airlinePassengerSatisfactionCRISP.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing Required Packages/Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Accessing the Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv(\"train.csv\")\n",
    "test = pd.read_csv(\"test.csv\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring the \"train\" dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(103904, 25)\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed:_0</th>\n",
       "      <th>id</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Customer_Type</th>\n",
       "      <th>Age</th>\n",
       "      <th>Type_of_Travel</th>\n",
       "      <th>Class</th>\n",
       "      <th>Flight_Distance</th>\n",
       "      <th>Inflight_wifi_service</th>\n",
       "      <th>Departure/Arrival_time_convenient</th>\n",
       "      <th>...</th>\n",
       "      <th>Inflight_entertainment</th>\n",
       "      <th>On-board_service</th>\n",
       "      <th>Leg_room_service</th>\n",
       "      <th>Baggage_handling</th>\n",
       "      <th>Checkin_service</th>\n",
       "      <th>Inflight_service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>Departure_Delay_in_Minutes</th>\n",
       "      <th>Arrival_Delay_in_Minutes</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>70172</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>13</td>\n",
       "      <td>Personal Travel</td>\n",
       "      <td>Eco Plus</td>\n",
       "      <td>460</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>5047</td>\n",
       "      <td>Male</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>25</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>235</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>110028</td>\n",
       "      <td>Female</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>26</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1142</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed:_0      id  Gender      Customer_Type  Age   Type_of_Travel  \\\n",
       "0           0   70172    Male     Loyal Customer   13  Personal Travel   \n",
       "1           1    5047    Male  disloyal Customer   25  Business travel   \n",
       "2           2  110028  Female     Loyal Customer   26  Business travel   \n",
       "\n",
       "      Class  Flight_Distance  Inflight_wifi_service  \\\n",
       "0  Eco Plus              460                      3   \n",
       "1  Business              235                      3   \n",
       "2  Business             1142                      2   \n",
       "\n",
       "   Departure/Arrival_time_convenient  ...  Inflight_entertainment  \\\n",
       "0                                  4  ...                       5   \n",
       "1                                  2  ...                       1   \n",
       "2                                  2  ...                       5   \n",
       "\n",
       "   On-board_service  Leg_room_service  Baggage_handling  Checkin_service  \\\n",
       "0                 4                 3                 4                4   \n",
       "1                 1                 5                 3                1   \n",
       "2                 4                 3                 4                4   \n",
       "\n",
       "   Inflight_service  Cleanliness  Departure_Delay_in_Minutes  \\\n",
       "0                 5            5                          25   \n",
       "1                 4            1                           1   \n",
       "2                 4            5                           0   \n",
       "\n",
       "   Arrival_Delay_in_Minutes  satisfaction  \n",
       "0                      18.0             0  \n",
       "1                       6.0             0  \n",
       "2                       0.0             1  \n",
       "\n",
       "[3 rows x 25 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(train.shape)\n",
    "train.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed:_0</th>\n",
       "      <th>id</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Customer_Type</th>\n",
       "      <th>Age</th>\n",
       "      <th>Type_of_Travel</th>\n",
       "      <th>Class</th>\n",
       "      <th>Flight_Distance</th>\n",
       "      <th>Inflight_wifi_service</th>\n",
       "      <th>Departure/Arrival_time_convenient</th>\n",
       "      <th>...</th>\n",
       "      <th>Inflight_entertainment</th>\n",
       "      <th>On-board_service</th>\n",
       "      <th>Leg_room_service</th>\n",
       "      <th>Baggage_handling</th>\n",
       "      <th>Checkin_service</th>\n",
       "      <th>Inflight_service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>Departure_Delay_in_Minutes</th>\n",
       "      <th>Arrival_Delay_in_Minutes</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>70172</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>13</td>\n",
       "      <td>Personal Travel</td>\n",
       "      <td>Eco Plus</td>\n",
       "      <td>460</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
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       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>5047</td>\n",
       "      <td>Male</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>25</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
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       "      <td>3</td>\n",
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       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>110028</td>\n",
       "      <td>Female</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>26</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1142</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
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       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>24026</td>\n",
       "      <td>Female</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>25</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>562</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
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       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>119299</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>61</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>214</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
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       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>103899</th>\n",
       "      <td>103899</td>\n",
       "      <td>94171</td>\n",
       "      <td>Female</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>23</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Eco</td>\n",
       "      <td>192</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103900</th>\n",
       "      <td>103900</td>\n",
       "      <td>73097</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>49</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>2347</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103901</th>\n",
       "      <td>103901</td>\n",
       "      <td>68825</td>\n",
       "      <td>Male</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>30</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1995</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103902</th>\n",
       "      <td>103902</td>\n",
       "      <td>54173</td>\n",
       "      <td>Female</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>22</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Eco</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103903</th>\n",
       "      <td>103903</td>\n",
       "      <td>62567</td>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>27</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1723</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>103904 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed:_0      id  Gender      Customer_Type  Age   Type_of_Travel  \\\n",
       "0                0   70172    Male     Loyal Customer   13  Personal Travel   \n",
       "1                1    5047    Male  disloyal Customer   25  Business travel   \n",
       "2                2  110028  Female     Loyal Customer   26  Business travel   \n",
       "3                3   24026  Female     Loyal Customer   25  Business travel   \n",
       "4                4  119299    Male     Loyal Customer   61  Business travel   \n",
       "...            ...     ...     ...                ...  ...              ...   \n",
       "103899      103899   94171  Female  disloyal Customer   23  Business travel   \n",
       "103900      103900   73097    Male     Loyal Customer   49  Business travel   \n",
       "103901      103901   68825    Male  disloyal Customer   30  Business travel   \n",
       "103902      103902   54173  Female  disloyal Customer   22  Business travel   \n",
       "103903      103903   62567    Male     Loyal Customer   27  Business travel   \n",
       "\n",
       "           Class  Flight_Distance  Inflight_wifi_service  \\\n",
       "0       Eco Plus              460                      3   \n",
       "1       Business              235                      3   \n",
       "2       Business             1142                      2   \n",
       "3       Business              562                      2   \n",
       "4       Business              214                      3   \n",
       "...          ...              ...                    ...   \n",
       "103899       Eco              192                      2   \n",
       "103900  Business             2347                      4   \n",
       "103901  Business             1995                      1   \n",
       "103902       Eco             1000                      1   \n",
       "103903  Business             1723                      1   \n",
       "\n",
       "        Departure/Arrival_time_convenient  ...  Inflight_entertainment  \\\n",
       "0                                       4  ...                       5   \n",
       "1                                       2  ...                       1   \n",
       "2                                       2  ...                       5   \n",
       "3                                       5  ...                       2   \n",
       "4                                       3  ...                       3   \n",
       "...                                   ...  ...                     ...   \n",
       "103899                                  1  ...                       2   \n",
       "103900                                  4  ...                       5   \n",
       "103901                                  1  ...                       4   \n",
       "103902                                  1  ...                       1   \n",
       "103903                                  3  ...                       1   \n",
       "\n",
       "        On-board_service  Leg_room_service  Baggage_handling  Checkin_service  \\\n",
       "0                      4                 3                 4                4   \n",
       "1                      1                 5                 3                1   \n",
       "2                      4                 3                 4                4   \n",
       "3                      2                 5                 3                1   \n",
       "4                      3                 4                 4                3   \n",
       "...                  ...               ...               ...              ...   \n",
       "103899                 3                 1                 4                2   \n",
       "103900                 5                 5                 5                5   \n",
       "103901                 3                 2                 4                5   \n",
       "103902                 4                 5                 1                5   \n",
       "103903                 1                 1                 4                4   \n",
       "\n",
       "        Inflight_service  Cleanliness  Departure_Delay_in_Minutes  \\\n",
       "0                      5            5                          25   \n",
       "1                      4            1                           1   \n",
       "2                      4            5                           0   \n",
       "3                      4            2                          11   \n",
       "4                      3            3                           0   \n",
       "...                  ...          ...                         ...   \n",
       "103899                 3            2                           3   \n",
       "103900                 5            4                           0   \n",
       "103901                 5            4                           7   \n",
       "103902                 4            1                           0   \n",
       "103903                 3            1                           0   \n",
       "\n",
       "        Arrival_Delay_in_Minutes  satisfaction  \n",
       "0                           18.0             0  \n",
       "1                            6.0             0  \n",
       "2                            0.0             1  \n",
       "3                            9.0             0  \n",
       "4                            0.0             1  \n",
       "...                          ...           ...  \n",
       "103899                       0.0             0  \n",
       "103900                       0.0             1  \n",
       "103901                      14.0             0  \n",
       "103902                       0.0             0  \n",
       "103903                       0.0             0  \n",
       "\n",
       "[103904 rows x 25 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Two unnecessary columns, 'Unnamed: 0' and 'id', are dropped from the 'train' dataset. After removing these columns, the 'train.info()' function is used to check the size and information of the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 103904 entries, 0 to 103903\n",
      "Data columns (total 23 columns):\n",
      " #   Column                             Non-Null Count   Dtype  \n",
      "---  ------                             --------------   -----  \n",
      " 0   Gender                             103904 non-null  object \n",
      " 1   Customer_Type                      103904 non-null  object \n",
      " 2   Age                                103904 non-null  int64  \n",
      " 3   Type_of_Travel                     103904 non-null  object \n",
      " 4   Class                              103904 non-null  object \n",
      " 5   Flight_Distance                    103904 non-null  int64  \n",
      " 6   Inflight_wifi_service              103904 non-null  int64  \n",
      " 7   Departure/Arrival_time_convenient  103904 non-null  int64  \n",
      " 8   Ease_of_Online_booking             103904 non-null  int64  \n",
      " 9   Gate_location                      103904 non-null  int64  \n",
      " 10  Food_and_drink                     103904 non-null  int64  \n",
      " 11  Online_boarding                    103904 non-null  int64  \n",
      " 12  Seat_comfort                       103904 non-null  int64  \n",
      " 13  Inflight_entertainment             103904 non-null  int64  \n",
      " 14  On-board_service                   103904 non-null  int64  \n",
      " 15  Leg_room_service                   103904 non-null  int64  \n",
      " 16  Baggage_handling                   103904 non-null  int64  \n",
      " 17  Checkin_service                    103904 non-null  int64  \n",
      " 18  Inflight_service                   103904 non-null  int64  \n",
      " 19  Cleanliness                        103904 non-null  int64  \n",
      " 20  Departure_Delay_in_Minutes         103904 non-null  int64  \n",
      " 21  Arrival_Delay_in_Minutes           103594 non-null  float64\n",
      " 22  satisfaction                       103904 non-null  int64  \n",
      "dtypes: float64(1), int64(18), object(4)\n",
      "memory usage: 18.2+ MB\n"
     ]
    }
   ],
   "source": [
    "# Removing unnecessary Columns\n",
    "train = train.drop('Unnamed:_0', axis=1)\n",
    "train = train.drop('id', axis=1)\n",
    "\n",
    "# Checking the Resulting Dataset Size\n",
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(103904, 23)\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Customer_Type</th>\n",
       "      <th>Age</th>\n",
       "      <th>Type_of_Travel</th>\n",
       "      <th>Class</th>\n",
       "      <th>Flight_Distance</th>\n",
       "      <th>Inflight_wifi_service</th>\n",
       "      <th>Departure/Arrival_time_convenient</th>\n",
       "      <th>Ease_of_Online_booking</th>\n",
       "      <th>Gate_location</th>\n",
       "      <th>...</th>\n",
       "      <th>Inflight_entertainment</th>\n",
       "      <th>On-board_service</th>\n",
       "      <th>Leg_room_service</th>\n",
       "      <th>Baggage_handling</th>\n",
       "      <th>Checkin_service</th>\n",
       "      <th>Inflight_service</th>\n",
       "      <th>Cleanliness</th>\n",
       "      <th>Departure_Delay_in_Minutes</th>\n",
       "      <th>Arrival_Delay_in_Minutes</th>\n",
       "      <th>satisfaction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Male</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>25</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>235</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>26</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1142</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender      Customer_Type  Age   Type_of_Travel     Class  Flight_Distance  \\\n",
       "0    Male     Loyal Customer   13  Personal Travel  Eco Plus              460   \n",
       "1    Male  disloyal Customer   25  Business travel  Business              235   \n",
       "2  Female     Loyal Customer   26  Business travel  Business             1142   \n",
       "\n",
       "   Inflight_wifi_service  Departure/Arrival_time_convenient  \\\n",
       "0                      3                                  4   \n",
       "1                      3                                  2   \n",
       "2                      2                                  2   \n",
       "\n",
       "   Ease_of_Online_booking  Gate_location  ...  Inflight_entertainment  \\\n",
       "0                       3              1  ...                       5   \n",
       "1                       3              3  ...                       1   \n",
       "2                       2              2  ...                       5   \n",
       "\n",
       "   On-board_service  Leg_room_service  Baggage_handling  Checkin_service  \\\n",
       "0                 4                 3                 4                4   \n",
       "1                 1                 5                 3                1   \n",
       "2                 4                 3                 4                4   \n",
       "\n",
       "   Inflight_service  Cleanliness  Departure_Delay_in_Minutes  \\\n",
       "0                 5            5                          25   \n",
       "1                 4            1                           1   \n",
       "2                 4            5                           0   \n",
       "\n",
       "   Arrival_Delay_in_Minutes  satisfaction  \n",
       "0                      18.0             0  \n",
       "1                       6.0             0  \n",
       "2                       0.0             1  \n",
       "\n",
       "[3 rows x 23 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the resulting dataframe (train)\n",
    "\n",
    "print(train.shape)\n",
    "train.head(3)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Column Name Modification: Replacing Spaces with Underscores (Train and Test Datasets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.columns = [c.replace(' ', '_') for c in train.columns]\n",
    "test.columns = [c.replace(' ', '_') for c in test.columns]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Label Encoding: Transforming \"Satisfaction\" Values into Binary Format (Train and Test Datasets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['satisfaction'].replace({'neutral or dissatisfied': 0, 'satisfied': 1},inplace = True)\n",
    "test['satisfaction'].replace({'neutral or dissatisfied': 0, 'satisfied': 1},inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
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       "      <td>Female</td>\n",
       "      <td>disloyal Customer</td>\n",
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       "      <td>Business travel</td>\n",
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       "      <td>Business travel</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>103901</th>\n",
       "      <td>Male</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>30</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1995</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>103902</th>\n",
       "      <td>Female</td>\n",
       "      <td>disloyal Customer</td>\n",
       "      <td>22</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Eco</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103903</th>\n",
       "      <td>Male</td>\n",
       "      <td>Loyal Customer</td>\n",
       "      <td>27</td>\n",
       "      <td>Business travel</td>\n",
       "      <td>Business</td>\n",
       "      <td>1723</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>103904 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Gender      Customer_Type  Age   Type_of_Travel     Class  \\\n",
       "0         Male     Loyal Customer   13  Personal Travel  Eco Plus   \n",
       "1         Male  disloyal Customer   25  Business travel  Business   \n",
       "2       Female     Loyal Customer   26  Business travel  Business   \n",
       "3       Female     Loyal Customer   25  Business travel  Business   \n",
       "4         Male     Loyal Customer   61  Business travel  Business   \n",
       "...        ...                ...  ...              ...       ...   \n",
       "103899  Female  disloyal Customer   23  Business travel       Eco   \n",
       "103900    Male     Loyal Customer   49  Business travel  Business   \n",
       "103901    Male  disloyal Customer   30  Business travel  Business   \n",
       "103902  Female  disloyal Customer   22  Business travel       Eco   \n",
       "103903    Male     Loyal Customer   27  Business travel  Business   \n",
       "\n",
       "        Flight_Distance  Inflight_wifi_service  \\\n",
       "0                   460                      3   \n",
       "1                   235                      3   \n",
       "2                  1142                      2   \n",
       "3                   562                      2   \n",
       "4                   214                      3   \n",
       "...                 ...                    ...   \n",
       "103899              192                      2   \n",
       "103900             2347                      4   \n",
       "103901             1995                      1   \n",
       "103902             1000                      1   \n",
       "103903             1723                      1   \n",
       "\n",
       "        Departure/Arrival_time_convenient  Ease_of_Online_booking  \\\n",
       "0                                       4                       3   \n",
       "1                                       2                       3   \n",
       "2                                       2                       2   \n",
       "3                                       5                       5   \n",
       "4                                       3                       3   \n",
       "...                                   ...                     ...   \n",
       "103899                                  1                       2   \n",
       "103900                                  4                       4   \n",
       "103901                                  1                       1   \n",
       "103902                                  1                       1   \n",
       "103903                                  3                       3   \n",
       "\n",
       "        Gate_location  ...  Inflight_entertainment  On-board_service  \\\n",
       "0                   1  ...                       5                 4   \n",
       "1                   3  ...                       1                 1   \n",
       "2                   2  ...                       5                 4   \n",
       "3                   5  ...                       2                 2   \n",
       "4                   3  ...                       3                 3   \n",
       "...               ...  ...                     ...               ...   \n",
       "103899              3  ...                       2                 3   \n",
       "103900              4  ...                       5                 5   \n",
       "103901              3  ...                       4                 3   \n",
       "103902              5  ...                       1                 4   \n",
       "103903              3  ...                       1                 1   \n",
       "\n",
       "        Leg_room_service  Baggage_handling  Checkin_service  Inflight_service  \\\n",
       "0                      3                 4                4                 5   \n",
       "1                      5                 3                1                 4   \n",
       "2                      3                 4                4                 4   \n",
       "3                      5                 3                1                 4   \n",
       "4                      4                 4                3                 3   \n",
       "...                  ...               ...              ...               ...   \n",
       "103899                 1                 4                2                 3   \n",
       "103900                 5                 5                5                 5   \n",
       "103901                 2                 4                5                 5   \n",
       "103902                 5                 1                5                 4   \n",
       "103903                 1                 4                4                 3   \n",
       "\n",
       "        Cleanliness  Departure_Delay_in_Minutes  Arrival_Delay_in_Minutes  \\\n",
       "0                 5                          25                      18.0   \n",
       "1                 1                           1                       6.0   \n",
       "2                 5                           0                       0.0   \n",
       "3                 2                          11                       9.0   \n",
       "4                 3                           0                       0.0   \n",
       "...             ...                         ...                       ...   \n",
       "103899            2                           3                       0.0   \n",
       "103900            4                           0                       0.0   \n",
       "103901            4                           7                      14.0   \n",
       "103902            1                           0                       0.0   \n",
       "103903            1                           0                       0.0   \n",
       "\n",
       "        satisfaction  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  1  \n",
       "3                  0  \n",
       "4                  1  \n",
       "...              ...  \n",
       "103899             0  \n",
       "103900             1  \n",
       "103901             0  \n",
       "103902             0  \n",
       "103903             0  \n",
       "\n",
       "[103904 rows x 23 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the satisfaction indicator\n",
    "fig = plt.figure(figsize=(4, 3))\n",
    "train.satisfaction.value_counts(normalize=True).plot(kind='bar', color=['red', 'green'], alpha=0.9, rot=0)\n",
    "\n",
    "# Setting plot title and axis labels\n",
    "plt.title('Distribution of Satisfaction Levels in the Dataset')\n",
    "plt.xlabel('Satisfaction Level')\n",
    "plt.ylabel('Proportion')\n",
    "\n",
    "# Displaying the plot\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The plot indicates a fairly balanced distribution of satisfaction levels, with approximately 55% for \"neutral/dissatisfied\" passengers and 45% for \"satisfied\" passengers. Consequently, there is no immediate need for resampling techniques to address class imbalance in the dataset."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Managing Missing Data: Strategies and Techniques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>Total</th>\n",
       "      <th>Percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Arrival_Delay_in_Minutes</th>\n",
       "      <td>310</td>\n",
       "      <td>0.002984</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Total   Percent\n",
       "Arrival_Delay_in_Minutes    310  0.002984"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total count of missing values for each column ('train' dataset) \n",
    "total = train.isnull().sum().sort_values(ascending=False)\n",
    "\n",
    "# Calculate the percentage of missing values for each column ('train' dataset)\n",
    "percent = (train.isnull().sum() / train.isnull().count()).sort_values(ascending=False)\n",
    "\n",
    "# Concatenate the total count and percentage of missing values into a DataFrame called 'missing'\n",
    "missing = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])\n",
    "\n",
    "# Exclude rows with zero total missing values\n",
    "missing = missing[missing['Total'] > 0]\n",
    "\n",
    "# Display the top rows of the 'missing' DataFrame\n",
    "missing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imputing missing value with mean - Train and Test\n",
    "train['Arrival_Delay_in_Minutes'] = train['Arrival_Delay_in_Minutes'].fillna(train['Arrival_Delay_in_Minutes'].mean())\n",
    "test['Arrival_Delay_in_Minutes'] = test['Arrival_Delay_in_Minutes'].fillna(test['Arrival_Delay_in_Minutes'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Gender', 'Customer_Type', 'Type_of_Travel', 'Class'], dtype='object')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the list of categorical variables\n",
    "train.select_dtypes(include=['object']).columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace NaN with mode (most frequent value) for categorical variables in the 'train' dataset\n",
    "train['Gender'] = train['Gender'].fillna(train['Gender'].mode()[0])\n",
    "train['Customer_Type'] = train['Customer_Type'].fillna(train['Customer_Type'].mode()[0])\n",
    "train['Type_of_Travel'] = train['Type_of_Travel'].fillna(train['Type_of_Travel'].mode()[0])\n",
    "train['Class'] = train['Class'].fillna(train['Class'].mode()[0])\n",
    "\n",
    "# Replace NaN with mode (most frequent value) for categorical variables in the 'test' dataset\n",
    "test['Gender'] = test['Gender'].fillna(test['Gender'].mode()[0])\n",
    "test['Customer_Type'] = test['Customer_Type'].fillna(test['Customer_Type'].mode()[0])\n",
    "test['Type_of_Travel'] = test['Type_of_Travel'].fillna(test['Type_of_Travel'].mode()[0])\n",
    "test['Class'] = test['Class'].fillna(test['Class'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.to_csv(\"data.csv\", sep=',', index=False, encoding='utf-8')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Uncovering Insights through Data Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 761.111x250 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 761.111x250 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exploring Satisfaction Levels by Gender and Customer Type\n",
    "\n",
    "with sns.axes_style(style='ticks'):\n",
    "    gender_plot = sns.catplot(x=\"satisfaction\", col=\"Gender\", col_wrap=2, data=train, kind=\"count\", height=2.5, aspect=1.5)\n",
    "    gender_plot.set_xticklabels([\"Neutral/Dissatisfied\", \"Satisfied\"])\n",
    "    gender_plot.set_axis_labels(\"Satisfaction\", \"Count\")\n",
    "    for ax in gender_plot.axes.flat:\n",
    "        for p in ax.patches:\n",
    "            ax.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 5), textcoords = 'offset points')\n",
    "    \n",
    "    customer_type_plot = sns.catplot(x=\"satisfaction\", col=\"Customer_Type\", col_wrap=2, data=train, kind=\"count\", height=2.5, aspect=1.5)\n",
    "    customer_type_plot.set_xticklabels([\"Neutral/Dissatisfied\", \"Satisfied\"])\n",
    "    customer_type_plot.set_axis_labels(\"Satisfaction\", \"Count\")\n",
    "    for ax in customer_type_plot.axes.flat:\n",
    "        for p in ax.patches:\n",
    "            ax.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 5), textcoords = 'offset points')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** \n",
    "\n",
    "Gender: The analysis reveals that there is a similar distribution of neutral/dissatisfied and satisfied customers across gender. Both male and female passengers exhibit a higher proportion of neutral/dissatisfied customers compared to satisfied customers.\n",
    "\n",
    "Customer Type: Among the customer types, even though the number of loyal passengers is relatively high, the ratio of satisfied to neutral/dissatisfied customers is almost evenly split in it (loyal passengers) at around 48:52."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\67373481.py:3: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  satisfaction_plot = sns.catplot(x=\"Flight_Distance\", y=\"Type_of_Travel\", hue=\"satisfaction\", col=\"Class\", data=train, kind=\"bar\", height=4.5, aspect=.8,ci=None)\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1160.74x450 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Type_of_Travel and Flight_Distance by Class\n",
    "with sns.axes_style(style='ticks'):\n",
    "    satisfaction_plot = sns.catplot(x=\"Flight_Distance\", y=\"Type_of_Travel\", hue=\"satisfaction\", col=\"Class\", data=train, kind=\"bar\", height=4.5, aspect=.8,ci=None)\n",
    "    satisfaction_plot.set_axis_labels(\"Flight Distance\", \"Type of Travel\")\n",
    "    satisfaction_plot.set_xticklabels(rotation=45)\n",
    "    satisfaction_plot.savefig('output1.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** The analysis reveals that within the business travel category and specifically in the business class, there is a notable increase in the number of satisfied passengers for longer flight distances. However, for other combinations of travel type, flight distance, and class, a relatively equal distribution of satisfied and neutral/dissatisfied passengers is observed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1580.74x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Passenger Satisfaction by Age\n",
    "with sns.axes_style(style='ticks'):\n",
    "    age_plot = sns.catplot(x=\"Age\", data=train, aspect=3.0, kind='count', hue='satisfaction', order=range(5, 80))\n",
    "    age_plot.set_ylabels('Number of Passengers')\n",
    "    age_plot.fig.suptitle('Passenger Satisfaction Distribution by Age', y=1.05)\n",
    "\n",
    "    # Highlight age groups 39-60\n",
    "    age_plot.ax.axvspan(33.5, 55.5, color='lightgreen', alpha=0.3)\n",
    "    \n",
    "    # Adjust x-axis range and labels\n",
    "    plt.xlim(5, 80)\n",
    "    plt.xticks(range(5, 81, 5), rotation=90)\n",
    "    age_plot.savefig('output2.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** From ages 7 to 38 and from ages 61 to 79, there is a notable prevalence of neutral/dissatisfied passengers compared to satisfied passengers. Conversely, in the age group of 39 to 60 (green highlighted), the number of satisfied passengers surpasses that of neutral/dissatisfied passengers. This age-based variation in satisfaction levels highlights the importance of considering age demographics when addressing customer satisfaction within the airline industry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\1709702048.py:3: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  g1 = sns.catplot(x=\"Class\", y=\"Departure_Delay_in_Minutes\", hue=\"satisfaction\", col=\"Type_of_Travel\", data=train, kind=\"bar\", height=4.5, aspect=1.0,ci=None)\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n",
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\1709702048.py:9: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  g2 = sns.catplot(x=\"Class\", y=\"Arrival_Delay_in_Minutes\", hue=\"satisfaction\", col=\"Type_of_Travel\", data=train, kind=\"bar\", height=4.5, aspect=1.0,ci=None)\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 980.736x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 980.736x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Departure and Arrival Delays by Type of Travel and Class\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g1 = sns.catplot(x=\"Class\", y=\"Departure_Delay_in_Minutes\", hue=\"satisfaction\", col=\"Type_of_Travel\", data=train, kind=\"bar\", height=4.5, aspect=1.0,ci=None)\n",
    "    g1.fig.suptitle('Departure Delay by Type of Travel and Class', y=1.05)\n",
    "    g1.set_xticklabels(rotation=45)\n",
    "    g1.set_ylabels('Departure Delay (in Minutes)')\n",
    "    g1.savefig('output3.png',format='png',bbox_inches='tight', dpi=1200)\n",
    "    \n",
    "    g2 = sns.catplot(x=\"Class\", y=\"Arrival_Delay_in_Minutes\", hue=\"satisfaction\", col=\"Type_of_Travel\", data=train, kind=\"bar\", height=4.5, aspect=1.0,ci=None)\n",
    "    g2.fig.suptitle('Arrival Delay by Type of Travel and Class', y=1.05)\n",
    "    g2.set_xticklabels(rotation=45)\n",
    "    g2.set_ylabels('Arrival Delay (in Minutes)')\n",
    "    g2.savefig('output4.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** In the case of personal type of travel, particularly for classes Eco Plus and Eco, it is evident that there is a significant increase in the number of neutral/dissatisfied passengers when the arrival delay is high, which is expected. \n",
    "\n",
    "When examining the data on a minute-by-minute basis, it is observed that all combinations have a higher count of neutral/dissatisfied passengers compared to satisfied passengers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\3193532758.py:4: FutureWarning: \n",
      "\n",
      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
      "\n",
      "  g = sns.catplot(x=\"Departure/Arrival_time_convenient\", y=\"Online_boarding\", hue=\"satisfaction\", col=\"Class\", data=train, kind=\"bar\", height=4.5, aspect=1.0,ci=None)\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1430.74x450 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Online Boarding Experience and Departure/Arrival Time Convenience by Class\n",
    "\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"Departure/Arrival_time_convenient\", y=\"Online_boarding\", hue=\"satisfaction\", col=\"Class\", data=train, kind=\"bar\", height=4.5, aspect=1.0,ci=None)\n",
    "    g.savefig('output5.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** In the Eco Plus class, a significant number of neutral/dissatisfied passengers are observed when the Departure/Arrival time convenience is rated as very inconvenient (score 0), despite positive online boarding experiences. However, in other class combinations, the number of satisfied passengers outweighs the number of neutral/dissatisfied passengers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1430.74x450 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Inflight Wi-Fi Service and Inflight Entertainment by Class\n",
    "\n",
    "# Analysis of Inflight Wi-Fi Service and Inflight Entertainment by Class\n",
    "\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"Inflight_wifi_service\", y=\"Inflight_entertainment\", hue=\"satisfaction\", col=\"Class\", data=train, kind=\"box\", height=4.5, aspect=1.0)\n",
    "    g.savefig('output6.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** \n",
    "\n",
    "(i) Eco Plus passengers show higher satisfaction levels when they do not have access to inflight Wi-Fi (rating 0) and when they experience moderate levels of inflight entertainment (ratings 2-4). \n",
    "\n",
    "(ii) In the case of Business class passengers, maximum satisfaction is achieved when they have access to the highest level of inflight entertainment (rating 5). \n",
    "\n",
    "(iii) For Eco class passengers, a combination of high levels of inflight entertainment (ratings 3-5) and excellent Wi-Fi service availability (rating 5) contributes to their satisfaction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\2225489277.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(x = \"Class\", y = \"Age\", palette = \"YlOrBr\", data = train, ax = ax[0])\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1, 2, figsize = (15,5))\n",
    "sns.boxplot(x = \"Class\", y = \"Age\", palette = \"YlOrBr\", data = train, ax = ax[0])\n",
    "sns.histplot(train, x = \"Age\", hue = \"Class\", multiple = \"stack\", palette = \"YlOrBr\", edgecolor = \".3\", linewidth = .5, ax = ax[1])\n",
    "f.savefig('output11.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Satisfaction Ratings for Online Booking, Seat Comfort, Cleanliness, and Food & Drink"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\174882871.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  g = sns.catplot(x=\"satisfaction\", col=\"Ease_of_Online_booking\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Satisfaction based on Ease of Online Booking\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"satisfaction\", col=\"Ease_of_Online_booking\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
    "    g.set_axis_labels(\"Satisfaction\", \"Count\")\n",
    "    g.savefig('output7.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\3315847564.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  g = sns.catplot(x=\"satisfaction\", col=\"Seat_comfort\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Satisfaction based on Seat Comfort\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"satisfaction\", col=\"Seat_comfort\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
    "    g.set_axis_labels(\"Satisfaction\", \"Count\")\n",
    "    g.savefig('output8.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\3392977758.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  g = sns.catplot(x=\"satisfaction\", col=\"Cleanliness\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Satisfaction based on Cleanliness\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"satisfaction\", col=\"Cleanliness\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
    "    g.set_axis_labels(\"Satisfaction\", \"Count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_11032\\4153320758.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  g = sns.catplot(x=\"satisfaction\", col=\"Food_and_drink\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
      "c:\\Users\\DELL\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\axisgrid.py:123: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Satisfaction based on Food and Drink\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"satisfaction\", col=\"Food_and_drink\", col_wrap=6, data=train, kind=\"count\", height=2.5, aspect=1.0, palette=\"Set1\")\n",
    "    g.set_axis_labels(\"Satisfaction\", \"Count\")\n",
    "    g.savefig('output9.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** Based on the analysis of these four features, it can be observed that the majority of satisfied passengers provided ratings of 4 and 5. On the other hand, passengers who rated these features below 4 tended to be more neutral or dissatisfied."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1441.24x450 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis of Baggage Handling and Gate Location by Class\n",
    "\n",
    "with sns.axes_style(style='ticks'):\n",
    "    g = sns.catplot(x=\"Gate_location\", y=\"Baggage_handling\", hue=\"satisfaction\", col=\"Class\", data=train, kind=\"box\", height=4.5, aspect=1.0)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** After analyzing the data, it is evident that in the business class category, a higher number of neutral/dissatisfied passengers can be observed across all gate locations when the baggage handling rating is below satisfactory (rating <= 4). Additionally, for Eco Plus class, when the gate location is 1, and for Eco class, when the gate location is 2, passengers tend to remain neutral/dissatisfied even when the baggage handling is rated as mediocre (rating 2 to 4). These findings highlight the importance of both gate location and quality of baggage handling in influencing passenger satisfaction levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap Analysis of Passenger Satisfaction Level for Checkin_service, Leg_room_service, On-board_service and Inflight_service\n",
    "\n",
    "fig, axarr = plt.subplots(2, 2, figsize=(10, 6))\n",
    "\n",
    "table1 = pd.crosstab(train['satisfaction'], train['Checkin_service'])\n",
    "sns.heatmap(table1, cmap='PuRd', ax = axarr[0][0])\n",
    "table2 = pd.crosstab(train['satisfaction'], train['Leg_room_service'])\n",
    "sns.heatmap(table2, cmap='YlOrBr', ax = axarr[0][1])\n",
    "table3 = pd.crosstab(train['satisfaction'], train['On-board_service'])\n",
    "sns.heatmap(table3, cmap='Greens', ax = axarr[1][0])\n",
    "table4 = pd.crosstab(train['satisfaction'], train['Inflight_service'])\n",
    "sns.heatmap(table4, cmap='PuBu', ax = axarr[1][1])\n",
    "\n",
    "plt.savefig('output10.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** Passenger satisfaction analysis reveals that for the check-in service, passengers who provided ratings of 0-2 were predominantly neutral or dissatisfied. Conversely, for the remaining services (leg room, on-board, and in-flight), satisfaction was primarily observed among passengers who rated these services with 4 or 5."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Encoding Categorical Variables Using Label Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For Train set\n",
    "lencoders = {}\n",
    "for col in train.select_dtypes(include=['object']).columns:\n",
    "    lencoders[col] = LabelEncoder()\n",
    "    train[col] = lencoders[col].fit_transform(train[col])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For Test Set\n",
    "lencoders_t = {}\n",
    "for col in test.select_dtypes(include=['object']).columns:\n",
    "    lencoders_t[col] = LabelEncoder()\n",
    "    test[col] = lencoders_t[col].fit_transform(test[col])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Identifying and Eliminating Outliers\n",
    "\n",
    "The interquartile range (IQR) for each numerical variable in the dataset, represents the range between the 25th and 75th percentiles of the data. For instance, the IQR for the 'Age' variable is 24, indicating that the middle 50% of the age values fall within this range. \n",
    "\n",
    "By calculating the IQR, we can identify potential outliers in the data by considering values that are significantly higher or lower than the range defined by the IQR."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gender                                  1.0\n",
      "Customer_Type                           0.0\n",
      "Age                                    24.0\n",
      "Type_of_Travel                          1.0\n",
      "Class                                   1.0\n",
      "Flight_Distance                      1329.0\n",
      "Inflight_wifi_service                   2.0\n",
      "Departure/Arrival_time_convenient       2.0\n",
      "Ease_of_Online_booking                  2.0\n",
      "Gate_location                           2.0\n",
      "Food_and_drink                          2.0\n",
      "Online_boarding                         2.0\n",
      "Seat_comfort                            3.0\n",
      "Inflight_entertainment                  2.0\n",
      "On-board_service                        2.0\n",
      "Leg_room_service                        2.0\n",
      "Baggage_handling                        2.0\n",
      "Checkin_service                         1.0\n",
      "Inflight_service                        2.0\n",
      "Cleanliness                             2.0\n",
      "Departure_Delay_in_Minutes             12.0\n",
      "Arrival_Delay_in_Minutes               13.0\n",
      "satisfaction                            1.0\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "Q1 = train.quantile(0.25)\n",
    "Q3 = train.quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "print(IQR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(61197, 23)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Removal of outliers from dataset\n",
    "train = train[~((train < (Q1 - 1.5 * IQR)) |(train > (Q3 + 1.5 * IQR))).any(axis=1)]\n",
    "train.shape"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Feature Correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x2000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation Heatmap\n",
    "\n",
    "corr = train.corr()\n",
    "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
    "f, ax = plt.subplots(figsize=(20, 20))\n",
    "cmap = sns.diverging_palette(240, 10, as_cmap=True)\n",
    "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=None, center=0,square=True, annot=True, linewidths=.5, cbar_kws={\"shrink\": .9})\n",
    "f.savefig('output12.png',format='png',bbox_inches='tight', dpi=1200)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** The feature \"Ease_of_Online_booking\" exhibits a strong correlation with \"Inflight_wifi_service\", while \"Inflight_service\" demonstrates a high correlation with \"Baggage_handling\". However, none of the feature pairs have a correlation coefficient equal to 1, indicating the absence of perfect multicollinearity. As a result, we do not need to discard any variables in our analysis."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Findings:** A set of six features has been identified (see above) as inherently important contributors to customer or passenger satisfaction. In order to validate the results, an additional feature importance method was employed for cross-referencing."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.4"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}