Bivariate Analysis.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',index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 22085 Raj Banjara White House</th>\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>Collection O 42514 Venkat Nagar</th>\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>Capital O 44354 Jubilee Banjara Suites</th>\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>OYO 35487 Hotel Meena Grand</th>\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>OYO 16018 Rainbow Saphire</th>\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>Collection O 46198 New Sree Krishna</th>\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>OYO 14224 Happy Guest house</th>\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>OYO 62547 Dream Connect Stays</th>\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>OYO 11376 Golden Park</th>\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>OYO 11316 Athithi Inn</th>\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>OYO 10272 Hotel Ruma</th>\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>OYO 18725 Sr Grand</th>\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>OYO 18302 Pride Banjara</th>\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>OYO 983 Hotel Surya Residency</th>\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>Capital O 46832 Gaayatri Residency Deluxe</th>\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>OYO 4025 Hotel Meredian Orchid</th>\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>OYO Townhouse 045 Lakdi ka Pul</th>\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>OYO 41751 Hotel Sabharwal</th>\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>OYO 47332 Hotel Dolphin</th>\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>OYO 30744 The  Gate</th>\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>OYO 37906 New Asian Lodge</th>\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>OYO 26562 Dazzle Stays</th>\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>SilverKey Executive Stays 27773 IAS Colony</th>\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>OYO 1410 Country Club Begumpet</th>\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>OYO 22907 Hotel Holiday Deluxe</th>\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>OYO 47727 S Grand</th>\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>Capital O 6422 Luxor Park</th>\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>OYO 9302 Hotel Baseraa Inn</th>\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>OYO 8941 Hotel Golden Leaves</th>\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>OYO Flagship 14348 Apollo Hospital</th>\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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 46744 Hotel Yash</th>\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>OYO 62553 Suvee Palace</th>\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>OYO 61639 Red Carmine</th>\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>OYO 44324 Comfort Stay Near Saket Metro</th>\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>OYO Home Luxe 30142 Fabulous Farmstay</th>\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>OYO 22321 Nitin Palace Guest House</th>\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>OYO Townhouse 002 Green Park</th>\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>Capital O 7075 The Oakland Plaza Hotel Deluxe</th>\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>OYO 14789 Kempinski Wide</th>\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>OYO 63837 Ambica Inn</th>\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>OYO 37512 Spacious Stay Saket Metro</th>\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>OYO 60334 Skp Bed &amp; Breakfast</th>\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>OYO 64271 Singh Hotel 2</th>\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>OYO 37055 M R Residency Saver</th>\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>Capital O 712 Defence Colony Deluxe</th>\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>OYO Home 47965 Cozy Stay Ignou Road Saket</th>\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>OYO Home 47964 Comfortable  Stay Ignou Road Saket</th>\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>OYO 44400 Retreat Inn</th>\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>OYO Flagship 36485 Smg Heritage Nehru Enclave</th>\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>Capital O 39462 Westyard Hotel</th>\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>OYO 40657 Aastha</th>\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>OYO 14765 Amar Villa</th>\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>OYO 7304 Stay Jangpura</th>\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>OYO 9536 Bee For Home Stay</th>\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>OYO 543 La Ola Boutique Hotel</th>\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>OYO 472 Hotel Sareen</th>\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>OYO 43002 The Royal Town Deluxe</th>\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>OYO 48664 Gour White House</th>\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>OYO 12532 Imperial Inn Deluxe</th>\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>OYO 13235 The Golden Door</th>\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 × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   Original_price  Offer  \\\n",
       "Name                                                                       \n",
       "OYO 22085 Raj Banjara White House                          2459.0   32.0   \n",
       "Collection O 42514 Venkat Nagar                            3158.0   32.0   \n",
       "Capital O 44354 Jubilee Banjara Suites                     1778.0   32.0   \n",
       "OYO 35487 Hotel Meena Grand                                2090.0   32.0   \n",
       "OYO 16018 Rainbow Saphire                                  2607.0   32.0   \n",
       "Collection O 46198 New Sree Krishna                        3964.0   32.0   \n",
       "OYO 14224 Happy Guest house                                2373.0   32.0   \n",
       "OYO 62547 Dream Connect Stays                              1941.0   32.0   \n",
       "OYO 11376 Golden Park                                      2205.0   45.0   \n",
       "OYO 11316 Athithi Inn                                      2178.0   38.0   \n",
       "OYO 10272 Hotel Ruma                                       1777.0   32.0   \n",
       "OYO 18725 Sr Grand                                         1910.0   32.0   \n",
       "OYO 18302 Pride Banjara                                    2260.0   32.0   \n",
       "OYO 983 Hotel Surya Residency                              2811.0   32.0   \n",
       "Capital O 46832 Gaayatri Residency Deluxe                  2098.0   32.0   \n",
       "OYO 4025 Hotel Meredian Orchid                             1865.0   35.0   \n",
       "OYO Townhouse 045 Lakdi ka Pul                             5129.0   32.0   \n",
       "OYO 41751 Hotel Sabharwal                                  1416.0   32.0   \n",
       "OYO 47332 Hotel Dolphin                                    2509.0   32.0   \n",
       "OYO 30744 The  Gate                                        2140.0   32.0   \n",
       "OYO 37906 New Asian Lodge                                  2420.0   32.0   \n",
       "OYO 26562 Dazzle Stays                                     1730.0   42.0   \n",
       "SilverKey Executive Stays 27773 IAS Colony                 1639.0   40.0   \n",
       "OYO 1410 Country Club Begumpet                             4417.0   32.0   \n",
       "OYO 22907 Hotel Holiday Deluxe                             2407.0   32.0   \n",
       "OYO 47727 S Grand                                          1427.0   32.0   \n",
       "Capital O 6422 Luxor Park                                  2737.0   32.0   \n",
       "OYO 9302 Hotel Baseraa Inn                                 2081.0   32.0   \n",
       "OYO 8941 Hotel Golden Leaves                               2449.0   32.0   \n",
       "OYO Flagship 14348 Apollo Hospital                         2746.0   44.0   \n",
       "...                                                           ...    ...   \n",
       "OYO 46744 Hotel Yash                                       1481.0   32.0   \n",
       "OYO 62553 Suvee Palace                                     1294.0   32.0   \n",
       "OYO 61639 Red Carmine                                      1777.0   32.0   \n",
       "OYO 44324 Comfort Stay Near Saket Metro                    2989.0   32.0   \n",
       "OYO Home Luxe 30142 Fabulous Farmstay                      2548.0   49.0   \n",
       "OYO 22321 Nitin Palace Guest House                         2822.0   32.0   \n",
       "OYO Townhouse 002 Green Park                               7806.0   32.0   \n",
       "Capital O 7075 The Oakland Plaza Hotel Deluxe              3078.0   32.0   \n",
       "OYO 14789 Kempinski Wide                                   3534.0   34.0   \n",
       "OYO 63837 Ambica Inn                                       2729.0   32.0   \n",
       "OYO 37512 Spacious Stay Saket Metro                        1981.0   32.0   \n",
       "OYO 60334 Skp Bed & Breakfast                              2225.0   32.0   \n",
       "OYO 64271 Singh Hotel 2                                    1140.0   32.0   \n",
       "OYO 37055 M R Residency Saver                              1481.0   32.0   \n",
       "Capital O 712 Defence Colony Deluxe                        3738.0   32.0   \n",
       "OYO Home 47965 Cozy Stay Ignou Road Saket                  2720.0   32.0   \n",
       "OYO Home 47964 Comfortable  Stay Ignou Road Saket          2720.0   32.0   \n",
       "OYO 44400 Retreat Inn                                      1878.0   32.0   \n",
       "OYO Flagship 36485 Smg Heritage Nehru Enclave              1777.0   32.0   \n",
       "Capital O 39462 Westyard Hotel                             2863.0   32.0   \n",
       "OYO 40657 Aastha                                           1372.0   32.0   \n",
       "OYO 14765 Amar Villa                                       4239.0   53.0   \n",
       "OYO 7304 Stay Jangpura                                     2843.0   32.0   \n",
       "OYO 9536 Bee For Home Stay                                 5011.0   62.0   \n",
       "OYO 543 La Ola Boutique Hotel                              2766.0   32.0   \n",
       "OYO 472 Hotel Sareen                                       2389.0   35.0   \n",
       "OYO 43002 The Royal Town Deluxe                            4522.0   32.0   \n",
       "OYO 48664 Gour White House                                 2526.0   32.0   \n",
       "OYO 12532 Imperial Inn Deluxe                              7544.0   32.0   \n",
       "OYO 13235 The Golden Door                                  6855.0   32.0   \n",
       "\n",
       "                                                   Final_price  Distance  \\\n",
       "Name                                                                       \n",
       "OYO 22085 Raj Banjara White House                       1677.0       1.7   \n",
       "Collection O 42514 Venkat Nagar                         2153.0       1.6   \n",
       "Capital O 44354 Jubilee Banjara Suites                  1213.0       1.1   \n",
       "OYO 35487 Hotel Meena Grand                             1425.0       4.0   \n",
       "OYO 16018 Rainbow Saphire                               1777.0       4.6   \n",
       "Collection O 46198 New Sree Krishna                     2703.0       6.1   \n",
       "OYO 14224 Happy Guest house                             1618.0       1.8   \n",
       "OYO 62547 Dream Connect Stays                           1324.0       0.6   \n",
       "OYO 11376 Golden Park                                   1212.0       5.3   \n",
       "OYO 11316 Athithi Inn                                   1348.0       4.8   \n",
       "OYO 10272 Hotel Ruma                                    1212.0       4.2   \n",
       "OYO 18725 Sr Grand                                      1303.0       3.3   \n",
       "OYO 18302 Pride Banjara                                 1541.0       1.1   \n",
       "OYO 983 Hotel Surya Residency                           1917.0       3.2   \n",
       "Capital O 46832 Gaayatri Residency Deluxe               1431.0       4.1   \n",
       "OYO 4025 Hotel Meredian Orchid                          1212.0       2.7   \n",
       "OYO Townhouse 045 Lakdi ka Pul                          3497.0       4.4   \n",
       "OYO 41751 Hotel Sabharwal                                966.0       7.2   \n",
       "OYO 47332 Hotel Dolphin                                 1711.0       4.2   \n",
       "OYO 30744 The  Gate                                     1459.0       3.4   \n",
       "OYO 37906 New Asian Lodge                               1650.0       4.0   \n",
       "OYO 26562 Dazzle Stays                                  1010.0       6.7   \n",
       "SilverKey Executive Stays 27773 IAS Colony               991.0       2.9   \n",
       "OYO 1410 Country Club Begumpet                          3012.0       5.9   \n",
       "OYO 22907 Hotel Holiday Deluxe                          1642.0       5.9   \n",
       "OYO 47727 S Grand                                        973.0       4.6   \n",
       "Capital O 6422 Luxor Park                               1867.0       7.1   \n",
       "OYO 9302 Hotel Baseraa Inn                              1419.0       6.8   \n",
       "OYO 8941 Hotel Golden Leaves                            1670.0       6.7   \n",
       "OYO Flagship 14348 Apollo Hospital                      1525.0       3.6   \n",
       "...                                                        ...       ...   \n",
       "OYO 46744 Hotel Yash                                    1010.0       8.5   \n",
       "OYO 62553 Suvee Palace                                   883.0       8.0   \n",
       "OYO 61639 Red Carmine                                   1212.0       8.9   \n",
       "OYO 44324 Comfort Stay Near Saket Metro                 2038.0       8.7   \n",
       "OYO Home Luxe 30142 Fabulous Farmstay                   1299.0       9.2   \n",
       "OYO 22321 Nitin Palace Guest House                      1924.0       6.8   \n",
       "OYO Townhouse 002 Green Park                            5323.0       7.3   \n",
       "Capital O 7075 The Oakland Plaza Hotel Deluxe           2099.0       1.6   \n",
       "OYO 14789 Kempinski Wide                                2349.0       3.2   \n",
       "OYO 63837 Ambica Inn                                    1861.0       5.4   \n",
       "OYO 37512 Spacious Stay Saket Metro                     1351.0       6.8   \n",
       "OYO 60334 Skp Bed & Breakfast                           1517.0       8.2   \n",
       "OYO 64271 Singh Hotel 2                                  778.0       6.1   \n",
       "OYO 37055 M R Residency Saver                           1010.0       8.7   \n",
       "Capital O 712 Defence Colony Deluxe                     2549.0       4.2   \n",
       "OYO Home 47965 Cozy Stay Ignou Road Saket               1855.0       6.3   \n",
       "OYO Home 47964 Comfortable  Stay Ignou Road Saket       1855.0       6.4   \n",
       "OYO 44400 Retreat Inn                                   1281.0       8.6   \n",
       "OYO Flagship 36485 Smg Heritage Nehru Enclave           1212.0       8.8   \n",
       "Capital O 39462 Westyard Hotel                          1952.0       5.6   \n",
       "OYO 40657 Aastha                                         936.0      10.0   \n",
       "OYO 14765 Amar Villa                                    2010.0       6.7   \n",
       "OYO 7304 Stay Jangpura                                  1939.0       7.0   \n",
       "OYO 9536 Bee For Home Stay                              1899.0       7.3   \n",
       "OYO 543 La Ola Boutique Hotel                           1886.0       1.5   \n",
       "OYO 472 Hotel Sareen                                    1552.0       2.0   \n",
       "OYO 43002 The Royal Town Deluxe                         3083.0       1.0   \n",
       "OYO 48664 Gour White House                              1723.0       2.8   \n",
       "OYO 12532 Imperial Inn Deluxe                           5144.0       1.3   \n",
       "OYO 13235 The Golden Door                               4674.0       2.8   \n",
       "\n",
       "                                                   Rating  Number_of_Rating  \\\n",
       "Name                                                                          \n",
       "OYO 22085 Raj Banjara White House                     4.4             201.0   \n",
       "Collection O 42514 Venkat Nagar                       4.4             879.0   \n",
       "Capital O 44354 Jubilee Banjara Suites                4.4            1258.0   \n",
       "OYO 35487 Hotel Meena Grand                           4.0             575.0   \n",
       "OYO 16018 Rainbow Saphire                             4.7             978.0   \n",
       "Collection O 46198 New Sree Krishna                   3.9             989.0   \n",
       "OYO 14224 Happy Guest house                           4.6             448.0   \n",
       "OYO 62547 Dream Connect Stays                         4.3             267.0   \n",
       "OYO 11376 Golden Park                                 4.4            1570.0   \n",
       "OYO 11316 Athithi Inn                                 3.3             697.0   \n",
       "OYO 10272 Hotel Ruma                                  4.2             488.0   \n",
       "OYO 18725 Sr Grand                                    4.4             294.0   \n",
       "OYO 18302 Pride Banjara                               0.0               0.0   \n",
       "OYO 983 Hotel Surya Residency                         4.2             264.0   \n",
       "Capital O 46832 Gaayatri Residency Deluxe             4.8             644.0   \n",
       "OYO 4025 Hotel Meredian Orchid                        4.1             558.0   \n",
       "OYO Townhouse 045 Lakdi ka Pul                        4.3            1934.0   \n",
       "OYO 41751 Hotel Sabharwal                             4.2             786.0   \n",
       "OYO 47332 Hotel Dolphin                               4.4             279.0   \n",
       "OYO 30744 The  Gate                                   4.3             440.0   \n",
       "OYO 37906 New Asian Lodge                             3.2             349.0   \n",
       "OYO 26562 Dazzle Stays                                3.9             371.0   \n",
       "SilverKey Executive Stays 27773 IAS Colony            3.8            2195.0   \n",
       "OYO 1410 Country Club Begumpet                        3.6             366.0   \n",
       "OYO 22907 Hotel Holiday Deluxe                        4.5             393.0   \n",
       "OYO 47727 S Grand                                     4.4             360.0   \n",
       "Capital O 6422 Luxor Park                             4.5            1914.0   \n",
       "OYO 9302 Hotel Baseraa Inn                            4.5             170.0   \n",
       "OYO 8941 Hotel Golden Leaves                          4.4             728.0   \n",
       "OYO Flagship 14348 Apollo Hospital                    4.3            1422.0   \n",
       "...                                                   ...               ...   \n",
       "OYO 46744 Hotel Yash                                  4.3             161.0   \n",
       "OYO 62553 Suvee Palace                                0.0               0.0   \n",
       "OYO 61639 Red Carmine                                 4.6             104.0   \n",
       "OYO 44324 Comfort Stay Near Saket Metro               4.6             878.0   \n",
       "OYO Home Luxe 30142 Fabulous Farmstay                 4.6             535.0   \n",
       "OYO 22321 Nitin Palace Guest House                    4.7             279.0   \n",
       "OYO Townhouse 002 Green Park                          4.8            1390.0   \n",
       "Capital O 7075 The Oakland Plaza Hotel Deluxe         4.0            1025.0   \n",
       "OYO 14789 Kempinski Wide                              4.3             195.0   \n",
       "OYO 63837 Ambica Inn                                  0.0               0.0   \n",
       "OYO 37512 Spacious Stay Saket Metro                   4.0             413.0   \n",
       "OYO 60334 Skp Bed & Breakfast                         3.4             114.0   \n",
       "OYO 64271 Singh Hotel 2                               0.0               0.0   \n",
       "OYO 37055 M R Residency Saver                         4.4             541.0   \n",
       "Capital O 712 Defence Colony Deluxe                   4.2             723.0   \n",
       "OYO Home 47965 Cozy Stay Ignou Road Saket             0.0               0.0   \n",
       "OYO Home 47964 Comfortable  Stay Ignou Road Saket     0.0               0.0   \n",
       "OYO 44400 Retreat Inn                                 3.7             315.0   \n",
       "OYO Flagship 36485 Smg Heritage Nehru Enclave         3.8            3842.0   \n",
       "Capital O 39462 Westyard Hotel                        4.0            2104.0   \n",
       "OYO 40657 Aastha                                      4.0             332.0   \n",
       "OYO 14765 Amar Villa                                  3.8             126.0   \n",
       "OYO 7304 Stay Jangpura                                0.0               0.0   \n",
       "OYO 9536 Bee For Home Stay                            4.2              47.0   \n",
       "OYO 543 La Ola Boutique Hotel                         4.2             143.0   \n",
       "OYO 472 Hotel Sareen                                  3.7              90.0   \n",
       "OYO 43002 The Royal Town Deluxe                       3.6             114.0   \n",
       "OYO 48664 Gour White House                            4.3             245.0   \n",
       "OYO 12532 Imperial Inn Deluxe                         4.8             271.0   \n",
       "OYO 13235 The Golden Door                             4.5             173.0   \n",
       "\n",
       "                                                                Summary  \\\n",
       "Name                                                                      \n",
       "OYO 22085 Raj Banjara White House                             Very Good   \n",
       "Collection O 42514 Venkat Nagar                               Very Good   \n",
       "Capital O 44354 Jubilee Banjara Suites                        Very Good   \n",
       "OYO 35487 Hotel Meena Grand                                   Very Good   \n",
       "OYO 16018 Rainbow Saphire                                     Excellent   \n",
       "Collection O 46198 New Sree Krishna                                Good   \n",
       "OYO 14224 Happy Guest house                                   Excellent   \n",
       "OYO 62547 Dream Connect Stays                                 Very Good   \n",
       "OYO 11376 Golden Park                                         Very Good   \n",
       "OYO 11316 Athithi Inn                                              Fair   \n",
       "OYO 10272 Hotel Ruma                                          Very Good   \n",
       "OYO 18725 Sr Grand                                            Very Good   \n",
       "OYO 18302 Pride Banjara                            Yet to be summarised   \n",
       "OYO 983 Hotel Surya Residency                                 Very Good   \n",
       "Capital O 46832 Gaayatri Residency Deluxe                     Excellent   \n",
       "OYO 4025 Hotel Meredian Orchid                                Very Good   \n",
       "OYO Townhouse 045 Lakdi ka Pul                                Very Good   \n",
       "OYO 41751 Hotel Sabharwal                                     Very Good   \n",
       "OYO 47332 Hotel Dolphin                                       Very Good   \n",
       "OYO 30744 The  Gate                                           Very Good   \n",
       "OYO 37906 New Asian Lodge                                          Fair   \n",
       "OYO 26562 Dazzle Stays                                             Good   \n",
       "SilverKey Executive Stays 27773 IAS Colony                         Good   \n",
       "OYO 1410 Country Club Begumpet                                     Good   \n",
       "OYO 22907 Hotel Holiday Deluxe                                Excellent   \n",
       "OYO 47727 S Grand                                             Very Good   \n",
       "Capital O 6422 Luxor Park                                     Excellent   \n",
       "OYO 9302 Hotel Baseraa Inn                                    Excellent   \n",
       "OYO 8941 Hotel Golden Leaves                                  Very Good   \n",
       "OYO Flagship 14348 Apollo Hospital                            Very Good   \n",
       "...                                                                 ...   \n",
       "OYO 46744 Hotel Yash                                          Very Good   \n",
       "OYO 62553 Suvee Palace                             Yet to be summarised   \n",
       "OYO 61639 Red Carmine                                         Excellent   \n",
       "OYO 44324 Comfort Stay Near Saket Metro                       Excellent   \n",
       "OYO Home Luxe 30142 Fabulous Farmstay                         Excellent   \n",
       "OYO 22321 Nitin Palace Guest House                            Excellent   \n",
       "OYO Townhouse 002 Green Park                                  Excellent   \n",
       "Capital O 7075 The Oakland Plaza Hotel Deluxe                 Very Good   \n",
       "OYO 14789 Kempinski Wide                                      Very Good   \n",
       "OYO 63837 Ambica Inn                               Yet to be summarised   \n",
       "OYO 37512 Spacious Stay Saket Metro                           Very Good   \n",
       "OYO 60334 Skp Bed & Breakfast                                      Fair   \n",
       "OYO 64271 Singh Hotel 2                            Yet to be summarised   \n",
       "OYO 37055 M R Residency Saver                                 Very Good   \n",
       "Capital O 712 Defence Colony Deluxe                           Very Good   \n",
       "OYO Home 47965 Cozy Stay Ignou Road Saket          Yet to be summarised   \n",
       "OYO Home 47964 Comfortable  Stay Ignou Road Saket  Yet to be summarised   \n",
       "OYO 44400 Retreat Inn                                              Good   \n",
       "OYO Flagship 36485 Smg Heritage Nehru Enclave                      Good   \n",
       "Capital O 39462 Westyard Hotel                                Very Good   \n",
       "OYO 40657 Aastha                                              Very Good   \n",
       "OYO 14765 Amar Villa                                               Good   \n",
       "OYO 7304 Stay Jangpura                             Yet to be summarised   \n",
       "OYO 9536 Bee For Home Stay                                    Very Good   \n",
       "OYO 543 La Ola Boutique Hotel                                 Very Good   \n",
       "OYO 472 Hotel Sareen                                               Good   \n",
       "OYO 43002 The Royal Town Deluxe                                    Good   \n",
       "OYO 48664 Gour White House                                    Very Good   \n",
       "OYO 12532 Imperial Inn Deluxe                                 Excellent   \n",
       "OYO 13235 The Golden Door                                     Excellent   \n",
       "\n",
       "                                                        Location       City  \n",
       "Name                                                                         \n",
       "OYO 22085 Raj Banjara White House                  Banjara Hills  Hyderabad  \n",
       "Collection O 42514 Venkat Nagar                    Banjara Hills  Hyderabad  \n",
       "Capital O 44354 Jubilee Banjara Suites             Banjara Hills  Hyderabad  \n",
       "OYO 35487 Hotel Meena Grand                        Banjara Hills  Hyderabad  \n",
       "OYO 16018 Rainbow Saphire                          Banjara Hills  Hyderabad  \n",
       "Collection O 46198 New Sree Krishna                Banjara Hills  Hyderabad  \n",
       "OYO 14224 Happy Guest house                        Banjara Hills  Hyderabad  \n",
       "OYO 62547 Dream Connect Stays                      Banjara Hills  Hyderabad  \n",
       "OYO 11376 Golden Park                              Banjara Hills  Hyderabad  \n",
       "OYO 11316 Athithi Inn                              Banjara Hills  Hyderabad  \n",
       "OYO 10272 Hotel Ruma                               Banjara Hills  Hyderabad  \n",
       "OYO 18725 Sr Grand                                 Banjara Hills  Hyderabad  \n",
       "OYO 18302 Pride Banjara                            Banjara Hills  Hyderabad  \n",
       "OYO 983 Hotel Surya Residency                      Banjara Hills  Hyderabad  \n",
       "Capital O 46832 Gaayatri Residency Deluxe          Banjara Hills  Hyderabad  \n",
       "OYO 4025 Hotel Meredian Orchid                     Banjara Hills  Hyderabad  \n",
       "OYO Townhouse 045 Lakdi ka Pul                     Banjara Hills  Hyderabad  \n",
       "OYO 41751 Hotel Sabharwal                          Banjara Hills  Hyderabad  \n",
       "OYO 47332 Hotel Dolphin                            Banjara Hills  Hyderabad  \n",
       "OYO 30744 The  Gate                                Banjara Hills  Hyderabad  \n",
       "OYO 37906 New Asian Lodge                          Banjara Hills  Hyderabad  \n",
       "OYO 26562 Dazzle Stays                             Banjara Hills  Hyderabad  \n",
       "SilverKey Executive Stays 27773 IAS Colony         Banjara Hills  Hyderabad  \n",
       "OYO 1410 Country Club Begumpet                     Banjara Hills  Hyderabad  \n",
       "OYO 22907 Hotel Holiday Deluxe                     Banjara Hills  Hyderabad  \n",
       "OYO 47727 S Grand                                  Banjara Hills  Hyderabad  \n",
       "Capital O 6422 Luxor Park                          Banjara Hills  Hyderabad  \n",
       "OYO 9302 Hotel Baseraa Inn                         Banjara Hills  Hyderabad  \n",
       "OYO 8941 Hotel Golden Leaves                       Banjara Hills  Hyderabad  \n",
       "OYO Flagship 14348 Apollo Hospital                 Banjara Hills  Hyderabad  \n",
       "...                                                          ...        ...  \n",
       "OYO 46744 Hotel Yash                                 Nehru Place      Delhi  \n",
       "OYO 62553 Suvee Palace                               Nehru Place      Delhi  \n",
       "OYO 61639 Red Carmine                                Nehru Place      Delhi  \n",
       "OYO 44324 Comfort Stay Near Saket Metro              Nehru Place      Delhi  \n",
       "OYO Home Luxe 30142 Fabulous Farmstay                Nehru Place      Delhi  \n",
       "OYO 22321 Nitin Palace Guest House                   Nehru Place      Delhi  \n",
       "OYO Townhouse 002 Green Park                         Nehru Place      Delhi  \n",
       "Capital O 7075 The Oakland Plaza Hotel Deluxe        Nehru Place      Delhi  \n",
       "OYO 14789 Kempinski Wide                             Nehru Place      Delhi  \n",
       "OYO 63837 Ambica Inn                                 Nehru Place      Delhi  \n",
       "OYO 37512 Spacious Stay Saket Metro                  Nehru Place      Delhi  \n",
       "OYO 60334 Skp Bed & Breakfast                        Nehru Place      Delhi  \n",
       "OYO 64271 Singh Hotel 2                              Nehru Place      Delhi  \n",
       "OYO 37055 M R Residency Saver                        Nehru Place      Delhi  \n",
       "Capital O 712 Defence Colony Deluxe                  Nehru Place      Delhi  \n",
       "OYO Home 47965 Cozy Stay Ignou Road Saket            Nehru Place      Delhi  \n",
       "OYO Home 47964 Comfortable  Stay Ignou Road Saket    Nehru Place      Delhi  \n",
       "OYO 44400 Retreat Inn                                Nehru Place      Delhi  \n",
       "OYO Flagship 36485 Smg Heritage Nehru Enclave        Nehru Place      Delhi  \n",
       "Capital O 39462 Westyard Hotel                       Nehru Place      Delhi  \n",
       "OYO 40657 Aastha                                     Nehru Place      Delhi  \n",
       "OYO 14765 Amar Villa                                 Nehru Place      Delhi  \n",
       "OYO 7304 Stay Jangpura                               Nehru Place      Delhi  \n",
       "OYO 9536 Bee For Home Stay                           Nehru Place      Delhi  \n",
       "OYO 543 La Ola Boutique Hotel                        Nehru Place      Delhi  \n",
       "OYO 472 Hotel Sareen                                 Nehru Place      Delhi  \n",
       "OYO 43002 The Royal Town Deluxe                      Nehru Place      Delhi  \n",
       "OYO 48664 Gour White House                           Nehru Place      Delhi  \n",
       "OYO 12532 Imperial Inn Deluxe                        Nehru Place      Delhi  \n",
       "OYO 13235 The Golden Door                            Nehru Place      Delhi  \n",
       "\n",
       "[11982 rows x 9 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# City"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## City vs Location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Jubilee Hills                         180\n",
       "Banjara Hills                         180\n",
       "Lakdikapool                           160\n",
       "Begumpet                              160\n",
       "Madhapur                              140\n",
       "Secunderabad Railway Station          140\n",
       "Mehdipatnam                           140\n",
       "Ameerpet                              140\n",
       "Hitech City                           140\n",
       "Nampally                              140\n",
       "LB Nagar                              140\n",
       "Himayathnagar                         140\n",
       "Kukatpally                            120\n",
       "Kondapur                              120\n",
       "Kachiguda Railway Station             100\n",
       "Gachibowli                            100\n",
       "Miyapur                                80\n",
       "Uppal                                  40\n",
       "Shamshabad                             40\n",
       "Rajiv Gandhi International Airport     40\n",
       "Name: Location, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')]['Location'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a23d4d198>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')]['Location'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observations\n",
    "\n",
    "- In Hyderabad, Jubilee Hills and Banjara Hills have the maximum number of hotels.\n",
    "- In Hyderabad, Uppal, Rajiv Gandhi International Airport and Shamshabad have the least number of hotels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MG Road                             240\n",
       "Jayanagar                           200\n",
       "Domlur                              200\n",
       "Indiranagar                         180\n",
       "BTM 2ndStage                        180\n",
       "Jp Nagar                            180\n",
       "Majestic City Railway Station       180\n",
       "Koramangala                         180\n",
       "Majestic                            180\n",
       "Kalyan Nagar                        160\n",
       "Hebbal                              140\n",
       "HSR Layout                          140\n",
       "Rajaji Nagar                        140\n",
       "Yeshwanthpur                        100\n",
       "Yelahanka                            80\n",
       "Marathahalli                         60\n",
       "Kempagowda International Airport     60\n",
       "KR Puram                             60\n",
       "Electronic City                      40\n",
       "Whitefield                           20\n",
       "Name: Location, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')]['Location'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2406fac8>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')]['Location'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observations\n",
    "\n",
    "- In Bangalore, MG Road has the highest number of hotels.\n",
    "- In Bangalore, Whitefield has the least number of hotels."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## City vs Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Very Good               1092\n",
       "Good                     519\n",
       "Excellent                476\n",
       "Fair                     211\n",
       "Yet to be summarised     134\n",
       "Fabulous                   8\n",
       "Name: Summary, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')]['Summary'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a241ee908>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')]['Summary'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation\n",
    "\n",
    "- More than 1000 properties are very good in Hyderabad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Very Good               1267\n",
       "Good                     582\n",
       "Excellent                482\n",
       "Yet to be summarised     219\n",
       "Fair                     155\n",
       "Fabulous                  15\n",
       "Name: Summary, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')]['Summary'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a24218588>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')]['Summary'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation\n",
    "\n",
    "- More than 1200 properties are Very Good in Bangalore."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CITY VS FINAL_PRICE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x104c0c048>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='City',y='Final_price',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8170.0"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Final_price'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capital O 22737 Chandra Grand Hotel</th>\n",
       "      <td>11983.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8170.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>661.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Capital O 22737 Chandra Grand Hotel</th>\n",
       "      <td>11983.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8170.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>661.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Original_price  Offer  Final_price  \\\n",
       "Name                                                                      \n",
       "Capital O 22737 Chandra Grand Hotel         11983.0   32.0       8170.0   \n",
       "Capital O 22737 Chandra Grand Hotel         11983.0   32.0       8170.0   \n",
       "\n",
       "                                     Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                      \n",
       "Capital O 22737 Chandra Grand Hotel       6.0     3.8             661.0   \n",
       "Capital O 22737 Chandra Grand Hotel      12.0     3.8             661.0   \n",
       "\n",
       "                                    Summary                      Location  \\\n",
       "Name                                                                        \n",
       "Capital O 22737 Chandra Grand Hotel    Good  Secunderabad Railway Station   \n",
       "Capital O 22737 Chandra Grand Hotel    Good                      LB Nagar   \n",
       "\n",
       "                                          City  \n",
       "Name                                            \n",
       "Capital O 22737 Chandra Grand Hotel  Hyderabad  \n",
       "Capital O 22737 Chandra Grand Hotel  Hyderabad  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Final_price']==8170)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "440.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Final_price'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>8.8</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>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Begumpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Begumpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Mehdipatnam</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Kachiguda Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 45127 Thirumala Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Uppal</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 45127 Thirumala Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Ameerpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Lakdikapool</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Himayathnagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Himayathnagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 45127 Thirumala Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Madhapur</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nampally</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Original_price  Offer  Final_price  \\\n",
       "Name                                                                          \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "\n",
       "                                         Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                          \n",
       "SPOT ON 65122 K-inn SPOT                      8.8     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       7.1     3.4             350.0   \n",
       "SPOT ON 65122 K-inn SPOT                      6.5     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       5.3     3.4             350.0   \n",
       "SPOT ON 65122 K-inn SPOT                      7.1     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      1.3     0.0               0.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT            5.8     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      4.9     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       0.6     3.4             350.0   \n",
       "SPOT ON 65122 K-inn SPOT                      8.6     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      8.8     0.0               0.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT            3.1     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      4.9     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      2.1     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       6.6     3.4             350.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT            7.5     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      2.6     0.0               0.0   \n",
       "\n",
       "                                                      Summary  \\\n",
       "Name                                                            \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "\n",
       "                                                             Location  \\\n",
       "Name                                                                    \n",
       "SPOT ON 65122 K-inn SPOT                                Banjara Hills   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                 Banjara Hills   \n",
       "SPOT ON 65122 K-inn SPOT                                     Begumpet   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                      Begumpet   \n",
       "SPOT ON 65122 K-inn SPOT                                  Mehdipatnam   \n",
       "SPOT ON 65122 K-inn SPOT                    Kachiguda Railway Station   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Secunderabad Railway Station   \n",
       "SPOT ON 65122 K-inn SPOT                 Secunderabad Railway Station   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Secunderabad Railway Station   \n",
       "SPOT ON 65122 K-inn SPOT                                     LB Nagar   \n",
       "SPOT ON 65122 K-inn SPOT                                        Uppal   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                           Ameerpet   \n",
       "SPOT ON 65122 K-inn SPOT                                  Lakdikapool   \n",
       "SPOT ON 65122 K-inn SPOT                                Himayathnagar   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                 Himayathnagar   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                           Madhapur   \n",
       "SPOT ON 65122 K-inn SPOT                                     Nampally   \n",
       "\n",
       "                                              City  \n",
       "Name                                                \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Final_price']==440)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20651.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Final_price'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Palette - Prestige Golfshire Club</th>\n",
       "      <td>32452.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>20651.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Original_price  Offer  Final_price  \\\n",
       "Name                                                                    \n",
       "Palette - Prestige Golfshire Club         32452.0   36.0      20651.0   \n",
       "\n",
       "                                   Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                    \n",
       "Palette - Prestige Golfshire Club      12.0     0.0               0.0   \n",
       "\n",
       "                                                Summary  \\\n",
       "Name                                                      \n",
       "Palette - Prestige Golfshire Club  Yet to be summarised   \n",
       "\n",
       "                                                           Location       City  \n",
       "Name                                                                            \n",
       "Palette - Prestige Golfshire Club  Kempagowda International Airport  Bangalore  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Final_price']==20651)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "440.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Final_price'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SPOT ON 47596 Gayatri Comforts SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>314.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Hebbal</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 47596 Gayatri Comforts SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>314.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Yelahanka</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Original_price  Offer  Final_price  \\\n",
       "Name                                                                      \n",
       "SPOT ON 47596 Gayatri Comforts SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 47596 Gayatri Comforts SPOT           645.0   32.0        440.0   \n",
       "\n",
       "                                     Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                      \n",
       "SPOT ON 47596 Gayatri Comforts SPOT      10.0     3.9             314.0   \n",
       "SPOT ON 47596 Gayatri Comforts SPOT       0.4     3.9             314.0   \n",
       "\n",
       "                                    Summary   Location       City  \n",
       "Name                                                               \n",
       "SPOT ON 47596 Gayatri Comforts SPOT    Good     Hebbal  Bangalore  \n",
       "SPOT ON 47596 Gayatri Comforts SPOT    Good  Yelahanka  Bangalore  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Final_price']==440)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a18c433c8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='City',y='Original_price',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11983.0"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Original_price'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capital O 22737 Chandra Grand Hotel</th>\n",
       "      <td>11983.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8170.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>661.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Capital O 22737 Chandra Grand Hotel</th>\n",
       "      <td>11983.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>8170.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>661.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Original_price  Offer  Final_price  \\\n",
       "Name                                                                      \n",
       "Capital O 22737 Chandra Grand Hotel         11983.0   32.0       8170.0   \n",
       "Capital O 22737 Chandra Grand Hotel         11983.0   32.0       8170.0   \n",
       "\n",
       "                                     Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                      \n",
       "Capital O 22737 Chandra Grand Hotel       6.0     3.8             661.0   \n",
       "Capital O 22737 Chandra Grand Hotel      12.0     3.8             661.0   \n",
       "\n",
       "                                    Summary                      Location  \\\n",
       "Name                                                                        \n",
       "Capital O 22737 Chandra Grand Hotel    Good  Secunderabad Railway Station   \n",
       "Capital O 22737 Chandra Grand Hotel    Good                      LB Nagar   \n",
       "\n",
       "                                          City  \n",
       "Name                                            \n",
       "Capital O 22737 Chandra Grand Hotel  Hyderabad  \n",
       "Capital O 22737 Chandra Grand Hotel  Hyderabad  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Original_price']==11983)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32452.0"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Original_price'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Palette - Prestige Golfshire Club</th>\n",
       "      <td>32452.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>20651.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Original_price  Offer  Final_price  \\\n",
       "Name                                                                    \n",
       "Palette - Prestige Golfshire Club         32452.0   36.0      20651.0   \n",
       "\n",
       "                                   Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                    \n",
       "Palette - Prestige Golfshire Club      12.0     0.0               0.0   \n",
       "\n",
       "                                                Summary  \\\n",
       "Name                                                      \n",
       "Palette - Prestige Golfshire Club  Yet to be summarised   \n",
       "\n",
       "                                                           Location       City  \n",
       "Name                                                                            \n",
       "Palette - Prestige Golfshire Club  Kempagowda International Airport  Bangalore  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Original_price']==32452)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "645.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Original_price'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th></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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>8.8</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>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Begumpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Begumpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Mehdipatnam</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Kachiguda Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 45127 Thirumala Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Uppal</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 45127 Thirumala Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Ameerpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Lakdikapool</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Himayathnagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 48349 Sri Sai Lohith Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Himayathnagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 45127 Thirumala Lodge SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Madhapur</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 65122 K-inn SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Nampally</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Original_price  Offer  Final_price  \\\n",
       "Name                                                                          \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                645.0   32.0        440.0   \n",
       "SPOT ON 65122 K-inn SPOT                          645.0   32.0        440.0   \n",
       "\n",
       "                                         Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                          \n",
       "SPOT ON 65122 K-inn SPOT                      8.8     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       7.1     3.4             350.0   \n",
       "SPOT ON 65122 K-inn SPOT                      6.5     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       5.3     3.4             350.0   \n",
       "SPOT ON 65122 K-inn SPOT                      7.1     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      1.3     0.0               0.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT            5.8     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      4.9     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       0.6     3.4             350.0   \n",
       "SPOT ON 65122 K-inn SPOT                      8.6     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      8.8     0.0               0.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT            3.1     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      4.9     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      2.1     0.0               0.0   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT       6.6     3.4             350.0   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT            7.5     0.0               0.0   \n",
       "SPOT ON 65122 K-inn SPOT                      2.6     0.0               0.0   \n",
       "\n",
       "                                                      Summary  \\\n",
       "Name                                                            \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                  Fair   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Yet to be summarised   \n",
       "SPOT ON 65122 K-inn SPOT                 Yet to be summarised   \n",
       "\n",
       "                                                             Location  \\\n",
       "Name                                                                    \n",
       "SPOT ON 65122 K-inn SPOT                                Banjara Hills   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                 Banjara Hills   \n",
       "SPOT ON 65122 K-inn SPOT                                     Begumpet   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                      Begumpet   \n",
       "SPOT ON 65122 K-inn SPOT                                  Mehdipatnam   \n",
       "SPOT ON 65122 K-inn SPOT                    Kachiguda Railway Station   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Secunderabad Railway Station   \n",
       "SPOT ON 65122 K-inn SPOT                 Secunderabad Railway Station   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Secunderabad Railway Station   \n",
       "SPOT ON 65122 K-inn SPOT                                     LB Nagar   \n",
       "SPOT ON 65122 K-inn SPOT                                        Uppal   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                           Ameerpet   \n",
       "SPOT ON 65122 K-inn SPOT                                  Lakdikapool   \n",
       "SPOT ON 65122 K-inn SPOT                                Himayathnagar   \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT                 Himayathnagar   \n",
       "SPOT ON 45127 Thirumala Lodge SPOT                           Madhapur   \n",
       "SPOT ON 65122 K-inn SPOT                                     Nampally   \n",
       "\n",
       "                                              City  \n",
       "Name                                                \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  \n",
       "SPOT ON 48349 Sri Sai Lohith Lodge SPOT  Hyderabad  \n",
       "SPOT ON 45127 Thirumala Lodge SPOT       Hyderabad  \n",
       "SPOT ON 65122 K-inn SPOT                 Hyderabad  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Original_price']==645)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "645.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Original_price'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SPOT ON 47596 Gayatri Comforts SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>314.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Hebbal</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPOT ON 47596 Gayatri Comforts SPOT</th>\n",
       "      <td>645.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>314.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Yelahanka</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Original_price  Offer  Final_price  \\\n",
       "Name                                                                      \n",
       "SPOT ON 47596 Gayatri Comforts SPOT           645.0   32.0        440.0   \n",
       "SPOT ON 47596 Gayatri Comforts SPOT           645.0   32.0        440.0   \n",
       "\n",
       "                                     Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                      \n",
       "SPOT ON 47596 Gayatri Comforts SPOT      10.0     3.9             314.0   \n",
       "SPOT ON 47596 Gayatri Comforts SPOT       0.4     3.9             314.0   \n",
       "\n",
       "                                    Summary   Location       City  \n",
       "Name                                                               \n",
       "SPOT ON 47596 Gayatri Comforts SPOT    Good     Hebbal  Bangalore  \n",
       "SPOT ON 47596 Gayatri Comforts SPOT    Good  Yelahanka  Bangalore  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Original_price']==645)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation   \n",
    "    - Mumbai has the highest Final_price and Original_price.\n",
    "\n",
    "    - Capital O 22737 Chandra Grand Hotel is the most expensive hotel in Hyderabad\n",
    "    - SPOT ON 65122 K - inn SPOT, SPOT ON 45127 Thirumala Lodge SPOT and SPOT ON 48349 Sri Sai Lohith Lodge SPOT are the cheapest hotels in Hyderabad.\n",
    "\n",
    "    - Palette -Prestige Golfshire Club is the most expensive hotel in Bangalore\n",
    "    - SPOT ON 47596 Gayatri Comforts SPOT  is the most cheapest hotel in Bangalore"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CITY VS OFFER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a18bf9e10>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='City',y='Offer',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2440.000000\n",
       "mean       33.416393\n",
       "std         4.459510\n",
       "min        32.000000\n",
       "25%        32.000000\n",
       "50%        32.000000\n",
       "75%        32.000000\n",
       "max        63.000000\n",
       "Name: Offer, dtype: float64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Offer'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2720.000000\n",
       "mean       34.656618\n",
       "std         6.536211\n",
       "min        32.000000\n",
       "25%        32.000000\n",
       "50%        32.000000\n",
       "75%        32.000000\n",
       "max        70.000000\n",
       "Name: Offer, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Offer'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Observations\n",
    "\n",
    "- Delhi offers the highest offers.\n",
    "- Hyderabad offers an average of 33.5% off\n",
    "- Bangalore offers an average of 34.65% off"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CITY VS NUMBER_OF_RATING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a18cf8b00>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='City',y='Number_of_Rating',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2440.000000\n",
       "mean      839.736475\n",
       "std       996.294909\n",
       "min         0.000000\n",
       "25%       225.000000\n",
       "50%       440.000000\n",
       "75%      1001.000000\n",
       "max      5342.000000\n",
       "Name: Number_of_Rating, dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Number_of_Rating'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2720.000000\n",
       "mean      610.291176\n",
       "std       834.700058\n",
       "min         0.000000\n",
       "25%       130.000000\n",
       "50%       309.000000\n",
       "75%       719.000000\n",
       "max      6803.000000\n",
       "Name: Number_of_Rating, dtype: float64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Number_of_Rating'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation\n",
    "\n",
    "- Hyderabad has the highest number of ratings.\n",
    "- Number of Ratings for hotels in hyderabad are at a mean of 839.73\n",
    "- Number of Ratings for hotels in bangalore are at a mean of 610.29"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CITY VS RATING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a18f886a0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='City',y='Rating',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.9"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Rating'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Banjara Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Begumpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Secunderabad Railway Station</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Ameerpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Lakdikapool</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Himayathnagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Nampally</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Original_price  Offer  \\\n",
       "Name                                                                    \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet          2087.0   32.0   \n",
       "\n",
       "                                                Final_price  Distance  Rating  \\\n",
       "Name                                                                            \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       7.8     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       3.1     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       2.7     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0      19.0     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       5.5     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       8.9     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       7.2     4.9   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet       1423.0       9.2     4.9   \n",
       "\n",
       "                                                Number_of_Rating   Summary  \\\n",
       "Name                                                                         \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet             299.0  Fabulous   \n",
       "\n",
       "                                                                    Location  \\\n",
       "Name                                                                           \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                 Banjara Hills   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                      Begumpet   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Secunderabad Railway Station   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                      LB Nagar   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                      Ameerpet   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                   Lakdikapool   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                 Himayathnagar   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                      Nampally   \n",
       "\n",
       "                                                     City  \n",
       "Name                                                       \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet  Hyderabad  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Rating']==4.9)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Rating'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 29020 Vm Comfort</th>\n",
       "      <td>2313.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1577.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 24130 Surya Comforts</th>\n",
       "      <td>1667.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>990.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Palette - Npg Hotel</th>\n",
       "      <td>2861.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1951.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 29020 Vm Comfort</th>\n",
       "      <td>2313.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1577.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Kalyan Nagar</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 19285 Uv Comforts</th>\n",
       "      <td>1892.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1290.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Kalyan Nagar</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 29020 Vm Comfort</th>\n",
       "      <td>2313.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1577.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Hebbal</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 19285 Uv Comforts</th>\n",
       "      <td>1892.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1290.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Hebbal</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 29020 Vm Comfort</th>\n",
       "      <td>2313.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1577.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Yelahanka</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 19285 Uv Comforts</th>\n",
       "      <td>1892.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1290.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Yelahanka</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Palette - Npg Hotel</th>\n",
       "      <td>2861.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1951.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Yelahanka</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 19285 Uv Comforts</th>\n",
       "      <td>1892.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1290.0</td>\n",
       "      <td>8.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>Yeshwanthpur</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Original_price  Offer  Final_price  Distance  \\\n",
       "Name                                                                     \n",
       "OYO 29020 Vm Comfort              2313.0   32.0       1577.0      17.0   \n",
       "OYO 24130 Surya Comforts          1667.0   41.0        990.0      17.0   \n",
       "Palette - Npg Hotel               2861.0   32.0       1951.0       9.5   \n",
       "OYO 29020 Vm Comfort              2313.0   32.0       1577.0       9.2   \n",
       "OYO 19285 Uv Comforts             1892.0   32.0       1290.0       8.0   \n",
       "OYO 29020 Vm Comfort              2313.0   32.0       1577.0       9.1   \n",
       "OYO 19285 Uv Comforts             1892.0   32.0       1290.0       6.6   \n",
       "OYO 29020 Vm Comfort              2313.0   32.0       1577.0       1.8   \n",
       "OYO 19285 Uv Comforts             1892.0   32.0       1290.0       6.7   \n",
       "Palette - Npg Hotel               2861.0   32.0       1951.0       9.2   \n",
       "OYO 19285 Uv Comforts             1892.0   32.0       1290.0       8.4   \n",
       "\n",
       "                          Rating  Number_of_Rating   Summary  \\\n",
       "Name                                                           \n",
       "OYO 29020 Vm Comfort         5.0               1.0  Fabulous   \n",
       "OYO 24130 Surya Comforts     5.0               2.0  Fabulous   \n",
       "Palette - Npg Hotel          5.0               1.0  Fabulous   \n",
       "OYO 29020 Vm Comfort         5.0               1.0  Fabulous   \n",
       "OYO 19285 Uv Comforts        5.0               1.0  Fabulous   \n",
       "OYO 29020 Vm Comfort         5.0               1.0  Fabulous   \n",
       "OYO 19285 Uv Comforts        5.0               1.0  Fabulous   \n",
       "OYO 29020 Vm Comfort         5.0               1.0  Fabulous   \n",
       "OYO 19285 Uv Comforts        5.0               1.0  Fabulous   \n",
       "Palette - Npg Hotel          5.0               1.0  Fabulous   \n",
       "OYO 19285 Uv Comforts        5.0               1.0  Fabulous   \n",
       "\n",
       "                                                  Location       City  \n",
       "Name                                                                   \n",
       "OYO 29020 Vm Comfort      Kempagowda International Airport  Bangalore  \n",
       "OYO 24130 Surya Comforts  Kempagowda International Airport  Bangalore  \n",
       "Palette - Npg Hotel       Kempagowda International Airport  Bangalore  \n",
       "OYO 29020 Vm Comfort                          Kalyan Nagar  Bangalore  \n",
       "OYO 19285 Uv Comforts                         Kalyan Nagar  Bangalore  \n",
       "OYO 29020 Vm Comfort                                Hebbal  Bangalore  \n",
       "OYO 19285 Uv Comforts                               Hebbal  Bangalore  \n",
       "OYO 29020 Vm Comfort                             Yelahanka  Bangalore  \n",
       "OYO 19285 Uv Comforts                            Yelahanka  Bangalore  \n",
       "Palette - Npg Hotel                              Yelahanka  Bangalore  \n",
       "OYO 19285 Uv Comforts                         Yeshwanthpur  Bangalore  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Rating']==5.0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2440.000000\n",
       "mean        3.881680\n",
       "std         1.018929\n",
       "min         0.000000\n",
       "25%         3.800000\n",
       "50%         4.200000\n",
       "75%         4.400000\n",
       "max         4.900000\n",
       "Name: Rating, dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Rating'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2720.000000\n",
       "mean        3.786801\n",
       "std         1.178425\n",
       "min         0.000000\n",
       "25%         3.800000\n",
       "50%         4.100000\n",
       "75%         4.400000\n",
       "max         5.000000\n",
       "Name: Rating, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Rating'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation\n",
    "\n",
    "- From the bar graph it can be infered that mean of the ratings of hotels is the highest in INDIA.\n",
    "- In Hyderabad, OYO 14501 Hotel Hill View Guest House Begumpet is the highest rated hotel.\n",
    "- In Bangalore, OYO 19285 Uv Comforts, Palette - Npg Hotel, OYO 29020 Vm Comfort and OYO 24130 Surya Comforts are rated the highest."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CITY VS DISTANCE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a18f33358>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='City',y='Distance',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Distance'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 47332 Hotel Dolphin</th>\n",
       "      <td>1481.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>4.4</td>\n",
       "      <td>279.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Jubilee Hills</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 9303 Celebrity Skyhy Rooms</th>\n",
       "      <td>3180.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2168.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>245.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Begumpet</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14731 Hallmark Inn Kukatpally</th>\n",
       "      <td>6592.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4495.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>466.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Kukatpally</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 2840 Kanha Grand</th>\n",
       "      <td>1481.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>4.1</td>\n",
       "      <td>542.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Lakdikapool</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Original_price  Offer  Final_price  \\\n",
       "Name                                                                    \n",
       "OYO 47332 Hotel Dolphin                    1481.0   32.0       1010.0   \n",
       "OYO 9303 Celebrity Skyhy Rooms             3180.0   32.0       2168.0   \n",
       "OYO 14731 Hallmark Inn Kukatpally          6592.0   32.0       4495.0   \n",
       "OYO 2840 Kanha Grand                       1481.0   32.0       1010.0   \n",
       "\n",
       "                                   Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                    \n",
       "OYO 47332 Hotel Dolphin                 0.1     4.4             279.0   \n",
       "OYO 9303 Celebrity Skyhy Rooms          0.1     3.9             245.0   \n",
       "OYO 14731 Hallmark Inn Kukatpally       0.1     3.9             466.0   \n",
       "OYO 2840 Kanha Grand                    0.1     4.1             542.0   \n",
       "\n",
       "                                     Summary       Location       City  \n",
       "Name                                                                    \n",
       "OYO 47332 Hotel Dolphin            Very Good  Jubilee Hills  Hyderabad  \n",
       "OYO 9303 Celebrity Skyhy Rooms          Good       Begumpet  Hyderabad  \n",
       "OYO 14731 Hallmark Inn Kukatpally       Good     Kukatpally  Hyderabad  \n",
       "OYO 2840 Kanha Grand               Very Good    Lakdikapool  Hyderabad  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Distance']==0.1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.0"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Hyderabad']['Distance'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 22085 Raj Banjara White House</th>\n",
       "      <td>2459.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1677.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>201.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 26562 Dazzle Stays</th>\n",
       "      <td>1730.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>371.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 18454 Hallmark Inn Begumpet</th>\n",
       "      <td>2390.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>239.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 33412 Spacious Stay Qutub Shahi Tomb</th>\n",
       "      <td>1796.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1225.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>360.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 46058 Pleasant Stay Near Moosapet Metro Station</th>\n",
       "      <td>2444.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1666.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>874.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 12237 Luxury Villas</th>\n",
       "      <td>2157.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1471.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>144.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 9386 Hotel Mannys Plaza</th>\n",
       "      <td>2157.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1471.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>252.0</td>\n",
       "      <td>Fair</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 14501 Hotel Hill View Guest House Begumpet</th>\n",
       "      <td>2087.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>299.0</td>\n",
       "      <td>Fabulous</td>\n",
       "      <td>LB Nagar</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO Flagship 35993 Puppalaguda</th>\n",
       "      <td>1481.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>650.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Rajiv Gandhi International Airport</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Capital O 44354 Jubilee Banjara Suites</th>\n",
       "      <td>1778.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1213.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1258.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Rajiv Gandhi International Airport</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 8941 Hotel Golden Leaves</th>\n",
       "      <td>2449.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1670.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>728.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Shamshabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 30396 Hotel Shri Chaitra Deluxe</th>\n",
       "      <td>2685.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1831.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>446.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Shamshabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 46837 Vivid Stay Near Sunshine Hospital</th>\n",
       "      <td>1777.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1212.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>222.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Shamshabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 40311 Hotel Ruhika</th>\n",
       "      <td>1146.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>781.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>33.0</td>\n",
       "      <td>Good</td>\n",
       "      <td>Shamshabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 49253 Raja Residency</th>\n",
       "      <td>1140.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>778.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Shamshabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO Home 48096 Jublee Homes</th>\n",
       "      <td>1802.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1229.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yet to be summarised</td>\n",
       "      <td>Shamshabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Original_price  Offer  \\\n",
       "Name                                                                        \n",
       "OYO 22085 Raj Banjara White House                           2459.0   32.0   \n",
       "OYO 26562 Dazzle Stays                                      1730.0   42.0   \n",
       "OYO 18454 Hallmark Inn Begumpet                             2390.0   58.0   \n",
       "OYO 33412 Spacious Stay Qutub Shahi Tomb                    1796.0   32.0   \n",
       "OYO 46058 Pleasant Stay Near Moosapet Metro Sta...          2444.0   32.0   \n",
       "OYO 12237 Luxury Villas                                     2157.0   32.0   \n",
       "OYO 9386 Hotel Mannys Plaza                                 2157.0   32.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet              2087.0   32.0   \n",
       "OYO Flagship 35993 Puppalaguda                              1481.0   32.0   \n",
       "Capital O 44354 Jubilee Banjara Suites                      1778.0   32.0   \n",
       "OYO 8941 Hotel Golden Leaves                                2449.0   32.0   \n",
       "OYO 30396 Hotel Shri Chaitra Deluxe                         2685.0   32.0   \n",
       "OYO 46837 Vivid Stay Near Sunshine Hospital                 1777.0   32.0   \n",
       "OYO 40311 Hotel Ruhika                                      1146.0   32.0   \n",
       "OYO 49253 Raja Residency                                    1140.0   32.0   \n",
       "OYO Home 48096 Jublee Homes                                 1802.0   32.0   \n",
       "\n",
       "                                                    Final_price  Distance  \\\n",
       "Name                                                                        \n",
       "OYO 22085 Raj Banjara White House                        1677.0      19.0   \n",
       "OYO 26562 Dazzle Stays                                   1010.0      19.0   \n",
       "OYO 18454 Hallmark Inn Begumpet                          1010.0      19.0   \n",
       "OYO 33412 Spacious Stay Qutub Shahi Tomb                 1225.0      19.0   \n",
       "OYO 46058 Pleasant Stay Near Moosapet Metro Sta...       1666.0      19.0   \n",
       "OYO 12237 Luxury Villas                                  1471.0      19.0   \n",
       "OYO 9386 Hotel Mannys Plaza                              1471.0      19.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet           1423.0      19.0   \n",
       "OYO Flagship 35993 Puppalaguda                           1010.0      19.0   \n",
       "Capital O 44354 Jubilee Banjara Suites                   1213.0      19.0   \n",
       "OYO 8941 Hotel Golden Leaves                             1670.0      19.0   \n",
       "OYO 30396 Hotel Shri Chaitra Deluxe                      1831.0      19.0   \n",
       "OYO 46837 Vivid Stay Near Sunshine Hospital              1212.0      19.0   \n",
       "OYO 40311 Hotel Ruhika                                    781.0      19.0   \n",
       "OYO 49253 Raja Residency                                  778.0      19.0   \n",
       "OYO Home 48096 Jublee Homes                              1229.0      19.0   \n",
       "\n",
       "                                                    Rating  Number_of_Rating  \\\n",
       "Name                                                                           \n",
       "OYO 22085 Raj Banjara White House                      4.4             201.0   \n",
       "OYO 26562 Dazzle Stays                                 3.9             371.0   \n",
       "OYO 18454 Hallmark Inn Begumpet                        4.7             239.0   \n",
       "OYO 33412 Spacious Stay Qutub Shahi Tomb               4.4             360.0   \n",
       "OYO 46058 Pleasant Stay Near Moosapet Metro Sta...     4.5             874.0   \n",
       "OYO 12237 Luxury Villas                                3.7             144.0   \n",
       "OYO 9386 Hotel Mannys Plaza                            3.2             252.0   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet         4.9             299.0   \n",
       "OYO Flagship 35993 Puppalaguda                         4.2             650.0   \n",
       "Capital O 44354 Jubilee Banjara Suites                 4.4            1258.0   \n",
       "OYO 8941 Hotel Golden Leaves                           4.4             728.0   \n",
       "OYO 30396 Hotel Shri Chaitra Deluxe                    3.9             446.0   \n",
       "OYO 46837 Vivid Stay Near Sunshine Hospital            4.5             222.0   \n",
       "OYO 40311 Hotel Ruhika                                 3.6              33.0   \n",
       "OYO 49253 Raja Residency                               4.5             162.0   \n",
       "OYO Home 48096 Jublee Homes                            0.0               0.0   \n",
       "\n",
       "                                                                 Summary  \\\n",
       "Name                                                                       \n",
       "OYO 22085 Raj Banjara White House                              Very Good   \n",
       "OYO 26562 Dazzle Stays                                              Good   \n",
       "OYO 18454 Hallmark Inn Begumpet                                Excellent   \n",
       "OYO 33412 Spacious Stay Qutub Shahi Tomb                       Very Good   \n",
       "OYO 46058 Pleasant Stay Near Moosapet Metro Sta...             Excellent   \n",
       "OYO 12237 Luxury Villas                                             Good   \n",
       "OYO 9386 Hotel Mannys Plaza                                         Fair   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                  Fabulous   \n",
       "OYO Flagship 35993 Puppalaguda                                 Very Good   \n",
       "Capital O 44354 Jubilee Banjara Suites                         Very Good   \n",
       "OYO 8941 Hotel Golden Leaves                                   Very Good   \n",
       "OYO 30396 Hotel Shri Chaitra Deluxe                                 Good   \n",
       "OYO 46837 Vivid Stay Near Sunshine Hospital                    Excellent   \n",
       "OYO 40311 Hotel Ruhika                                              Good   \n",
       "OYO 49253 Raja Residency                                       Excellent   \n",
       "OYO Home 48096 Jublee Homes                         Yet to be summarised   \n",
       "\n",
       "                                                                              Location  \\\n",
       "Name                                                                                     \n",
       "OYO 22085 Raj Banjara White House                                             LB Nagar   \n",
       "OYO 26562 Dazzle Stays                                                        LB Nagar   \n",
       "OYO 18454 Hallmark Inn Begumpet                                               LB Nagar   \n",
       "OYO 33412 Spacious Stay Qutub Shahi Tomb                                      LB Nagar   \n",
       "OYO 46058 Pleasant Stay Near Moosapet Metro Sta...                            LB Nagar   \n",
       "OYO 12237 Luxury Villas                                                       LB Nagar   \n",
       "OYO 9386 Hotel Mannys Plaza                                                   LB Nagar   \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet                                LB Nagar   \n",
       "OYO Flagship 35993 Puppalaguda                      Rajiv Gandhi International Airport   \n",
       "Capital O 44354 Jubilee Banjara Suites              Rajiv Gandhi International Airport   \n",
       "OYO 8941 Hotel Golden Leaves                                                Shamshabad   \n",
       "OYO 30396 Hotel Shri Chaitra Deluxe                                         Shamshabad   \n",
       "OYO 46837 Vivid Stay Near Sunshine Hospital                                 Shamshabad   \n",
       "OYO 40311 Hotel Ruhika                                                      Shamshabad   \n",
       "OYO 49253 Raja Residency                                                    Shamshabad   \n",
       "OYO Home 48096 Jublee Homes                                                 Shamshabad   \n",
       "\n",
       "                                                         City  \n",
       "Name                                                           \n",
       "OYO 22085 Raj Banjara White House                   Hyderabad  \n",
       "OYO 26562 Dazzle Stays                              Hyderabad  \n",
       "OYO 18454 Hallmark Inn Begumpet                     Hyderabad  \n",
       "OYO 33412 Spacious Stay Qutub Shahi Tomb            Hyderabad  \n",
       "OYO 46058 Pleasant Stay Near Moosapet Metro Sta...  Hyderabad  \n",
       "OYO 12237 Luxury Villas                             Hyderabad  \n",
       "OYO 9386 Hotel Mannys Plaza                         Hyderabad  \n",
       "OYO 14501 Hotel Hill View Guest House Begumpet      Hyderabad  \n",
       "OYO Flagship 35993 Puppalaguda                      Hyderabad  \n",
       "Capital O 44354 Jubilee Banjara Suites              Hyderabad  \n",
       "OYO 8941 Hotel Golden Leaves                        Hyderabad  \n",
       "OYO 30396 Hotel Shri Chaitra Deluxe                 Hyderabad  \n",
       "OYO 46837 Vivid Stay Near Sunshine Hospital         Hyderabad  \n",
       "OYO 40311 Hotel Ruhika                              Hyderabad  \n",
       "OYO 49253 Raja Residency                            Hyderabad  \n",
       "OYO Home 48096 Jublee Homes                         Hyderabad  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Hyderabad')&(df['Distance']==19)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Distance'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 47451 Elegant Indira Nagar</th>\n",
       "      <td>3058.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2085.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>4.1</td>\n",
       "      <td>98.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Indiranagar</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OYO 13594 Mathrushree Residency</th>\n",
       "      <td>6584.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4489.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>4.5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Rajaji Nagar</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Original_price  Offer  Final_price  Distance  \\\n",
       "Name                                                                            \n",
       "OYO 47451 Elegant Indira Nagar           3058.0   32.0       2085.0       0.1   \n",
       "OYO 13594 Mathrushree Residency          6584.0   32.0       4489.0       0.1   \n",
       "\n",
       "                                 Rating  Number_of_Rating    Summary  \\\n",
       "Name                                                                   \n",
       "OYO 47451 Elegant Indira Nagar      4.1              98.0  Very Good   \n",
       "OYO 13594 Mathrushree Residency     4.5              50.0  Excellent   \n",
       "\n",
       "                                     Location       City  \n",
       "Name                                                      \n",
       "OYO 47451 Elegant Indira Nagar    Indiranagar  Bangalore  \n",
       "OYO 13594 Mathrushree Residency  Rajaji Nagar  Bangalore  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Distance']==0.1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19.0"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['City']=='Bangalore']['Distance'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OYO 40115 J P Palace</th>\n",
       "      <td>1878.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1281.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>481.0</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Capital O 49358 Blue Meridian Inn</th>\n",
       "      <td>11185.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7627.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>440.0</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>Kempagowda International Airport</td>\n",
       "      <td>Bangalore</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Original_price  Offer  Final_price  \\\n",
       "Name                                                                    \n",
       "OYO 40115 J P Palace                       1878.0   32.0       1281.0   \n",
       "Capital O 49358 Blue Meridian Inn         11185.0   32.0       7627.0   \n",
       "\n",
       "                                   Distance  Rating  Number_of_Rating  \\\n",
       "Name                                                                    \n",
       "OYO 40115 J P Palace                   19.0     4.8             481.0   \n",
       "Capital O 49358 Blue Meridian Inn      19.0     4.4             440.0   \n",
       "\n",
       "                                     Summary  \\\n",
       "Name                                           \n",
       "OYO 40115 J P Palace               Excellent   \n",
       "Capital O 49358 Blue Meridian Inn  Very Good   \n",
       "\n",
       "                                                           Location       City  \n",
       "Name                                                                            \n",
       "OYO 40115 J P Palace               Kempagowda International Airport  Bangalore  \n",
       "Capital O 49358 Blue Meridian Inn  Kempagowda International Airport  Bangalore  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['City']=='Bangalore')&(df['Distance']==19)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation\n",
    "\n",
    "- Least distance from the location can be observed in the data from Chennai.\n",
    "\n",
    "- In Bangalore, Hotels with maximum distance from the specified location are Capital O 49358 Blue Meridian Inn and OYO 40115 J P Palace.\n",
    "\n",
    "- In Bangalore, Hotels with minimum distance from the specified location are OYO 13594 Mathrushree Residency and  OYO 47451 Elegant Indira Nagar\n",
    "\n",
    "- In Hyderabad, Hotels with maximum distance from the speccified location are in the locations of Shamshabad, LB Nagar and a couple in Rajiv Gandhi International Airport.\n",
    "\n",
    "- In Hyderabad, Hotels with minimum distance from the specified location are OYO 47332 Hotel Dolphin, OYO 9303 Celebrity Skyhy Rooms, OYO 14731 Hallmark Inn Kukatpally and OYO 2840 Kanha Grand."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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