data_stats2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Acknowledgements\n",
    "\n",
    "The data was scraped from Booking.com. All data in the file is publicly available to everyone already. Data is originally owned by Booking.com. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Context\n",
    "\n",
    "This dataset contains 515,000 customer reviews and scoring of 1493 luxury hotels across Europe. Meanwhile, the geographical location of hotels are also provided for further analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## About the Dataset\n",
    "\n",
    "The csv file contains 17 fields. The description of each field is as below:\n",
    "\n",
    "* Hotel_Address: Address of hotel.\n",
    "* Review_Date: Date when reviewer posted the corresponding review.\n",
    "* Average_Score: Average Score of the hotel, calculated based on the latest comment in the last year.\n",
    "* Hotel_Name: Name of Hotel\n",
    "* Reviewer_Nationality: Nationality of Reviewer\n",
    "* Negative_Review: Negative Review the reviewer gave to the hotel. If the reviewer does not give the negative review, then it should be: 'No Negative'\n",
    "* Review_Total_Negative_Word_Counts: Total number of words in the negative review.\n",
    "* Positive_Review: Positive Review the reviewer gave to the hotel. If the reviewer does not give the negative review, then it should be: 'No Positive'\n",
    "* Review_Total_Positive_Word_Counts: Total number of words in the positive review.\n",
    "* Reviewer_Score: Score the reviewer has given to the hotel, based on his/her experience\n",
    "* Total_Number_of_Reviews_Reviewer_Has_Given: Number of Reviews the reviewers has given in the past.\n",
    "* Total_Number_of_Reviews: Total number of valid reviews the hotel has.\n",
    "* Tags: Tags reviewer gave the hotel.\n",
    "* Days_since_review: Duration between the review date and scrape date.\n",
    "* Additional_Number_of_Scoring: There are also some guests who just made a scoring on the service rather than a review. This number indicates how many valid scores without review in there.\n",
    "* lat: Latitude of the hotel\n",
    "* lng: longtitude of the hotel\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import folium\n",
    "import missingno as msno"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading the dataset from the Hotel_reviews dataset\n",
    "df = pd.read_csv(\"../files/Hotel_Reviews.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(515738, 17)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Printing the shape of the dataset\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of data points :  515738 \n",
      "Number of features: 17\n"
     ]
    },
    {
     "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>Hotel_Address</th>\n",
       "      <th>Additional_Number_of_Scoring</th>\n",
       "      <th>Review_Date</th>\n",
       "      <th>Average_Score</th>\n",
       "      <th>Hotel_Name</th>\n",
       "      <th>Reviewer_Nationality</th>\n",
       "      <th>Negative_Review</th>\n",
       "      <th>Review_Total_Negative_Word_Counts</th>\n",
       "      <th>Total_Number_of_Reviews</th>\n",
       "      <th>Positive_Review</th>\n",
       "      <th>Review_Total_Positive_Word_Counts</th>\n",
       "      <th>Total_Number_of_Reviews_Reviewer_Has_Given</th>\n",
       "      <th>Reviewer_Score</th>\n",
       "      <th>Tags</th>\n",
       "      <th>days_since_review</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>8/3/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>Russia</td>\n",
       "      <td>I am so angry that i made this post available...</td>\n",
       "      <td>397</td>\n",
       "      <td>1403</td>\n",
       "      <td>Only the park outside of the hotel was beauti...</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>2.9</td>\n",
       "      <td>[' Leisure trip ', ' Couple ', ' Duplex Double...</td>\n",
       "      <td>0 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>8/3/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>Ireland</td>\n",
       "      <td>No Negative</td>\n",
       "      <td>0</td>\n",
       "      <td>1403</td>\n",
       "      <td>No real complaints the hotel was great great ...</td>\n",
       "      <td>105</td>\n",
       "      <td>7</td>\n",
       "      <td>7.5</td>\n",
       "      <td>[' Leisure trip ', ' Couple ', ' Duplex Double...</td>\n",
       "      <td>0 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>7/31/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Rooms are nice but for elderly a bit difficul...</td>\n",
       "      <td>42</td>\n",
       "      <td>1403</td>\n",
       "      <td>Location was good and staff were ok It is cut...</td>\n",
       "      <td>21</td>\n",
       "      <td>9</td>\n",
       "      <td>7.1</td>\n",
       "      <td>[' Leisure trip ', ' Family with young childre...</td>\n",
       "      <td>3 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>7/31/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>My room was dirty and I was afraid to walk ba...</td>\n",
       "      <td>210</td>\n",
       "      <td>1403</td>\n",
       "      <td>Great location in nice surroundings the bar a...</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>[' Leisure trip ', ' Solo traveler ', ' Duplex...</td>\n",
       "      <td>3 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>s Gravesandestraat 55 Oost 1092 AA Amsterdam ...</td>\n",
       "      <td>194</td>\n",
       "      <td>7/24/2017</td>\n",
       "      <td>7.7</td>\n",
       "      <td>Hotel Arena</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>You When I booked with your company on line y...</td>\n",
       "      <td>140</td>\n",
       "      <td>1403</td>\n",
       "      <td>Amazing location and building Romantic setting</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>6.7</td>\n",
       "      <td>[' Leisure trip ', ' Couple ', ' Suite ', ' St...</td>\n",
       "      <td>10 days</td>\n",
       "      <td>52.360576</td>\n",
       "      <td>4.915968</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Hotel_Address  \\\n",
       "0   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...   \n",
       "1   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...   \n",
       "2   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...   \n",
       "3   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...   \n",
       "4   s Gravesandestraat 55 Oost 1092 AA Amsterdam ...   \n",
       "\n",
       "   Additional_Number_of_Scoring Review_Date  Average_Score   Hotel_Name  \\\n",
       "0                           194    8/3/2017            7.7  Hotel Arena   \n",
       "1                           194    8/3/2017            7.7  Hotel Arena   \n",
       "2                           194   7/31/2017            7.7  Hotel Arena   \n",
       "3                           194   7/31/2017            7.7  Hotel Arena   \n",
       "4                           194   7/24/2017            7.7  Hotel Arena   \n",
       "\n",
       "  Reviewer_Nationality                                    Negative_Review  \\\n",
       "0              Russia    I am so angry that i made this post available...   \n",
       "1             Ireland                                         No Negative   \n",
       "2           Australia    Rooms are nice but for elderly a bit difficul...   \n",
       "3      United Kingdom    My room was dirty and I was afraid to walk ba...   \n",
       "4         New Zealand    You When I booked with your company on line y...   \n",
       "\n",
       "   Review_Total_Negative_Word_Counts  Total_Number_of_Reviews  \\\n",
       "0                                397                     1403   \n",
       "1                                  0                     1403   \n",
       "2                                 42                     1403   \n",
       "3                                210                     1403   \n",
       "4                                140                     1403   \n",
       "\n",
       "                                     Positive_Review  \\\n",
       "0   Only the park outside of the hotel was beauti...   \n",
       "1   No real complaints the hotel was great great ...   \n",
       "2   Location was good and staff were ok It is cut...   \n",
       "3   Great location in nice surroundings the bar a...   \n",
       "4    Amazing location and building Romantic setting    \n",
       "\n",
       "   Review_Total_Positive_Word_Counts  \\\n",
       "0                                 11   \n",
       "1                                105   \n",
       "2                                 21   \n",
       "3                                 26   \n",
       "4                                  8   \n",
       "\n",
       "   Total_Number_of_Reviews_Reviewer_Has_Given  Reviewer_Score  \\\n",
       "0                                           7             2.9   \n",
       "1                                           7             7.5   \n",
       "2                                           9             7.1   \n",
       "3                                           1             3.8   \n",
       "4                                           3             6.7   \n",
       "\n",
       "                                                Tags days_since_review  \\\n",
       "0  [' Leisure trip ', ' Couple ', ' Duplex Double...            0 days   \n",
       "1  [' Leisure trip ', ' Couple ', ' Duplex Double...            0 days   \n",
       "2  [' Leisure trip ', ' Family with young childre...            3 days   \n",
       "3  [' Leisure trip ', ' Solo traveler ', ' Duplex...            3 days   \n",
       "4  [' Leisure trip ', ' Couple ', ' Suite ', ' St...           10 days   \n",
       "\n",
       "         lat       lng  \n",
       "0  52.360576  4.915968  \n",
       "1  52.360576  4.915968  \n",
       "2  52.360576  4.915968  \n",
       "3  52.360576  4.915968  \n",
       "4  52.360576  4.915968  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print ('Number of data points : ', df.shape[0], \\\n",
    "       '\\nNumber of features:', df.shape[1])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Deduplication"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "526\n",
      "After removing Duplicates: (515212, 17)\n"
     ]
    }
   ],
   "source": [
    "#Removing duplicates from the dataset\n",
    "print(sum(df.duplicated()))\n",
    "df = df.drop_duplicates()\n",
    "print('After removing Duplicates: {}'.format(df.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- We observe that 526 reviews are duplicate and we removed them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking for missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f737d3ffe48>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.matrix(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- From the above plot we can see that there are some missing values in lat(Latitude) and lng(Longitude) features in the dataset.\n",
    "- Lets look at the missing values in the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of missing values in the dataset: 3268\n"
     ]
    }
   ],
   "source": [
    "nans = lambda df: df[df.isnull().any(axis=1)]\n",
    "nans_df = nans(df)\n",
    "nans_df = nans_df[['Hotel_Name','lat','lng']]\n",
    "print('Number of missing values in the dataset: {}'.format(len(nans_df)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                                    3268\n",
       "unique                                     17\n",
       "top       Fleming s Selection Hotel Wien City\n",
       "freq                                      658\n",
       "Name: Hotel_Name, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nans_df.Hotel_Name.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- We see that there are about 3268 Nan (missing values) from 17 Hotels lat,lng information is not available in the dataset.\n",
    "- i.e., 1.13% of Hotels lat,lng information is missing.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Fleming s Selection Hotel Wien City                 658\n",
       "Hotel City Central                                  563\n",
       "Hotel Atlanta                                       389\n",
       "Maison Albar Hotel Paris Op ra Diamond              290\n",
       "Hotel Daniel Vienna                                 245\n",
       "Hotel Pension Baron am Schottentor                  223\n",
       "Austria Trend Hotel Schloss Wilhelminenberg Wien    194\n",
       "Derag Livinghotel Kaiser Franz Joseph Vienna        147\n",
       "NH Collection Barcelona Podium                      146\n",
       "City Hotel Deutschmeister                            93\n",
       "Hotel Park Villa                                     61\n",
       "Cordial Theaterhotel Wien                            57\n",
       "Holiday Inn Paris Montmartre                         55\n",
       "Roomz Vienna                                         49\n",
       "Mercure Paris Gare Montparnasse                      37\n",
       "Renaissance Barcelona Hotel                          33\n",
       "Hotel Advance                                        28\n",
       "Name: Hotel_Name, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's look at the reviews frequency of the missing Hotels.\n",
    "nans_df.Hotel_Name.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Instead of removing the Nan values from the dataset, Try to fill the Nan values with the similar Hotel_Addresses lat, lng values in the dataset. If the Hotel_Address is matched with the other rows(i.e Nan valued rows) in the dataset, Fill the Nan values in the dataset with the matched values(i.e., lat,lng).\n",
    "- Let's look into the datset to find the similar Hotel information is availble: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of reviews in the dataset to that Hotel:\n",
      "Fleming s Selection Hotel Wien City: 658\n",
      "Hotel City Central: 563\n",
      "Hotel Atlanta: 389\n",
      "Maison Albar Hotel Paris Op ra Diamond: 290\n",
      "Hotel Daniel Vienna: 245\n",
      "Hotel Pension Baron am Schottentor: 223\n",
      "Austria Trend Hotel Schloss Wilhelminenberg Wien: 194\n",
      "Derag Livinghotel Kaiser Franz Joseph Vienna: 147\n",
      "NH Collection Barcelona Podium: 146\n",
      "City Hotel Deutschmeister: 93\n",
      "Hotel Park Villa: 61\n",
      "Cordial Theaterhotel Wien: 57\n",
      "Holiday Inn Paris Montmartre: 55\n",
      "Roomz Vienna: 49\n",
      "Mercure Paris Gare Montparnasse: 37\n",
      "Renaissance Barcelona Hotel: 33\n",
      "Hotel Advance: 28\n"
     ]
    }
   ],
   "source": [
    "print('Number of reviews in the dataset to that Hotel:')\n",
    "print('Fleming s Selection Hotel Wien City: {}'.format(len(df.loc[df.Hotel_Name == 'Fleming s Selection Hotel Wien City'])))\n",
    "print('Hotel City Central: {}'.format(len(df.loc[df.Hotel_Name == 'Hotel City Central'])))\n",
    "print('Hotel Atlanta: {}'.format(len(df.loc[df.Hotel_Name == 'Hotel Atlanta'])))\n",
    "print('Maison Albar Hotel Paris Op ra Diamond: {}'.format(len(df.loc[df.Hotel_Name == 'Maison Albar Hotel Paris Op ra Diamond'])))\n",
    "print('Hotel Daniel Vienna: {}'.format(len(df.loc[df.Hotel_Name == 'Hotel Daniel Vienna'])))\n",
    "print('Hotel Pension Baron am Schottentor: {}'.format(len(df.loc[df.Hotel_Name == 'Hotel Pension Baron am Schottentor'])))\n",
    "print('Austria Trend Hotel Schloss Wilhelminenberg Wien: {}'.format(len(df.loc[df.Hotel_Name == 'Austria Trend Hotel Schloss Wilhelminenberg Wien'])))\n",
    "print('Derag Livinghotel Kaiser Franz Joseph Vienna: {}'.format(len(df.loc[df.Hotel_Name == 'Derag Livinghotel Kaiser Franz Joseph Vienna'])))\n",
    "print('NH Collection Barcelona Podium: {}'.format(len(df.loc[df.Hotel_Name == 'NH Collection Barcelona Podium'])))\n",
    "print('City Hotel Deutschmeister: {}'.format(len(df.loc[df.Hotel_Name == 'City Hotel Deutschmeister'])))\n",
    "print('Hotel Park Villa: {}'.format(len(df.loc[df.Hotel_Name == 'Hotel Park Villa'])))\n",
    "print('Cordial Theaterhotel Wien: {}'.format(len(df.loc[df.Hotel_Name == 'Cordial Theaterhotel Wien'])))\n",
    "print('Holiday Inn Paris Montmartre: {}'.format(len(df.loc[df.Hotel_Name == 'Holiday Inn Paris Montmartre'])))\n",
    "print('Roomz Vienna: {}'.format(len(df.loc[df.Hotel_Name == 'Roomz Vienna'])))\n",
    "print('Mercure Paris Gare Montparnasse: {}'.format(len(df.loc[df.Hotel_Name == 'Mercure Paris Gare Montparnasse'])))\n",
    "print('Renaissance Barcelona Hotel: {}'.format(len(df.loc[df.Hotel_Name == 'Renaissance Barcelona Hotel'])))\n",
    "print('Hotel Advance: {}'.format(len(df.loc[df.Hotel_Name == 'Hotel Advance'])))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- From the above figures we see that the missing values and available values in the dataset are same.(i.e the inflat,lng values are not available in the entire dataset).\n",
    "- So, Now we can fill the NaN values in the dataset manually. (Simply we can ignore those rows in the dataset by removing them. But i decided not to delete the information and fill the lat,lng values manually just because when it comes to Business problem if i try to remove the data i am losing information of 17 Hotel's. It seems like losing our 17 clients.)\n",
    "- For filling the lat,lng information of Hotel's by using this site [http://latlong.org/]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Latitude information of Hotels\n",
    "loc_lat = {'Fleming s Selection Hotel Wien City':48.209270,\n",
    "       'Hotel City Central':48.2136,\n",
    "       'Hotel Atlanta':48.210033,\n",
    "       'Maison Albar Hotel Paris Op ra Diamond':48.875343,\n",
    "       'Hotel Daniel Vienna':48.1888,\n",
    "       'Hotel Pension Baron am Schottentor':48.216701,\n",
    "      'Austria Trend Hotel Schloss Wilhelminenberg Wien':48.2195,\n",
    "      'Derag Livinghotel Kaiser Franz Joseph Vienna':48.245998,\n",
    "      'NH Collection Barcelona Podium':41.3916,\n",
    "      'City Hotel Deutschmeister':48.22088,\n",
    "      'Hotel Park Villa':48.233577,\n",
    "      'Cordial Theaterhotel Wien':48.209488,\n",
    "      'Holiday Inn Paris Montmartre':48.888920,\n",
    "      'Roomz Vienna':48.186605,\n",
    "      'Mercure Paris Gare Montparnasse':48.840012,\n",
    "      'Renaissance Barcelona Hotel':41.392673,\n",
    "      'Hotel Advance':41.383308}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Longitude information of Hotels\n",
    "loc_lng ={'Fleming s Selection Hotel Wien City':16.353479,\n",
    "       'Hotel City Central':16.3799,\n",
    "       'Hotel Atlanta':16.363449,\n",
    "       'Maison Albar Hotel Paris Op ra Diamond':2.323358,\n",
    "       'Hotel Daniel Vienna':16.3840,\n",
    "       'Hotel Pension Baron am Schottentor':16.359819,\n",
    "      'Austria Trend Hotel Schloss Wilhelminenberg Wien':16.2856,\n",
    "      'Derag Livinghotel Kaiser Franz Joseph Vienna':16.341080,\n",
    "      'NH Collection Barcelona Podium':2.1779,\n",
    "      'City Hotel Deutschmeister':16.36663,\n",
    "      'Hotel Park Villa':16.345682,\n",
    "      'Cordial Theaterhotel Wien':16.351585,\n",
    "      'Holiday Inn Paris Montmartre':2.333087,\n",
    "      'Roomz Vienna':16.420643,\n",
    "      'Mercure Paris Gare Montparnasse':2.323595,\n",
    "      'Renaissance Barcelona Hotel':2.167494,\n",
    "      'Hotel Advance':2.162828}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#filling the latitude information\n",
    "df['lat'] = df['lat'].fillna(df['Hotel_Name'].apply(lambda x: loc_lat.get(x)))\n",
    "#filling longitude information\n",
    "df['lng'] = df['lng'].fillna(df['Hotel_Name'].apply(lambda x: loc_lng.get(x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f737242be48>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#looking whether information is correctly filled or not.\n",
    "msno.matrix(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving the data to pickle files\n",
    "df.to_pickle('../files/hotel_reviews_cleaned')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading the data from the pickle file\n",
    "df = pd.read_pickle('../files/hotel_reviews_cleaned')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic stats for features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hotel Name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                                         515212\n",
       "unique                                          1492\n",
       "top       Britannia International Hotel Canary Wharf\n",
       "freq                                            4789\n",
       "Name: Hotel_Name, dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Hotel_Name.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- There are 1492 Hotel Names and the most reviewed Hotel is Britannia International Hotel Canary Wharf with 4789 reviews."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f735f97a9b0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's look at the top 10 reviewed Hotels\n",
    "Hotel_Name_count = df.Hotel_Name.value_counts()\n",
    "Hotel_Name_count[:10].plot(kind='bar',figsize=(10,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Average_Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pylab as plt\n",
    "%matplotlib inline\n",
    "from matplotlib.pylab import rcParams\n",
    "rcParams['figure.figsize'] = 50, 18\n",
    "rcParams[\"axes.labelsize\"] = 16\n",
    "from matplotlib import pyplot\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f737e32a048>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2160x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_plot = df[[\"Hotel_Name\",\"Average_Score\"]].drop_duplicates()\n",
    "sns.set(font_scale = 2.5)\n",
    "a4_dims = (30, 12)\n",
    "fig, ax = pyplot.subplots(figsize=a4_dims)\n",
    "sns.countplot(ax = ax,x = \"Average_Score\",data=data_plot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- We see that most of the Hotels average_score lie in the range of 8.0 and 9.1 range"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviewer Nationality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3600x1296 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "Reviewer_Nat_Count = df.Reviewer_Nationality.value_counts()\n",
    "wordcloud = WordCloud(background_color='black', width = 600,\\\n",
    "                      height=200, max_font_size=50, max_words=40).generate_from_frequencies(Reviewer_Nat_Count)\n",
    "wordcloud.recolor(random_state=312)\n",
    "plt.imshow(wordcloud)\n",
    "plt.title(\"Wordcloud for countries \")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count               515212\n",
       "unique                 227\n",
       "top        United Kingdom \n",
       "freq                245110\n",
       "Name: Reviewer_Nationality, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Reviewer_Nationality.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " United Kingdom               245110\n",
      " United States of America      35349\n",
      " Australia                     21648\n",
      " Ireland                       14814\n",
      " United Arab Emirates          10229\n",
      " Saudi Arabia                   8940\n",
      " Netherlands                    8757\n",
      " Switzerland                    8669\n",
      " Germany                        7929\n",
      " Canada                         7883\n",
      "Name: Reviewer_Nationality, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Let's look at the Top 10 Reviewer's Nationalities\n",
    "print(Reviewer_Nat_Count[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- From this we can conclude: the Reviewers belongs to 227 different countries and almost 47.57%(245110/515212) of Reviewers are from United Kingdom"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Review Date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       515212\n",
       "unique         731\n",
       "top       8/2/2017\n",
       "freq          2584\n",
       "Name: Review_Date, dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Review_Date.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- There Reviews are given on 731 dates and the most Reviews are given on 8/2/2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f737d83fbe0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 3600x1296 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's look at the top 10 Reviews given dates\n",
    "Review_Date_count = df.Review_Date.value_counts()\n",
    "Review_Date_count[:10].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Total Number of Reviews Reviewer Has Given "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f737d823630>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3600x1296 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Reviewers_freq = df.Total_Number_of_Reviews_Reviewer_Has_Given.value_counts()\n",
    "Reviewers_freq[:10].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1     154506\n",
       "2      67011\n",
       "3      46802\n",
       "4      34991\n",
       "5      27604\n",
       "6      22593\n",
       "7      18599\n",
       "8      16126\n",
       "9      13526\n",
       "10     11702\n",
       "Name: Total_Number_of_Reviews_Reviewer_Has_Given, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Reviewers_freq[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- We see that almost 29.99% (154506 / 515212) of user's reviewed for the first_time."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting Hotels in Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1492"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Loading the unique Hotel's information to plot them on the map\n",
    "temp_df = df.drop_duplicates(['Hotel_Name'])\n",
    "len(temp_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe 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