What is the most booked neighbourhood in Paris ?.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a4a0b2d8",
   "metadata": {},
   "source": [
    "# Question 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f91c131",
   "metadata": {},
   "source": [
    "## What is the most booked neighbourhood in Paris ?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "245d0943",
   "metadata": {},
   "source": [
    "### Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c14eeb6e",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "This notebook contains the analysis performed to solve our first question about the **most booked neighbourhood** in **Paris** in **June** 2022.\n",
    "The data was collected from [**Inside Airbnb** website](http://insideairbnb.com/get-the-data/).\n",
    "Check this section to get the [**listings**](http://data.insideairbnb.com/france/ile-de-france/paris/2022-06-06/data/listings.csv.gz) data, the [**calendar**](http://data.insideairbnb.com/france/ile-de-france/paris/2022-06-06/data/calendar.csv.gz) and also the [**reviews**](http://data.insideairbnb.com/france/ile-de-france/paris/2022-06-06/data/reviews.csv.gz) data provided in **Paris, Île-de-France, France** section.\n",
    "This data will be used to answer the questions and complete this analysis about **Paris-Airbnb-data**.\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fab1e707",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "25769054",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading the data files\n",
    "listings = pd.read_csv('data/paris-airbnb/listings.csv')\n",
    "calendar = pd.read_csv('data/paris-airbnb/calendar.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7852b7a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>description</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>picture_url</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_url</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>calculated_host_listings_count_entire_homes</th>\n",
       "      <th>calculated_host_listings_count_private_rooms</th>\n",
       "      <th>calculated_host_listings_count_shared_rooms</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26660141</td>\n",
       "      <td>https://www.airbnb.com/rooms/26660141</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>CHARMANT APPARTEMENT,  50M2 AUX PORTES DE PARIS</td>\n",
       "      <td>Charmant appartement avec petit balcon filant,...</td>\n",
       "      <td>La rue principale à la sortie du métro est trè...</td>\n",
       "      <td>https://a0.muscache.com/pictures/a776b332-0fde...</td>\n",
       "      <td>200407698</td>\n",
       "      <td>https://www.airbnb.com/users/show/200407698</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.88</td>\n",
       "      <td>4.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25177338</td>\n",
       "      <td>https://www.airbnb.com/rooms/25177338</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>Cosy and quiet appartement at Les Lilas</td>\n",
       "      <td>&lt;b&gt;The space&lt;/b&gt;&lt;br /&gt;Le logement est situé da...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/pictures/e984c1e4-6d40...</td>\n",
       "      <td>185793394</td>\n",
       "      <td>https://www.airbnb.com/users/show/185793394</td>\n",
       "      <td>...</td>\n",
       "      <td>4.56</td>\n",
       "      <td>4.50</td>\n",
       "      <td>4.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>t</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25218084</td>\n",
       "      <td>https://www.airbnb.com/rooms/25218084</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>paris avec une maison</td>\n",
       "      <td>une maison restaurée et faite à notre image ap...</td>\n",
       "      <td>Être dans un véritable maison avec un parc à q...</td>\n",
       "      <td>https://a0.muscache.com/pictures/dbfc69a1-76cb...</td>\n",
       "      <td>190542280</td>\n",
       "      <td>https://www.airbnb.com/users/show/190542280</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23135649</td>\n",
       "      <td>https://www.airbnb.com/rooms/23135649</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>Charming studio, Pont de Neuilly - Paris</td>\n",
       "      <td>Studio apartment in the heart of the prestigio...</td>\n",
       "      <td>The Saint James district of Neuilly sur Seine ...</td>\n",
       "      <td>https://a0.muscache.com/pictures/58399f3d-c271...</td>\n",
       "      <td>171938056</td>\n",
       "      <td>https://www.airbnb.com/users/show/171938056</td>\n",
       "      <td>...</td>\n",
       "      <td>4.94</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23259887</td>\n",
       "      <td>https://www.airbnb.com/rooms/23259887</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>A cosy appartement</td>\n",
       "      <td>Situé dans un quartier agréable proche de Chât...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/pictures/ad0ade9c-89d5...</td>\n",
       "      <td>20135501</td>\n",
       "      <td>https://www.airbnb.com/users/show/20135501</td>\n",
       "      <td>...</td>\n",
       "      <td>4.86</td>\n",
       "      <td>4.91</td>\n",
       "      <td>4.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>t</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id                            listing_url       scrape_id  \\\n",
       "0  26660141  https://www.airbnb.com/rooms/26660141  20220606014139   \n",
       "1  25177338  https://www.airbnb.com/rooms/25177338  20220606014139   \n",
       "2  25218084  https://www.airbnb.com/rooms/25218084  20220606014139   \n",
       "3  23135649  https://www.airbnb.com/rooms/23135649  20220606014139   \n",
       "4  23259887  https://www.airbnb.com/rooms/23259887  20220606014139   \n",
       "\n",
       "  last_scraped                                             name  \\\n",
       "0   2022-06-07  CHARMANT APPARTEMENT,  50M2 AUX PORTES DE PARIS   \n",
       "1   2022-06-07          Cosy and quiet appartement at Les Lilas   \n",
       "2   2022-06-07                            paris avec une maison   \n",
       "3   2022-06-07         Charming studio, Pont de Neuilly - Paris   \n",
       "4   2022-06-07                               A cosy appartement   \n",
       "\n",
       "                                         description  \\\n",
       "0  Charmant appartement avec petit balcon filant,...   \n",
       "1  <b>The space</b><br />Le logement est situé da...   \n",
       "2  une maison restaurée et faite à notre image ap...   \n",
       "3  Studio apartment in the heart of the prestigio...   \n",
       "4  Situé dans un quartier agréable proche de Chât...   \n",
       "\n",
       "                               neighborhood_overview  \\\n",
       "0  La rue principale à la sortie du métro est trè...   \n",
       "1                                                NaN   \n",
       "2  Être dans un véritable maison avec un parc à q...   \n",
       "3  The Saint James district of Neuilly sur Seine ...   \n",
       "4                                                NaN   \n",
       "\n",
       "                                         picture_url    host_id  \\\n",
       "0  https://a0.muscache.com/pictures/a776b332-0fde...  200407698   \n",
       "1  https://a0.muscache.com/pictures/e984c1e4-6d40...  185793394   \n",
       "2  https://a0.muscache.com/pictures/dbfc69a1-76cb...  190542280   \n",
       "3  https://a0.muscache.com/pictures/58399f3d-c271...  171938056   \n",
       "4  https://a0.muscache.com/pictures/ad0ade9c-89d5...   20135501   \n",
       "\n",
       "                                      host_url  ...  \\\n",
       "0  https://www.airbnb.com/users/show/200407698  ...   \n",
       "1  https://www.airbnb.com/users/show/185793394  ...   \n",
       "2  https://www.airbnb.com/users/show/190542280  ...   \n",
       "3  https://www.airbnb.com/users/show/171938056  ...   \n",
       "4   https://www.airbnb.com/users/show/20135501  ...   \n",
       "\n",
       "  review_scores_communication review_scores_location review_scores_value  \\\n",
       "0                        5.00                   4.88                4.94   \n",
       "1                        4.56                   4.50                4.56   \n",
       "2                        5.00                   4.50                5.00   \n",
       "3                        4.94                   4.87                4.61   \n",
       "4                        4.86                   4.91                4.65   \n",
       "\n",
       "  license instant_bookable calculated_host_listings_count  \\\n",
       "0     NaN                f                              1   \n",
       "1     NaN                t                              1   \n",
       "2     NaN                f                              1   \n",
       "3     NaN                f                              1   \n",
       "4     NaN                t                              1   \n",
       "\n",
       "  calculated_host_listings_count_entire_homes  \\\n",
       "0                                           1   \n",
       "1                                           1   \n",
       "2                                           1   \n",
       "3                                           0   \n",
       "4                                           1   \n",
       "\n",
       "  calculated_host_listings_count_private_rooms  \\\n",
       "0                                            0   \n",
       "1                                            0   \n",
       "2                                            0   \n",
       "3                                            1   \n",
       "4                                            0   \n",
       "\n",
       "  calculated_host_listings_count_shared_rooms reviews_per_month  \n",
       "0                                           0              0.38  \n",
       "1                                           0              0.35  \n",
       "2                                           0              0.05  \n",
       "3                                           0              0.65  \n",
       "4                                           0              0.87  \n",
       "\n",
       "[5 rows x 74 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking into the dataframes\n",
    "listings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c1424a48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>listing_id</th>\n",
       "      <th>date</th>\n",
       "      <th>available</th>\n",
       "      <th>price</th>\n",
       "      <th>adjusted_price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-08</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-09</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-10</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-11</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   listing_id        date available   price adjusted_price  minimum_nights  \\\n",
       "0    26660141  2022-06-07         f  $90.00         $90.00             5.0   \n",
       "1    26660141  2022-06-08         f  $90.00         $90.00             5.0   \n",
       "2    26660141  2022-06-09         f  $90.00         $90.00             5.0   \n",
       "3    26660141  2022-06-10         f  $90.00         $90.00             5.0   \n",
       "4    26660141  2022-06-11         f  $90.00         $90.00             5.0   \n",
       "\n",
       "   maximum_nights  \n",
       "0             8.0  \n",
       "1             8.0  \n",
       "2             8.0  \n",
       "3             8.0  \n",
       "4             8.0  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calendar.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6211d77a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of listings dataframe is: (56739, 74)\n",
      "The shape of calendar dataframe is: (20707929, 7)\n"
     ]
    }
   ],
   "source": [
    "# Calculating the shapes of dataframes\n",
    "\n",
    "print('The shape of listings dataframe is:',listings.shape)\n",
    "print('The shape of calendar dataframe is:',calendar.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "aa57532f",
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>neighbourhood_group_cleansed</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>accommodates</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>calculated_host_listings_count_entire_homes</th>\n",
       "      <th>calculated_host_listings_count_private_rooms</th>\n",
       "      <th>calculated_host_listings_count_shared_rooms</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.673900e+04</td>\n",
       "      <td>5.673900e+04</td>\n",
       "      <td>5.673900e+04</td>\n",
       "      <td>56727.000000</td>\n",
       "      <td>56727.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>44684.000000</td>\n",
       "      <td>44673.000000</td>\n",
       "      <td>44681.000000</td>\n",
       "      <td>44670.000000</td>\n",
       "      <td>44668.000000</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>56739.000000</td>\n",
       "      <td>45281.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.935639e+16</td>\n",
       "      <td>2.022061e+13</td>\n",
       "      <td>1.128384e+08</td>\n",
       "      <td>12.481041</td>\n",
       "      <td>12.481041</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.863462</td>\n",
       "      <td>2.343554</td>\n",
       "      <td>3.060135</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.593612</td>\n",
       "      <td>4.793961</td>\n",
       "      <td>4.804103</td>\n",
       "      <td>4.789998</td>\n",
       "      <td>4.608434</td>\n",
       "      <td>10.025045</td>\n",
       "      <td>9.264915</td>\n",
       "      <td>0.538836</td>\n",
       "      <td>0.034826</td>\n",
       "      <td>0.980303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.922281e+17</td>\n",
       "      <td>2.722680e+01</td>\n",
       "      <td>1.360755e+08</td>\n",
       "      <td>83.879858</td>\n",
       "      <td>83.879858</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.020537</td>\n",
       "      <td>0.040348</td>\n",
       "      <td>1.666769</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.523597</td>\n",
       "      <td>0.402834</td>\n",
       "      <td>0.401047</td>\n",
       "      <td>0.353174</td>\n",
       "      <td>0.467024</td>\n",
       "      <td>31.835610</td>\n",
       "      <td>31.685771</td>\n",
       "      <td>3.410858</td>\n",
       "      <td>0.672199</td>\n",
       "      <td>1.541610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.396000e+03</td>\n",
       "      <td>2.022061e+13</td>\n",
       "      <td>2.626000e+03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.803750</td>\n",
       "      <td>2.206290</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.369082e+07</td>\n",
       "      <td>2.022061e+13</td>\n",
       "      <td>1.463397e+07</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.849310</td>\n",
       "      <td>2.319836</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.440000</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>4.780000</td>\n",
       "      <td>4.730000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.092530e+07</td>\n",
       "      <td>2.022061e+13</td>\n",
       "      <td>4.425650e+07</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.865160</td>\n",
       "      <td>2.347200</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.940000</td>\n",
       "      <td>4.900000</td>\n",
       "      <td>4.710000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.460000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.716712e+07</td>\n",
       "      <td>2.022061e+13</td>\n",
       "      <td>1.767666e+08</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.879630</td>\n",
       "      <td>2.370911</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.960000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.890000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.421428e+17</td>\n",
       "      <td>2.022061e+13</td>\n",
       "      <td>4.625783e+08</td>\n",
       "      <td>1246.000000</td>\n",
       "      <td>1246.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.913920</td>\n",
       "      <td>2.487250</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>233.000000</td>\n",
       "      <td>233.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>85.170000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id     scrape_id       host_id  host_listings_count  \\\n",
       "count  5.673900e+04  5.673900e+04  5.673900e+04         56727.000000   \n",
       "mean   6.935639e+16  2.022061e+13  1.128384e+08            12.481041   \n",
       "std    1.922281e+17  2.722680e+01  1.360755e+08            83.879858   \n",
       "min    5.396000e+03  2.022061e+13  2.626000e+03             0.000000   \n",
       "25%    1.369082e+07  2.022061e+13  1.463397e+07             1.000000   \n",
       "50%    3.092530e+07  2.022061e+13  4.425650e+07             1.000000   \n",
       "75%    4.716712e+07  2.022061e+13  1.767666e+08             2.000000   \n",
       "max    6.421428e+17  2.022061e+13  4.625783e+08          1246.000000   \n",
       "\n",
       "       host_total_listings_count  neighbourhood_group_cleansed      latitude  \\\n",
       "count               56727.000000                           0.0  56739.000000   \n",
       "mean                   12.481041                           NaN     48.863462   \n",
       "std                    83.879858                           NaN      0.020537   \n",
       "min                     0.000000                           NaN     48.803750   \n",
       "25%                     1.000000                           NaN     48.849310   \n",
       "50%                     1.000000                           NaN     48.865160   \n",
       "75%                     2.000000                           NaN     48.879630   \n",
       "max                  1246.000000                           NaN     48.913920   \n",
       "\n",
       "          longitude  accommodates  bathrooms  ...  review_scores_cleanliness  \\\n",
       "count  56739.000000  56739.000000        0.0  ...               44684.000000   \n",
       "mean       2.343554      3.060135        NaN  ...                   4.593612   \n",
       "std        0.040348      1.666769        NaN  ...                   0.523597   \n",
       "min        2.206290      0.000000        NaN  ...                   0.000000   \n",
       "25%        2.319836      2.000000        NaN  ...                   4.440000   \n",
       "50%        2.347200      2.000000        NaN  ...                   4.750000   \n",
       "75%        2.370911      4.000000        NaN  ...                   4.960000   \n",
       "max        2.487250     16.000000        NaN  ...                   5.000000   \n",
       "\n",
       "       review_scores_checkin  review_scores_communication  \\\n",
       "count           44673.000000                 44681.000000   \n",
       "mean                4.793961                     4.804103   \n",
       "std                 0.402834                     0.401047   \n",
       "min                 0.000000                     0.000000   \n",
       "25%                 4.750000                     4.780000   \n",
       "50%                 4.920000                     4.940000   \n",
       "75%                 5.000000                     5.000000   \n",
       "max                 5.000000                     5.000000   \n",
       "\n",
       "       review_scores_location  review_scores_value  \\\n",
       "count            44670.000000         44668.000000   \n",
       "mean                 4.789998             4.608434   \n",
       "std                  0.353174             0.467024   \n",
       "min                  0.000000             0.000000   \n",
       "25%                  4.730000             4.500000   \n",
       "50%                  4.900000             4.710000   \n",
       "75%                  5.000000             4.890000   \n",
       "max                  5.000000             5.000000   \n",
       "\n",
       "       calculated_host_listings_count  \\\n",
       "count                    56739.000000   \n",
       "mean                        10.025045   \n",
       "std                         31.835610   \n",
       "min                          1.000000   \n",
       "25%                          1.000000   \n",
       "50%                          1.000000   \n",
       "75%                          2.000000   \n",
       "max                        233.000000   \n",
       "\n",
       "       calculated_host_listings_count_entire_homes  \\\n",
       "count                                 56739.000000   \n",
       "mean                                      9.264915   \n",
       "std                                      31.685771   \n",
       "min                                       0.000000   \n",
       "25%                                       1.000000   \n",
       "50%                                       1.000000   \n",
       "75%                                       1.000000   \n",
       "max                                     233.000000   \n",
       "\n",
       "       calculated_host_listings_count_private_rooms  \\\n",
       "count                                  56739.000000   \n",
       "mean                                       0.538836   \n",
       "std                                        3.410858   \n",
       "min                                        0.000000   \n",
       "25%                                        0.000000   \n",
       "50%                                        0.000000   \n",
       "75%                                        0.000000   \n",
       "max                                       75.000000   \n",
       "\n",
       "       calculated_host_listings_count_shared_rooms  reviews_per_month  \n",
       "count                                 56739.000000       45281.000000  \n",
       "mean                                      0.034826           0.980303  \n",
       "std                                       0.672199           1.541610  \n",
       "min                                       0.000000           0.010000  \n",
       "25%                                       0.000000           0.140000  \n",
       "50%                                       0.000000           0.460000  \n",
       "75%                                       0.000000           1.220000  \n",
       "max                                      26.000000          85.170000  \n",
       "\n",
       "[8 rows x 40 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Viewing some descriptive statistics about the numerical values of listings dataframe\n",
    "listings.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b17740bb",
   "metadata": {},
   "source": [
    "\n",
    "We can notice for the moment that **neighbourhood_group_cleansed** and **bathrooms** are the columns with the most missing values. We can confirm that by taking a look into the number of missing values per column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e8814948",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                                  0\n",
       "availability_30                     0\n",
       "number_of_reviews                   0\n",
       "neighbourhood_cleansed              0\n",
       "calendar_last_scraped               0\n",
       "                                ...  \n",
       "license                         24724\n",
       "host_about                      29151\n",
       "calendar_updated                56739\n",
       "neighbourhood_group_cleansed    56739\n",
       "bathrooms                       56739\n",
       "Length: 74, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View the count of missing values of listings dataframe\n",
    "\n",
    "listings.isnull().sum().sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c44c7563",
   "metadata": {},
   "source": [
    "We can also notice that the **calendar_updated** column is full of missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9fd7f136",
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# Plot the ratio of missing values with the number of values for the listings dataframe\n",
    "\n",
    "(listings.isnull().sum()/listings.shape[0]).sort_values(ascending=False)[:10].plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25b36482",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "This plot shows the top 10 columns with missing values, we can see that **neighbourhood_group_cleansed**, **bathrooms** and **calendar_updated** come first with 100 % of missing values rate compared to the whole values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6711a7c4",
   "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>listing_id</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.070793e+07</td>\n",
       "      <td>2.070756e+07</td>\n",
       "      <td>2.070756e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.936259e+16</td>\n",
       "      <td>8.954375e+01</td>\n",
       "      <td>4.780960e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.922339e+17</td>\n",
       "      <td>1.602215e+02</td>\n",
       "      <td>3.200689e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.396000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.368675e+07</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>3.000000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.092166e+07</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.125000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.716802e+07</td>\n",
       "      <td>3.000000e+01</td>\n",
       "      <td>1.125000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.421428e+17</td>\n",
       "      <td>9.999000e+03</td>\n",
       "      <td>2.147484e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         listing_id  minimum_nights  maximum_nights\n",
       "count  2.070793e+07    2.070756e+07    2.070756e+07\n",
       "mean   6.936259e+16    8.954375e+01    4.780960e+05\n",
       "std    1.922339e+17    1.602215e+02    3.200689e+07\n",
       "min    5.396000e+03    1.000000e+00    1.000000e+00\n",
       "25%    1.368675e+07    2.000000e+00    3.000000e+02\n",
       "50%    3.092166e+07    3.000000e+00    1.125000e+03\n",
       "75%    4.716802e+07    3.000000e+01    1.125000e+03\n",
       "max    6.421428e+17    9.999000e+03    2.147484e+09"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Viewing some descriptive statistics about the numerical values of calendar dataframe\n",
    "calendar.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93c95361",
   "metadata": {},
   "source": [
    "\n",
    "We can notice that **maxiumum_nights** is the column with the biggest variations of values.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b14d20bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "listing_id          0\n",
       "date                0\n",
       "available           0\n",
       "price             173\n",
       "adjusted_price    173\n",
       "minimum_nights    366\n",
       "maximum_nights    366\n",
       "dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View the count of missing values of calendar dataframe\n",
    "calendar.isnull().sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "88a1246f",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "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": [
    "# Plot the number of missing values with the number of values for the calendar dataframe\n",
    "(calendar.isnull().sum()).plot(kind='bar');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d82f27ae",
   "metadata": {},
   "source": [
    "\n",
    "We can conclude from the previous figure that there's a small number of missing values in **calendar** dataframe compared to the whole size of the dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3353ed3e",
   "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>id</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>description</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>picture_url</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_url</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>calculated_host_listings_count_entire_homes</th>\n",
       "      <th>calculated_host_listings_count_private_rooms</th>\n",
       "      <th>calculated_host_listings_count_shared_rooms</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26660141</td>\n",
       "      <td>https://www.airbnb.com/rooms/26660141</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>CHARMANT APPARTEMENT,  50M2 AUX PORTES DE PARIS</td>\n",
       "      <td>Charmant appartement avec petit balcon filant,...</td>\n",
       "      <td>La rue principale à la sortie du métro est trè...</td>\n",
       "      <td>https://a0.muscache.com/pictures/a776b332-0fde...</td>\n",
       "      <td>200407698</td>\n",
       "      <td>https://www.airbnb.com/users/show/200407698</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.88</td>\n",
       "      <td>4.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25177338</td>\n",
       "      <td>https://www.airbnb.com/rooms/25177338</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>Cosy and quiet appartement at Les Lilas</td>\n",
       "      <td>&lt;b&gt;The space&lt;/b&gt;&lt;br /&gt;Le logement est situé da...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/pictures/e984c1e4-6d40...</td>\n",
       "      <td>185793394</td>\n",
       "      <td>https://www.airbnb.com/users/show/185793394</td>\n",
       "      <td>...</td>\n",
       "      <td>4.56</td>\n",
       "      <td>4.50</td>\n",
       "      <td>4.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>t</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25218084</td>\n",
       "      <td>https://www.airbnb.com/rooms/25218084</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>paris avec une maison</td>\n",
       "      <td>une maison restaurée et faite à notre image ap...</td>\n",
       "      <td>Être dans un véritable maison avec un parc à q...</td>\n",
       "      <td>https://a0.muscache.com/pictures/dbfc69a1-76cb...</td>\n",
       "      <td>190542280</td>\n",
       "      <td>https://www.airbnb.com/users/show/190542280</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23135649</td>\n",
       "      <td>https://www.airbnb.com/rooms/23135649</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>Charming studio, Pont de Neuilly - Paris</td>\n",
       "      <td>Studio apartment in the heart of the prestigio...</td>\n",
       "      <td>The Saint James district of Neuilly sur Seine ...</td>\n",
       "      <td>https://a0.muscache.com/pictures/58399f3d-c271...</td>\n",
       "      <td>171938056</td>\n",
       "      <td>https://www.airbnb.com/users/show/171938056</td>\n",
       "      <td>...</td>\n",
       "      <td>4.94</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23259887</td>\n",
       "      <td>https://www.airbnb.com/rooms/23259887</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>A cosy appartement</td>\n",
       "      <td>Situé dans un quartier agréable proche de Chât...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://a0.muscache.com/pictures/ad0ade9c-89d5...</td>\n",
       "      <td>20135501</td>\n",
       "      <td>https://www.airbnb.com/users/show/20135501</td>\n",
       "      <td>...</td>\n",
       "      <td>4.86</td>\n",
       "      <td>4.91</td>\n",
       "      <td>4.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>t</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 71 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id                            listing_url       scrape_id  \\\n",
       "0  26660141  https://www.airbnb.com/rooms/26660141  20220606014139   \n",
       "1  25177338  https://www.airbnb.com/rooms/25177338  20220606014139   \n",
       "2  25218084  https://www.airbnb.com/rooms/25218084  20220606014139   \n",
       "3  23135649  https://www.airbnb.com/rooms/23135649  20220606014139   \n",
       "4  23259887  https://www.airbnb.com/rooms/23259887  20220606014139   \n",
       "\n",
       "  last_scraped                                             name  \\\n",
       "0   2022-06-07  CHARMANT APPARTEMENT,  50M2 AUX PORTES DE PARIS   \n",
       "1   2022-06-07          Cosy and quiet appartement at Les Lilas   \n",
       "2   2022-06-07                            paris avec une maison   \n",
       "3   2022-06-07         Charming studio, Pont de Neuilly - Paris   \n",
       "4   2022-06-07                               A cosy appartement   \n",
       "\n",
       "                                         description  \\\n",
       "0  Charmant appartement avec petit balcon filant,...   \n",
       "1  <b>The space</b><br />Le logement est situé da...   \n",
       "2  une maison restaurée et faite à notre image ap...   \n",
       "3  Studio apartment in the heart of the prestigio...   \n",
       "4  Situé dans un quartier agréable proche de Chât...   \n",
       "\n",
       "                               neighborhood_overview  \\\n",
       "0  La rue principale à la sortie du métro est trè...   \n",
       "1                                                NaN   \n",
       "2  Être dans un véritable maison avec un parc à q...   \n",
       "3  The Saint James district of Neuilly sur Seine ...   \n",
       "4                                                NaN   \n",
       "\n",
       "                                         picture_url    host_id  \\\n",
       "0  https://a0.muscache.com/pictures/a776b332-0fde...  200407698   \n",
       "1  https://a0.muscache.com/pictures/e984c1e4-6d40...  185793394   \n",
       "2  https://a0.muscache.com/pictures/dbfc69a1-76cb...  190542280   \n",
       "3  https://a0.muscache.com/pictures/58399f3d-c271...  171938056   \n",
       "4  https://a0.muscache.com/pictures/ad0ade9c-89d5...   20135501   \n",
       "\n",
       "                                      host_url  ...  \\\n",
       "0  https://www.airbnb.com/users/show/200407698  ...   \n",
       "1  https://www.airbnb.com/users/show/185793394  ...   \n",
       "2  https://www.airbnb.com/users/show/190542280  ...   \n",
       "3  https://www.airbnb.com/users/show/171938056  ...   \n",
       "4   https://www.airbnb.com/users/show/20135501  ...   \n",
       "\n",
       "  review_scores_communication review_scores_location review_scores_value  \\\n",
       "0                        5.00                   4.88                4.94   \n",
       "1                        4.56                   4.50                4.56   \n",
       "2                        5.00                   4.50                5.00   \n",
       "3                        4.94                   4.87                4.61   \n",
       "4                        4.86                   4.91                4.65   \n",
       "\n",
       "  license instant_bookable calculated_host_listings_count  \\\n",
       "0     NaN                f                              1   \n",
       "1     NaN                t                              1   \n",
       "2     NaN                f                              1   \n",
       "3     NaN                f                              1   \n",
       "4     NaN                t                              1   \n",
       "\n",
       "  calculated_host_listings_count_entire_homes  \\\n",
       "0                                           1   \n",
       "1                                           1   \n",
       "2                                           1   \n",
       "3                                           0   \n",
       "4                                           1   \n",
       "\n",
       "  calculated_host_listings_count_private_rooms  \\\n",
       "0                                            0   \n",
       "1                                            0   \n",
       "2                                            0   \n",
       "3                                            1   \n",
       "4                                            0   \n",
       "\n",
       "  calculated_host_listings_count_shared_rooms reviews_per_month  \n",
       "0                                           0              0.38  \n",
       "1                                           0              0.35  \n",
       "2                                           0              0.05  \n",
       "3                                           0              0.65  \n",
       "4                                           0              0.87  \n",
       "\n",
       "[5 rows x 71 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop the duplicates and columns that are fully missing from the listings dataframe\n",
    "listings = listings.drop_duplicates()\n",
    "listings = listings.dropna(axis=1,how='all')\n",
    "listings.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61f3d10b",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "We dropped the **neighbourhood_group_cleansed**, **bathrooms** and **calendar_updated** columns from the listings dataframe.\n",
    "\n",
    "Since we are interested in solving our first question about the **most booked neighbourhoods in Paris**, we are going to work with a slice of the data that doesn't include missing values in the **neighbourhood** column and **neighbourhood_cleansed** column. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "fe23e2b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>name</th>\n",
       "      <th>description</th>\n",
       "      <th>neighborhood_overview</th>\n",
       "      <th>picture_url</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_url</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>calculated_host_listings_count_entire_homes</th>\n",
       "      <th>calculated_host_listings_count_private_rooms</th>\n",
       "      <th>calculated_host_listings_count_shared_rooms</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26660141</td>\n",
       "      <td>https://www.airbnb.com/rooms/26660141</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>CHARMANT APPARTEMENT,  50M2 AUX PORTES DE PARIS</td>\n",
       "      <td>Charmant appartement avec petit balcon filant,...</td>\n",
       "      <td>La rue principale à la sortie du métro est trè...</td>\n",
       "      <td>https://a0.muscache.com/pictures/a776b332-0fde...</td>\n",
       "      <td>200407698</td>\n",
       "      <td>https://www.airbnb.com/users/show/200407698</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.88</td>\n",
       "      <td>4.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25218084</td>\n",
       "      <td>https://www.airbnb.com/rooms/25218084</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>paris avec une maison</td>\n",
       "      <td>une maison restaurée et faite à notre image ap...</td>\n",
       "      <td>Être dans un véritable maison avec un parc à q...</td>\n",
       "      <td>https://a0.muscache.com/pictures/dbfc69a1-76cb...</td>\n",
       "      <td>190542280</td>\n",
       "      <td>https://www.airbnb.com/users/show/190542280</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23135649</td>\n",
       "      <td>https://www.airbnb.com/rooms/23135649</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>Charming studio, Pont de Neuilly - Paris</td>\n",
       "      <td>Studio apartment in the heart of the prestigio...</td>\n",
       "      <td>The Saint James district of Neuilly sur Seine ...</td>\n",
       "      <td>https://a0.muscache.com/pictures/58399f3d-c271...</td>\n",
       "      <td>171938056</td>\n",
       "      <td>https://www.airbnb.com/users/show/171938056</td>\n",
       "      <td>...</td>\n",
       "      <td>4.94</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>26767859</td>\n",
       "      <td>https://www.airbnb.com/rooms/26767859</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>Private room in a beautiful duplex next to Paris</td>\n",
       "      <td>Private room in a nice duplex (with two rooms)...</td>\n",
       "      <td>10 minutes walk from the Parc de la Villette (...</td>\n",
       "      <td>https://a0.muscache.com/pictures/1de4e19a-a452...</td>\n",
       "      <td>7786899</td>\n",
       "      <td>https://www.airbnb.com/users/show/7786899</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9748063</td>\n",
       "      <td>https://www.airbnb.com/rooms/9748063</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>High standing residence,  amazing view over Paris</td>\n",
       "      <td>Bright, panoramic view over Paris, Triple orie...</td>\n",
       "      <td>Puteaux is located at the doors of Paris and t...</td>\n",
       "      <td>https://a0.muscache.com/pictures/e8102d2c-2f6b...</td>\n",
       "      <td>50285920</td>\n",
       "      <td>https://www.airbnb.com/users/show/50285920</td>\n",
       "      <td>...</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.71</td>\n",
       "      <td>4.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 71 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id                            listing_url       scrape_id  \\\n",
       "0  26660141  https://www.airbnb.com/rooms/26660141  20220606014139   \n",
       "2  25218084  https://www.airbnb.com/rooms/25218084  20220606014139   \n",
       "3  23135649  https://www.airbnb.com/rooms/23135649  20220606014139   \n",
       "6  26767859  https://www.airbnb.com/rooms/26767859  20220606014139   \n",
       "9   9748063   https://www.airbnb.com/rooms/9748063  20220606014139   \n",
       "\n",
       "  last_scraped                                               name  \\\n",
       "0   2022-06-07    CHARMANT APPARTEMENT,  50M2 AUX PORTES DE PARIS   \n",
       "2   2022-06-07                              paris avec une maison   \n",
       "3   2022-06-07           Charming studio, Pont de Neuilly - Paris   \n",
       "6   2022-06-07   Private room in a beautiful duplex next to Paris   \n",
       "9   2022-06-06  High standing residence,  amazing view over Paris   \n",
       "\n",
       "                                         description  \\\n",
       "0  Charmant appartement avec petit balcon filant,...   \n",
       "2  une maison restaurée et faite à notre image ap...   \n",
       "3  Studio apartment in the heart of the prestigio...   \n",
       "6  Private room in a nice duplex (with two rooms)...   \n",
       "9  Bright, panoramic view over Paris, Triple orie...   \n",
       "\n",
       "                               neighborhood_overview  \\\n",
       "0  La rue principale à la sortie du métro est trè...   \n",
       "2  Être dans un véritable maison avec un parc à q...   \n",
       "3  The Saint James district of Neuilly sur Seine ...   \n",
       "6  10 minutes walk from the Parc de la Villette (...   \n",
       "9  Puteaux is located at the doors of Paris and t...   \n",
       "\n",
       "                                         picture_url    host_id  \\\n",
       "0  https://a0.muscache.com/pictures/a776b332-0fde...  200407698   \n",
       "2  https://a0.muscache.com/pictures/dbfc69a1-76cb...  190542280   \n",
       "3  https://a0.muscache.com/pictures/58399f3d-c271...  171938056   \n",
       "6  https://a0.muscache.com/pictures/1de4e19a-a452...    7786899   \n",
       "9  https://a0.muscache.com/pictures/e8102d2c-2f6b...   50285920   \n",
       "\n",
       "                                      host_url  ...  \\\n",
       "0  https://www.airbnb.com/users/show/200407698  ...   \n",
       "2  https://www.airbnb.com/users/show/190542280  ...   \n",
       "3  https://www.airbnb.com/users/show/171938056  ...   \n",
       "6    https://www.airbnb.com/users/show/7786899  ...   \n",
       "9   https://www.airbnb.com/users/show/50285920  ...   \n",
       "\n",
       "  review_scores_communication review_scores_location review_scores_value  \\\n",
       "0                        5.00                   4.88                4.94   \n",
       "2                        5.00                   4.50                5.00   \n",
       "3                        4.94                   4.87                4.61   \n",
       "6                        5.00                   4.00                4.00   \n",
       "9                        4.85                   4.71                4.73   \n",
       "\n",
       "  license instant_bookable calculated_host_listings_count  \\\n",
       "0     NaN                f                              1   \n",
       "2     NaN                f                              1   \n",
       "3     NaN                f                              1   \n",
       "6     NaN                f                              3   \n",
       "9     NaN                f                              1   \n",
       "\n",
       "  calculated_host_listings_count_entire_homes  \\\n",
       "0                                           1   \n",
       "2                                           1   \n",
       "3                                           0   \n",
       "6                                           1   \n",
       "9                                           1   \n",
       "\n",
       "  calculated_host_listings_count_private_rooms  \\\n",
       "0                                            0   \n",
       "2                                            0   \n",
       "3                                            1   \n",
       "6                                            2   \n",
       "9                                            0   \n",
       "\n",
       "  calculated_host_listings_count_shared_rooms reviews_per_month  \n",
       "0                                           0              0.38  \n",
       "2                                           0              0.05  \n",
       "3                                           0              0.65  \n",
       "6                                           0              0.03  \n",
       "9                                           0              0.75  \n",
       "\n",
       "[5 rows x 71 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listings = listings.dropna(subset=['neighbourhood','neighbourhood_cleansed'])\n",
    "listings.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ef19a4b",
   "metadata": {},
   "source": [
    "### To answer the first question, we need to merge the two dataframes **listings** and **calendar** to get more insights about the availability of listings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "ee413430",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename the column listings ID column to match with listing_id in calendar dataframe \n",
    "# and also calendar_last_scraped to match the date column of calendar dataframe\n",
    "listings.rename(columns={\"id\":'listing_id','calendar_last_scraped':'date','has_availability':'available'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "16e2690e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['listing_id', 'listing_url', 'scrape_id', 'last_scraped', 'name',\n",
       "       'description', 'neighborhood_overview', 'picture_url', 'host_id',\n",
       "       'host_url', 'host_name', 'host_since', 'host_location', 'host_about',\n",
       "       'host_response_time', 'host_response_rate', 'host_acceptance_rate',\n",
       "       'host_is_superhost', 'host_thumbnail_url', 'host_picture_url',\n",
       "       'host_neighbourhood', 'host_listings_count',\n",
       "       'host_total_listings_count', 'host_verifications',\n",
       "       'host_has_profile_pic', 'host_identity_verified', 'neighbourhood',\n",
       "       'neighbourhood_cleansed', 'latitude', 'longitude', 'property_type',\n",
       "       'room_type', 'accommodates', 'bathrooms_text', 'bedrooms', 'beds',\n",
       "       'amenities', 'price', 'minimum_nights', 'maximum_nights',\n",
       "       'minimum_minimum_nights', 'maximum_minimum_nights',\n",
       "       'minimum_maximum_nights', 'maximum_maximum_nights',\n",
       "       'minimum_nights_avg_ntm', 'maximum_nights_avg_ntm', 'available',\n",
       "       'availability_30', 'availability_60', 'availability_90',\n",
       "       'availability_365', 'date', 'number_of_reviews',\n",
       "       'number_of_reviews_ltm', 'number_of_reviews_l30d', 'first_review',\n",
       "       'last_review', 'review_scores_rating', 'review_scores_accuracy',\n",
       "       'review_scores_cleanliness', 'review_scores_checkin',\n",
       "       'review_scores_communication', 'review_scores_location',\n",
       "       'review_scores_value', 'license', 'instant_bookable',\n",
       "       'calculated_host_listings_count',\n",
       "       'calculated_host_listings_count_entire_homes',\n",
       "       'calculated_host_listings_count_private_rooms',\n",
       "       'calculated_host_listings_count_shared_rooms', 'reviews_per_month'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listings.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a557778a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "f    14868257\n",
       "t     5839672\n",
       "Name: available, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View the availability options from calendar dataframe\n",
    "calendar.available.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "2e067b7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "t    33199\n",
       "f       56\n",
       "Name: available, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View the available and booked listings \n",
    "listings.available.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6e05053",
   "metadata": {},
   "source": [
    "We have a binary availability options **t** for True which means available listing and **f** for False that means booked listing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "cd41c955",
   "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>listing_id</th>\n",
       "      <th>date</th>\n",
       "      <th>available</th>\n",
       "      <th>price</th>\n",
       "      <th>adjusted_price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-08</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-09</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-10</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26660141</td>\n",
       "      <td>2022-06-11</td>\n",
       "      <td>f</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>$90.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   listing_id        date available   price adjusted_price  minimum_nights  \\\n",
       "0    26660141  2022-06-07         f  $90.00         $90.00             5.0   \n",
       "1    26660141  2022-06-08         f  $90.00         $90.00             5.0   \n",
       "2    26660141  2022-06-09         f  $90.00         $90.00             5.0   \n",
       "3    26660141  2022-06-10         f  $90.00         $90.00             5.0   \n",
       "4    26660141  2022-06-11         f  $90.00         $90.00             5.0   \n",
       "\n",
       "   maximum_nights  \n",
       "0             8.0  \n",
       "1             8.0  \n",
       "2             8.0  \n",
       "3             8.0  \n",
       "4             8.0  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the booked listings and drop missing values and duplicates\n",
    "calendar = calendar.dropna(subset=['listing_id','available','date','minimum_nights','maximum_nights'])\n",
    "calendar = calendar.drop_duplicates()\n",
    "booked_listings = calendar.loc[calendar.available=='f']\n",
    "booked_listings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "befe9a68",
   "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>listing_id</th>\n",
       "      <th>date</th>\n",
       "      <th>available</th>\n",
       "      <th>price</th>\n",
       "      <th>adjusted_price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>calculated_host_listings_count_entire_homes</th>\n",
       "      <th>calculated_host_listings_count_private_rooms</th>\n",
       "      <th>calculated_host_listings_count_shared_rooms</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1384098</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$140.00</td>\n",
       "      <td>$140.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/1384098</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>4.67</td>\n",
       "      <td>4.33</td>\n",
       "      <td>4.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2142687</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$46.00</td>\n",
       "      <td>$46.00</td>\n",
       "      <td>120.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/2142687</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.95</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.75</td>\n",
       "      <td>Available with a mobility lease only (\"bail mo...</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3076637</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$360.00</td>\n",
       "      <td>$360.00</td>\n",
       "      <td>7.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/3076637</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4806693</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$226.00</td>\n",
       "      <td>$226.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/4806693</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5475961</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$99.00</td>\n",
       "      <td>$99.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/5475961</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.71</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6106068</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$80.00</td>\n",
       "      <td>$80.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/6106068</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7003002</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$79.00</td>\n",
       "      <td>$79.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/7003002</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7222381</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$160.00</td>\n",
       "      <td>$160.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/7222381</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7271622</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$55.00</td>\n",
       "      <td>$55.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/7271622</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8181428</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$38.00</td>\n",
       "      <td>$38.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/8181428</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8380535</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$49.00</td>\n",
       "      <td>$49.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/8380535</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9049740</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$51.00</td>\n",
       "      <td>$51.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/9049740</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10727407</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$80.00</td>\n",
       "      <td>$80.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/10727407</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10897769</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$60.00</td>\n",
       "      <td>$60.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/10897769</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>12533798</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$60.00</td>\n",
       "      <td>$60.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/12533798</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>14004277</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$125.00</td>\n",
       "      <td>$125.00</td>\n",
       "      <td>7.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/14004277</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>4.69</td>\n",
       "      <td>4.78</td>\n",
       "      <td>4.73</td>\n",
       "      <td>7511703170231</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>18171688</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$85.00</td>\n",
       "      <td>$85.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/18171688</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18146940</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$113.00</td>\n",
       "      <td>$113.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/18146940</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>4.74</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.51</td>\n",
       "      <td>7511001701467</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20228970</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$40.00</td>\n",
       "      <td>$40.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/20228970</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>25577292</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$92.00</td>\n",
       "      <td>$92.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/25577292</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.82</td>\n",
       "      <td>4.89</td>\n",
       "      <td>4.46</td>\n",
       "      <td>7511401913371</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>26430769</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$85.00</td>\n",
       "      <td>$85.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/26430769</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>27029503</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$45.00</td>\n",
       "      <td>$45.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/27029503</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>30690798</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$160.00</td>\n",
       "      <td>$160.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/30690798</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7511502718543</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>30761855</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$82.00</td>\n",
       "      <td>$82.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/30761855</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.92</td>\n",
       "      <td>4.50</td>\n",
       "      <td>7511002680573</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>32753347</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$115.00</td>\n",
       "      <td>$115.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/32753347</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>35543595</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$45.00</td>\n",
       "      <td>$45.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/35543595</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>35700689</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$200.00</td>\n",
       "      <td>$200.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/35700689</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>36799515</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$65.00</td>\n",
       "      <td>$65.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/36799515</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>4.78</td>\n",
       "      <td>4.93</td>\n",
       "      <td>4.57</td>\n",
       "      <td>7511203776124</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>40675708</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$140.00</td>\n",
       "      <td>$140.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/40675708</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>40931504</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$77.00</td>\n",
       "      <td>$77.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/40931504</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.18</td>\n",
       "      <td>7511304252484</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>40907092</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$84.00</td>\n",
       "      <td>$84.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/40907092</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.79</td>\n",
       "      <td>4.79</td>\n",
       "      <td>4.63</td>\n",
       "      <td>7511004261475</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>41264583</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$418.00</td>\n",
       "      <td>$418.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/41264583</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>44091787</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$75.00</td>\n",
       "      <td>$75.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/44091787</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.64</td>\n",
       "      <td>4.57</td>\n",
       "      <td>4.64</td>\n",
       "      <td>7511804594025</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>45743800</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$59.00</td>\n",
       "      <td>$59.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/45743800</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>3.33</td>\n",
       "      <td>4.67</td>\n",
       "      <td>4.00</td>\n",
       "      <td>7511204601416</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>47325501</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$135.00</td>\n",
       "      <td>$108.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/47325501</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.77</td>\n",
       "      <td>4.44</td>\n",
       "      <td>4.27</td>\n",
       "      <td>7511004752712</td>\n",
       "      <td>f</td>\n",
       "      <td>98</td>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>50024965</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$210.00</td>\n",
       "      <td>$210.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/50024965</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Available with a mobility lease only (\"bail mo...</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>51314622</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$87.00</td>\n",
       "      <td>$87.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/51314622</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.60</td>\n",
       "      <td>7510905513495</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>53521019</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$217.00</td>\n",
       "      <td>$217.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/53521019</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>7511005939278</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>54372932</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$83.00</td>\n",
       "      <td>$83.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/54372932</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>7511906079284</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>549756582281388816</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$60.00</td>\n",
       "      <td>$60.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/549756582281388816</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>605621159096518819</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$56.00</td>\n",
       "      <td>$56.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/605621159096518819</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7511505554903</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>605622762821121970</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$95.00</td>\n",
       "      <td>$95.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/605622762821121970</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7511803940165</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>605624107364152491</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$73.00</td>\n",
       "      <td>$73.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/605624107364152491</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7510301545866</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>610734301192562815</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$76.00</td>\n",
       "      <td>$76.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/610734301192562815</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Available with a mobility lease only (\"bail mo...</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>614197429015067131</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$58.00</td>\n",
       "      <td>$58.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/614197429015067131</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7511505554804</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>614197797820515063</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$58.00</td>\n",
       "      <td>$58.00</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/614197797820515063</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Available with a mobility lease only (\"bail mo...</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>615741987349944051</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$69.00</td>\n",
       "      <td>$69.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/615741987349944051</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Available with a mobility lease only (\"bail mo...</td>\n",
       "      <td>f</td>\n",
       "      <td>130</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47 rows × 72 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            listing_id        date available    price adjusted_price  \\\n",
       "0              1384098  2022-06-06         f  $140.00        $140.00   \n",
       "1              2142687  2022-06-07         f   $46.00         $46.00   \n",
       "2              3076637  2022-06-07         f  $360.00        $360.00   \n",
       "3              4806693  2022-06-07         f  $226.00        $226.00   \n",
       "4              5475961  2022-06-07         f   $99.00         $99.00   \n",
       "5              6106068  2022-06-07         f   $80.00         $80.00   \n",
       "6              7003002  2022-06-07         f   $79.00         $79.00   \n",
       "7              7222381  2022-06-07         f  $160.00        $160.00   \n",
       "8              7271622  2022-06-07         f   $55.00         $55.00   \n",
       "9              8181428  2022-06-07         f   $38.00         $38.00   \n",
       "10             8380535  2022-06-07         f   $49.00         $49.00   \n",
       "11             9049740  2022-06-07         f   $51.00         $51.00   \n",
       "12            10727407  2022-06-07         f   $80.00         $80.00   \n",
       "13            10897769  2022-06-07         f   $60.00         $60.00   \n",
       "14            12533798  2022-06-07         f   $60.00         $60.00   \n",
       "15            14004277  2022-06-06         f  $125.00        $125.00   \n",
       "16            18171688  2022-06-06         f   $85.00         $85.00   \n",
       "17            18146940  2022-06-06         f  $113.00        $113.00   \n",
       "18            20228970  2022-06-06         f   $40.00         $40.00   \n",
       "19            25577292  2022-06-07         f   $92.00         $92.00   \n",
       "20            26430769  2022-06-07         f   $85.00         $85.00   \n",
       "21            27029503  2022-06-07         f   $45.00         $45.00   \n",
       "22            30690798  2022-06-07         f  $160.00        $160.00   \n",
       "23            30761855  2022-06-07         f   $82.00         $82.00   \n",
       "24            32753347  2022-06-07         f  $115.00        $115.00   \n",
       "25            35543595  2022-06-07         f   $45.00         $45.00   \n",
       "26            35700689  2022-06-07         f  $200.00        $200.00   \n",
       "27            36799515  2022-06-06         f   $65.00         $65.00   \n",
       "28            40675708  2022-06-07         f  $140.00        $140.00   \n",
       "29            40931504  2022-06-07         f   $77.00         $77.00   \n",
       "30            40907092  2022-06-07         f   $84.00         $84.00   \n",
       "31            41264583  2022-06-07         f  $418.00        $418.00   \n",
       "32            44091787  2022-06-07         f   $75.00         $75.00   \n",
       "33            45743800  2022-06-07         f   $59.00         $59.00   \n",
       "34            47325501  2022-06-07         f  $135.00        $108.00   \n",
       "35            50024965  2022-06-07         f  $210.00        $210.00   \n",
       "36            51314622  2022-06-07         f   $87.00         $87.00   \n",
       "37            53521019  2022-06-07         f  $217.00        $217.00   \n",
       "38            54372932  2022-06-07         f   $83.00         $83.00   \n",
       "39  549756582281388816  2022-06-06         f   $60.00         $60.00   \n",
       "40  605621159096518819  2022-06-07         f   $56.00         $56.00   \n",
       "41  605622762821121970  2022-06-07         f   $95.00         $95.00   \n",
       "42  605624107364152491  2022-06-07         f   $73.00         $73.00   \n",
       "43  610734301192562815  2022-06-07         f   $76.00         $76.00   \n",
       "44  614197429015067131  2022-06-07         f   $58.00         $58.00   \n",
       "45  614197797820515063  2022-06-07         f   $58.00         $58.00   \n",
       "46  615741987349944051  2022-06-07         f   $69.00         $69.00   \n",
       "\n",
       "    minimum_nights  maximum_nights  \\\n",
       "0            365.0          1125.0   \n",
       "1            120.0           365.0   \n",
       "2              7.0            21.0   \n",
       "3            365.0          1125.0   \n",
       "4            365.0          1125.0   \n",
       "5            365.0          1125.0   \n",
       "6            365.0           365.0   \n",
       "7            365.0          1125.0   \n",
       "8            365.0          1125.0   \n",
       "9              1.0             2.0   \n",
       "10           365.0          1125.0   \n",
       "11             1.0          1125.0   \n",
       "12           365.0          1125.0   \n",
       "13           365.0          1125.0   \n",
       "14           365.0          1125.0   \n",
       "15             7.0            90.0   \n",
       "16           365.0          1125.0   \n",
       "17             1.0          1125.0   \n",
       "18           365.0          1125.0   \n",
       "19             1.0          1125.0   \n",
       "20           365.0          1125.0   \n",
       "21             1.0          1125.0   \n",
       "22             2.0            15.0   \n",
       "23             1.0          1125.0   \n",
       "24             2.0            31.0   \n",
       "25           365.0          1125.0   \n",
       "26           365.0          1125.0   \n",
       "27             3.0            14.0   \n",
       "28           365.0          1125.0   \n",
       "29             1.0          1125.0   \n",
       "30             1.0          1125.0   \n",
       "31           365.0          1125.0   \n",
       "32             1.0          1125.0   \n",
       "33             1.0           365.0   \n",
       "34             1.0          1125.0   \n",
       "35            30.0          1125.0   \n",
       "36             1.0           365.0   \n",
       "37             1.0           365.0   \n",
       "38             1.0           365.0   \n",
       "39             3.0           365.0   \n",
       "40            90.0          1125.0   \n",
       "41            90.0          1125.0   \n",
       "42            90.0          1125.0   \n",
       "43            90.0          1125.0   \n",
       "44            90.0          1125.0   \n",
       "45            90.0          1125.0   \n",
       "46            30.0          1125.0   \n",
       "\n",
       "                                        listing_url       scrape_id  \\\n",
       "0              https://www.airbnb.com/rooms/1384098  20220606014139   \n",
       "1              https://www.airbnb.com/rooms/2142687  20220606014139   \n",
       "2              https://www.airbnb.com/rooms/3076637  20220606014139   \n",
       "3              https://www.airbnb.com/rooms/4806693  20220606014139   \n",
       "4              https://www.airbnb.com/rooms/5475961  20220606014139   \n",
       "5              https://www.airbnb.com/rooms/6106068  20220606014139   \n",
       "6              https://www.airbnb.com/rooms/7003002  20220606014139   \n",
       "7              https://www.airbnb.com/rooms/7222381  20220606014139   \n",
       "8              https://www.airbnb.com/rooms/7271622  20220606014139   \n",
       "9              https://www.airbnb.com/rooms/8181428  20220606014139   \n",
       "10             https://www.airbnb.com/rooms/8380535  20220606014139   \n",
       "11             https://www.airbnb.com/rooms/9049740  20220606014139   \n",
       "12            https://www.airbnb.com/rooms/10727407  20220606014139   \n",
       "13            https://www.airbnb.com/rooms/10897769  20220606014139   \n",
       "14            https://www.airbnb.com/rooms/12533798  20220606014139   \n",
       "15            https://www.airbnb.com/rooms/14004277  20220606014139   \n",
       "16            https://www.airbnb.com/rooms/18171688  20220606014139   \n",
       "17            https://www.airbnb.com/rooms/18146940  20220606014139   \n",
       "18            https://www.airbnb.com/rooms/20228970  20220606014139   \n",
       "19            https://www.airbnb.com/rooms/25577292  20220606014139   \n",
       "20            https://www.airbnb.com/rooms/26430769  20220606014139   \n",
       "21            https://www.airbnb.com/rooms/27029503  20220606014139   \n",
       "22            https://www.airbnb.com/rooms/30690798  20220606014139   \n",
       "23            https://www.airbnb.com/rooms/30761855  20220606014139   \n",
       "24            https://www.airbnb.com/rooms/32753347  20220606014139   \n",
       "25            https://www.airbnb.com/rooms/35543595  20220606014139   \n",
       "26            https://www.airbnb.com/rooms/35700689  20220606014139   \n",
       "27            https://www.airbnb.com/rooms/36799515  20220606014139   \n",
       "28            https://www.airbnb.com/rooms/40675708  20220606014139   \n",
       "29            https://www.airbnb.com/rooms/40931504  20220606014139   \n",
       "30            https://www.airbnb.com/rooms/40907092  20220606014139   \n",
       "31            https://www.airbnb.com/rooms/41264583  20220606014139   \n",
       "32            https://www.airbnb.com/rooms/44091787  20220606014139   \n",
       "33            https://www.airbnb.com/rooms/45743800  20220606014139   \n",
       "34            https://www.airbnb.com/rooms/47325501  20220606014139   \n",
       "35            https://www.airbnb.com/rooms/50024965  20220606014139   \n",
       "36            https://www.airbnb.com/rooms/51314622  20220606014139   \n",
       "37            https://www.airbnb.com/rooms/53521019  20220606014139   \n",
       "38            https://www.airbnb.com/rooms/54372932  20220606014139   \n",
       "39  https://www.airbnb.com/rooms/549756582281388816  20220606014139   \n",
       "40  https://www.airbnb.com/rooms/605621159096518819  20220606014139   \n",
       "41  https://www.airbnb.com/rooms/605622762821121970  20220606014139   \n",
       "42  https://www.airbnb.com/rooms/605624107364152491  20220606014139   \n",
       "43  https://www.airbnb.com/rooms/610734301192562815  20220606014139   \n",
       "44  https://www.airbnb.com/rooms/614197429015067131  20220606014139   \n",
       "45  https://www.airbnb.com/rooms/614197797820515063  20220606014139   \n",
       "46  https://www.airbnb.com/rooms/615741987349944051  20220606014139   \n",
       "\n",
       "   last_scraped  ... review_scores_communication review_scores_location  \\\n",
       "0    2022-06-06  ...                        4.67                   4.33   \n",
       "1    2022-06-07  ...                        4.95                   4.85   \n",
       "2    2022-06-07  ...                         NaN                    NaN   \n",
       "3    2022-06-07  ...                         NaN                    NaN   \n",
       "4    2022-06-07  ...                        4.71                   4.83   \n",
       "5    2022-06-07  ...                        5.00                   5.00   \n",
       "6    2022-06-07  ...                         NaN                    NaN   \n",
       "7    2022-06-07  ...                        5.00                   5.00   \n",
       "8    2022-06-07  ...                         NaN                    NaN   \n",
       "9    2022-06-07  ...                        5.00                   5.00   \n",
       "10   2022-06-07  ...                         NaN                    NaN   \n",
       "11   2022-06-07  ...                         NaN                    NaN   \n",
       "12   2022-06-07  ...                         NaN                    NaN   \n",
       "13   2022-06-07  ...                        5.00                   4.00   \n",
       "14   2022-06-07  ...                         NaN                    NaN   \n",
       "15   2022-06-06  ...                        4.69                   4.78   \n",
       "16   2022-06-06  ...                        5.00                   5.00   \n",
       "17   2022-06-06  ...                        4.74                   4.45   \n",
       "18   2022-06-06  ...                         NaN                    NaN   \n",
       "19   2022-06-07  ...                        4.82                   4.89   \n",
       "20   2022-06-07  ...                         NaN                    NaN   \n",
       "21   2022-06-07  ...                        5.00                   5.00   \n",
       "22   2022-06-07  ...                         NaN                    NaN   \n",
       "23   2022-06-07  ...                        4.83                   4.92   \n",
       "24   2022-06-07  ...                        5.00                   5.00   \n",
       "25   2022-06-07  ...                        5.00                   5.00   \n",
       "26   2022-06-07  ...                        5.00                   5.00   \n",
       "27   2022-06-06  ...                        4.78                   4.93   \n",
       "28   2022-06-07  ...                        5.00                   5.00   \n",
       "29   2022-06-07  ...                        4.36                   4.45   \n",
       "30   2022-06-07  ...                        4.79                   4.79   \n",
       "31   2022-06-07  ...                         NaN                    NaN   \n",
       "32   2022-06-07  ...                        4.64                   4.57   \n",
       "33   2022-06-07  ...                        3.33                   4.67   \n",
       "34   2022-06-07  ...                        4.77                   4.44   \n",
       "35   2022-06-07  ...                         NaN                    NaN   \n",
       "36   2022-06-07  ...                        4.60                   4.80   \n",
       "37   2022-06-07  ...                        5.00                   5.00   \n",
       "38   2022-06-07  ...                        5.00                   5.00   \n",
       "39   2022-06-06  ...                        5.00                   5.00   \n",
       "40   2022-06-07  ...                         NaN                    NaN   \n",
       "41   2022-06-07  ...                         NaN                    NaN   \n",
       "42   2022-06-07  ...                         NaN                    NaN   \n",
       "43   2022-06-07  ...                        4.00                   1.00   \n",
       "44   2022-06-07  ...                         NaN                    NaN   \n",
       "45   2022-06-07  ...                         NaN                    NaN   \n",
       "46   2022-06-07  ...                         NaN                    NaN   \n",
       "\n",
       "   review_scores_value                                            license  \\\n",
       "0                 4.67                                                NaN   \n",
       "1                 4.75  Available with a mobility lease only (\"bail mo...   \n",
       "2                  NaN                                                NaN   \n",
       "3                  NaN                                                NaN   \n",
       "4                 4.65                                                NaN   \n",
       "5                 5.00                                                NaN   \n",
       "6                  NaN                                                NaN   \n",
       "7                 5.00                                                NaN   \n",
       "8                  NaN                                                NaN   \n",
       "9                 5.00                                                NaN   \n",
       "10                 NaN                                                NaN   \n",
       "11                 NaN                                                NaN   \n",
       "12                 NaN                                                NaN   \n",
       "13                5.00                                                NaN   \n",
       "14                 NaN                                                NaN   \n",
       "15                4.73                                      7511703170231   \n",
       "16                5.00                                                NaN   \n",
       "17                4.51                                      7511001701467   \n",
       "18                 NaN                                                NaN   \n",
       "19                4.46                                      7511401913371   \n",
       "20                 NaN                                                NaN   \n",
       "21                5.00                                                NaN   \n",
       "22                 NaN                                      7511502718543   \n",
       "23                4.50                                      7511002680573   \n",
       "24                5.00                                                NaN   \n",
       "25                4.67                                                NaN   \n",
       "26                5.00                                                NaN   \n",
       "27                4.57                                      7511203776124   \n",
       "28                3.00                                                NaN   \n",
       "29                4.18                                      7511304252484   \n",
       "30                4.63                                      7511004261475   \n",
       "31                 NaN                                                NaN   \n",
       "32                4.64                                      7511804594025   \n",
       "33                4.00                                      7511204601416   \n",
       "34                4.27                                      7511004752712   \n",
       "35                 NaN  Available with a mobility lease only (\"bail mo...   \n",
       "36                4.60                                      7510905513495   \n",
       "37                4.00                                      7511005939278   \n",
       "38                4.50                                      7511906079284   \n",
       "39                5.00                                                NaN   \n",
       "40                 NaN                                      7511505554903   \n",
       "41                 NaN                                      7511803940165   \n",
       "42                 NaN                                      7510301545866   \n",
       "43                2.00  Available with a mobility lease only (\"bail mo...   \n",
       "44                 NaN                                      7511505554804   \n",
       "45                 NaN  Available with a mobility lease only (\"bail mo...   \n",
       "46                 NaN  Available with a mobility lease only (\"bail mo...   \n",
       "\n",
       "    instant_bookable calculated_host_listings_count  \\\n",
       "0                  f                              4   \n",
       "1                  f                              1   \n",
       "2                  f                              1   \n",
       "3                  f                              2   \n",
       "4                  f                              1   \n",
       "5                  f                              1   \n",
       "6                  f                              1   \n",
       "7                  f                              2   \n",
       "8                  f                              1   \n",
       "9                  f                              1   \n",
       "10                 f                              1   \n",
       "11                 f                              1   \n",
       "12                 f                              1   \n",
       "13                 f                              1   \n",
       "14                 f                              1   \n",
       "15                 f                              1   \n",
       "16                 f                              1   \n",
       "17                 f                              1   \n",
       "18                 f                              1   \n",
       "19                 f                              1   \n",
       "20                 f                              1   \n",
       "21                 f                              1   \n",
       "22                 f                              1   \n",
       "23                 f                              1   \n",
       "24                 f                              1   \n",
       "25                 f                              1   \n",
       "26                 f                              1   \n",
       "27                 f                              1   \n",
       "28                 f                              1   \n",
       "29                 f                              1   \n",
       "30                 f                              1   \n",
       "31                 f                              1   \n",
       "32                 f                              1   \n",
       "33                 f                              1   \n",
       "34                 f                             98   \n",
       "35                 f                              1   \n",
       "36                 f                              1   \n",
       "37                 f                              1   \n",
       "38                 f                              1   \n",
       "39                 f                              2   \n",
       "40                 f                            130   \n",
       "41                 f                            130   \n",
       "42                 f                            130   \n",
       "43                 f                            130   \n",
       "44                 f                            130   \n",
       "45                 f                            130   \n",
       "46                 f                            130   \n",
       "\n",
       "   calculated_host_listings_count_entire_homes  \\\n",
       "0                                            4   \n",
       "1                                            1   \n",
       "2                                            1   \n",
       "3                                            2   \n",
       "4                                            1   \n",
       "5                                            1   \n",
       "6                                            1   \n",
       "7                                            1   \n",
       "8                                            1   \n",
       "9                                            0   \n",
       "10                                           1   \n",
       "11                                           0   \n",
       "12                                           1   \n",
       "13                                           1   \n",
       "14                                           1   \n",
       "15                                           1   \n",
       "16                                           1   \n",
       "17                                           1   \n",
       "18                                           1   \n",
       "19                                           1   \n",
       "20                                           1   \n",
       "21                                           0   \n",
       "22                                           1   \n",
       "23                                           1   \n",
       "24                                           0   \n",
       "25                                           1   \n",
       "26                                           1   \n",
       "27                                           1   \n",
       "28                                           1   \n",
       "29                                           1   \n",
       "30                                           1   \n",
       "31                                           1   \n",
       "32                                           1   \n",
       "33                                           1   \n",
       "34                                          98   \n",
       "35                                           1   \n",
       "36                                           1   \n",
       "37                                           1   \n",
       "38                                           1   \n",
       "39                                           0   \n",
       "40                                         130   \n",
       "41                                         130   \n",
       "42                                         130   \n",
       "43                                         130   \n",
       "44                                         130   \n",
       "45                                         130   \n",
       "46                                         130   \n",
       "\n",
       "   calculated_host_listings_count_private_rooms  \\\n",
       "0                                             0   \n",
       "1                                             0   \n",
       "2                                             0   \n",
       "3                                             0   \n",
       "4                                             0   \n",
       "5                                             0   \n",
       "6                                             0   \n",
       "7                                             1   \n",
       "8                                             0   \n",
       "9                                             1   \n",
       "10                                            0   \n",
       "11                                            1   \n",
       "12                                            0   \n",
       "13                                            0   \n",
       "14                                            0   \n",
       "15                                            0   \n",
       "16                                            0   \n",
       "17                                            0   \n",
       "18                                            0   \n",
       "19                                            0   \n",
       "20                                            0   \n",
       "21                                            1   \n",
       "22                                            0   \n",
       "23                                            0   \n",
       "24                                            1   \n",
       "25                                            0   \n",
       "26                                            0   \n",
       "27                                            0   \n",
       "28                                            0   \n",
       "29                                            0   \n",
       "30                                            0   \n",
       "31                                            0   \n",
       "32                                            0   \n",
       "33                                            0   \n",
       "34                                            0   \n",
       "35                                            0   \n",
       "36                                            0   \n",
       "37                                            0   \n",
       "38                                            0   \n",
       "39                                            2   \n",
       "40                                            0   \n",
       "41                                            0   \n",
       "42                                            0   \n",
       "43                                            0   \n",
       "44                                            0   \n",
       "45                                            0   \n",
       "46                                            0   \n",
       "\n",
       "   calculated_host_listings_count_shared_rooms reviews_per_month  \n",
       "0                                            0              0.05  \n",
       "1                                            0              0.22  \n",
       "2                                            0               NaN  \n",
       "3                                            0               NaN  \n",
       "4                                            0              0.83  \n",
       "5                                            0              0.01  \n",
       "6                                            0               NaN  \n",
       "7                                            0              0.02  \n",
       "8                                            0               NaN  \n",
       "9                                            0              0.05  \n",
       "10                                           0               NaN  \n",
       "11                                           0               NaN  \n",
       "12                                           0               NaN  \n",
       "13                                           0              0.01  \n",
       "14                                           0               NaN  \n",
       "15                                           0              0.68  \n",
       "16                                           0              0.02  \n",
       "17                                           0              1.07  \n",
       "18                                           0               NaN  \n",
       "19                                           0              2.37  \n",
       "20                                           0              0.02  \n",
       "21                                           0              0.02  \n",
       "22                                           0               NaN  \n",
       "23                                           0              0.58  \n",
       "24                                           0              0.03  \n",
       "25                                           0              0.09  \n",
       "26                                           0              0.08  \n",
       "27                                           0              2.08  \n",
       "28                                           0              0.03  \n",
       "29                                           0              0.40  \n",
       "30                                           0              0.64  \n",
       "31                                           0               NaN  \n",
       "32                                           0              0.61  \n",
       "33                                           0              0.29  \n",
       "34                                           0              2.76  \n",
       "35                                           0               NaN  \n",
       "36                                           0              0.54  \n",
       "37                                           0              0.17  \n",
       "38                                           0              0.52  \n",
       "39                                           0              2.00  \n",
       "40                                           0               NaN  \n",
       "41                                           0               NaN  \n",
       "42                                           0               NaN  \n",
       "43                                           0              0.83  \n",
       "44                                           0               NaN  \n",
       "45                                           0               NaN  \n",
       "46                                           0               NaN  \n",
       "\n",
       "[47 rows x 72 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge booked listings with listings \n",
    "merged_df = pd.merge(booked_listings,listings,on=['listing_id','price','available','date','minimum_nights','maximum_nights'],how='inner')\n",
    "merged_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e12777b",
   "metadata": {},
   "source": [
    "\n",
    "There are only **47** listings who correspond to the bookings calendar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "13d41376",
   "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>listing_id</th>\n",
       "      <th>date</th>\n",
       "      <th>available</th>\n",
       "      <th>price</th>\n",
       "      <th>adjusted_price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>maximum_nights</th>\n",
       "      <th>listing_url</th>\n",
       "      <th>scrape_id</th>\n",
       "      <th>last_scraped</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_communication</th>\n",
       "      <th>review_scores_location</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>license</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>calculated_host_listings_count_entire_homes</th>\n",
       "      <th>calculated_host_listings_count_private_rooms</th>\n",
       "      <th>calculated_host_listings_count_shared_rooms</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1384098</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>f</td>\n",
       "      <td>$140.00</td>\n",
       "      <td>$140.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/1384098</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-06</td>\n",
       "      <td>...</td>\n",
       "      <td>4.67</td>\n",
       "      <td>4.33</td>\n",
       "      <td>4.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2142687</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$46.00</td>\n",
       "      <td>$46.00</td>\n",
       "      <td>120.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/2142687</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.95</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.75</td>\n",
       "      <td>Available with a mobility lease only (\"bail mo...</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3076637</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$360.00</td>\n",
       "      <td>$360.00</td>\n",
       "      <td>7.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/3076637</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4806693</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$226.00</td>\n",
       "      <td>$226.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/4806693</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5475961</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>f</td>\n",
       "      <td>$99.00</td>\n",
       "      <td>$99.00</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>https://www.airbnb.com/rooms/5475961</td>\n",
       "      <td>20220606014139</td>\n",
       "      <td>2022-06-07</td>\n",
       "      <td>...</td>\n",
       "      <td>4.71</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 72 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   listing_id        date available    price adjusted_price  minimum_nights  \\\n",
       "0     1384098  2022-06-06         f  $140.00        $140.00           365.0   \n",
       "1     2142687  2022-06-07         f   $46.00         $46.00           120.0   \n",
       "2     3076637  2022-06-07         f  $360.00        $360.00             7.0   \n",
       "3     4806693  2022-06-07         f  $226.00        $226.00           365.0   \n",
       "4     5475961  2022-06-07         f   $99.00         $99.00           365.0   \n",
       "\n",
       "   maximum_nights                           listing_url       scrape_id  \\\n",
       "0          1125.0  https://www.airbnb.com/rooms/1384098  20220606014139   \n",
       "1           365.0  https://www.airbnb.com/rooms/2142687  20220606014139   \n",
       "2            21.0  https://www.airbnb.com/rooms/3076637  20220606014139   \n",
       "3          1125.0  https://www.airbnb.com/rooms/4806693  20220606014139   \n",
       "4          1125.0  https://www.airbnb.com/rooms/5475961  20220606014139   \n",
       "\n",
       "  last_scraped  ... review_scores_communication review_scores_location  \\\n",
       "0   2022-06-06  ...                        4.67                   4.33   \n",
       "1   2022-06-07  ...                        4.95                   4.85   \n",
       "2   2022-06-07  ...                         NaN                    NaN   \n",
       "3   2022-06-07  ...                         NaN                    NaN   \n",
       "4   2022-06-07  ...                        4.71                   4.83   \n",
       "\n",
       "  review_scores_value                                            license  \\\n",
       "0                4.67                                                NaN   \n",
       "1                4.75  Available with a mobility lease only (\"bail mo...   \n",
       "2                 NaN                                                NaN   \n",
       "3                 NaN                                                NaN   \n",
       "4                4.65                                                NaN   \n",
       "\n",
       "   instant_bookable calculated_host_listings_count  \\\n",
       "0                 f                              4   \n",
       "1                 f                              1   \n",
       "2                 f                              1   \n",
       "3                 f                              2   \n",
       "4                 f                              1   \n",
       "\n",
       "  calculated_host_listings_count_entire_homes  \\\n",
       "0                                           4   \n",
       "1                                           1   \n",
       "2                                           1   \n",
       "3                                           2   \n",
       "4                                           1   \n",
       "\n",
       "  calculated_host_listings_count_private_rooms  \\\n",
       "0                                            0   \n",
       "1                                            0   \n",
       "2                                            0   \n",
       "3                                            0   \n",
       "4                                            0   \n",
       "\n",
       "  calculated_host_listings_count_shared_rooms reviews_per_month  \n",
       "0                                           0              0.05  \n",
       "1                                           0              0.22  \n",
       "2                                           0               NaN  \n",
       "3                                           0               NaN  \n",
       "4                                           0              0.83  \n",
       "\n",
       "[5 rows x 72 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "238ebd67",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The starting date of the bookings is: 2022-06-06\n",
      "The end date of the bookings is: 2022-06-07\n"
     ]
    }
   ],
   "source": [
    "# Look into the date range of the bookings\n",
    "print('The starting date of the bookings is:',merged_df.date.min())\n",
    "print('The end date of the bookings is:',merged_df.date.max())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18a75a88",
   "metadata": {},
   "source": [
    "\n",
    "And now we have the merged dataframe, we're going to be interested in the **neighbourhood_cleansed** column to find out which are the neighbourhoods the most booked in Paris.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "06a99a6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Take a look at the most booked neighbourhood values\n",
    "neighbourhoods = merged_df['neighbourhood_cleansed']\n",
    "most_booked = neighbourhoods.sort_values(ascending=False).value_counts(dropna=False).head(10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "49cc579c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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": [
    "# Plot the most booked neighbourhoods in Paris \n",
    "palette_color = sns.color_palette(\"bright\")\n",
    "plt.title('The most booked neighbourhoods in Paris',fontsize=20,y=1.1);\n",
    "plt.xlabel('Neighbourhoods')\n",
    "plt.ylabel('Number of bookings')\n",
    "most_booked.plot(kind='bar', color=palette_color);\n",
    "plt.savefig('blog/most_booked.jpg', bbox_inches='tight')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "54a572bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "customdata": [
          [
           365,
           1125,
           "$140.00",
           "$140.00",
           "f"
          ],
          [
           365,
           1125,
           "$55.00",
           "$55.00",
           "f"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>neighbourhood_cleansed=Bourse<br>latitude=%{lat}<br>longitude=%{lon}<br>minimum_nights=%{customdata[0]}<br>maximum_nights=%{customdata[1]}<br>price=%{customdata[2]}<br>adjusted_price=%{customdata[3]}<br>available=%{customdata[4]}<extra></extra>",
         "hovertext": [
          "Bourse",
          "Bourse"
         ],
         "lat": [
          48.86895,
          48.86905
         ],
         "legendgroup": "Bourse",
         "lon": [
          2.35082,
          2.34983
         ],
         "marker": {
          "color": "#636efa"
         },
         "mode": "markers",
         "name": "Bourse",
         "showlegend": true,
         "subplot": "mapbox",
         "type": "scattermapbox"
        },
        {
         "customdata": [
          [
           120,
           365,
           "$46.00",
           "$46.00",
           "f"
          ],
          [
           2,
           31,
           "$115.00",
           "$115.00",
           "f"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>neighbourhood_cleansed=Palais-Bourbon<br>latitude=%{lat}<br>longitude=%{lon}<br>minimum_nights=%{customdata[0]}<br>maximum_nights=%{customdata[1]}<br>price=%{customdata[2]}<br>adjusted_price=%{customdata[3]}<br>available=%{customdata[4]}<extra></extra>",
         "hovertext": [
          "Palais-Bourbon",
          "Palais-Bourbon"
         ],
         "lat": [
          48.85417,
          48.85696
         ],
         "legendgroup": "Palais-Bourbon",
         "lon": [
          2.3206,
          2.30532
         ],
         "marker": {
          "color": "#EF553B"
         },
         "mode": "markers",
         "name": "Palais-Bourbon",
         "showlegend": true,
         "subplot": "mapbox",
         "type": "scattermapbox"
        },
        {
         "customdata": [
          [
           7,
           21,
           "$360.00",
           "$360.00",
           "f"
          ],
          [
           365,
           1125,
           "$49.00",
           "$49.00",
           "f"
          ],
          [
           365,
           1125,
           "$200.00",
           "$200.00",
           "f"
          ],
          [
           3,
           365,
           "$60.00",
           "$60.00",
           "f"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>neighbourhood_cleansed=Passy<br>latitude=%{lat}<br>longitude=%{lon}<br>minimum_nights=%{customdata[0]}<br>maximum_nights=%{customdata[1]}<br>price=%{customdata[2]}<br>adjusted_price=%{customdata[3]}<br>available=%{customdata[4]}<extra></extra>",
         "hovertext": [
          "Passy",
          "Passy",
          "Passy",
          "Passy"
         ],
         "lat": [
          48.875,
          48.86355,
          48.84386,
          48.85635
         ],
         "legendgroup": "Passy",
         "lon": [
          2.24966,
          2.27172,
          2.27033,
          2.28152
         ],
         "marker": {
          "color": "#00cc96"
         },
         "mode": "markers",
         "name": "Passy",
         "showlegend": true,
         "subplot": "mapbox",
         "type": "scattermapbox"
        },
        {
         "customdata": [
          [
           365,
           1125,
           "$226.00",
           "$226.00",
           "f"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>neighbourhood_cleansed=Élysée<br>latitude=%{lat}<br>longitude=%{lon}<br>minimum_nights=%{customdata[0]}<br>maximum_nights=%{customdata[1]}<br>price=%{customdata[2]}<br>adjusted_price=%{customdata[3]}<br>available=%{customdata[4]}<extra></extra>",
         "hovertext": [
          "Élysée"
         ],
         "lat": [
          48.87426
         ],
         "legendgroup": "Élysée",
         "lon": [
          2.30715
         ],
         "marker": {
          "color": "#ab63fa"
         },
         "mode": "markers",
         "name": "Élysée",
         "showlegend": true,
         "subplot": "mapbox",
         "type": "scattermapbox"
        },
        {
         "customdata": [
          [
           365,
           1125,
           "$99.00",
           "$99.00",
           "f"
          ],
          [
           365,
           1125,
           "$80.00",
           "$80.00",
           "f"
          ],
          [
           365,
           1125,
           "$80.00",
           "$80.00",
           "f"
          ],
          [
           365,
           1125,
           "$60.00",
           "$60.00",
           "f"
          ],
          [
           1,
           1125,
           "$77.00",
           "$77.00",
           "f"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>neighbourhood_cleansed=Gobelins<br>latitude=%{lat}<br>longitude=%{lon}<br>minimum_nights=%{customdata[0]}<br>maximum_nights=%{customdata[1]}<br>price=%{customdata[2]}<br>adjusted_price=%{customdata[3]}<br>available=%{customdata[4]}<extra></extra>",
         "hovertext": [
          "Gobelins",
          "Gobelins",
          "Gobelins",
          "Gobelins",
          "Gobelins"
         ],
         "lat": [
          48.82759,
          48.83434,
          48.82556,
          48.8204,
          48.82457
         ],
         "legendgroup": "Gobelins",
         "lon": [
          2.35609,
          2.36077,
          2.36235,
          2.36364,
          2.36297
         ],
         "marker": {
          "color": "#FFA15A"
         },
         "mode": "markers",
         "name": "Gobelins",
         "showlegend": true,
         "subplot": "mapbox",
         "type": "scattermapbox"
        },
        {
         "customdata": [
          [
           365,
           365,
           "$79.00",
           "$79.00",
           "f"
          ],
          [
           365,
           1125,
           "$60.00",
           "$60.00",
           "f"
          ],
          [
           7,
           90,
           "$125.00",
           "$125.00",
           "f"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>neighbourhood_cleansed=Batignolles-Monceau<br>latitude=%{lat}<br>longitude=%{lon}<br>minimum_nights=%{customdata[0]}<br>maximum_nights=%{customdata[1]}<br>price=%{customdata[2]}<br>adjusted_price=%{customdata[3]}<br>available=%{customdata[4]}<extra></extra>",
         "hovertext": [
          "Batignolles-Monceau",
          "Batignolles-Monceau",
          "Batignolles-Monceau"
         ],
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# Plot the available listings\n",
    "\n",
    "fig = px.scatter_mapbox(merged_df, lat=\"latitude\",color='neighbourhood_cleansed', lon=\"longitude\", hover_name=\"neighbourhood_cleansed\", hover_data=[\"minimum_nights\",\"maximum_nights\",\"price\",\"adjusted_price\",'available'],\n",
    "                         zoom=9, height=600,width=800)\n",
    "fig.update_layout(mapbox_style=\"open-street-map\")\n",
    "fig.update_layout(margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0})\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "399f4f88",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67367183",
   "metadata": {},
   "source": [
    "\n",
    "We can see that **Paris, Île-de-France, France** with **47** available bookings in total, is the most booked region in Paris between **2022-06-06** and **2022-06-07** with neighbourhoods as listed in the figure above .\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30899877",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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