Flight Fare Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Airline</th>\n",
       "      <th>Date_of_Journey</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Dep_Time</th>\n",
       "      <th>Arrival_Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>24/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>22:20</td>\n",
       "      <td>01:10 22 Mar</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>3897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Air India</td>\n",
       "      <td>1/05/2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → IXR → BBI → BLR</td>\n",
       "      <td>05:50</td>\n",
       "      <td>13:15</td>\n",
       "      <td>7h 25m</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>7662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>9/06/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → LKO → BOM → COK</td>\n",
       "      <td>09:25</td>\n",
       "      <td>04:25 10 Jun</td>\n",
       "      <td>19h</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>13882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>12/05/2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → NAG → BLR</td>\n",
       "      <td>18:05</td>\n",
       "      <td>23:30</td>\n",
       "      <td>5h 25m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>01/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → NAG → DEL</td>\n",
       "      <td>16:50</td>\n",
       "      <td>21:35</td>\n",
       "      <td>4h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>13302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Airline Date_of_Journey    Source Destination                  Route  \\\n",
       "0       IndiGo      24/03/2019  Banglore   New Delhi              BLR → DEL   \n",
       "1    Air India       1/05/2019   Kolkata    Banglore  CCU → IXR → BBI → BLR   \n",
       "2  Jet Airways       9/06/2019     Delhi      Cochin  DEL → LKO → BOM → COK   \n",
       "3       IndiGo      12/05/2019   Kolkata    Banglore        CCU → NAG → BLR   \n",
       "4       IndiGo      01/03/2019  Banglore   New Delhi        BLR → NAG → DEL   \n",
       "\n",
       "  Dep_Time  Arrival_Time Duration Total_Stops Additional_Info  Price  \n",
       "0    22:20  01:10 22 Mar   2h 50m    non-stop         No info   3897  \n",
       "1    05:50         13:15   7h 25m     2 stops         No info   7662  \n",
       "2    09:25  04:25 10 Jun      19h     2 stops         No info  13882  \n",
       "3    18:05         23:30   5h 25m      1 stop         No info   6218  \n",
       "4    16:50         21:35   4h 45m      1 stop         No info  13302  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"G:\\DATA SCIENCE\\MACHINE LEARNING\\Projects\\Flight Fare Prediction\\Data_Train.xlsx\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10683 entries, 0 to 10682\n",
      "Data columns (total 11 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   Airline          10683 non-null  object\n",
      " 1   Date_of_Journey  10683 non-null  object\n",
      " 2   Source           10683 non-null  object\n",
      " 3   Destination      10683 non-null  object\n",
      " 4   Route            10682 non-null  object\n",
      " 5   Dep_Time         10683 non-null  object\n",
      " 6   Arrival_Time     10683 non-null  object\n",
      " 7   Duration         10683 non-null  object\n",
      " 8   Total_Stops      10682 non-null  object\n",
      " 9   Additional_Info  10683 non-null  object\n",
      " 10  Price            10683 non-null  int64 \n",
      "dtypes: int64(1), object(10)\n",
      "memory usage: 918.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Airline            0\n",
       "Date_of_Journey    0\n",
       "Source             0\n",
       "Destination        0\n",
       "Route              1\n",
       "Dep_Time           0\n",
       "Arrival_Time       0\n",
       "Duration           0\n",
       "Total_Stops        1\n",
       "Additional_Info    0\n",
       "Price              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()#to check nan values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2h 50m     550\n",
       "1h 30m     386\n",
       "2h 45m     337\n",
       "2h 55m     337\n",
       "2h 35m     329\n",
       "          ... \n",
       "3h 25m       1\n",
       "28h 30m      1\n",
       "30h 25m      1\n",
       "37h 10m      1\n",
       "31h 50m      1\n",
       "Name: Duration, Length: 368, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Duration'].value_counts()#to check unique values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Airline            0\n",
       "Date_of_Journey    0\n",
       "Source             0\n",
       "Destination        0\n",
       "Route              0\n",
       "Dep_Time           0\n",
       "Arrival_Time       0\n",
       "Duration           0\n",
       "Total_Stops        0\n",
       "Additional_Info    0\n",
       "Price              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dropna(inplace=True)\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data preprocessing for date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['j_day']=pd.to_datetime(df.Date_of_Journey,format='%d/%m/%Y').dt.day\n",
    "#.dt.day method will extract only day from the date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['j_month']=pd.to_datetime(df.Date_of_Journey,format='%d/%m/%Y').dt.month\n",
    "#.dt.month will extract only month from date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Dep_Time</th>\n",
       "      <th>Arrival_Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>22:20</td>\n",
       "      <td>01:10 22 Mar</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>3897</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Air India</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → IXR → BBI → BLR</td>\n",
       "      <td>05:50</td>\n",
       "      <td>13:15</td>\n",
       "      <td>7h 25m</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>7662</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → LKO → BOM → COK</td>\n",
       "      <td>09:25</td>\n",
       "      <td>04:25 10 Jun</td>\n",
       "      <td>19h</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>13882</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → NAG → BLR</td>\n",
       "      <td>18:05</td>\n",
       "      <td>23:30</td>\n",
       "      <td>5h 25m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6218</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → NAG → DEL</td>\n",
       "      <td>16:50</td>\n",
       "      <td>21:35</td>\n",
       "      <td>4h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>13302</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Airline    Source Destination                  Route Dep_Time  \\\n",
       "0       IndiGo  Banglore   New Delhi              BLR → DEL    22:20   \n",
       "1    Air India   Kolkata    Banglore  CCU → IXR → BBI → BLR    05:50   \n",
       "2  Jet Airways     Delhi      Cochin  DEL → LKO → BOM → COK    09:25   \n",
       "3       IndiGo   Kolkata    Banglore        CCU → NAG → BLR    18:05   \n",
       "4       IndiGo  Banglore   New Delhi        BLR → NAG → DEL    16:50   \n",
       "\n",
       "   Arrival_Time Duration Total_Stops Additional_Info  Price  j_day  j_month  \n",
       "0  01:10 22 Mar   2h 50m    non-stop         No info   3897     24        3  \n",
       "1         13:15   7h 25m     2 stops         No info   7662      1        5  \n",
       "2  04:25 10 Jun      19h     2 stops         No info  13882      9        6  \n",
       "3         23:30   5h 25m      1 stop         No info   6218     12        5  \n",
       "4         21:35   4h 45m      1 stop         No info  13302      1        3  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(['Date_of_Journey'],axis=1,inplace=True)#we dont require it now\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data preprocessing for dep time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Arrival_Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>01:10 22 Mar</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>3897</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Air India</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → IXR → BBI → BLR</td>\n",
       "      <td>13:15</td>\n",
       "      <td>7h 25m</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>7662</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → LKO → BOM → COK</td>\n",
       "      <td>04:25 10 Jun</td>\n",
       "      <td>19h</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>13882</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → NAG → BLR</td>\n",
       "      <td>23:30</td>\n",
       "      <td>5h 25m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6218</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → NAG → DEL</td>\n",
       "      <td>21:35</td>\n",
       "      <td>4h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>13302</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Airline    Source Destination                  Route  Arrival_Time  \\\n",
       "0       IndiGo  Banglore   New Delhi              BLR → DEL  01:10 22 Mar   \n",
       "1    Air India   Kolkata    Banglore  CCU → IXR → BBI → BLR         13:15   \n",
       "2  Jet Airways     Delhi      Cochin  DEL → LKO → BOM → COK  04:25 10 Jun   \n",
       "3       IndiGo   Kolkata    Banglore        CCU → NAG → BLR         23:30   \n",
       "4       IndiGo  Banglore   New Delhi        BLR → NAG → DEL         21:35   \n",
       "\n",
       "  Duration Total_Stops Additional_Info  Price  j_day  j_month  d_hour  d_min  \n",
       "0   2h 50m    non-stop         No info   3897     24        3      22     20  \n",
       "1   7h 25m     2 stops         No info   7662      1        5       5     50  \n",
       "2      19h     2 stops         No info  13882      9        6       9     25  \n",
       "3   5h 25m      1 stop         No info   6218     12        5      18      5  \n",
       "4   4h 45m      1 stop         No info  13302      1        3      16     50  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['d_hour']=pd.to_datetime(df['Dep_Time']).dt.hour\n",
    "df['d_min']=pd.to_datetime(df['Dep_Time']).dt.minute\n",
    "df.drop(['Dep_Time'],axis=1,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data preprocessing for Arrival_Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>A_hour</th>\n",
       "      <th>A_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>3897</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Air India</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → IXR → BBI → BLR</td>\n",
       "      <td>7h 25m</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>7662</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → LKO → BOM → COK</td>\n",
       "      <td>19h</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>13882</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → NAG → BLR</td>\n",
       "      <td>5h 25m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6218</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → NAG → DEL</td>\n",
       "      <td>4h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>13302</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Airline    Source Destination                  Route Duration  \\\n",
       "0       IndiGo  Banglore   New Delhi              BLR → DEL   2h 50m   \n",
       "1    Air India   Kolkata    Banglore  CCU → IXR → BBI → BLR   7h 25m   \n",
       "2  Jet Airways     Delhi      Cochin  DEL → LKO → BOM → COK      19h   \n",
       "3       IndiGo   Kolkata    Banglore        CCU → NAG → BLR   5h 25m   \n",
       "4       IndiGo  Banglore   New Delhi        BLR → NAG → DEL   4h 45m   \n",
       "\n",
       "  Total_Stops Additional_Info  Price  j_day  j_month  d_hour  d_min  A_hour  \\\n",
       "0    non-stop         No info   3897     24        3      22     20       1   \n",
       "1     2 stops         No info   7662      1        5       5     50      13   \n",
       "2     2 stops         No info  13882      9        6       9     25       4   \n",
       "3      1 stop         No info   6218     12        5      18      5      23   \n",
       "4      1 stop         No info  13302      1        3      16     50      21   \n",
       "\n",
       "   A_min  \n",
       "0     10  \n",
       "1     15  \n",
       "2     25  \n",
       "3     30  \n",
       "4     35  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['A_hour']=pd.to_datetime(df['Arrival_Time']).dt.hour\n",
    "df['A_min']=pd.to_datetime(df['Arrival_Time']).dt.minute\n",
    "df.drop(['Arrival_Time'],axis=1,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data preprocessing in Duration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['5h', '25m']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'5h 25m'.split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "duration = list(df[\"Duration\"])\n",
    "\n",
    "for i in range(len(duration)):\n",
    "    if len(duration[i].split()) != 2:    \n",
    "        if \"h\" in duration[i]:\n",
    "            duration[i] = duration[i].strip() + \" 0m\"   \n",
    "        else:\n",
    "            duration[i] = \"0h \" + duration[i]           \n",
    "\n",
    "duration_hours = []\n",
    "duration_mins = []\n",
    "for i in range(len(duration)):\n",
    "    duration_hours.append(int(duration[i].split(sep = \"h\")[0]))    \n",
    "    duration_mins.append(int(duration[i].split(sep = \"m\")[0].split()[-1]))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['duration_hours'] = duration_hours\n",
    "df['duration_mins'] = duration_mins\n",
    "df.drop('Duration',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>A_hour</th>\n",
       "      <th>A_min</th>\n",
       "      <th>duration_hours</th>\n",
       "      <th>duration_mins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>3897</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Air India</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → IXR → BBI → BLR</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>7662</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → LKO → BOM → COK</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>13882</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → NAG → BLR</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6218</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → NAG → DEL</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>13302</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Airline    Source Destination                  Route Total_Stops  \\\n",
       "0       IndiGo  Banglore   New Delhi              BLR → DEL    non-stop   \n",
       "1    Air India   Kolkata    Banglore  CCU → IXR → BBI → BLR     2 stops   \n",
       "2  Jet Airways     Delhi      Cochin  DEL → LKO → BOM → COK     2 stops   \n",
       "3       IndiGo   Kolkata    Banglore        CCU → NAG → BLR      1 stop   \n",
       "4       IndiGo  Banglore   New Delhi        BLR → NAG → DEL      1 stop   \n",
       "\n",
       "  Additional_Info  Price  j_day  j_month  d_hour  d_min  A_hour  A_min  \\\n",
       "0         No info   3897     24        3      22     20       1     10   \n",
       "1         No info   7662      1        5       5     50      13     15   \n",
       "2         No info  13882      9        6       9     25       4     25   \n",
       "3         No info   6218     12        5      18      5      23     30   \n",
       "4         No info  13302      1        3      16     50      21     35   \n",
       "\n",
       "   duration_hours  duration_mins  \n",
       "0               2             50  \n",
       "1               7             25  \n",
       "2              19              0  \n",
       "3               5             25  \n",
       "4               4             45  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Handling categorical data\n",
    "1. nominal data --> data are not in any order then we do onehotencoding\n",
    "2. ordinal data --> data are in order we do labelencoding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Handling Airline column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Jet Airways                          3849\n",
       "IndiGo                               2053\n",
       "Air India                            1751\n",
       "Multiple carriers                    1196\n",
       "SpiceJet                              818\n",
       "Vistara                               479\n",
       "Air Asia                              319\n",
       "GoAir                                 194\n",
       "Multiple carriers Premium economy      13\n",
       "Jet Airways Business                    6\n",
       "Vistara Premium economy                 3\n",
       "Trujet                                  1\n",
       "Name: Airline, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Airline'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1570d112908>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(y='Price',x='Airline',data=df.sort_values('Price',ascending=False),kind='boxen',height=6,aspect=3)\n",
    "#so it shows that jet airways Business has heighest price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Airline_Air India</th>\n",
       "      <th>Airline_GoAir</th>\n",
       "      <th>Airline_IndiGo</th>\n",
       "      <th>Airline_Jet Airways</th>\n",
       "      <th>Airline_Jet Airways Business</th>\n",
       "      <th>Airline_Multiple carriers</th>\n",
       "      <th>Airline_Multiple carriers Premium economy</th>\n",
       "      <th>Airline_SpiceJet</th>\n",
       "      <th>Airline_Trujet</th>\n",
       "      <th>Airline_Vistara</th>\n",
       "      <th>Airline_Vistara Premium economy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Airline_Air India  Airline_GoAir  Airline_IndiGo  Airline_Jet Airways  \\\n",
       "0                  0              0               1                    0   \n",
       "1                  1              0               0                    0   \n",
       "2                  0              0               0                    1   \n",
       "3                  0              0               1                    0   \n",
       "4                  0              0               1                    0   \n",
       "\n",
       "   Airline_Jet Airways Business  Airline_Multiple carriers  \\\n",
       "0                             0                          0   \n",
       "1                             0                          0   \n",
       "2                             0                          0   \n",
       "3                             0                          0   \n",
       "4                             0                          0   \n",
       "\n",
       "   Airline_Multiple carriers Premium economy  Airline_SpiceJet  \\\n",
       "0                                          0                 0   \n",
       "1                                          0                 0   \n",
       "2                                          0                 0   \n",
       "3                                          0                 0   \n",
       "4                                          0                 0   \n",
       "\n",
       "   Airline_Trujet  Airline_Vistara  Airline_Vistara Premium economy  \n",
       "0               0                0                                0  \n",
       "1               0                0                                0  \n",
       "2               0                0                                0  \n",
       "3               0                0                                0  \n",
       "4               0                0                                0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#airline is nominal categorical data\n",
    "Airline=df[['Airline']]\n",
    "Airline=pd.get_dummies(Airline,drop_first=True)\n",
    "Airline.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Handling source column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Delhi       4536\n",
       "Kolkata     2871\n",
       "Banglore    2197\n",
       "Mumbai       697\n",
       "Chennai      381\n",
       "Name: Source, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Source'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1570e2ce608>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(y='Price',x='Source',data=df.sort_values('Price',ascending=False),kind='boxen',height=6,aspect=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>Source_Chennai</th>\n",
       "      <th>Source_Delhi</th>\n",
       "      <th>Source_Kolkata</th>\n",
       "      <th>Source_Mumbai</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Source_Chennai  Source_Delhi  Source_Kolkata  Source_Mumbai\n",
       "0               0             0               0              0\n",
       "1               0             0               1              0\n",
       "2               0             1               0              0\n",
       "3               0             0               1              0\n",
       "4               0             0               0              0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Source = df[['Source']]\n",
    "Source=pd.get_dummies(Source,drop_first=True)\n",
    "Source.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Handling destination column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cochin       4536\n",
       "Banglore     2871\n",
       "Delhi        1265\n",
       "New Delhi     932\n",
       "Hyderabad     697\n",
       "Kolkata       381\n",
       "Name: Destination, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Destination'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x157083268c8>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(y='Price',x='Destination',data=df.sort_values('Price',ascending=False),kind='boxen',height=6,aspect=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Destination_Cochin</th>\n",
       "      <th>Destination_Delhi</th>\n",
       "      <th>Destination_Hyderabad</th>\n",
       "      <th>Destination_Kolkata</th>\n",
       "      <th>Destination_New Delhi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Destination_Cochin  Destination_Delhi  Destination_Hyderabad  \\\n",
       "0                   0                  0                      0   \n",
       "1                   0                  0                      0   \n",
       "2                   1                  0                      0   \n",
       "3                   0                  0                      0   \n",
       "4                   0                  0                      0   \n",
       "\n",
       "   Destination_Kolkata  Destination_New Delhi  \n",
       "0                    0                      1  \n",
       "1                    0                      0  \n",
       "2                    0                      0  \n",
       "3                    0                      0  \n",
       "4                    0                      1  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Destination = df[['Destination']]\n",
    "Destination=pd.get_dummies(Destination,drop_first=True)\n",
    "Destination.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Handling Route and total_stops column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                    BLR → DEL\n",
       "1        CCU → IXR → BBI → BLR\n",
       "2        DEL → LKO → BOM → COK\n",
       "3              CCU → NAG → BLR\n",
       "4              BLR → NAG → DEL\n",
       "                 ...          \n",
       "10678                CCU → BLR\n",
       "10679                CCU → BLR\n",
       "10680                BLR → DEL\n",
       "10681                BLR → DEL\n",
       "10682    DEL → GOI → BOM → COK\n",
       "Name: Route, Length: 10682, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Route']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Additional_info contains almost no_info so we drop it\n",
    "#route and total_stops are the same as \n",
    "df.drop(['Route','Additional_Info'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1 stop      5625\n",
       "non-stop    3491\n",
       "2 stops     1520\n",
       "3 stops       45\n",
       "4 stops        1\n",
       "Name: Total_Stops, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Total_Stops'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Price</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>A_hour</th>\n",
       "      <th>A_min</th>\n",
       "      <th>duration_hours</th>\n",
       "      <th>duration_mins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>3897</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Air India</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>7662</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>13882</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>6218</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>13302</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Airline    Source Destination Total_Stops  Price  j_day  j_month  \\\n",
       "0       IndiGo  Banglore   New Delhi    non-stop   3897     24        3   \n",
       "1    Air India   Kolkata    Banglore     2 stops   7662      1        5   \n",
       "2  Jet Airways     Delhi      Cochin     2 stops  13882      9        6   \n",
       "3       IndiGo   Kolkata    Banglore      1 stop   6218     12        5   \n",
       "4       IndiGo  Banglore   New Delhi      1 stop  13302      1        3   \n",
       "\n",
       "   d_hour  d_min  A_hour  A_min  duration_hours  duration_mins  \n",
       "0      22     20       1     10               2             50  \n",
       "1       5     50      13     15               7             25  \n",
       "2       9     25       4     25              19              0  \n",
       "3      18      5      23     30               5             25  \n",
       "4      16     50      21     35               4             45  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.replace({'non-stop':0,'1 stop':1,'2 stops':2,'3 stops':3,'4 stops':4},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "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_Stops</th>\n",
       "      <th>Price</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>A_hour</th>\n",
       "      <th>A_min</th>\n",
       "      <th>duration_hours</th>\n",
       "      <th>duration_mins</th>\n",
       "      <th>...</th>\n",
       "      <th>Airline_Vistara Premium economy</th>\n",
       "      <th>Source_Chennai</th>\n",
       "      <th>Source_Delhi</th>\n",
       "      <th>Source_Kolkata</th>\n",
       "      <th>Source_Mumbai</th>\n",
       "      <th>Destination_Cochin</th>\n",
       "      <th>Destination_Delhi</th>\n",
       "      <th>Destination_Hyderabad</th>\n",
       "      <th>Destination_Kolkata</th>\n",
       "      <th>Destination_New Delhi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3897</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>7662</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>13882</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>6218</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>13302</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total_Stops  Price  j_day  j_month  d_hour  d_min  A_hour  A_min  \\\n",
       "0            0   3897     24        3      22     20       1     10   \n",
       "1            2   7662      1        5       5     50      13     15   \n",
       "2            2  13882      9        6       9     25       4     25   \n",
       "3            1   6218     12        5      18      5      23     30   \n",
       "4            1  13302      1        3      16     50      21     35   \n",
       "\n",
       "   duration_hours  duration_mins  ...  Airline_Vistara Premium economy  \\\n",
       "0               2             50  ...                                0   \n",
       "1               7             25  ...                                0   \n",
       "2              19              0  ...                                0   \n",
       "3               5             25  ...                                0   \n",
       "4               4             45  ...                                0   \n",
       "\n",
       "   Source_Chennai  Source_Delhi  Source_Kolkata  Source_Mumbai  \\\n",
       "0               0             0               0              0   \n",
       "1               0             0               1              0   \n",
       "2               0             1               0              0   \n",
       "3               0             0               1              0   \n",
       "4               0             0               0              0   \n",
       "\n",
       "   Destination_Cochin  Destination_Delhi  Destination_Hyderabad  \\\n",
       "0                   0                  0                      0   \n",
       "1                   0                  0                      0   \n",
       "2                   1                  0                      0   \n",
       "3                   0                  0                      0   \n",
       "4                   0                  0                      0   \n",
       "\n",
       "   Destination_Kolkata  Destination_New Delhi  \n",
       "0                    0                      1  \n",
       "1                    0                      0  \n",
       "2                    0                      0  \n",
       "3                    0                      0  \n",
       "4                    0                      1  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df,Airline,Source,Destination],axis=1)\n",
    "df.drop(['Airline','Source','Destination'],axis=1,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Airline</th>\n",
       "      <th>Date_of_Journey</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Dep_Time</th>\n",
       "      <th>Arrival_Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>6/06/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>17:30</td>\n",
       "      <td>04:25 07 Jun</td>\n",
       "      <td>10h 55m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>12/05/2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → MAA → BLR</td>\n",
       "      <td>06:20</td>\n",
       "      <td>10:20</td>\n",
       "      <td>4h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>21/05/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>19:15</td>\n",
       "      <td>19:00 22 May</td>\n",
       "      <td>23h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>21/05/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>08:00</td>\n",
       "      <td>21:00</td>\n",
       "      <td>13h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Air Asia</td>\n",
       "      <td>24/06/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>23:55</td>\n",
       "      <td>02:45 25 Jun</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Airline Date_of_Journey    Source Destination            Route  \\\n",
       "0        Jet Airways       6/06/2019     Delhi      Cochin  DEL → BOM → COK   \n",
       "1             IndiGo      12/05/2019   Kolkata    Banglore  CCU → MAA → BLR   \n",
       "2        Jet Airways      21/05/2019     Delhi      Cochin  DEL → BOM → COK   \n",
       "3  Multiple carriers      21/05/2019     Delhi      Cochin  DEL → BOM → COK   \n",
       "4           Air Asia      24/06/2019  Banglore       Delhi        BLR → DEL   \n",
       "\n",
       "  Dep_Time  Arrival_Time Duration Total_Stops              Additional_Info  \n",
       "0    17:30  04:25 07 Jun  10h 55m      1 stop                      No info  \n",
       "1    06:20         10:20       4h      1 stop                      No info  \n",
       "2    19:15  19:00 22 May  23h 45m      1 stop  In-flight meal not included  \n",
       "3    08:00         21:00      13h      1 stop                      No info  \n",
       "4    23:55  02:45 25 Jun   2h 50m    non-stop                      No info  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_excel('G:\\DATA SCIENCE\\MACHINE LEARNING\\Projects\\Flight Fare Prediction\\Test_set.xlsx')\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Airline            0\n",
       "Date_of_Journey    0\n",
       "Source             0\n",
       "Destination        0\n",
       "Route              0\n",
       "Dep_Time           0\n",
       "Arrival_Time       0\n",
       "Duration           0\n",
       "Total_Stops        0\n",
       "Additional_Info    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.dropna(inplace=True)\n",
    "df1.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Dep_Time</th>\n",
       "      <th>Arrival_Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>17:30</td>\n",
       "      <td>04:25 07 Jun</td>\n",
       "      <td>10h 55m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → MAA → BLR</td>\n",
       "      <td>06:20</td>\n",
       "      <td>10:20</td>\n",
       "      <td>4h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>19:15</td>\n",
       "      <td>19:00 22 May</td>\n",
       "      <td>23h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>08:00</td>\n",
       "      <td>21:00</td>\n",
       "      <td>13h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Air Asia</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>23:55</td>\n",
       "      <td>02:45 25 Jun</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Airline    Source Destination            Route Dep_Time  \\\n",
       "0        Jet Airways     Delhi      Cochin  DEL → BOM → COK    17:30   \n",
       "1             IndiGo   Kolkata    Banglore  CCU → MAA → BLR    06:20   \n",
       "2        Jet Airways     Delhi      Cochin  DEL → BOM → COK    19:15   \n",
       "3  Multiple carriers     Delhi      Cochin  DEL → BOM → COK    08:00   \n",
       "4           Air Asia  Banglore       Delhi        BLR → DEL    23:55   \n",
       "\n",
       "   Arrival_Time Duration Total_Stops              Additional_Info  j_day  \\\n",
       "0  04:25 07 Jun  10h 55m      1 stop                      No info      6   \n",
       "1         10:20       4h      1 stop                      No info     12   \n",
       "2  19:00 22 May  23h 45m      1 stop  In-flight meal not included     21   \n",
       "3         21:00      13h      1 stop                      No info     21   \n",
       "4  02:45 25 Jun   2h 50m    non-stop                      No info     24   \n",
       "\n",
       "   j_month  \n",
       "0        6  \n",
       "1        5  \n",
       "2        5  \n",
       "3        5  \n",
       "4        6  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['j_day']=pd.to_datetime(df1.Date_of_Journey,format='%d/%m/%Y').dt.day\n",
    "df1['j_month']=pd.to_datetime(df1.Date_of_Journey,format='%d/%m/%Y').dt.month\n",
    "df1.drop(['Date_of_Journey'],axis=1,inplace=True)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Arrival_Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>04:25 07 Jun</td>\n",
       "      <td>10h 55m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → MAA → BLR</td>\n",
       "      <td>10:20</td>\n",
       "      <td>4h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>19:00 22 May</td>\n",
       "      <td>23h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>21:00</td>\n",
       "      <td>13h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Air Asia</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>02:45 25 Jun</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Airline    Source Destination            Route  Arrival_Time  \\\n",
       "0        Jet Airways     Delhi      Cochin  DEL → BOM → COK  04:25 07 Jun   \n",
       "1             IndiGo   Kolkata    Banglore  CCU → MAA → BLR         10:20   \n",
       "2        Jet Airways     Delhi      Cochin  DEL → BOM → COK  19:00 22 May   \n",
       "3  Multiple carriers     Delhi      Cochin  DEL → BOM → COK         21:00   \n",
       "4           Air Asia  Banglore       Delhi        BLR → DEL  02:45 25 Jun   \n",
       "\n",
       "  Duration Total_Stops              Additional_Info  j_day  j_month  d_hour  \\\n",
       "0  10h 55m      1 stop                      No info      6        6      17   \n",
       "1       4h      1 stop                      No info     12        5       6   \n",
       "2  23h 45m      1 stop  In-flight meal not included     21        5      19   \n",
       "3      13h      1 stop                      No info     21        5       8   \n",
       "4   2h 50m    non-stop                      No info     24        6      23   \n",
       "\n",
       "   d_min  \n",
       "0     30  \n",
       "1     20  \n",
       "2     15  \n",
       "3      0  \n",
       "4     55  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['d_hour']=pd.to_datetime(df1['Dep_Time']).dt.hour\n",
    "df1['d_min']=pd.to_datetime(df1['Dep_Time']).dt.minute\n",
    "df1.drop(['Dep_Time'],axis=1,inplace=True)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Route</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>Additional_Info</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>a_hour</th>\n",
       "      <th>a_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>10h 55m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → MAA → BLR</td>\n",
       "      <td>4h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>23h 45m</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>13h</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Air Asia</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>2h 50m</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Airline    Source Destination            Route Duration  \\\n",
       "0        Jet Airways     Delhi      Cochin  DEL → BOM → COK  10h 55m   \n",
       "1             IndiGo   Kolkata    Banglore  CCU → MAA → BLR       4h   \n",
       "2        Jet Airways     Delhi      Cochin  DEL → BOM → COK  23h 45m   \n",
       "3  Multiple carriers     Delhi      Cochin  DEL → BOM → COK      13h   \n",
       "4           Air Asia  Banglore       Delhi        BLR → DEL   2h 50m   \n",
       "\n",
       "  Total_Stops              Additional_Info  j_day  j_month  d_hour  d_min  \\\n",
       "0      1 stop                      No info      6        6      17     30   \n",
       "1      1 stop                      No info     12        5       6     20   \n",
       "2      1 stop  In-flight meal not included     21        5      19     15   \n",
       "3      1 stop                      No info     21        5       8      0   \n",
       "4    non-stop                      No info     24        6      23     55   \n",
       "\n",
       "   a_hour  a_min  \n",
       "0       4     25  \n",
       "1      10     20  \n",
       "2      19      0  \n",
       "3      21      0  \n",
       "4       2     45  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['a_hour']=pd.to_datetime(df1['Arrival_Time']).dt.hour\n",
    "df1['a_min']=pd.to_datetime(df1['Arrival_Time']).dt.minute\n",
    "df1.drop(['Arrival_Time'],axis=1,inplace=True)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "duration = list(df1[\"Duration\"])\n",
    "\n",
    "for i in range(len(duration)):\n",
    "    if len(duration[i].split()) != 2:    \n",
    "        if \"h\" in duration[i]:\n",
    "            duration[i] = duration[i].strip() + \" 0m\"   # Adds 0 minute\n",
    "        else:\n",
    "            duration[i] = \"0h \" + duration[i]           # Adds 0 hour\n",
    "\n",
    "duration_hours = []\n",
    "duration_mins = []\n",
    "for i in range(len(duration)):\n",
    "    duration_hours.append(int(duration[i].split(sep = \"h\")[0]))    # Extract hours from duration\n",
    "    duration_mins.append(int(duration[i].split(sep = \"m\")[0].split()[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['duration_hours'] = duration_hours\n",
    "df1['duration_mins'] = duration_mins\n",
    "df1.drop('Duration',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Airline_Air India</th>\n",
       "      <th>Airline_GoAir</th>\n",
       "      <th>Airline_IndiGo</th>\n",
       "      <th>Airline_Jet Airways</th>\n",
       "      <th>Airline_Jet Airways Business</th>\n",
       "      <th>Airline_Multiple carriers</th>\n",
       "      <th>Airline_Multiple carriers Premium economy</th>\n",
       "      <th>Airline_SpiceJet</th>\n",
       "      <th>Airline_Vistara</th>\n",
       "      <th>Airline_Vistara Premium economy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Airline_Air India  Airline_GoAir  Airline_IndiGo  Airline_Jet Airways  \\\n",
       "0                  0              0               0                    1   \n",
       "1                  0              0               1                    0   \n",
       "2                  0              0               0                    1   \n",
       "3                  0              0               0                    0   \n",
       "4                  0              0               0                    0   \n",
       "\n",
       "   Airline_Jet Airways Business  Airline_Multiple carriers  \\\n",
       "0                             0                          0   \n",
       "1                             0                          0   \n",
       "2                             0                          0   \n",
       "3                             0                          1   \n",
       "4                             0                          0   \n",
       "\n",
       "   Airline_Multiple carriers Premium economy  Airline_SpiceJet  \\\n",
       "0                                          0                 0   \n",
       "1                                          0                 0   \n",
       "2                                          0                 0   \n",
       "3                                          0                 0   \n",
       "4                                          0                 0   \n",
       "\n",
       "   Airline_Vistara  Airline_Vistara Premium economy  \n",
       "0                0                                0  \n",
       "1                0                                0  \n",
       "2                0                                0  \n",
       "3                0                                0  \n",
       "4                0                                0  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Airline=df1[['Airline']]\n",
    "Airline=pd.get_dummies(Airline,drop_first=True)\n",
    "Airline.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Source_Chennai</th>\n",
       "      <th>Source_Delhi</th>\n",
       "      <th>Source_Kolkata</th>\n",
       "      <th>Source_Mumbai</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Source_Chennai  Source_Delhi  Source_Kolkata  Source_Mumbai\n",
       "0               0             1               0              0\n",
       "1               0             0               1              0\n",
       "2               0             1               0              0\n",
       "3               0             1               0              0\n",
       "4               0             0               0              0"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Source = df1[['Source']]\n",
    "Source=pd.get_dummies(Source,drop_first=True)\n",
    "Source.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Destination_Cochin</th>\n",
       "      <th>Destination_Delhi</th>\n",
       "      <th>Destination_Hyderabad</th>\n",
       "      <th>Destination_Kolkata</th>\n",
       "      <th>Destination_New Delhi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Destination_Cochin  Destination_Delhi  Destination_Hyderabad  \\\n",
       "0                   1                  0                      0   \n",
       "1                   0                  0                      0   \n",
       "2                   1                  0                      0   \n",
       "3                   1                  0                      0   \n",
       "4                   0                  1                      0   \n",
       "\n",
       "   Destination_Kolkata  Destination_New Delhi  \n",
       "0                    0                      0  \n",
       "1                    0                      0  \n",
       "2                    0                      0  \n",
       "3                    0                      0  \n",
       "4                    0                      0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Destination = df1[['Destination']]\n",
    "Destination=pd.get_dummies(Destination,drop_first=True)\n",
    "Destination.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>Airline</th>\n",
       "      <th>Source</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Total_Stops</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>a_hour</th>\n",
       "      <th>a_min</th>\n",
       "      <th>duration_hours</th>\n",
       "      <th>duration_mins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IndiGo</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Air Asia</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Airline    Source Destination Total_Stops  j_day  j_month  \\\n",
       "0        Jet Airways     Delhi      Cochin      1 stop      6        6   \n",
       "1             IndiGo   Kolkata    Banglore      1 stop     12        5   \n",
       "2        Jet Airways     Delhi      Cochin      1 stop     21        5   \n",
       "3  Multiple carriers     Delhi      Cochin      1 stop     21        5   \n",
       "4           Air Asia  Banglore       Delhi    non-stop     24        6   \n",
       "\n",
       "   d_hour  d_min  a_hour  a_min  duration_hours  duration_mins  \n",
       "0      17     30       4     25              10             55  \n",
       "1       6     20      10     20               4              0  \n",
       "2      19     15      19      0              23             45  \n",
       "3       8      0      21      0              13              0  \n",
       "4      23     55       2     45               2             50  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.drop(['Route','Additional_Info'],axis=1,inplace=True)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.replace({'non-stop':0,'1 stop':1,'2 stops':2,'3 stops':3,'4 stops':4},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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_Stops</th>\n",
       "      <th>j_day</th>\n",
       "      <th>j_month</th>\n",
       "      <th>d_hour</th>\n",
       "      <th>d_min</th>\n",
       "      <th>a_hour</th>\n",
       "      <th>a_min</th>\n",
       "      <th>duration_hours</th>\n",
       "      <th>duration_mins</th>\n",
       "      <th>Airline_Air India</th>\n",
       "      <th>...</th>\n",
       "      <th>Airline_Vistara Premium economy</th>\n",
       "      <th>Source_Chennai</th>\n",
       "      <th>Source_Delhi</th>\n",
       "      <th>Source_Kolkata</th>\n",
       "      <th>Source_Mumbai</th>\n",
       "      <th>Destination_Cochin</th>\n",
       "      <th>Destination_Delhi</th>\n",
       "      <th>Destination_Hyderabad</th>\n",
       "      <th>Destination_Kolkata</th>\n",
       "      <th>Destination_New Delhi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Total_Stops  j_day  j_month  d_hour  d_min  a_hour  a_min  duration_hours  \\\n",
       "0            1      6        6      17     30       4     25              10   \n",
       "1            1     12        5       6     20      10     20               4   \n",
       "2            1     21        5      19     15      19      0              23   \n",
       "3            1     21        5       8      0      21      0              13   \n",
       "4            0     24        6      23     55       2     45               2   \n",
       "\n",
       "   duration_mins  Airline_Air India  ...  Airline_Vistara Premium economy  \\\n",
       "0             55                  0  ...                                0   \n",
       "1              0                  0  ...                                0   \n",
       "2             45                  0  ...                                0   \n",
       "3              0                  0  ...                                0   \n",
       "4             50                  0  ...                                0   \n",
       "\n",
       "   Source_Chennai  Source_Delhi  Source_Kolkata  Source_Mumbai  \\\n",
       "0               0             1               0              0   \n",
       "1               0             0               1              0   \n",
       "2               0             1               0              0   \n",
       "3               0             1               0              0   \n",
       "4               0             0               0              0   \n",
       "\n",
       "   Destination_Cochin  Destination_Delhi  Destination_Hyderabad  \\\n",
       "0                   1                  0                      0   \n",
       "1                   0                  0                      0   \n",
       "2                   1                  0                      0   \n",
       "3                   1                  0                      0   \n",
       "4                   0                  1                      0   \n",
       "\n",
       "   Destination_Kolkata  Destination_New Delhi  \n",
       "0                    0                      0  \n",
       "1                    0                      0  \n",
       "2                    0                      0  \n",
       "3                    0                      0  \n",
       "4                    0                      0  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.concat([df1,Airline,Source,Destination],axis=1)\n",
    "df1.drop(['Airline','Source','Destination'],axis=1,inplace=True)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Total_Stops', 'Price', 'j_day', 'j_month', 'd_hour', 'd_min', 'A_hour',\n",
       "       'A_min', 'duration_hours', 'duration_mins', 'Airline_Air India',\n",
       "       'Airline_GoAir', 'Airline_IndiGo', 'Airline_Jet Airways',\n",
       "       'Airline_Jet Airways Business', 'Airline_Multiple carriers',\n",
       "       'Airline_Multiple carriers Premium economy', 'Airline_SpiceJet',\n",
       "       'Airline_Trujet', 'Airline_Vistara', 'Airline_Vistara Premium economy',\n",
       "       'Source_Chennai', 'Source_Delhi', 'Source_Kolkata', 'Source_Mumbai',\n",
       "       'Destination_Cochin', 'Destination_Delhi', 'Destination_Hyderabad',\n",
       "       'Destination_Kolkata', 'Destination_New Delhi'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop('Price',axis=1)\n",
    "Y = df['Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "sns.heatmap(df.corr(),annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\n",
       "                    max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "                    max_samples=None, min_impurity_decrease=0.0,\n",
       "                    min_impurity_split=None, min_samples_leaf=1,\n",
       "                    min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "                    n_estimators=100, n_jobs=None, oob_score=False,\n",
       "                    random_state=None, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import ExtraTreesRegressor\n",
    "sl = ExtraTreesRegressor()\n",
    "sl.fit(X,Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.24533499e-01, 1.44403525e-01, 5.28127134e-02, 2.31608101e-02,\n",
       "       2.10855287e-02, 2.87999616e-02, 1.89690724e-02, 1.21633080e-01,\n",
       "       1.77967166e-02, 1.09020162e-02, 2.08093968e-03, 1.80652975e-02,\n",
       "       1.41245295e-01, 6.71752838e-02, 1.73942555e-02, 8.52286279e-04,\n",
       "       3.25193967e-03, 1.01714673e-04, 5.36426905e-03, 8.83534917e-05,\n",
       "       5.36754101e-04, 1.48179153e-02, 3.52375226e-03, 6.15756184e-03,\n",
       "       7.45060010e-03, 1.51487661e-02, 7.30853447e-03, 5.90919665e-04,\n",
       "       2.47486382e-02])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sl.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,9))\n",
    "imp = pd.Series(sl.feature_importances_,index=X.columns)\n",
    "imp.nlargest(20).plot(kind='barh')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_test,Y_train,Y_test = train_test_split(X,Y,test_size=0.2,random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n",
       "                      max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "                      max_samples=None, min_impurity_decrease=0.0,\n",
       "                      min_impurity_split=None, min_samples_leaf=1,\n",
       "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "                      n_estimators=100, n_jobs=None, oob_score=False,\n",
       "                      random_state=None, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "rf = RandomForestRegressor()\n",
    "rf.fit(X_train,Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = rf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9558489253068194"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf.score(X_train,Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8009959673422774"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf.score(X_test,Y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1571072f0c8>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(Y_test-y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "(unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \\UXXXXXXXX escape (<ipython-input-65-e9d5298961e9>, line 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-65-e9d5298961e9>\"\u001b[1;36m, line \u001b[1;32m2\u001b[0m\n\u001b[1;33m    with open('C:\\Users\\Gitesh\\DATA SCIENCE\\MACHINE_LEARNING\\PROJECTS\\Flight fare prediction\\model','wb') as file:\u001b[0m\n\u001b[1;37m             ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \\UXXXXXXXX escape\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "with open('C:\\Users\\Gitesh\\DATA SCIENCE\\MACHINE_LEARNING\\PROJECTS\\Flight fare prediction\\model','wb') as file:\n",
    "    pickle.dump(rf,file)"
   ]
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}