Hotel satisfaction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "196ff5f3",
   "metadata": {},
   "source": [
    "# Import CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "34b0d381",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6703c797",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>purpose_of_travel</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Type Of Booking</th>\n",
       "      <th>Hotel wifi service</th>\n",
       "      <th>Departure/Arrival  convenience</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Hotel location</th>\n",
       "      <th>Food and drink</th>\n",
       "      <th>Stay comfort</th>\n",
       "      <th>Common Room entertainment</th>\n",
       "      <th>Checkin/Checkout service</th>\n",
       "      <th>Other service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>70172</td>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>aviation</td>\n",
       "      <td>Personal Travel</td>\n",
       "      <td>Not defined</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5047</td>\n",
       "      <td>Male</td>\n",
       "      <td>25</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>110028</td>\n",
       "      <td>Female</td>\n",
       "      <td>26</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24026</td>\n",
       "      <td>Female</td>\n",
       "      <td>25</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>119299</td>\n",
       "      <td>Male</td>\n",
       "      <td>61</td>\n",
       "      <td>aviation</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  Gender  Age purpose_of_travel   Type of Travel Type Of Booking  \\\n",
       "0   70172    Male   13          aviation  Personal Travel     Not defined   \n",
       "1    5047    Male   25           tourism     Group Travel  Group bookings   \n",
       "2  110028  Female   26           tourism     Group Travel  Group bookings   \n",
       "3   24026  Female   25           tourism     Group Travel  Group bookings   \n",
       "4  119299    Male   61          aviation     Group Travel  Group bookings   \n",
       "\n",
       "   Hotel wifi service  Departure/Arrival  convenience  Ease of Online booking  \\\n",
       "0                   3                               4                       3   \n",
       "1                   3                               2                       3   \n",
       "2                   2                               2                       2   \n",
       "3                   2                               5                       5   \n",
       "4                   3                               3                       3   \n",
       "\n",
       "   Hotel location  Food and drink  Stay comfort  Common Room entertainment  \\\n",
       "0               1               5             5                          5   \n",
       "1               3               1             1                          1   \n",
       "2               2               5             5                          5   \n",
       "3               5               2             2                          2   \n",
       "4               3               4             5                          3   \n",
       "\n",
       "   Checkin/Checkout service  Other service  Cleanliness  \\\n",
       "0                         4              5            5   \n",
       "1                         1              4            1   \n",
       "2                         4              4            5   \n",
       "3                         1              4            2   \n",
       "4                         3              3            3   \n",
       "\n",
       "              satisfaction  \n",
       "0  neutral or dissatisfied  \n",
       "1  neutral or dissatisfied  \n",
       "2                satisfied  \n",
       "3  neutral or dissatisfied  \n",
       "4                satisfied  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"Dataset6_Hotel_Satisfaction.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e2b4ffe",
   "metadata": {},
   "source": [
    "# Data Description"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b7685b4",
   "metadata": {},
   "source": [
    "## About Dataset:\n",
    "- Age - 7 to 85\n",
    "- purposeoftravel - aviation, academic, personal, business, tourism.\n",
    "- Type of Travel - Group travel, Personal Travel.\n",
    "- Type Of Booking - Group bookings, Individual/Couple.\n",
    "- Hotel wifi service - Ratings out of 5.\n",
    "- Departure/Arrival convenience - Ratings out of 5.\n",
    "- Ease of Online booking - Ratings out of 5.\n",
    "- Hotel location - Ratings out of 5.\n",
    "- Food and drink - Ratings out of 5.\n",
    "- Stay comfort - Ratings out of 5.\n",
    "- Common Room entertainment - Ratings out of 5.\n",
    "- Checkin/Checkout service - Ratings out of 5.\n",
    "- Other service - Ratings out of 5.\n",
    "- Cleanliness - Ratings out of 5.\n",
    "- satisfaction - satisfied, neutral or dissatisfied."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eefb4c1a",
   "metadata": {},
   "source": [
    "# Data Understanding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0b9473d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 103904 entries, 0 to 103903\n",
      "Data columns (total 17 columns):\n",
      " #   Column                          Non-Null Count   Dtype \n",
      "---  ------                          --------------   ----- \n",
      " 0   id                              103904 non-null  int64 \n",
      " 1   Gender                          103904 non-null  object\n",
      " 2   Age                             103904 non-null  int64 \n",
      " 3   purpose_of_travel               103904 non-null  object\n",
      " 4   Type of Travel                  103904 non-null  object\n",
      " 5   Type Of Booking                 103904 non-null  object\n",
      " 6   Hotel wifi service              103904 non-null  int64 \n",
      " 7   Departure/Arrival  convenience  103904 non-null  int64 \n",
      " 8   Ease of Online booking          103904 non-null  int64 \n",
      " 9   Hotel location                  103904 non-null  int64 \n",
      " 10  Food and drink                  103904 non-null  int64 \n",
      " 11  Stay comfort                    103904 non-null  int64 \n",
      " 12  Common Room entertainment       103904 non-null  int64 \n",
      " 13  Checkin/Checkout service        103904 non-null  int64 \n",
      " 14  Other service                   103904 non-null  int64 \n",
      " 15  Cleanliness                     103904 non-null  int64 \n",
      " 16  satisfaction                    103904 non-null  object\n",
      "dtypes: int64(12), object(5)\n",
      "memory usage: 13.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7f0b3ea5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Age</th>\n",
       "      <th>Hotel wifi service</th>\n",
       "      <th>Departure/Arrival  convenience</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Hotel location</th>\n",
       "      <th>Food and drink</th>\n",
       "      <th>Stay comfort</th>\n",
       "      <th>Common Room entertainment</th>\n",
       "      <th>Checkin/Checkout service</th>\n",
       "      <th>Other service</th>\n",
       "      <th>Cleanliness</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
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       "      <td>103904.000000</td>\n",
       "      <td>103904.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>64924.210502</td>\n",
       "      <td>39.379706</td>\n",
       "      <td>2.729683</td>\n",
       "      <td>3.060296</td>\n",
       "      <td>2.756901</td>\n",
       "      <td>2.976883</td>\n",
       "      <td>3.202129</td>\n",
       "      <td>3.439396</td>\n",
       "      <td>3.358158</td>\n",
       "      <td>3.304290</td>\n",
       "      <td>3.640428</td>\n",
       "      <td>3.286351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>37463.812252</td>\n",
       "      <td>15.114964</td>\n",
       "      <td>1.327829</td>\n",
       "      <td>1.525075</td>\n",
       "      <td>1.398929</td>\n",
       "      <td>1.277621</td>\n",
       "      <td>1.329533</td>\n",
       "      <td>1.319088</td>\n",
       "      <td>1.332991</td>\n",
       "      <td>1.265396</td>\n",
       "      <td>1.175663</td>\n",
       "      <td>1.312273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>32533.750000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>64856.500000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>97368.250000</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>129880.000000</td>\n",
       "      <td>85.000000</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>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id            Age  Hotel wifi service  \\\n",
       "count  103904.000000  103904.000000       103904.000000   \n",
       "mean    64924.210502      39.379706            2.729683   \n",
       "std     37463.812252      15.114964            1.327829   \n",
       "min         1.000000       7.000000            0.000000   \n",
       "25%     32533.750000      27.000000            2.000000   \n",
       "50%     64856.500000      40.000000            3.000000   \n",
       "75%     97368.250000      51.000000            4.000000   \n",
       "max    129880.000000      85.000000            5.000000   \n",
       "\n",
       "       Departure/Arrival  convenience  Ease of Online booking  Hotel location  \\\n",
       "count                   103904.000000           103904.000000   103904.000000   \n",
       "mean                         3.060296                2.756901        2.976883   \n",
       "std                          1.525075                1.398929        1.277621   \n",
       "min                          0.000000                0.000000        0.000000   \n",
       "25%                          2.000000                2.000000        2.000000   \n",
       "50%                          3.000000                3.000000        3.000000   \n",
       "75%                          4.000000                4.000000        4.000000   \n",
       "max                          5.000000                5.000000        5.000000   \n",
       "\n",
       "       Food and drink   Stay comfort  Common Room entertainment  \\\n",
       "count   103904.000000  103904.000000              103904.000000   \n",
       "mean         3.202129       3.439396                   3.358158   \n",
       "std          1.329533       1.319088                   1.332991   \n",
       "min          0.000000       0.000000                   0.000000   \n",
       "25%          2.000000       2.000000                   2.000000   \n",
       "50%          3.000000       4.000000                   4.000000   \n",
       "75%          4.000000       5.000000                   4.000000   \n",
       "max          5.000000       5.000000                   5.000000   \n",
       "\n",
       "       Checkin/Checkout service  Other service    Cleanliness  \n",
       "count             103904.000000  103904.000000  103904.000000  \n",
       "mean                   3.304290       3.640428       3.286351  \n",
       "std                    1.265396       1.175663       1.312273  \n",
       "min                    0.000000       0.000000       0.000000  \n",
       "25%                    3.000000       3.000000       2.000000  \n",
       "50%                    3.000000       4.000000       3.000000  \n",
       "75%                    4.000000       5.000000       4.000000  \n",
       "max                    5.000000       5.000000       5.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "09f00ef2",
   "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>Gender</th>\n",
       "      <th>purpose_of_travel</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Type Of Booking</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>103904</td>\n",
       "      <td>103904</td>\n",
       "      <td>103904</td>\n",
       "      <td>103904</td>\n",
       "      <td>103904</td>\n",
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       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Female</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>52727</td>\n",
       "      <td>32053</td>\n",
       "      <td>71655</td>\n",
       "      <td>49665</td>\n",
       "      <td>58879</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "        Gender purpose_of_travel Type of Travel Type Of Booking  \\\n",
       "count   103904            103904         103904          103904   \n",
       "unique       2                 5              2               3   \n",
       "top     Female           tourism   Group Travel  Group bookings   \n",
       "freq     52727             32053          71655           49665   \n",
       "\n",
       "                   satisfaction  \n",
       "count                    103904  \n",
       "unique                        2  \n",
       "top     neutral or dissatisfied  \n",
       "freq                      58879  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include='object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8971636b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                                0\n",
       "Gender                            0\n",
       "Age                               0\n",
       "purpose_of_travel                 0\n",
       "Type of Travel                    0\n",
       "Type Of Booking                   0\n",
       "Hotel wifi service                0\n",
       "Departure/Arrival  convenience    0\n",
       "Ease of Online booking            0\n",
       "Hotel location                    0\n",
       "Food and drink                    0\n",
       "Stay comfort                      0\n",
       "Common Room entertainment         0\n",
       "Checkin/Checkout service          0\n",
       "Other service                     0\n",
       "Cleanliness                       0\n",
       "satisfaction                      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "375542d7",
   "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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>purpose_of_travel</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Type Of Booking</th>\n",
       "      <th>Hotel wifi service</th>\n",
       "      <th>Departure/Arrival  convenience</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Hotel location</th>\n",
       "      <th>Food and drink</th>\n",
       "      <th>Stay comfort</th>\n",
       "      <th>Common Room entertainment</th>\n",
       "      <th>Checkin/Checkout service</th>\n",
       "      <th>Other service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [id, Gender, Age, purpose_of_travel, Type of Travel, Type Of Booking, Hotel wifi service, Departure/Arrival  convenience, Ease of Online booking, Hotel location, Food and drink, Stay comfort, Common Room entertainment, Checkin/Checkout service, Other service, Cleanliness, satisfaction]\n",
       "Index: []"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated(keep='first')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a58c16de",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns='id', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "84727e98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Gender', 'Age', 'purpose_of_travel', 'Type of Travel',\n",
       "       'Type Of Booking', 'Hotel wifi service',\n",
       "       'Departure/Arrival  convenience', 'Ease of Online booking',\n",
       "       'Hotel location', 'Food and drink', 'Stay comfort',\n",
       "       'Common Room entertainment', 'Checkin/Checkout service',\n",
       "       'Other service', 'Cleanliness', 'satisfaction'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d82165af",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "44490a22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Type Of Booking', ylabel='count'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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AAAAAAAAbkawBAAAAAAAAAACwEckaAAAAAAAAAAAAG5GsAQAAAAAAAAAAsBHJGgAAAAAAAAAAABuRrAEAAAAAAAAAALDR/wdajUry91fHBAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 2000x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axarr = plt.subplots(2,2, figsize=(20,12))\n",
    "sns.countplot(x='Gender', hue='satisfaction', data=df, ax=axarr[0][0])\n",
    "sns.countplot(x='purpose_of_travel', hue='satisfaction', data=df, ax=axarr[0][1])\n",
    "sns.countplot(x='Type of Travel', hue='satisfaction', data=df, ax=axarr[1][0])\n",
    "sns.countplot(x='Type Of Booking', hue='satisfaction', data=df, ax=axarr[1][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5c387ab6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='satisfaction', ylabel='Stay comfort'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1200 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axarr = plt.subplots(3,2, figsize=(20,12))\n",
    "sns.boxplot(y='Hotel wifi service', x='satisfaction', hue='satisfaction', data=df, ax=axarr[0][0])\n",
    "sns.boxplot(y='Departure/Arrival  convenience', x='satisfaction', data=df, hue='satisfaction', ax=axarr[0][1])\n",
    "sns.boxplot(y='Ease of Online booking', x='satisfaction', data=df, hue='satisfaction', ax=axarr[1][0])\n",
    "sns.boxplot(y='Hotel location', x='satisfaction', data=df, hue='satisfaction', ax=axarr[1][1])\n",
    "sns.boxplot(y='Food and drink', x='satisfaction', hue='satisfaction', data=df, ax=axarr[2][0])\n",
    "sns.boxplot(y='Stay comfort', x='satisfaction', hue='satisfaction', data=df, ax=axarr[2][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "819accf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='satisfaction', ylabel='Cleanliness'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axarr = plt.subplots(2,2, figsize=(20,12))\n",
    "sns.boxplot(y='Common Room entertainment', x='satisfaction', data=df, hue='satisfaction', ax=axarr[0][0])\n",
    "sns.boxplot(y='Checkin/Checkout service', x='satisfaction', data=df, hue='satisfaction', ax=axarr[0][1])\n",
    "sns.boxplot(y='Other service', x='satisfaction', hue='satisfaction', data=df, ax=axarr[1][0])\n",
    "sns.boxplot(y='Cleanliness', x='satisfaction', hue='satisfaction', data=df, ax=axarr[1][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c49b0cfa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='satisfaction', ylabel='count'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axarr = plt.subplots(figsize=(3,3))\n",
    "sns.countplot(data=df, x='satisfaction')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "59791633",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm = df.corr()\n",
    "plt.figure(figsize=(10,5))\n",
    "sns.heatmap(cm, annot=True, cmap='Blues')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "246ec8c4",
   "metadata": {},
   "source": [
    "# Feature engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ade14519",
   "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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>purpose_of_travel</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Type Of Booking</th>\n",
       "      <th>Hotel wifi service</th>\n",
       "      <th>Departure/Arrival  convenience</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Hotel location</th>\n",
       "      <th>Food and drink</th>\n",
       "      <th>Stay comfort</th>\n",
       "      <th>Common Room entertainment</th>\n",
       "      <th>Checkin/Checkout service</th>\n",
       "      <th>Other service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>aviation</td>\n",
       "      <td>Personal Travel</td>\n",
       "      <td>Not defined</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>25</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>26</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>25</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>neutral or dissatisfied</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>61</td>\n",
       "      <td>aviation</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>satisfied</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age purpose_of_travel   Type of Travel Type Of Booking  \\\n",
       "0    Male   13          aviation  Personal Travel     Not defined   \n",
       "1    Male   25           tourism     Group Travel  Group bookings   \n",
       "2  Female   26           tourism     Group Travel  Group bookings   \n",
       "3  Female   25           tourism     Group Travel  Group bookings   \n",
       "4    Male   61          aviation     Group Travel  Group bookings   \n",
       "\n",
       "   Hotel wifi service  Departure/Arrival  convenience  Ease of Online booking  \\\n",
       "0                   3                               4                       3   \n",
       "1                   3                               2                       3   \n",
       "2                   2                               2                       2   \n",
       "3                   2                               5                       5   \n",
       "4                   3                               3                       3   \n",
       "\n",
       "   Hotel location  Food and drink  Stay comfort  Common Room entertainment  \\\n",
       "0               1               5             5                          5   \n",
       "1               3               1             1                          1   \n",
       "2               2               5             5                          5   \n",
       "3               5               2             2                          2   \n",
       "4               3               4             5                          3   \n",
       "\n",
       "   Checkin/Checkout service  Other service  Cleanliness  \\\n",
       "0                         4              5            5   \n",
       "1                         1              4            1   \n",
       "2                         4              4            5   \n",
       "3                         1              4            2   \n",
       "4                         3              3            3   \n",
       "\n",
       "              satisfaction  \n",
       "0  neutral or dissatisfied  \n",
       "1  neutral or dissatisfied  \n",
       "2                satisfied  \n",
       "3  neutral or dissatisfied  \n",
       "4                satisfied  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7957747e",
   "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",
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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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>purpose_of_travel</th>\n",
       "      <th>Type of Travel</th>\n",
       "      <th>Type Of Booking</th>\n",
       "      <th>Hotel wifi service</th>\n",
       "      <th>Departure/Arrival  convenience</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Hotel location</th>\n",
       "      <th>Food and drink</th>\n",
       "      <th>Stay comfort</th>\n",
       "      <th>Common Room entertainment</th>\n",
       "      <th>Checkin/Checkout service</th>\n",
       "      <th>Other service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>aviation</td>\n",
       "      <td>Personal Travel</td>\n",
       "      <td>Not defined</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>25</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>26</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>25</td>\n",
       "      <td>tourism</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>61</td>\n",
       "      <td>aviation</td>\n",
       "      <td>Group Travel</td>\n",
       "      <td>Group bookings</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age purpose_of_travel   Type of Travel Type Of Booking  \\\n",
       "0    Male   13          aviation  Personal Travel     Not defined   \n",
       "1    Male   25           tourism     Group Travel  Group bookings   \n",
       "2  Female   26           tourism     Group Travel  Group bookings   \n",
       "3  Female   25           tourism     Group Travel  Group bookings   \n",
       "4    Male   61          aviation     Group Travel  Group bookings   \n",
       "\n",
       "   Hotel wifi service  Departure/Arrival  convenience  Ease of Online booking  \\\n",
       "0                   3                               4                       3   \n",
       "1                   3                               2                       3   \n",
       "2                   2                               2                       2   \n",
       "3                   2                               5                       5   \n",
       "4                   3                               3                       3   \n",
       "\n",
       "   Hotel location  Food and drink  Stay comfort  Common Room entertainment  \\\n",
       "0               1               5             5                          5   \n",
       "1               3               1             1                          1   \n",
       "2               2               5             5                          5   \n",
       "3               5               2             2                          2   \n",
       "4               3               4             5                          3   \n",
       "\n",
       "   Checkin/Checkout service  Other service  Cleanliness  satisfaction  \n",
       "0                         4              5            5             1  \n",
       "1                         1              4            1             1  \n",
       "2                         4              4            5             0  \n",
       "3                         1              4            2             1  \n",
       "4                         3              3            3             0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.replace({'satisfaction':{'satisfied':0, 'neutral or dissatisfied':1}}, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fd71b753",
   "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>Age</th>\n",
       "      <th>Hotel wifi service</th>\n",
       "      <th>Departure/Arrival  convenience</th>\n",
       "      <th>Ease of Online booking</th>\n",
       "      <th>Hotel location</th>\n",
       "      <th>Food and drink</th>\n",
       "      <th>Stay comfort</th>\n",
       "      <th>Common Room entertainment</th>\n",
       "      <th>Checkin/Checkout service</th>\n",
       "      <th>Other service</th>\n",
       "      <th>...</th>\n",
       "      <th>purpose_of_travel_academic</th>\n",
       "      <th>purpose_of_travel_aviation</th>\n",
       "      <th>purpose_of_travel_business</th>\n",
       "      <th>purpose_of_travel_personal</th>\n",
       "      <th>purpose_of_travel_tourism</th>\n",
       "      <th>Type of Travel_Group Travel</th>\n",
       "      <th>Type of Travel_Personal Travel</th>\n",
       "      <th>Type Of Booking_Group bookings</th>\n",
       "      <th>Type Of Booking_Individual/Couple</th>\n",
       "      <th>Type Of Booking_Not defined</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Hotel wifi service  Departure/Arrival  convenience  \\\n",
       "0   13                   3                               4   \n",
       "1   25                   3                               2   \n",
       "2   26                   2                               2   \n",
       "3   25                   2                               5   \n",
       "4   61                   3                               3   \n",
       "\n",
       "   Ease of Online booking  Hotel location  Food and drink  Stay comfort  \\\n",
       "0                       3               1               5             5   \n",
       "1                       3               3               1             1   \n",
       "2                       2               2               5             5   \n",
       "3                       5               5               2             2   \n",
       "4                       3               3               4             5   \n",
       "\n",
       "   Common Room entertainment  Checkin/Checkout service  Other service  ...  \\\n",
       "0                          5                         4              5  ...   \n",
       "1                          1                         1              4  ...   \n",
       "2                          5                         4              4  ...   \n",
       "3                          2                         1              4  ...   \n",
       "4                          3                         3              3  ...   \n",
       "\n",
       "   purpose_of_travel_academic  purpose_of_travel_aviation  \\\n",
       "0                           0                           1   \n",
       "1                           0                           0   \n",
       "2                           0                           0   \n",
       "3                           0                           0   \n",
       "4                           0                           1   \n",
       "\n",
       "   purpose_of_travel_business  purpose_of_travel_personal  \\\n",
       "0                           0                           0   \n",
       "1                           0                           0   \n",
       "2                           0                           0   \n",
       "3                           0                           0   \n",
       "4                           0                           0   \n",
       "\n",
       "   purpose_of_travel_tourism  Type of Travel_Group Travel  \\\n",
       "0                          0                            0   \n",
       "1                          1                            1   \n",
       "2                          1                            1   \n",
       "3                          1                            1   \n",
       "4                          0                            1   \n",
       "\n",
       "   Type of Travel_Personal Travel  Type Of Booking_Group bookings  \\\n",
       "0                               1                               0   \n",
       "1                               0                               1   \n",
       "2                               0                               1   \n",
       "3                               0                               1   \n",
       "4                               0                               1   \n",
       "\n",
       "   Type Of Booking_Individual/Couple  Type Of Booking_Not defined  \n",
       "0                                  0                            1  \n",
       "1                                  0                            0  \n",
       "2                                  0                            0  \n",
       "3                                  0                            0  \n",
       "4                                  0                            0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.get_dummies(df)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "78e7c8ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Age', 'Hotel wifi service', 'Departure/Arrival  convenience',\n",
       "       'Ease of Online booking', 'Hotel location', 'Food and drink',\n",
       "       'Stay comfort', 'Common Room entertainment', 'Checkin/Checkout service',\n",
       "       'Other service', 'Cleanliness', 'satisfaction', 'Gender_Female',\n",
       "       'Gender_Male', 'purpose_of_travel_academic',\n",
       "       'purpose_of_travel_aviation', 'purpose_of_travel_business',\n",
       "       'purpose_of_travel_personal', 'purpose_of_travel_tourism',\n",
       "       'Type of Travel_Group Travel', 'Type of Travel_Personal Travel',\n",
       "       'Type Of Booking_Group bookings', 'Type Of Booking_Individual/Couple',\n",
       "       'Type Of Booking_Not defined'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "41acf374",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "x = df1.drop('satisfaction', axis=1).copy()\n",
    "y = df1['satisfaction'].copy()\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3f7c691f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((83123, 23), (20781, 23), (83123,), (20781,))"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape, x_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "518013c8",
   "metadata": {},
   "source": [
    "# Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f594e890",
   "metadata": {},
   "outputs": [],
   "source": [
    "# fit models\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "# scoring functions\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "346991c5",
   "metadata": {},
   "source": [
    "## KNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1ae06949",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier()"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn = KNeighborsClassifier()\n",
    "knn.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "21ba8e63",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.90      0.87      0.89      9068\n",
      "           1       0.90      0.93      0.92     11713\n",
      "\n",
      "    accuracy                           0.90     20781\n",
      "   macro avg       0.90      0.90      0.90     20781\n",
      "weighted avg       0.90      0.90      0.90     20781\n",
      "\n"
     ]
    }
   ],
   "source": [
    "y_pred_knn = knn.predict(x_test)\n",
    "print(classification_report(y_test, y_pred_knn))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "baa000ec",
   "metadata": {},
   "source": [
    "## Gradient boosting "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6ae3e2dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GradientBoostingClassifier()"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gbc = GradientBoostingClassifier()\n",
    "gbc.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d5a85f82",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.92      0.91      0.92      9068\n",
      "           1       0.93      0.94      0.94     11713\n",
      "\n",
      "    accuracy                           0.93     20781\n",
      "   macro avg       0.93      0.93      0.93     20781\n",
      "weighted avg       0.93      0.93      0.93     20781\n",
      "\n"
     ]
    }
   ],
   "source": [
    "y_pred_gbc = gbc.predict(x_test)\n",
    "print(classification_report(y_test, y_pred_gbc))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b4d918b",
   "metadata": {},
   "source": [
    "## Random forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "79bd1f6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier()"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf = RandomForestClassifier()\n",
    "rf.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "33ef2237",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.95      0.93      0.94      9068\n",
      "           1       0.95      0.96      0.95     11713\n",
      "\n",
      "    accuracy                           0.95     20781\n",
      "   macro avg       0.95      0.94      0.95     20781\n",
      "weighted avg       0.95      0.95      0.95     20781\n",
      "\n"
     ]
    }
   ],
   "source": [
    "y_pred_rf = rf.predict(x_test)\n",
    "print(classification_report(y_test, y_pred_rf))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "964c3c80",
   "metadata": {},
   "source": [
    "# Feature Importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "80dc5a4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 23 artists>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fi = rf.feature_importances_\n",
    "col = x_train.columns\n",
    "plt.barh(col,fi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7ebc517",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}