAauMRGkhuXoO4BSfadhD5PWdY2RrQ3N8mfk6Sj7Mjha0vy8CQ/ah/PSPLz9nHX62nb22YyY5QkSZIkaRAMXGKjF6pqh+XQ7HXA0wCSrAts2NHf36pqz+XQ530kcQNZSZIkSdLAWikSG0l2S3J6knOT/DrJBl3qvD7Jr5KsleRVSc5IMi/J15OsluRNST7ZUX9Wki+2j2/sKH9XkjOTzE/ygbZsvyRvax8fmOQ37eNdknxvlLAPB17ePn4J8JOOPqYlOX+ca777etqiVyU5Jcn5SbZr62zXlp3b3j++49p+mORnwLFj9SNJkiRJUj9bKRIbwO+Ap1bVljQJg/06DyZ5C7AbsAcwDZgJPK2qpgN3AnsBP6JJMAybCcwZ0c5zgCFgO2A6sHWSnYATgae31bYBpiRZA9gROGmUmI8HdkqyGk2CY84o9e6j83qq6pa2+IHtzJL/Ag5qyy4Gdmpfl/2Bj3Y0sz2wd1U9c6L9SpIkSZLUb1aWZQiPAOYk2RC4P3Bpx7H/AP5KkwS4PckuwNbAme0WF2sBV1XV1Un+lOSpwELg8cDJI/p5Tns7t30+hSbR8R2aJMc6wG3AOTQJjqcDbxsl5jtpEjIzgbWqalHHlhtjudf1dJQfBlBVJyZ5ULu8ZR3gkCRDQAFrdNQ/rqr+OZEOJUmSJEnqVytLYuOLwGer6qgkM4ADOo6dTzO74hE0CY8Ah1TV/3ZpZw7w7zQzHY6oqhpxPMDHqurrI09Msgh4NXAKMB/YGdgEuGiMuA8HjhgR73hGXs+wkbEW8CHghKp6cZJpwNyO4zctQZ+SJEmSJPWllWUpylTg8vbx3iOOnQu8ETgqycNploDsmeRhAEkekuRRbd2f0CxXeQXdl4YcA7wmyZT23I2G26FZjrJve38SsA8wr0typNNJwMdoZ1tM0MjrGTazjWlHYHFVLeber8usJehDkiRJkqSBMIiJjbWT/LXj9k6aGQ8/THIScM3IE6rqdzRJh18AVwHvBY5NMh84jvYbSarqWuBC4FFVdUaXdo4Fvg+cmmQBzb4c67SHT2rbObWqrgRuZfT9NYbbq6r6dFXdJ+Zxzrv7epKs1xZf234t7deA17ZlnwQ+luRkYLUl6UOSJEmSpEGQsScUaFWyePHiu98MC3d5di9DkSRpYAwdf1yvQ+iZhQsXMjQ01OswNA7Hqf85Rv3PMeovU6dOvdcGlYM4Y0OSJEmSJAkwsSFJkiRJkgbYyvKtKJpkq/K02n7nNLjB4Dj1P8eo/zlGkiRpIpyxIUmSJEmSBpaJDUmSJEmSNLBMbEiSJEmSpIHlHhvqauanj+51CBrTJb0OQBPiOPU/x6j/9f8Yzdl3116HIEnSKs0ZG5IkSZIkaWCZ2JAkSZIkSQPLxIYkSZIkSRpYJjYGWJK3J1l7lGObJpmX5NwkmyQ5pS2fluSVKzZSSZIkSZKWDxMbg+3tQNfEBrAH8NOq2rKqLqmqHdryaYCJDUmSJEnSSsHERp9J8qokZ7SzLb6eZLUkX01yVpILknygrfc24OHACUlOGNHG82mSHq8bPpbkxvbwx4Gnt+2/Y4VdmCRJkiRJy4Ff99pHkjwBmAk8rapuT/IVYC/g/6rqn0lWA45P8uSq+kKSdwI7V9U1ne1U1S+TfA24sao+PaKbdwP7VtULV8AlSZIkSZK0XJnY6C+7AFsDZyYBWAu4Cvj3JG+gGa8Ngc2A+b0KUpIkSZKkfmFio78EOKSq/vfuguTRwHHAtlV1bZLZwJo9ik+SJEmSpL7iHhv95XhgzyQPA0jyEOCRwE3A4iQbAM/rqH8DsM4S9rE050iSJEmS1JdMbPSRqroQeC9wbJL5NDM1bgPOBS4ADgJO7jjlG8CvOjYI/VaSbcbpZj5wR5Lz3DxUkiRJkjToXIrSZ6pqDjBnRPFpo9T9IvDFjuev63h8wIi6U9r722n28pAkSZIkaeA5Y0OSJEmSJA0sExuSJEmSJGlguRRFXc3Zd9deh6BRLFy4kKGhoV6HoXE4Tv3PMep/jpEkSZqIVFWvY1CfWLx4sW8GSZIkSVJfmzp1ajqfuxRFkiRJkiQNLBMbkiRJkiRpYLkURZIkSZIkDSxnbEiSJEmSpIFlYkMAJNk1ye+T/DHJu3sdjxpJDkpyVZLzO8oekuS4JAvb+wf3MsZVXZKNk5yQ5KIkFyT577bcceoTSdZMckaS89ox+kBb7hj1mSSrJTk3yc/b545Rn0myKMmCJPOSnNWWOU59JMm6SX6U5OL236btHaP+keTx7c/P8O36JG93jPpLkne0/2c4P8lh7f8lHKM+ZmJDJFkN+DLwPGAz4BVJNuttVGrNBkZ+9+67geOragg4vn2u3rkD+H9V9QTgqcCb258fx6l/3AY8s6q2AKYDuyZ5Ko5RP/pv4KKO545Rf9q5qqZX1Tbtc8epv3weOLqqNgW2oPmZcoz6RFX9vv35mQ5sDdwMHIFj1DeSbAS8DdimqjYHVgNejmPU10xsCGA74I9V9aeq+hdwOLB7j2MSUFUnAv8cUbw7cEj7+BBgjxUZk+6tqq6oqnPaxzfQ/AdyIxynvlGNG9una7S3wjHqK0keAbwA+FZHsWM0GBynPpHkQcBOwLcBqupfVXUdjlG/2gW4pKouwzHqN6sDayVZHVgb+BuOUV8zsSFoPoT9peP5X9sy9acNquoKaD5UAw/rcTxqJZkGbAmcjuPUV9olDvOAq4Djqsox6j+fA/YD7uooc4z6TwHHJjk7yRvaMsepfzwGuBo4uF3W9a0kD8Qx6lcvBw5rHztGfaKqLgc+DfwZuAJYXFXH4hj1NRMbAkiXMr8uR1oCSaYAPwbeXlXX9zoe3VtV3dlO+30EsF2SzXsckjokeSFwVVWd3etYNK6nVdVWNMtX35xkp14HpHtZHdgK+GpVbQnchNPl+1KS+wMvAn7Y61h0b+3eGbsDjwYeDjwwyat6G5XGY2JD0MzQ2Ljj+SNoplupP12ZZEOA9v6qHsezykuyBk1S49Cq+klb7Dj1oXZK9lyavWsco/7xNOBFSRbRLId8ZpLv4Rj1nar6W3t/Fc2+ANvhOPWTvwJ/bWelAfyIJtHhGPWf5wHnVNWV7XPHqH88C7i0qq6uqtuBnwA74Bj1NRMbAjgTGEry6DZ7/HLgqB7HpNEdBezdPt4b+GkPY1nlJQnNWuaLquqzHYccpz6RZP0k67aP16L5D8vFOEZ9o6r+t6oeUVXTaP4N+k1VvQrHqK8keWCSdYYfA88Bzsdx6htV9XfgL0ke3xbtAlyIY9SPXsE9y1DAMeonfwaemmTt9v95u9DsoeYY9bFUueJAkOT5NOubVwMOqqqP9DYiASQ5DJgBrAdcCbwfOBL4AfBIml+8L6uqkRuMagVJsiNwErCAe/YGeA/NPhuOUx9I8mSaTb5Wo0no/6CqPpjkoThGfSfJDGDfqnqhY9RfkjyGZpYGNEsevl9VH3Gc+kuS6TSb8N4f+BPwatrffThGfSHJ2jT72z2mqha3Zf4c9ZH2q+Fn0nz73bnA64ApOEZ9y8SGJEmSJEkaWC5FkSRJkiRJA8vEhiRJkiRJGlgmNiRJkiRJ0sAysSFJkiRJkgaWiQ1JkiRJkjSwTGxIkqRJleSAJJXkmC7HfpRk7gqMZUYby+Yrqs8lkeQJSU5KclMb57Tl3N/j2vFZd0T5rLb/KUvY3n7tV/RKktQzJjYkSdLy8pwk2/Y6iD73KWBd4EXA9sAVy7m/xwHvb/ucDPsBMyapLUmSloqJDUmStDz8E5gP/F+vA1mekqy5jE1sChxXVcdX1WlVddtkxCVJ0qrExIYkSVoeCvgo8KIkTxqtUrss4pou5ZXkLR3PFyX5dJJ3J7kiyeIkn0nj+UkuSHJDkiOTPLhLVw9P8vN2ycefk+zTpc8dk/w2yc1J/pHkm0nW6Tg+vFxjuyRzk9wCvGuMa5ue5Pi2vWuTHJpkg/bYtCQFbAK8o2137hhtrZ3kC0n+nuTWJGcmec6IOouSfHpE2d1LTNolIz9rD13ali8ao881k3wyyV+S3JbkvCTP7+wPeCjw/ratGl6WkuS17ZjckuSa9nV94mh9SZK0LExsSJKk5eWHwB+YvFkbLwe2A14NfBJ4J/BZ4EPA+4B9gGcAH+ty7rdpZpC8BPgV8NUkLxw+mORpwPHA34E9gbcDzwcO7tLWYcDP2+M/7xZokvWBucDawCuBt7axHZfk/jRLTrZv+/t++/i/xrj2b7bX/RHgxcBfgF8k2XGMc0Y6B9i3ffySts8Xj1H/R8AsmgTVbsCZwFFJprfHXwwspnltt29v5yTZCfga8D3gecBrgFOAqUsQqyRJE7Z6rwOQJEkrp6q6K8nHgW8n2b+q/rCMTd4KvKyq7gSOTrI7TcJgqKouBUiyBbA3TZKj06+q6j3t42OSPAZ4L/ckJj4OnFJVM4dPSHI5cHySzavq/I62vlBVnx8n1v/X3j+3qq5v2/sDcDrw0qo6DDgtyW3AFVV12mgNJXkC8Arg1VV1SFt2DE2i5n3Ac8eJBYCquj7J79un51bVojH63AV4ATCjqn7bFh+b5HE0iaqXVdW5Se4A/toZf5LtgPlV1ZlgOmoiMUqStDScsSFJkpan7wF/Bv53Etqa2yY1hv0RWDSc1OgoW7+dFdHpiBHPfwJsnWS1JGvTzDb4QZLVh2/A74Dbga1HnPuLCcS6HXDscFIDoKrOABYBSzLLAmBbIDQzYIbbuqt9vqRtTdSzaGaTnDziNTke2Gacc+cBWyY5MMlOXcZCkqRJZWJDkiQtN1V1B82ykVcledQyNnfdiOf/GqUswMgP01d1eb46sB7wYGA14Cs0iYzh223AGsDGI869cgKxbjhKvSuBh0zg/JFt3VhVN3dpa+0kD1jC9iZiPeDfuPfrcTtwAPd9Pe6lqn5Ns2xmJ5rlONck+UqSBy6HOCVJcimKJEla7g6iWfbxP12O3cqIJMQom38uq4d1eX4HcA2wJs1mpwcAv+xy7t9GPK8J9HdFlz4BNgDOnsD5I9uakmTtEcmNDYCbO75J5T6vJUueRBn2T+ByYI+lObldMnNIu9fIS4ADgeuBdy9lPJIkjcoZG5IkablqP3h/mmYTyQ1HHP4rsE6SjTrKnsPkG7lJ5ouBs6vqzqq6CTgNeHxVndXlNjKxMRGnA88d8a0q2wLTaJa4LIkzaZIpe3a0lfZ5Z1t/BZ4w4txnj3j+r/Z+vK+pPZ5mxsaN3V6TEe2N2lZVXV1VXwdOAjYbp09JkpaKMzYkSdKK8HXgPcAOwG87yo8GbgEOSvIZ4NHcd+PPyfC8JB9p+34JzQf+3TuO70ezUehdNN8GcgPwSJoNNP9vKTY+/SzwJpqNSj8BTKHZoHQB8OMlaaiqLkpyGPClJA+i2Ufk9cCmbR/DjgC+mOQ9NMmQlwAjv2J1ePPQNyY5nGbGx4Iu3R4HHEPzLS6fAC4AHgRMB9asquE9Uy4GXpDkaODGtv19aWaKzKWZEbMlzTfCOFtDkrRcOGNDkiQtd+0SigO7lF8DvBR4BHAk8Cqar0edbK8Dtmr7eCHw5qq6+5s6qup3NHtCrA98F/gZTbLjL0xsT417qaqrgZ1ploccBnyZZtbCs6vqX2OdO4rXA4fQfAvKT4FHAS9s4x72DeBzwNuAH9DMpvjwiLguo0k8vAQ4meY6u8VfbZ2DaL769hia5NT23HuWyLuAm2g2VD2TZqPVM2lmZ3ytPe9NNMt8xvsmGUmSlkqaf7ckSZIkSZIGjzM2JEmSJEnSwDKxIUmSJEmSBpaJDUmSJEmSNLBMbEiSJEmSpIFlYkOSJEmSJA0sExuSJEmSJGlgmdiQJEmSJEkDy8SGJEmSJEkaWCY2JEmSJEnSwPr/AM8aaB6lWGQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "chains=df['name'].value_counts()[:20]\n",
    "sns.barplot(x=chains,y=chains.index,palette='Set1')\n",
    "plt.title(\"Most famous restaurant chains in Bangaluru\",size=20,pad=20)\n",
    "plt.xlabel(\"Number of outlets\",size=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa69e6e1",
   "metadata": {},
   "source": [
    "### Building Our Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "4a564fcc",
   "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>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>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>dish_liked</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>cost</th>\n",
       "      <th>reviews_list</th>\n",
       "      <th>menu_item</th>\n",
       "      <th>type</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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</td>\n",
       "      <td>775</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>800.0</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>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</td>\n",
       "      <td>787</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>800.0</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>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</td>\n",
       "      <td>918</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>800.0</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>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</td>\n",
       "      <td>88</td>\n",
       "      <td>Banashankari</td>\n",
       "      <td>Quick Bites</td>\n",
       "      <td>Masala Dosa</td>\n",
       "      <td>South Indian, North Indian</td>\n",
       "      <td>300.0</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>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</td>\n",
       "      <td>166</td>\n",
       "      <td>Basavanagudi</td>\n",
       "      <td>Casual Dining</td>\n",
       "      <td>Panipuri, Gol Gappe</td>\n",
       "      <td>North Indian, Rajasthani</td>\n",
       "      <td>600.0</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             address                   name  \\\n",
       "0  942, 21st Main Road, 2nd Stage, Banashankari, ...                  Jalsa   \n",
       "1  2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...         Spice Elephant   \n",
       "2  1112, Next to KIMS Medical College, 17th Cross...        San Churro Cafe   \n",
       "3  1st Floor, Annakuteera, 3rd Stage, Banashankar...  Addhuri Udupi Bhojana   \n",
       "4  10, 3rd Floor, Lakshmi Associates, Gandhi Baza...          Grand Village   \n",
       "\n",
       "  online_order book_table  rate  votes      location            rest_type  \\\n",
       "0          Yes        Yes   4.1    775  Banashankari        Casual Dining   \n",
       "1          Yes         No   4.1    787  Banashankari        Casual Dining   \n",
       "2          Yes         No   3.8    918  Banashankari  Cafe, Casual Dining   \n",
       "3           No         No   3.7     88  Banashankari          Quick Bites   \n",
       "4           No         No   3.8    166  Basavanagudi        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",
       "                         cuisines   cost  \\\n",
       "0  North Indian, Mughlai, Chinese  800.0   \n",
       "1     Chinese, North Indian, Thai  800.0   \n",
       "2          Cafe, Mexican, Italian  800.0   \n",
       "3      South Indian, North Indian  300.0   \n",
       "4        North Indian, Rajasthani  600.0   \n",
       "\n",
       "                                        reviews_list menu_item    type  \\\n",
       "0  [('Rated 4.0', 'RATED\\n  A beautiful place to ...        []  Buffet   \n",
       "1  [('Rated 4.0', 'RATED\\n  Had been here for din...        []  Buffet   \n",
       "2  [('Rated 3.0', \"RATED\\n  Ambience is not that ...        []  Buffet   \n",
       "3  [('Rated 4.0', \"RATED\\n  Great food and proper...        []  Buffet   \n",
       "4  [('Rated 4.0', 'RATED\\n  Very good restaurant ...        []  Buffet   \n",
       "\n",
       "           city  \n",
       "0  Banashankari  \n",
       "1  Banashankari  \n",
       "2  Banashankari  \n",
       "3  Banashankari  \n",
       "4  Banashankari  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62f24324",
   "metadata": {},
   "source": [
    "### Convert the online categorical variables into a numeric format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "3dd6eafc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.online_order[df.online_order == 'Yes'] = 1 \n",
    "df.online_order[df.online_order == 'No'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "80e82573",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    16378\n",
       "0     6870\n",
       "Name: online_order, dtype: int64"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.online_order.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "57c5552f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.online_order = pd.to_numeric(df.online_order)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "475436bd",
   "metadata": {},
   "source": [
    "### change the string categorical into to a categorical int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "5cb9b638",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.book_table[df.book_table == 'Yes'] = 1 \n",
    "df.book_table[df.book_table == 'No'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "1d6e8c4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.book_table = pd.to_numeric(df.book_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "7da7da7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    17191\n",
       "1     6057\n",
       "Name: book_table, dtype: int64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.book_table.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e933457",
   "metadata": {},
   "source": [
    "Label encode the categorical variables to make it easier to build algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "82d23510",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "8ac70d33",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.location = le.fit_transform(df.location)\n",
    "df.rest_type = le.fit_transform(df.rest_type)\n",
    "df.cuisines = le.fit_transform(df.cuisines)\n",
    "df.menu_item = le.fit_transform(df.menu_item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "ba1ea7e2",
   "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>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>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>dish_liked</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>cost</th>\n",
       "      <th>reviews_list</th>\n",
       "      <th>menu_item</th>\n",
       "      <th>type</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>942, 21st Main Road, 2nd Stage, Banashankari, ...</td>\n",
       "      <td>Jalsa</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.1</td>\n",
       "      <td>775</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>Pasta, Lunch Buffet, Masala Papad, Paneer Laja...</td>\n",
       "      <td>1386</td>\n",
       "      <td>800.0</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  A beautiful place to ...</td>\n",
       "      <td>5047</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...</td>\n",
       "      <td>Spice Elephant</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>787</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>Momos, Lunch Buffet, Chocolate Nirvana, Thai G...</td>\n",
       "      <td>594</td>\n",
       "      <td>800.0</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Had been here for din...</td>\n",
       "      <td>5047</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1112, Next to KIMS Medical College, 17th Cross...</td>\n",
       "      <td>San Churro Cafe</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>918</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>Churros, Cannelloni, Minestrone Soup, Hot Choc...</td>\n",
       "      <td>484</td>\n",
       "      <td>800.0</td>\n",
       "      <td>[('Rated 3.0', \"RATED\\n  Ambience is not that ...</td>\n",
       "      <td>5047</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1st Floor, Annakuteera, 3rd Stage, Banashankar...</td>\n",
       "      <td>Addhuri Udupi Bhojana</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>88</td>\n",
       "      <td>1</td>\n",
       "      <td>62</td>\n",
       "      <td>Masala Dosa</td>\n",
       "      <td>1587</td>\n",
       "      <td>300.0</td>\n",
       "      <td>[('Rated 4.0', \"RATED\\n  Great food and proper...</td>\n",
       "      <td>5047</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10, 3rd Floor, Lakshmi Associates, Gandhi Baza...</td>\n",
       "      <td>Grand Village</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>166</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>Panipuri, Gol Gappe</td>\n",
       "      <td>1406</td>\n",
       "      <td>600.0</td>\n",
       "      <td>[('Rated 4.0', 'RATED\\n  Very good restaurant ...</td>\n",
       "      <td>5047</td>\n",
       "      <td>Buffet</td>\n",
       "      <td>Banashankari</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             address                   name  \\\n",
       "0  942, 21st Main Road, 2nd Stage, Banashankari, ...                  Jalsa   \n",
       "1  2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...         Spice Elephant   \n",
       "2  1112, Next to KIMS Medical College, 17th Cross...        San Churro Cafe   \n",
       "3  1st Floor, Annakuteera, 3rd Stage, Banashankar...  Addhuri Udupi Bhojana   \n",
       "4  10, 3rd Floor, Lakshmi Associates, Gandhi Baza...          Grand Village   \n",
       "\n",
       "   online_order  book_table  rate  votes  location  rest_type  \\\n",
       "0             1           1   4.1    775         1         20   \n",
       "1             1           0   4.1    787         1         20   \n",
       "2             1           0   3.8    918         1         16   \n",
       "3             0           0   3.7     88         1         62   \n",
       "4             0           0   3.8    166         4         20   \n",
       "\n",
       "                                          dish_liked  cuisines   cost  \\\n",
       "0  Pasta, Lunch Buffet, Masala Papad, Paneer Laja...      1386  800.0   \n",
       "1  Momos, Lunch Buffet, Chocolate Nirvana, Thai G...       594  800.0   \n",
       "2  Churros, Cannelloni, Minestrone Soup, Hot Choc...       484  800.0   \n",
       "3                                        Masala Dosa      1587  300.0   \n",
       "4                                Panipuri, Gol Gappe      1406  600.0   \n",
       "\n",
       "                                        reviews_list  menu_item    type  \\\n",
       "0  [('Rated 4.0', 'RATED\\n  A beautiful place to ...       5047  Buffet   \n",
       "1  [('Rated 4.0', 'RATED\\n  Had been here for din...       5047  Buffet   \n",
       "2  [('Rated 3.0', \"RATED\\n  Ambience is not that ...       5047  Buffet   \n",
       "3  [('Rated 4.0', \"RATED\\n  Great food and proper...       5047  Buffet   \n",
       "4  [('Rated 4.0', 'RATED\\n  Very good restaurant ...       5047  Buffet   \n",
       "\n",
       "           city  \n",
       "0  Banashankari  \n",
       "1  Banashankari  \n",
       "2  Banashankari  \n",
       "3  Banashankari  \n",
       "4  Banashankari  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "92a2c32f",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data=df.iloc[:,[2,3,4,5,6,7,9,10,12]]\n",
    "my_data.to_csv('Zomato_df.csv') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "1637d60d",
   "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>online_order</th>\n",
       "      <th>book_table</th>\n",
       "      <th>votes</th>\n",
       "      <th>location</th>\n",
       "      <th>rest_type</th>\n",
       "      <th>cuisines</th>\n",
       "      <th>cost</th>\n",
       "      <th>menu_item</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>775</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>1386</td>\n",
       "      <td>800.0</td>\n",
       "      <td>5047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>787</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>594</td>\n",
       "      <td>800.0</td>\n",
       "      <td>5047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>918</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>484</td>\n",
       "      <td>800.0</td>\n",
       "      <td>5047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>88</td>\n",
       "      <td>1</td>\n",
       "      <td>62</td>\n",
       "      <td>1587</td>\n",
       "      <td>300.0</td>\n",
       "      <td>5047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>166</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>1406</td>\n",
       "      <td>600.0</td>\n",
       "      <td>5047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   online_order  book_table  votes  location  rest_type  cuisines   cost  \\\n",
       "0             1           1    775         1         20      1386  800.0   \n",
       "1             1           0    787         1         20       594  800.0   \n",
       "2             1           0    918         1         16       484  800.0   \n",
       "3             0           0     88         1         62      1587  300.0   \n",
       "4             0           0    166         4         20      1406  600.0   \n",
       "\n",
       "   menu_item  \n",
       "0       5047  \n",
       "1       5047  \n",
       "2       5047  \n",
       "3       5047  \n",
       "4       5047  "
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = df.iloc[:,[2,3,5,6,7,9,10,12]]\n",
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "de0fb8b7",
   "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",
       "        ... \n",
       "23243    3.8\n",
       "23244    3.9\n",
       "23245    2.8\n",
       "23246    2.5\n",
       "23247    4.3\n",
       "Name: rate, Length: 23248, dtype: float64"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = df['rate']\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "aac11697",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=.3,random_state=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "571cd896",
   "metadata": {},
   "source": [
    "## Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "1b9741e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_model=LinearRegression()\n",
    "lr_model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "46da0c17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2281882852296726"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score\n",
    "y_pred=lr_model.predict(x_test)\n",
    "r2_score(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ed62674",
   "metadata": {},
   "source": [
    "### Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "137c2425",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8809706960047533"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "RF_Model=RandomForestRegressor(n_estimators=650,random_state=245,min_samples_leaf=.0001)\n",
    "RF_Model.fit(x_train,y_train)\n",
    "y_predict=RF_Model.predict(x_test)\n",
    "r2_score(y_test,y_predict)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef2511da",
   "metadata": {},
   "source": [
    "### ExtraTree Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "460b948c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.932945228744891"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Preparing Extra Tree Regression\n",
    "from sklearn.ensemble import  ExtraTreesRegressor\n",
    "ET_Model=ExtraTreesRegressor(n_estimators = 120)\n",
    "ET_Model.fit(x_train,y_train)\n",
    "y_predict=ET_Model.predict(x_test)\n",
    "\n",
    "\n",
    "from sklearn.metrics import r2_score\n",
    "r2_score(y_test,y_predict)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8eac2a49",
   "metadata": {},
   "source": [
    "Extra Tree Regressor gives us the best model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "b5af67c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use pickle to save our model so that we can use it later\n",
    "\n",
    "import pickle \n",
    "# Saving model to disk\n",
    "pickle.dump(ET_Model, open('model.pkl','wb'))\n",
    "model=pickle.load(open('model.pkl','rb'))"
   ]
  }
 ],
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