Data_Understanding.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('Cleaned_Data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Original_price</th>\n",
       "      <th>Offer</th>\n",
       "      <th>Final_price</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Number_of_Rating</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Location</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OYO 22085 Raj Banjara White House</td>\n",
       "      <td>2459.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1677.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>201.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Collection O 42514 Venkat Nagar</td>\n",
       "      <td>3158.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2153.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>4.4</td>\n",
       "      <td>879.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Capital O 44354 Jubilee Banjara Suites</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1213.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1258.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OYO 35487 Hotel Meena Grand</td>\n",
       "      <td>2090.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1425.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>575.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OYO 16018 Rainbow Saphire</td>\n",
       "      <td>2607.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1777.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.7</td>\n",
       "      <td>978.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Collection O 46198 New Sree Krishna</td>\n",
       "      <td>3964.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2703.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>989.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>OYO 14224 Happy Guest house</td>\n",
       "      <td>2373.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1618.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>4.6</td>\n",
       "      <td>448.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>OYO 62547 Dream Connect Stays</td>\n",
       "      <td>1941.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1324.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>4.3</td>\n",
       "      <td>267.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OYO 11376 Golden Park</td>\n",
       "      <td>2205.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1570.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>OYO 11316 Athithi Inn</td>\n",
       "      <td>2178.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1348.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.3</td>\n",
       "      <td>697.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>OYO 10272 Hotel Ruma</td>\n",
       "      <td>1777.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>488.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>OYO 18725 Sr Grand</td>\n",
       "      <td>1910.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1303.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>4.4</td>\n",
       "      <td>294.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>OYO 18302 Pride Banjara</td>\n",
       "      <td>2260.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1541.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>OYO 983 Hotel Surya Residency</td>\n",
       "      <td>2811.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>264.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Capital O 46832 Gaayatri Residency Deluxe</td>\n",
       "      <td>2098.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1431.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>4.8</td>\n",
       "      <td>644.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>OYO 4025 Hotel Meredian Orchid</td>\n",
       "      <td>1865.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>4.1</td>\n",
       "      <td>558.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>OYO Townhouse 045 Lakdi ka Pul</td>\n",
       "      <td>5129.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3497.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>OYO 41751 Hotel Sabharwal</td>\n",
       "      <td>1416.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>966.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>786.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>OYO 47332 Hotel Dolphin</td>\n",
       "      <td>2509.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1711.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>4.4</td>\n",
       "      <td>279.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>OYO 30744 The  Gate</td>\n",
       "      <td>2140.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1459.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>440.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>OYO 37906 New Asian Lodge</td>\n",
       "      <td>2420.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1650.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>349.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>OYO 26562 Dazzle Stays</td>\n",
       "      <td>1730.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>371.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>SilverKey Executive Stays 27773 IAS Colony</td>\n",
       "      <td>1639.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>991.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2195.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>OYO 1410 Country Club Begumpet</td>\n",
       "      <td>4417.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3012.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>3.6</td>\n",
       "      <td>366.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>OYO 22907 Hotel Holiday Deluxe</td>\n",
       "      <td>2407.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1642.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>393.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>OYO 47727 S Grand</td>\n",
       "      <td>1427.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>973.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.4</td>\n",
       "      <td>360.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Capital O 6422 Luxor Park</td>\n",
       "      <td>2737.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1867.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1914.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>OYO 9302 Hotel Baseraa Inn</td>\n",
       "      <td>2081.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1419.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>4.5</td>\n",
       "      <td>170.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>OYO 8941 Hotel Golden Leaves</td>\n",
       "      <td>2449.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1670.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>728.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>OYO Flagship 14348 Apollo Hospital</td>\n",
       "      <td>2746.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1422.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11952</th>\n",
       "      <td>OYO 46744 Hotel Yash</td>\n",
       "      <td>1481.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>4.3</td>\n",
       "      <td>161.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11953</th>\n",
       "      <td>OYO 62553 Suvee Palace</td>\n",
       "      <td>1294.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>883.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11954</th>\n",
       "      <td>OYO 61639 Red Carmine</td>\n",
       "      <td>1777.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>4.6</td>\n",
       "      <td>104.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11955</th>\n",
       "      <td>OYO 44324 Comfort Stay Near Saket Metro</td>\n",
       "      <td>2989.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2038.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>4.6</td>\n",
       "      <td>878.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11956</th>\n",
       "      <td>OYO Home Luxe 30142 Fabulous Farmstay</td>\n",
       "      <td>2548.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1299.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>535.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11957</th>\n",
       "      <td>OYO 22321 Nitin Palace Guest House</td>\n",
       "      <td>2822.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>4.7</td>\n",
       "      <td>279.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11958</th>\n",
       "      <td>OYO Townhouse 002 Green Park</td>\n",
       "      <td>7806.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5323.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1390.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11959</th>\n",
       "      <td>Capital O 7075 The Oakland Plaza Hotel Deluxe</td>\n",
       "      <td>3078.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1025.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11960</th>\n",
       "      <td>OYO 14789 Kempinski Wide</td>\n",
       "      <td>3534.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2349.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.3</td>\n",
       "      <td>195.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11961</th>\n",
       "      <td>OYO 63837 Ambica Inn</td>\n",
       "      <td>2729.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1861.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11962</th>\n",
       "      <td>OYO 37512 Spacious Stay Saket Metro</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1351.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>413.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11963</th>\n",
       "      <td>OYO 60334 Skp Bed &amp; Breakfast</td>\n",
       "      <td>2225.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1517.0</td>\n",
       "      <td>8.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>114.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11964</th>\n",
       "      <td>OYO 64271 Singh Hotel 2</td>\n",
       "      <td>1140.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>778.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11965</th>\n",
       "      <td>OYO 37055 M R Residency Saver</td>\n",
       "      <td>1481.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>541.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11966</th>\n",
       "      <td>Capital O 712 Defence Colony Deluxe</td>\n",
       "      <td>3738.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2549.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>723.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11967</th>\n",
       "      <td>OYO Home 47965 Cozy Stay Ignou Road Saket</td>\n",
       "      <td>2720.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1855.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11968</th>\n",
       "      <td>OYO Home 47964 Comfortable  Stay Ignou Road Saket</td>\n",
       "      <td>2720.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1855.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11969</th>\n",
       "      <td>OYO 44400 Retreat Inn</td>\n",
       "      <td>1878.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1281.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>3.7</td>\n",
       "      <td>315.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11970</th>\n",
       "      <td>OYO Flagship 36485 Smg Heritage Nehru Enclave</td>\n",
       "      <td>1777.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>8.8</td>\n",
       "      <td>3.8</td>\n",
       "      <td>3842.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11971</th>\n",
       "      <td>Capital O 39462 Westyard Hotel</td>\n",
       "      <td>2863.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2104.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11972</th>\n",
       "      <td>OYO 40657 Aastha</td>\n",
       "      <td>1372.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11973</th>\n",
       "      <td>OYO 14765 Amar Villa</td>\n",
       "      <td>4239.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>3.8</td>\n",
       "      <td>126.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11974</th>\n",
       "      <td>OYO 7304 Stay Jangpura</td>\n",
       "      <td>2843.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1939.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11975</th>\n",
       "      <td>OYO 9536 Bee For Home Stay</td>\n",
       "      <td>5011.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>1899.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>4.2</td>\n",
       "      <td>47.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11976</th>\n",
       "      <td>OYO 543 La Ola Boutique Hotel</td>\n",
       "      <td>2766.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1886.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>143.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11977</th>\n",
       "      <td>OYO 472 Hotel Sareen</td>\n",
       "      <td>2389.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1552.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11978</th>\n",
       "      <td>OYO 43002 The Royal Town Deluxe</td>\n",
       "      <td>4522.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3083.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11979</th>\n",
       "      <td>OYO 48664 Gour White House</td>\n",
       "      <td>2526.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1723.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.3</td>\n",
       "      <td>245.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11980</th>\n",
       "      <td>OYO 12532 Imperial Inn Deluxe</td>\n",
       "      <td>7544.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5144.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>4.8</td>\n",
       "      <td>271.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11981</th>\n",
       "      <td>OYO 13235 The Golden Door</td>\n",
       "      <td>6855.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4674.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.5</td>\n",
       "      <td>173.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11982 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Name  Original_price  \\\n",
       "0                      OYO 22085 Raj Banjara White House          2459.0   \n",
       "1                        Collection O 42514 Venkat Nagar          3158.0   \n",
       "2                 Capital O 44354 Jubilee Banjara Suites          1778.0   \n",
       "3                            OYO 35487 Hotel Meena Grand          2090.0   \n",
       "4                              OYO 16018 Rainbow Saphire          2607.0   \n",
       "5                    Collection O 46198 New Sree Krishna          3964.0   \n",
       "6                            OYO 14224 Happy Guest house          2373.0   \n",
       "7                          OYO 62547 Dream Connect Stays          1941.0   \n",
       "8                                  OYO 11376 Golden Park          2205.0   \n",
       "9                                  OYO 11316 Athithi Inn          2178.0   \n",
       "10                                  OYO 10272 Hotel Ruma          1777.0   \n",
       "11                                    OYO 18725 Sr Grand          1910.0   \n",
       "12                               OYO 18302 Pride Banjara          2260.0   \n",
       "13                         OYO 983 Hotel Surya Residency          2811.0   \n",
       "14             Capital O 46832 Gaayatri Residency Deluxe          2098.0   \n",
       "15                        OYO 4025 Hotel Meredian Orchid          1865.0   \n",
       "16                        OYO Townhouse 045 Lakdi ka Pul          5129.0   \n",
       "17                             OYO 41751 Hotel Sabharwal          1416.0   \n",
       "18                               OYO 47332 Hotel Dolphin          2509.0   \n",
       "19                                   OYO 30744 The  Gate          2140.0   \n",
       "20                             OYO 37906 New Asian Lodge          2420.0   \n",
       "21                                OYO 26562 Dazzle Stays          1730.0   \n",
       "22            SilverKey Executive Stays 27773 IAS Colony          1639.0   \n",
       "23                        OYO 1410 Country Club Begumpet          4417.0   \n",
       "24                        OYO 22907 Hotel Holiday Deluxe          2407.0   \n",
       "25                                     OYO 47727 S Grand          1427.0   \n",
       "26                             Capital O 6422 Luxor Park          2737.0   \n",
       "27                            OYO 9302 Hotel Baseraa Inn          2081.0   \n",
       "28                          OYO 8941 Hotel Golden Leaves          2449.0   \n",
       "29                    OYO Flagship 14348 Apollo Hospital          2746.0   \n",
       "...                                                  ...             ...   \n",
       "11952                               OYO 46744 Hotel Yash          1481.0   \n",
       "11953                             OYO 62553 Suvee Palace          1294.0   \n",
       "11954                              OYO 61639 Red Carmine          1777.0   \n",
       "11955            OYO 44324 Comfort Stay Near Saket Metro          2989.0   \n",
       "11956              OYO Home Luxe 30142 Fabulous Farmstay          2548.0   \n",
       "11957                 OYO 22321 Nitin Palace Guest House          2822.0   \n",
       "11958                       OYO Townhouse 002 Green Park          7806.0   \n",
       "11959      Capital O 7075 The Oakland Plaza Hotel Deluxe          3078.0   \n",
       "11960                           OYO 14789 Kempinski Wide          3534.0   \n",
       "11961                               OYO 63837 Ambica Inn          2729.0   \n",
       "11962                OYO 37512 Spacious Stay Saket Metro          1981.0   \n",
       "11963                      OYO 60334 Skp Bed & Breakfast          2225.0   \n",
       "11964                            OYO 64271 Singh Hotel 2          1140.0   \n",
       "11965                      OYO 37055 M R Residency Saver          1481.0   \n",
       "11966                Capital O 712 Defence Colony Deluxe          3738.0   \n",
       "11967          OYO Home 47965 Cozy Stay Ignou Road Saket          2720.0   \n",
       "11968  OYO Home 47964 Comfortable  Stay Ignou Road Saket          2720.0   \n",
       "11969                              OYO 44400 Retreat Inn          1878.0   \n",
       "11970      OYO Flagship 36485 Smg Heritage Nehru Enclave          1777.0   \n",
       "11971                     Capital O 39462 Westyard Hotel          2863.0   \n",
       "11972                                   OYO 40657 Aastha          1372.0   \n",
       "11973                               OYO 14765 Amar Villa          4239.0   \n",
       "11974                             OYO 7304 Stay Jangpura          2843.0   \n",
       "11975                         OYO 9536 Bee For Home Stay          5011.0   \n",
       "11976                      OYO 543 La Ola Boutique Hotel          2766.0   \n",
       "11977                               OYO 472 Hotel Sareen          2389.0   \n",
       "11978                    OYO 43002 The Royal Town Deluxe          4522.0   \n",
       "11979                         OYO 48664 Gour White House          2526.0   \n",
       "11980                      OYO 12532 Imperial Inn Deluxe          7544.0   \n",
       "11981                          OYO 13235 The Golden Door          6855.0   \n",
       "\n",
       "       Offer  Final_price  Distance  Rating  Number_of_Rating  \\\n",
       "0       32.0       1677.0       1.7     4.4             201.0   \n",
       "1       32.0       2153.0       1.6     4.4             879.0   \n",
       "2       32.0       1213.0       1.1     4.4            1258.0   \n",
       "3       32.0       1425.0       4.0     4.0             575.0   \n",
       "4       32.0       1777.0       4.6     4.7             978.0   \n",
       "5       32.0       2703.0       6.1     3.9             989.0   \n",
       "6       32.0       1618.0       1.8     4.6             448.0   \n",
       "7       32.0       1324.0       0.6     4.3             267.0   \n",
       "8       45.0       1212.0       5.3     4.4            1570.0   \n",
       "9       38.0       1348.0       4.8     3.3             697.0   \n",
       "10      32.0       1212.0       4.2     4.2             488.0   \n",
       "11      32.0       1303.0       3.3     4.4             294.0   \n",
       "12      32.0       1541.0       1.1     0.0               0.0   \n",
       "13      32.0       1917.0       3.2     4.2             264.0   \n",
       "14      32.0       1431.0       4.1     4.8             644.0   \n",
       "15      35.0       1212.0       2.7     4.1             558.0   \n",
       "16      32.0       3497.0       4.4     4.3            1934.0   \n",
       "17      32.0        966.0       7.2     4.2             786.0   \n",
       "18      32.0       1711.0       4.2     4.4             279.0   \n",
       "19      32.0       1459.0       3.4     4.3             440.0   \n",
       "20      32.0       1650.0       4.0     3.2             349.0   \n",
       "21      42.0       1010.0       6.7     3.9             371.0   \n",
       "22      40.0        991.0       2.9     3.8            2195.0   \n",
       "23      32.0       3012.0       5.9     3.6             366.0   \n",
       "24      32.0       1642.0       5.9     4.5             393.0   \n",
       "25      32.0        973.0       4.6     4.4             360.0   \n",
       "26      32.0       1867.0       7.1     4.5            1914.0   \n",
       "27      32.0       1419.0       6.8     4.5             170.0   \n",
       "28      32.0       1670.0       6.7     4.4             728.0   \n",
       "29      44.0       1525.0       3.6     4.3            1422.0   \n",
       "...      ...          ...       ...     ...               ...   \n",
       "11952   32.0       1010.0       8.5     4.3             161.0   \n",
       "11953   32.0        883.0       8.0     0.0               0.0   \n",
       "11954   32.0       1212.0       8.9     4.6             104.0   \n",
       "11955   32.0       2038.0       8.7     4.6             878.0   \n",
       "11956   49.0       1299.0       9.2     4.6             535.0   \n",
       "11957   32.0       1924.0       6.8     4.7             279.0   \n",
       "11958   32.0       5323.0       7.3     4.8            1390.0   \n",
       "11959   32.0       2099.0       1.6     4.0            1025.0   \n",
       "11960   34.0       2349.0       3.2     4.3             195.0   \n",
       "11961   32.0       1861.0       5.4     0.0               0.0   \n",
       "11962   32.0       1351.0       6.8     4.0             413.0   \n",
       "11963   32.0       1517.0       8.2     3.4             114.0   \n",
       "11964   32.0        778.0       6.1     0.0               0.0   \n",
       "11965   32.0       1010.0       8.7     4.4             541.0   \n",
       "11966   32.0       2549.0       4.2     4.2             723.0   \n",
       "11967   32.0       1855.0       6.3     0.0               0.0   \n",
       "11968   32.0       1855.0       6.4     0.0               0.0   \n",
       "11969   32.0       1281.0       8.6     3.7             315.0   \n",
       "11970   32.0       1212.0       8.8     3.8            3842.0   \n",
       "11971   32.0       1952.0       5.6     4.0            2104.0   \n",
       "11972   32.0        936.0      10.0     4.0             332.0   \n",
       "11973   53.0       2010.0       6.7     3.8             126.0   \n",
       "11974   32.0       1939.0       7.0     0.0               0.0   \n",
       "11975   62.0       1899.0       7.3     4.2              47.0   \n",
       "11976   32.0       1886.0       1.5     4.2             143.0   \n",
       "11977   35.0       1552.0       2.0     3.7              90.0   \n",
       "11978   32.0       3083.0       1.0     3.6             114.0   \n",
       "11979   32.0       1723.0       2.8     4.3             245.0   \n",
       "11980   32.0       5144.0       1.3     4.8             271.0   \n",
       "11981   32.0       4674.0       2.8     4.5             173.0   \n",
       "\n",
       "                    Summary       Location       City  \n",
       "0                 Very Good  Banjara Hills  Hyderabad  \n",
       "1                 Very Good  Banjara Hills  Hyderabad  \n",
       "2                 Very Good  Banjara Hills  Hyderabad  \n",
       "3                 Very Good  Banjara Hills  Hyderabad  \n",
       "4                 Excellent  Banjara Hills  Hyderabad  \n",
       "5                      Good  Banjara Hills  Hyderabad  \n",
       "6                 Excellent  Banjara Hills  Hyderabad  \n",
       "7                 Very Good  Banjara Hills  Hyderabad  \n",
       "8                 Very Good  Banjara Hills  Hyderabad  \n",
       "9                      Fair  Banjara Hills  Hyderabad  \n",
       "10                Very Good  Banjara Hills  Hyderabad  \n",
       "11                Very Good  Banjara Hills  Hyderabad  \n",
       "12     Yet to be summarised  Banjara Hills  Hyderabad  \n",
       "13                Very Good  Banjara Hills  Hyderabad  \n",
       "14                Excellent  Banjara Hills  Hyderabad  \n",
       "15                Very Good  Banjara Hills  Hyderabad  \n",
       "16                Very Good  Banjara Hills  Hyderabad  \n",
       "17                Very Good  Banjara Hills  Hyderabad  \n",
       "18                Very Good  Banjara Hills  Hyderabad  \n",
       "19                Very Good  Banjara Hills  Hyderabad  \n",
       "20                     Fair  Banjara Hills  Hyderabad  \n",
       "21                     Good  Banjara Hills  Hyderabad  \n",
       "22                     Good  Banjara Hills  Hyderabad  \n",
       "23                     Good  Banjara Hills  Hyderabad  \n",
       "24                Excellent  Banjara Hills  Hyderabad  \n",
       "25                Very Good  Banjara Hills  Hyderabad  \n",
       "26                Excellent  Banjara Hills  Hyderabad  \n",
       "27                Excellent  Banjara Hills  Hyderabad  \n",
       "28                Very Good  Banjara Hills  Hyderabad  \n",
       "29                Very Good  Banjara Hills  Hyderabad  \n",
       "...                     ...            ...        ...  \n",
       "11952             Very Good    Nehru Place      Delhi  \n",
       "11953  Yet to be summarised    Nehru Place      Delhi  \n",
       "11954             Excellent    Nehru Place      Delhi  \n",
       "11955             Excellent    Nehru Place      Delhi  \n",
       "11956             Excellent    Nehru Place      Delhi  \n",
       "11957             Excellent    Nehru Place      Delhi  \n",
       "11958             Excellent    Nehru Place      Delhi  \n",
       "11959             Very Good    Nehru Place      Delhi  \n",
       "11960             Very Good    Nehru Place      Delhi  \n",
       "11961  Yet to be summarised    Nehru Place      Delhi  \n",
       "11962             Very Good    Nehru Place      Delhi  \n",
       "11963                  Fair    Nehru Place      Delhi  \n",
       "11964  Yet to be summarised    Nehru Place      Delhi  \n",
       "11965             Very Good    Nehru Place      Delhi  \n",
       "11966             Very Good    Nehru Place      Delhi  \n",
       "11967  Yet to be summarised    Nehru Place      Delhi  \n",
       "11968  Yet to be summarised    Nehru Place      Delhi  \n",
       "11969                  Good    Nehru Place      Delhi  \n",
       "11970                  Good    Nehru Place      Delhi  \n",
       "11971             Very Good    Nehru Place      Delhi  \n",
       "11972             Very Good    Nehru Place      Delhi  \n",
       "11973                  Good    Nehru Place      Delhi  \n",
       "11974  Yet to be summarised    Nehru Place      Delhi  \n",
       "11975             Very Good    Nehru Place      Delhi  \n",
       "11976             Very Good    Nehru Place      Delhi  \n",
       "11977                  Good    Nehru Place      Delhi  \n",
       "11978                  Good    Nehru Place      Delhi  \n",
       "11979             Very Good    Nehru Place      Delhi  \n",
       "11980             Excellent    Nehru Place      Delhi  \n",
       "11981             Excellent    Nehru Place      Delhi  \n",
       "\n",
       "[11982 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Original_price</th>\n",
       "      <th>Offer</th>\n",
       "      <th>Final_price</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Number_of_Rating</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Location</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OYO 22085 Raj Banjara White House</td>\n",
       "      <td>2459.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1677.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>201.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Collection O 42514 Venkat Nagar</td>\n",
       "      <td>3158.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2153.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>4.4</td>\n",
       "      <td>879.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Capital O 44354 Jubilee Banjara Suites</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1213.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1258.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OYO 35487 Hotel Meena Grand</td>\n",
       "      <td>2090.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1425.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>575.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OYO 16018 Rainbow Saphire</td>\n",
       "      <td>2607.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1777.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.7</td>\n",
       "      <td>978.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Name  Original_price  Offer  Final_price  \\\n",
       "0       OYO 22085 Raj Banjara White House          2459.0   32.0       1677.0   \n",
       "1         Collection O 42514 Venkat Nagar          3158.0   32.0       2153.0   \n",
       "2  Capital O 44354 Jubilee Banjara Suites          1778.0   32.0       1213.0   \n",
       "3             OYO 35487 Hotel Meena Grand          2090.0   32.0       1425.0   \n",
       "4               OYO 16018 Rainbow Saphire          2607.0   32.0       1777.0   \n",
       "\n",
       "   Distance  Rating  Number_of_Rating    Summary       Location       City  \n",
       "0       1.7     4.4             201.0  Very Good  Banjara Hills  Hyderabad  \n",
       "1       1.6     4.4             879.0  Very Good  Banjara Hills  Hyderabad  \n",
       "2       1.1     4.4            1258.0  Very Good  Banjara Hills  Hyderabad  \n",
       "3       4.0     4.0             575.0  Very Good  Banjara Hills  Hyderabad  \n",
       "4       4.6     4.7             978.0  Excellent  Banjara Hills  Hyderabad  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Original_price</th>\n",
       "      <th>Offer</th>\n",
       "      <th>Final_price</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Number_of_Rating</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Location</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11977</th>\n",
       "      <td>OYO 472 Hotel Sareen</td>\n",
       "      <td>2389.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1552.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11978</th>\n",
       "      <td>OYO 43002 The Royal Town Deluxe</td>\n",
       "      <td>4522.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3083.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11979</th>\n",
       "      <td>OYO 48664 Gour White House</td>\n",
       "      <td>2526.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1723.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.3</td>\n",
       "      <td>245.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11980</th>\n",
       "      <td>OYO 12532 Imperial Inn Deluxe</td>\n",
       "      <td>7544.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5144.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>4.8</td>\n",
       "      <td>271.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11981</th>\n",
       "      <td>OYO 13235 The Golden Door</td>\n",
       "      <td>6855.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4674.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.5</td>\n",
       "      <td>173.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Nehru Place</td>\n",
       "      <td>Delhi</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Name  Original_price  Offer  Final_price  \\\n",
       "11977             OYO 472 Hotel Sareen          2389.0   35.0       1552.0   \n",
       "11978  OYO 43002 The Royal Town Deluxe          4522.0   32.0       3083.0   \n",
       "11979       OYO 48664 Gour White House          2526.0   32.0       1723.0   \n",
       "11980    OYO 12532 Imperial Inn Deluxe          7544.0   32.0       5144.0   \n",
       "11981        OYO 13235 The Golden Door          6855.0   32.0       4674.0   \n",
       "\n",
       "       Distance  Rating  Number_of_Rating    Summary     Location   City  \n",
       "11977       2.0     3.7              90.0       Good  Nehru Place  Delhi  \n",
       "11978       1.0     3.6             114.0       Good  Nehru Place  Delhi  \n",
       "11979       2.8     4.3             245.0  Very Good  Nehru Place  Delhi  \n",
       "11980       1.3     4.8             271.0  Excellent  Nehru Place  Delhi  \n",
       "11981       2.8     4.5             173.0  Excellent  Nehru Place  Delhi  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11982, 10)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- The total data includes 11982 hotels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Name', 'Original_price', 'Offer', 'Final_price', 'Distance', 'Rating',\n",
       "       'Number_of_Rating', 'Summary', 'Location', 'City'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name                 object\n",
       "Original_price      float64\n",
       "Offer               float64\n",
       "Final_price         float64\n",
       "Distance            float64\n",
       "Rating              float64\n",
       "Number_of_Rating    float64\n",
       "Summary              object\n",
       "Location             object\n",
       "City                 object\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Understand Categorical Data\n",
    "\n",
    "- Columns containing categorical columns:\n",
    "    - City\n",
    "    - Location\n",
    "    - Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## City"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Hyderabad', 'Bangalore', 'Chennai', 'Mumbai', 'Delhi'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['City'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['City'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Delhi        3602\n",
       "Bangalore    2720\n",
       "Hyderabad    2440\n",
       "Chennai      1760\n",
       "Mumbai       1460\n",
       "Name: City, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['City'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- We can see from the above data that, Delhi has the maximum number of hotels compared to the rest.\n",
    "- While Chennai has the least number of hotels."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Banjara Hills', 'Jubilee Hills', 'Kondapur', 'Hitech City',\n",
       "       'Begumpet', 'Mehdipatnam', 'Kachiguda Railway Station',\n",
       "       'Secunderabad Railway Station', 'LB Nagar', 'Kukatpally', 'Uppal',\n",
       "       'Gachibowli', 'Ameerpet', 'Rajiv Gandhi International Airport',\n",
       "       'Lakdikapool', 'Shamshabad', 'Himayathnagar', 'Madhapur',\n",
       "       'Miyapur', 'Nampally', 'Indiranagar', 'Domlur', 'Majestic',\n",
       "       'Jayanagar', 'Whitefield', 'Majestic City Railway Station',\n",
       "       'Kempagowda International Airport', 'Kalyan Nagar', 'Rajaji Nagar',\n",
       "       'Hebbal', 'HSR Layout', 'Yelahanka', 'MG Road', 'KR Puram',\n",
       "       'Jp Nagar', 'Electronic City', 'Yeshwanthpur', 'Koramangala',\n",
       "       'BTM 2ndStage', 'Marathahalli', 'Sholinganallur', 'Velachery',\n",
       "       'Egmore', 'Chennai Central Railway Station', 'Guindy',\n",
       "       'Vadapalani', 'Mogappair', 'Porur', 'Thiruvanmiyu',\n",
       "       'Chennai International Airport', 'East Coast Road', 'Tnagar',\n",
       "       'Nungambakkam', 'Koyambedu', 'Chennai Egmore Railway Station',\n",
       "       'Old Mahabalipuram Road', 'Thoraipakkam', 'Tambaram', 'Medavakkam',\n",
       "       'Adyar', 'Sakinaka', 'Panvel', 'Bandra Kurla Complex',\n",
       "       'Dadar Railway Station', 'Andheri West', 'Thane', 'Ghatkopar',\n",
       "       'Andheri East', 'Andheri', 'CBD Belapur', 'Mumbai Central',\n",
       "       'Malad West', 'Mumbai Airport', 'CST Railway Station', 'Chembur',\n",
       "       'Bandra', 'Dadar', 'Navi Mumbai', 'Vashi', 'Powai',\n",
       "       'Indira Gandhi Airport', 'Pitampura',\n",
       "       'Hazrat Nizammudin Railway Station', 'Rohini', 'Greater Kailash',\n",
       "       'Paschim Vihar', 'Kalkaji', 'New Delhi', 'Sector 7 Dwaraka',\n",
       "       'Laxminagar', 'Saket', 'Kashmiri Gate ISBT', 'Paharganj',\n",
       "       'Mahipalpur', 'Karol Bagh', 'New Delhi Railway Station', 'Dwaraka',\n",
       "       'Lajpat Nagar', 'Karol Bagh Metro Station', 'Nehru Place'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Location'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Location'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mahipalpur                            320\n",
       "Laxminagar                            260\n",
       "New Delhi Railway Station             260\n",
       "Sector 7 Dwaraka                      240\n",
       "MG Road                               240\n",
       "Saket                                 220\n",
       "Hazrat Nizammudin Railway Station     200\n",
       "Jayanagar                             200\n",
       "Paschim Vihar                         200\n",
       "Karol Bagh                            200\n",
       "Paharganj                             200\n",
       "Domlur                                200\n",
       "Karol Bagh Metro Station              200\n",
       "Jubilee Hills                         180\n",
       "Majestic                              180\n",
       "Indira Gandhi Airport                 180\n",
       "Indiranagar                           180\n",
       "BTM 2ndStage                          180\n",
       "Kashmiri Gate ISBT                    180\n",
       "Pitampura                             180\n",
       "Jp Nagar                              180\n",
       "Banjara Hills                         180\n",
       "Majestic City Railway Station         180\n",
       "Koramangala                           180\n",
       "Rohini                                162\n",
       "Kalyan Nagar                          160\n",
       "Nungambakkam                          160\n",
       "Koyambedu                             160\n",
       "Begumpet                              160\n",
       "Adyar                                 160\n",
       "                                     ... \n",
       "Miyapur                                80\n",
       "Velachery                              80\n",
       "Powai                                  80\n",
       "Thiruvanmiyu                           80\n",
       "Yelahanka                              80\n",
       "Chembur                                80\n",
       "Chennai International Airport          80\n",
       "Porur                                  60\n",
       "KR Puram                               60\n",
       "Marathahalli                           60\n",
       "Kempagowda International Airport       60\n",
       "Uppal                                  40\n",
       "Old Mahabalipuram Road                 40\n",
       "Electronic City                        40\n",
       "Thoraipakkam                           40\n",
       "Rajiv Gandhi International Airport     40\n",
       "Medavakkam                             40\n",
       "Shamshabad                             40\n",
       "Dadar                                  20\n",
       "Navi Mumbai                            20\n",
       "Sholinganallur                         20\n",
       "Tambaram                               20\n",
       "Whitefield                             20\n",
       "New Delhi                              20\n",
       "Dadar Railway Station                  20\n",
       "Panvel                                 20\n",
       "Vashi                                  20\n",
       "Malad West                             20\n",
       "CBD Belapur                            20\n",
       "East Coast Road                        20\n",
       "Name: Location, Length: 100, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Location'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- There are 100 locations.\n",
    "- Mahipalpur has the most number of hotels."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Very Good', 'Excellent', 'Good', 'Fair', 'Yet to be summarised',\n",
       "       'Fabulous'], dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Summary'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Summary'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Very Good               4982\n",
       "Good                    3067\n",
       "Excellent               1743\n",
       "Yet to be summarised    1122\n",
       "Fair                     980\n",
       "Fabulous                  88\n",
       "Name: Summary, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Summary'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- It can be seen that the summary has been divided into 6.\n",
    "- 4982 hotels from the data fall under 'Very Good'.\n",
    "- While only 88 hotels are 'Fabulous'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Understand Numerical Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Original_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11982.000000\n",
       "mean      2895.721249\n",
       "std       1870.412218\n",
       "min        602.000000\n",
       "25%       1797.000000\n",
       "50%       2299.000000\n",
       "75%       3305.000000\n",
       "max      32452.000000\n",
       "Name: Original_price, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Original_price'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Minimum Original_price for the data is Rs.602\n",
    "- Maximum Original_price for the data is Rs.32452\n",
    "- Mean value of Original_price is Rs.2895.7212\n",
    "- Median value of Original_price is Rs.2299\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Offer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11982.000000\n",
       "mean        34.331247\n",
       "std          5.889520\n",
       "min         32.000000\n",
       "25%         32.000000\n",
       "50%         32.000000\n",
       "75%         32.000000\n",
       "max         71.000000\n",
       "Name: Offer, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Offer'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Minimum Offer for the data is 32%\n",
    "- Maximum Offer for the data is 71%\n",
    "- Mean value of Offer is 34.33%\n",
    "- Median value of Offer is 32%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11982.000000\n",
       "mean      1908.409698\n",
       "std       1272.557859\n",
       "min        411.000000\n",
       "25%       1212.000000\n",
       "50%       1506.000000\n",
       "75%       2135.250000\n",
       "max      20651.000000\n",
       "Name: Final_price, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Final_price'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Minimum Final_price for the data is Rs.411\n",
    "- Maximum Final_price for the data is Rs.20651\n",
    "- Mean value of Final_price is Rs.1908.409698\n",
    "- Median value of Final_price is Rs.1506"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11982.000000\n",
       "mean         6.155658\n",
       "std          3.386736\n",
       "min          0.000000\n",
       "25%          3.600000\n",
       "50%          6.200000\n",
       "75%          8.300000\n",
       "max         20.000000\n",
       "Name: Distance, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Distance'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Minimum Distance for the data is 0.0 km\n",
    "- Maximum Distance for the data is 20 km\n",
    "- Mean value of Distance is 6.155658 km\n",
    "- Median value of Distance is 6.2 km"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11982.000000\n",
       "mean         3.670547\n",
       "std          1.243398\n",
       "min          0.000000\n",
       "25%          3.600000\n",
       "50%          4.000000\n",
       "75%          4.300000\n",
       "max          5.000000\n",
       "Name: Rating, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Rating'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Minimum Rating for the data is 0\n",
    "- Maximum Rating for the data is 5\n",
    "- Mean value of Rating is 3.67\n",
    "- Median value of Rating is 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Number of Rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    11982.000000\n",
       "mean       588.801536\n",
       "std        807.178290\n",
       "min          0.000000\n",
       "25%        116.000000\n",
       "50%        290.000000\n",
       "75%        719.000000\n",
       "max       6943.000000\n",
       "Name: Number_of_Rating, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Number_of_Rating'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Minimum Number of Rating for the data is 0 Ratings\n",
    "- Maximum Number of Rating for the data is 6943 Ratings\n",
    "- Mean value of Number of Rating is 588.801536 Ratings\n",
    "- Median value of Number of Rating is 290 Ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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