Project4@Flight_Data_Representation_MachineLearning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*******Flight_Data_Project********\n"
     ]
    }
   ],
   "source": [
    "print('*******Flight_Data_Project********')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sklearn\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import preprocessing\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import metrics\n",
    "import seaborn as sn\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import re\n",
    "%matplotlib inline\n",
    "from sklearn import model_selection, preprocessing, naive_bayes,metrics\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10683, 11)\n"
     ]
    }
   ],
   "source": [
    "df_flights = pd.read_csv('/Users/jaswanthjerripothula/Downloads/flights_data.csv')\n",
    "print(df_flights.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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(minutes)</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>170</td>\n",
       "      <td>0</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>445</td>\n",
       "      <td>2</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>1140</td>\n",
       "      <td>2</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>325</td>\n",
       "      <td>1</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>285</td>\n",
       "      <td>1</td>\n",
       "      <td>No info</td>\n",
       "      <td>13302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>SpiceJet</td>\n",
       "      <td>24/06/2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → BLR</td>\n",
       "      <td>09:00</td>\n",
       "      <td>11:25</td>\n",
       "      <td>145</td>\n",
       "      <td>0</td>\n",
       "      <td>No info</td>\n",
       "      <td>3873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>12/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → BOM → DEL</td>\n",
       "      <td>18:55</td>\n",
       "      <td>10:25 13 Mar</td>\n",
       "      <td>930</td>\n",
       "      <td>1</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>11087d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>01/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → BOM → DEL</td>\n",
       "      <td>08:00</td>\n",
       "      <td>05:05 02 Mar</td>\n",
       "      <td>1265</td>\n",
       "      <td>1</td>\n",
       "      <td>No info</td>\n",
       "      <td>22270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>12/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → BOM → DEL</td>\n",
       "      <td>08:55</td>\n",
       "      <td>10:25 13 Mar</td>\n",
       "      <td>1530</td>\n",
       "      <td>1</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>11087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>27/05/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>11:25</td>\n",
       "      <td>19:15</td>\n",
       "      <td>470</td>\n",
       "      <td>1</td>\n",
       "      <td>No info</td>\n",
       "      <td>8625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Air India</td>\n",
       "      <td>1/06/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BLR → COK</td>\n",
       "      <td>09:45</td>\n",
       "      <td>23:00</td>\n",
       "      <td>795</td>\n",
       "      <td>1</td>\n",
       "      <td>No info</td>\n",
       "      <td>8907</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Airline Date_of_Journey    Source Destination  \\\n",
       "0              IndiGo      24/03/2019  Banglore   New Delhi   \n",
       "1           Air India       1/05/2019   Kolkata    Banglore   \n",
       "2         Jet Airways       9/06/2019     Delhi      Cochin   \n",
       "3              IndiGo      12/05/2019   Kolkata    Banglore   \n",
       "4              IndiGo      01/03/2019  Banglore   New Delhi   \n",
       "5            SpiceJet      24/06/2019   Kolkata    Banglore   \n",
       "6         Jet Airways      12/03/2019  Banglore   New Delhi   \n",
       "7         Jet Airways      01/03/2019  Banglore   New Delhi   \n",
       "8         Jet Airways      12/03/2019  Banglore   New Delhi   \n",
       "9   Multiple carriers      27/05/2019     Delhi      Cochin   \n",
       "10          Air India       1/06/2019     Delhi      Cochin   \n",
       "\n",
       "                    Route Dep_Time  Arrival_Time  Duration(minutes)  \\\n",
       "0               BLR → DEL    22:20  01:10 22 Mar                170   \n",
       "1   CCU → IXR → BBI → BLR    05:50         13:15                445   \n",
       "2   DEL → LKO → BOM → COK    09:25  04:25 10 Jun               1140   \n",
       "3         CCU → NAG → BLR    18:05         23:30                325   \n",
       "4         BLR → NAG → DEL    16:50         21:35                285   \n",
       "5               CCU → BLR    09:00         11:25                145   \n",
       "6         BLR → BOM → DEL    18:55  10:25 13 Mar                930   \n",
       "7         BLR → BOM → DEL    08:00  05:05 02 Mar               1265   \n",
       "8         BLR → BOM → DEL    08:55  10:25 13 Mar               1530   \n",
       "9         DEL → BOM → COK    11:25         19:15                470   \n",
       "10        DEL → BLR → COK    09:45         23:00                795   \n",
       "\n",
       "   Total_Stops              Additional_Info   Price  \n",
       "0            0                      No info    3897  \n",
       "1            2                      No info    7662  \n",
       "2            2                      No info   13882  \n",
       "3            1                      No info    6218  \n",
       "4            1                      No info   13302  \n",
       "5            0                      No info    3873  \n",
       "6            1  In-flight meal not included  11087d  \n",
       "7            1                      No info   22270  \n",
       "8            1  In-flight meal not included   11087  \n",
       "9            1                      No info    8625  \n",
       "10           1                      No info    8907  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_flights.head(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</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(minutes)</th>\n",
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       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10672</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>27/06/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → AMD → BOM → COK</td>\n",
       "      <td>23:05</td>\n",
       "      <td>19:00 28 Jun</td>\n",
       "      <td>1195</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>11150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10673</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>27/05/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → AMD → BOM → COK</td>\n",
       "      <td>13:25</td>\n",
       "      <td>04:25 28 May</td>\n",
       "      <td>900</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>16704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10674</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>12/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → BOM → DEL</td>\n",
       "      <td>20:35</td>\n",
       "      <td>21:20 13 Mar</td>\n",
       "      <td>1485</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>In-flight meal not included</td>\n",
       "      <td>11087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10675</th>\n",
       "      <td>Air India</td>\n",
       "      <td>9/06/2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>BOM → HYD</td>\n",
       "      <td>06:20</td>\n",
       "      <td>07:40</td>\n",
       "      <td>80</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>3100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10676</th>\n",
       "      <td>Multiple carriers</td>\n",
       "      <td>1/05/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → BOM → COK</td>\n",
       "      <td>10:20</td>\n",
       "      <td>19:00</td>\n",
       "      <td>520</td>\n",
       "      <td>1 stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>9794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10677</th>\n",
       "      <td>SpiceJet</td>\n",
       "      <td>21/05/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>05:55</td>\n",
       "      <td>08:35</td>\n",
       "      <td>160</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No check-in baggage included</td>\n",
       "      <td>3257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10678</th>\n",
       "      <td>Air Asia</td>\n",
       "      <td>9/04/2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → BLR</td>\n",
       "      <td>19:55</td>\n",
       "      <td>22:25</td>\n",
       "      <td>150</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>4107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10679</th>\n",
       "      <td>Air India</td>\n",
       "      <td>27/04/2019</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>CCU → BLR</td>\n",
       "      <td>20:45</td>\n",
       "      <td>23:20</td>\n",
       "      <td>155</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>4145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10680</th>\n",
       "      <td>Jet Airways</td>\n",
       "      <td>27/04/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>08:20</td>\n",
       "      <td>11:20</td>\n",
       "      <td>180</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>7229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10681</th>\n",
       "      <td>Vistara</td>\n",
       "      <td>01/03/2019</td>\n",
       "      <td>Banglore</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>BLR → DEL</td>\n",
       "      <td>11:30</td>\n",
       "      <td>14:10</td>\n",
       "      <td>160</td>\n",
       "      <td>non-stop</td>\n",
       "      <td>No info</td>\n",
       "      <td>12648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10682</th>\n",
       "      <td>Air India</td>\n",
       "      <td>9/05/2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>DEL → GOI → BOM → COK</td>\n",
       "      <td>10:55</td>\n",
       "      <td>19:15</td>\n",
       "      <td>500</td>\n",
       "      <td>2 stops</td>\n",
       "      <td>No info</td>\n",
       "      <td>11753</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Airline Date_of_Journey    Source Destination  \\\n",
       "10672        Jet Airways      27/06/2019     Delhi      Cochin   \n",
       "10673        Jet Airways      27/05/2019     Delhi      Cochin   \n",
       "10674        Jet Airways      12/03/2019  Banglore   New Delhi   \n",
       "10675          Air India       9/06/2019    Mumbai   Hyderabad   \n",
       "10676  Multiple carriers       1/05/2019     Delhi      Cochin   \n",
       "10677           SpiceJet      21/05/2019  Banglore       Delhi   \n",
       "10678           Air Asia       9/04/2019   Kolkata    Banglore   \n",
       "10679          Air India      27/04/2019   Kolkata    Banglore   \n",
       "10680        Jet Airways      27/04/2019  Banglore       Delhi   \n",
       "10681            Vistara      01/03/2019  Banglore   New Delhi   \n",
       "10682          Air India       9/05/2019     Delhi      Cochin   \n",
       "\n",
       "                       Route Dep_Time  Arrival_Time  Duration(minutes)  \\\n",
       "10672  DEL → AMD → BOM → COK    23:05  19:00 28 Jun               1195   \n",
       "10673  DEL → AMD → BOM → COK    13:25  04:25 28 May                900   \n",
       "10674        BLR → BOM → DEL    20:35  21:20 13 Mar               1485   \n",
       "10675              BOM → HYD    06:20         07:40                 80   \n",
       "10676        DEL → BOM → COK    10:20         19:00                520   \n",
       "10677              BLR → DEL    05:55         08:35                160   \n",
       "10678              CCU → BLR    19:55         22:25                150   \n",
       "10679              CCU → BLR    20:45         23:20                155   \n",
       "10680              BLR → DEL    08:20         11:20                180   \n",
       "10681              BLR → DEL    11:30         14:10                160   \n",
       "10682  DEL → GOI → BOM → COK    10:55         19:15                500   \n",
       "\n",
       "      Total_Stops               Additional_Info  Price  \n",
       "10672     2 stops   In-flight meal not included  11150  \n",
       "10673     2 stops                       No info  16704  \n",
       "10674      1 stop   In-flight meal not included  11087  \n",
       "10675    non-stop                       No info   3100  \n",
       "10676      1 stop                       No info   9794  \n",
       "10677    non-stop  No check-in baggage included   3257  \n",
       "10678    non-stop                       No info   4107  \n",
       "10679    non-stop                       No info   4145  \n",
       "10680    non-stop                       No info   7229  \n",
       "10681    non-stop                       No info  12648  \n",
       "10682     2 stops                       No info  11753  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_flights.tail(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Airline              10683\n",
       "Date_of_Journey      10683\n",
       "Source               10683\n",
       "Destination          10683\n",
       "Route                10667\n",
       "Dep_Time             10683\n",
       "Arrival_Time         10683\n",
       "Duration(minutes)    10683\n",
       "Total_Stops          10656\n",
       "Additional_Info      10683\n",
       "Price                10683\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_flights.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Duration(minutes)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Airline</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Air Asia</th>\n",
       "      <td>319.0</td>\n",
       "      <td>348.275862</td>\n",
       "      <td>271.237275</td>\n",
       "      <td>150.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>500.00</td>\n",
       "      <td>955.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Air India</th>\n",
       "      <td>1752.0</td>\n",
       "      <td>943.421804</td>\n",
       "      <td>604.195715</td>\n",
       "      <td>75.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>955.0</td>\n",
       "      <td>1440.00</td>\n",
       "      <td>2480.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GoAir</th>\n",
       "      <td>194.0</td>\n",
       "      <td>298.969072</td>\n",
       "      <td>136.836838</td>\n",
       "      <td>155.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>370.00</td>\n",
       "      <td>555.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IndiGo</th>\n",
       "      <td>2053.0</td>\n",
       "      <td>285.406722</td>\n",
       "      <td>218.846252</td>\n",
       "      <td>85.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>320.00</td>\n",
       "      <td>985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jet Airways</th>\n",
       "      <td>3849.0</td>\n",
       "      <td>849.733697</td>\n",
       "      <td>507.925442</td>\n",
       "      <td>80.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>1295.00</td>\n",
       "      <td>2860.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jet Airways Business</th>\n",
       "      <td>6.0</td>\n",
       "      <td>386.666667</td>\n",
       "      <td>96.884811</td>\n",
       "      <td>280.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>475.00</td>\n",
       "      <td>500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Multiple carriers</th>\n",
       "      <td>1196.0</td>\n",
       "      <td>625.769231</td>\n",
       "      <td>156.407344</td>\n",
       "      <td>375.0</td>\n",
       "      <td>480.0</td>\n",
       "      <td>615.0</td>\n",
       "      <td>750.00</td>\n",
       "      <td>935.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Multiple carriers Premium economy</th>\n",
       "      <td>13.0</td>\n",
       "      <td>606.538462</td>\n",
       "      <td>173.893941</td>\n",
       "      <td>395.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>725.00</td>\n",
       "      <td>900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SpiceJet</th>\n",
       "      <td>818.0</td>\n",
       "      <td>178.484108</td>\n",
       "      <td>89.628434</td>\n",
       "      <td>80.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>173.75</td>\n",
       "      <td>520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trujet</th>\n",
       "      <td>1.0</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>195.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>195.00</td>\n",
       "      <td>195.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vistara</th>\n",
       "      <td>479.0</td>\n",
       "      <td>598.413361</td>\n",
       "      <td>553.519349</td>\n",
       "      <td>135.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>972.50</td>\n",
       "      <td>1750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vistara Premium economy</th>\n",
       "      <td>3.0</td>\n",
       "      <td>153.333333</td>\n",
       "      <td>17.559423</td>\n",
       "      <td>135.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>162.50</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Duration(minutes)                          \\\n",
       "                                              count        mean         std   \n",
       "Airline                                                                       \n",
       "Air Asia                                      319.0  348.275862  271.237275   \n",
       "Air India                                    1752.0  943.421804  604.195715   \n",
       "GoAir                                         194.0  298.969072  136.836838   \n",
       "IndiGo                                       2053.0  285.406722  218.846252   \n",
       "Jet Airways                                  3849.0  849.733697  507.925442   \n",
       "Jet Airways Business                            6.0  386.666667   96.884811   \n",
       "Multiple carriers                            1196.0  625.769231  156.407344   \n",
       "Multiple carriers Premium economy              13.0  606.538462  173.893941   \n",
       "SpiceJet                                      818.0  178.484108   89.628434   \n",
       "Trujet                                          1.0  195.000000         NaN   \n",
       "Vistara                                       479.0  598.413361  553.519349   \n",
       "Vistara Premium economy                         3.0  153.333333   17.559423   \n",
       "\n",
       "                                                                         \n",
       "                                     min    25%    50%      75%     max  \n",
       "Airline                                                                  \n",
       "Air Asia                           150.0  155.0  170.0   500.00   955.0  \n",
       "Air India                           75.0  320.0  955.0  1440.00  2480.0  \n",
       "GoAir                              155.0  175.0  310.0   370.00   555.0  \n",
       "IndiGo                              85.0  155.0  175.0   320.00   985.0  \n",
       "Jet Airways                         80.0  435.0  800.0  1295.00  2860.0  \n",
       "Jet Airways Business               280.0  310.0  370.0   475.00   500.0  \n",
       "Multiple carriers                  375.0  480.0  615.0   750.00   935.0  \n",
       "Multiple carriers Premium economy  395.0  440.0  620.0   725.00   900.0  \n",
       "SpiceJet                            80.0  140.0  150.0   173.75   520.0  \n",
       "Trujet                             195.0  195.0  195.0   195.00   195.0  \n",
       "Vistara                            135.0  160.0  190.0   972.50  1750.0  \n",
       "Vistara Premium economy            135.0  145.0  155.0   162.50   170.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_flights.groupby('Airline').describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
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       "      <th>Additional_Info</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Airline</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>Air Asia</th>\n",
       "      <td>319</td>\n",
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       "      <td>318</td>\n",
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       "      <th>Air India</th>\n",
       "      <td>1752</td>\n",
       "      <td>1752</td>\n",
       "      <td>1752</td>\n",
       "      <td>1748</td>\n",
       "      <td>1752</td>\n",
       "      <td>1752</td>\n",
       "      <td>1752</td>\n",
       "      <td>1748</td>\n",
       "      <td>1752</td>\n",
       "      <td>1752</td>\n",
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       "    <tr>\n",
       "      <th>GoAir</th>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>193</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IndiGo</th>\n",
       "      <td>2053</td>\n",
       "      <td>2053</td>\n",
       "      <td>2053</td>\n",
       "      <td>2049</td>\n",
       "      <td>2053</td>\n",
       "      <td>2053</td>\n",
       "      <td>2053</td>\n",
       "      <td>2047</td>\n",
       "      <td>2053</td>\n",
       "      <td>2053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jet Airways</th>\n",
       "      <td>3849</td>\n",
       "      <td>3849</td>\n",
       "      <td>3849</td>\n",
       "      <td>3848</td>\n",
       "      <td>3849</td>\n",
       "      <td>3849</td>\n",
       "      <td>3849</td>\n",
       "      <td>3843</td>\n",
       "      <td>3849</td>\n",
       "      <td>3849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jet Airways Business</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Multiple carriers</th>\n",
       "      <td>1196</td>\n",
       "      <td>1196</td>\n",
       "      <td>1196</td>\n",
       "      <td>1194</td>\n",
       "      <td>1196</td>\n",
       "      <td>1196</td>\n",
       "      <td>1196</td>\n",
       "      <td>1193</td>\n",
       "      <td>1196</td>\n",
       "      <td>1196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Multiple carriers Premium economy</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SpiceJet</th>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "      <td>815</td>\n",
       "      <td>818</td>\n",
       "      <td>818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trujet</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vistara</th>\n",
       "      <td>479</td>\n",
       "      <td>479</td>\n",
       "      <td>479</td>\n",
       "      <td>475</td>\n",
       "      <td>479</td>\n",
       "      <td>479</td>\n",
       "      <td>479</td>\n",
       "      <td>475</td>\n",
       "      <td>479</td>\n",
       "      <td>479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vistara Premium economy</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Date_of_Journey  Source  Destination  \\\n",
       "Airline                                                                   \n",
       "Air Asia                                       319     319          319   \n",
       "Air India                                     1752    1752         1752   \n",
       "GoAir                                          194     194          194   \n",
       "IndiGo                                        2053    2053         2053   \n",
       "Jet Airways                                   3849    3849         3849   \n",
       "Jet Airways Business                             6       6            6   \n",
       "Multiple carriers                             1196    1196         1196   \n",
       "Multiple carriers Premium economy               13      13           13   \n",
       "SpiceJet                                       818     818          818   \n",
       "Trujet                                           1       1            1   \n",
       "Vistara                                        479     479          479   \n",
       "Vistara Premium economy                          3       3            3   \n",
       "\n",
       "                                   Route  Dep_Time  Arrival_Time  \\\n",
       "Airline                                                            \n",
       "Air Asia                             318       319           319   \n",
       "Air India                           1748      1752          1752   \n",
       "GoAir                                194       194           194   \n",
       "IndiGo                              2049      2053          2053   \n",
       "Jet Airways                         3848      3849          3849   \n",
       "Jet Airways Business                   6         6             6   \n",
       "Multiple carriers                   1194      1196          1196   \n",
       "Multiple carriers Premium economy     13        13            13   \n",
       "SpiceJet                             818       818           818   \n",
       "Trujet                                 1         1             1   \n",
       "Vistara                              475       479           479   \n",
       "Vistara Premium economy                3         3             3   \n",
       "\n",
       "                                   Duration(minutes)  Total_Stops  \\\n",
       "Airline                                                             \n",
       "Air Asia                                         319          319   \n",
       "Air India                                       1752         1748   \n",
       "GoAir                                            194          193   \n",
       "IndiGo                                          2053         2047   \n",
       "Jet Airways                                     3849         3843   \n",
       "Jet Airways Business                               6            6   \n",
       "Multiple carriers                               1196         1193   \n",
       "Multiple carriers Premium economy                 13           13   \n",
       "SpiceJet                                         818          815   \n",
       "Trujet                                             1            1   \n",
       "Vistara                                          479          475   \n",
       "Vistara Premium economy                            3            3   \n",
       "\n",
       "                                   Additional_Info  Price  \n",
       "Airline                                                    \n",
       "Air Asia                                       319    319  \n",
       "Air India                                     1752   1752  \n",
       "GoAir                                          194    194  \n",
       "IndiGo                                        2053   2053  \n",
       "Jet Airways                                   3849   3849  \n",
       "Jet Airways Business                             6      6  \n",
       "Multiple carriers                             1196   1196  \n",
       "Multiple carriers Premium economy               13     13  \n",
       "SpiceJet                                       818    818  \n",
       "Trujet                                           1      1  \n",
       "Vistara                                        479    479  \n",
       "Vistara Premium economy                          3      3  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_flights.groupby('Airline').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "category_count = pd.DataFrame()\n",
    "category_count['count'] = df_flights['Airline'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Jet Airways                          3849\n",
       "IndiGo                               2053\n",
       "Air India                            1752\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: count, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_count['count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11]),\n",
       " [Text(0, 0, 'Jet Airways'),\n",
       "  Text(1, 0, 'IndiGo'),\n",
       "  Text(2, 0, 'Air India'),\n",
       "  Text(3, 0, 'Multiple carriers'),\n",
       "  Text(4, 0, 'SpiceJet'),\n",
       "  Text(5, 0, 'Vistara'),\n",
       "  Text(6, 0, 'Air Asia'),\n",
       "  Text(7, 0, 'GoAir'),\n",
       "  Text(8, 0, 'Multiple carriers Premium economy'),\n",
       "  Text(9, 0, 'Jet Airways Business'),\n",
       "  Text(10, 0, 'Vistara Premium economy'),\n",
       "  Text(11, 0, 'Trujet')])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig , ax = plt.subplots(figsize = (14,6))\n",
    "sn.barplot (x = category_count.index , y = category_count['count'],ax = ax)\n",
    "ax.set_ylabel ('Number of Flights',fontsize = 12)\n",
    "ax.set_xlabel ('Airlines',fontsize = 12)\n",
    "ax.tick_params(labelsize = 10)\n",
    "plt.xticks(rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAEGCAYAAACUzrmNAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAZK0lEQVR4nO3df7gkVX3n8fdHQCQCKjKyIwMOblgjv0QZEUUFxSiKCrpqcFWIi8HwoOKq2YBrosZFzboaxR9EdF2HREWCyA8DCzoKui4KM/JjGJCAgoggjIoyokEZvvmjzt1pLvfe6hmm7+1h3q/n6aerTtep/lbdvv3tU6fqVKoKSZJm8qC5DkCSNP5MFpKkXiYLSVIvk4UkqZfJQpLUa9O5DmBUtt1221q4cOFchyFJG5Rly5b9rKrmTS5/wCaLhQsXsnTp0rkOQ5I2KEl+NFW5h6EkSb1MFpKkXiYLSVIvk4UkqZfJQpLUy2QhSeplspAk9TJZSJJ6mSwkSb0esFdwS2tj34/uO9chjMS33/jtuQ5BDxC2LCRJvUwWkqReJgtJUi+ThSSpl8lCktTLZCFJ6mWykCT1MllIknqZLCRJvUwWkqReJgtJUi+ThSSpl8lCktTLZCFJ6mWykCT1MllIknqZLCRJvUwWkqReJgtJUi+ThSSp18iTRZJNklya5CttfpskX01ybXt+xMCyxyW5Lsk1SZ43UL5XkuXttROSZNRxS5LWmI2WxTHA1QPzxwJLqmpnYEmbJ8kuwKHArsCBwCeSbNLqnAgcCezcHgfOQtySpGakySLJAuAg4NMDxQcDi9v0YuCQgfJTququqroeuA7YO8l8YOuquqiqCjh5oI4kaRaMumXxYeC/AvcMlG1XVbcAtOdHtfLtgR8PLHdTK9u+TU8uv48kRyZZmmTpypUr18sGSJJGmCySvBC4raqWDVtlirKaofy+hVUnVdWiqlo0b968Id9WktRn0xGue1/gxUleADwE2DrJPwK3JplfVbe0Q0y3teVvAnYYqL8AuLmVL5iiXJI0S0bWsqiq46pqQVUtpOu4/npVvRo4Czi8LXY4cGabPgs4NMnmSXai68i+uB2qWpVkn3YW1GEDdSRJs2CULYvpvB84NckRwI3AywGqakWSU4GrgLuBo6tqdatzFPBZYAvg3PaQJM2SWUkWVXUBcEGb/jlwwDTLHQ8cP0X5UmC30UUoSZqJV3BLknqZLCRJvUwWkqReJgtJUi+ThSSpl8lCktTLZCFJ6mWykCT1MllIknqZLCRJvUwWkqReJgtJUi+ThSSpl8lCktTLZCFJ6mWykCT1MllIknqZLCRJvUwWkqReJgtJUi+ThSSpl8lCktTLZCFJ6mWykCT1MllIknqZLCRJvXqTRZKXJ9mqTb8jyelJnjT60CRJ42KYlsVfVdWqJE8HngcsBk4cbViSpHEyTLJY3Z4PAk6sqjOBB48uJEnSuBkmWfwkySeBVwDnJNl8yHqSpAeIYb70XwGcBxxYVb8EtgH+YpRBSZLGyzDJ4pNVdXpVXQtQVbcArxltWJKkcTJMsth1cCbJJsBeowlHkjSOpk0WSY5LsgrYI8kd7bEKuA04c9YilCTNuWmTRVW9r6q2Aj5QVVu3x1ZV9ciqOm4WY5QkzbFN+xaoquOSbA88ZnD5qvrmKAOTJI2P3mSR5P3AocBVrLnmogCThSRtJHqTBfAS4HFVddfarDjJQ+gSyubtfU6rqncm2Qb4IrAQuAF4RVXd3uocBxxBl5TeVFXntfK9gM8CWwDnAMdUVa1NPJKkdTfM2VA/BDZbh3XfBTy7qp4A7AkcmGQf4FhgSVXtDCxp8yTZha4FsytwIPCJduYVdMOLHAns3B4HrkM8kqR1NG3LIslH6Q43/Qa4LMkSugQAQFW9aaYVt1/+v26zm7VHAQcD+7fyxcAFwF+28lNaC+b6JNcBeye5Adi6qi5qcZ0MHAKcO/xmSpLuj5kOQy1tz8uAs9Zl5a1lsAz4Q+DjVfXdJNu1C/uoqluSPKotvj3wnYHqN7Wy37fpyeVTvd+RdC0Qdtxxx3UJWZI0hWmTRVUtvr8rr6rVwJ5JHg58OcluMyyeqVYxQ/lU73cScBLAokWL7NOQpPVkmLOhlnPfL+df0bU8/ntV/bxvHVX1yyQX0PU13JpkfmtVzKe7yA+6FsMOA9UWADe38gVTlEuSZskwHdznAv8MvKo9zga+BfyU7gylKSWZ11oUJNkCeA7wfbpDWoe3xQ5nzdXgZwGHJtk8yU50HdkXt0NWq5LskyTAYXgFuSTNqmFOnd23qvYdmF+e5NtVtW+SV89Qbz6wuPVbPAg4taq+kuQi4NQkRwA3Ai8HqKoVSU6lu57jbuDodhgL4CjWnDp7LnZuS9KsGiZZbJnkKVX1XYAkewNbttfunq5SVV0BPHGK8p8DB0xT53jg+CnKlwIz9XdIkkZomGTxOuAzSbak62y+A3hdkocC7xtlcBqtG/9m97kOYSR2/Ovlcx2C9IAzzNhQlwC7J3kYkHYDpAmnjiowSdL4mOmivFdX1T8mecukcgCq6kMjjk2SNCZmalk8tD1vNRuBSJLG10wX5X2yPb979sKRJI2jmQ5DnTBTxb6xoSRJDxwzHYZaNmtRSJLG2kzJ4nNVNe11FJKkjcdMw31cPDHRhiuXJG2kZkoWg6O97jvtUpKkB7yZkoVDfEuSgJn7LP4oyRV0LYx/36Zp81VVe4w8OknSWJgpWTx+1qKQJI21mS7K+9FsBiJJGl/D3PxIkrSRM1lIknpNmyySLGnPfzt74UiSxtFMHdzzk+wHvDjJKdz7uguq6nsjjUySNDZmShZ/DRwLLAAm37uigGePKihJ0niZ6Wyo04DTkvxVVb1nFmOSJI2ZYW6r+p4kLwae2YouqKqvjDYsSdI46T0bKsn7gGOAq9rjmFYmSdpI9LYsgIOAPavqHoAki4FLgeNGGZgkaXwMe53FwwemHzaCOCRJY2yYlsX7gEuTfIPu9NlnYqtCkjYqw3RwfyHJBcCT6ZLFX1bVT0cdmCRpfAzTsqCqbgHOGnEskqQx5dhQkqReJgtJUq8Zk0WSByW5craCkSSNpxmTRbu24vIkO85SPJKkMTRMB/d8YEWSi4E7Jwqr6sUji2qE9vqLk+c6hJFY9oHD5joESQ9gwySLd488CknSWBvmOosLkzwG2LmqvpbkD4BNRh+aJGlcDDOQ4J8BpwGfbEXbA2eMMCZJ0pgZ5tTZo4F9gTsAqupa4FGjDEqSNF6GSRZ3VdXvJmaSbEp3p7wZJdkhyTeSXJ1kRZJjWvk2Sb6a5Nr2/IiBOscluS7JNUmeN1C+V5Ll7bUTkmSq95QkjcYwyeLCJG8Htkjyx8A/AWcPUe9u4K1V9XhgH+DoJLvQ3ap1SVXtDCxp87TXDgV2BQ4EPpFkom/kROBIYOf2OHDI7ZMkrQfDJItjgZXAcuD1wDnAO/oqVdUtVfW9Nr0KuJquv+NgYHFbbDFwSJs+GDilqu6qquuB64C9k8wHtq6qi6qqgJMH6kiSZsEwZ0Pd02549F26w0/XtC/toSVZCDyxrWO7NjAhVXVLkon+j+2B7wxUu6mV/b5NTy6XJM2SYc6GOgj4AXAC8DHguiTPH/YNkmwJfAl4c1XdMdOiU5TVDOVTvdeRSZYmWbpy5cphQ5Qk9RjmMNQHgWdV1f5VtR/wLODvhll5ks3oEsXnqur0VnxrO7REe76tld8E7DBQfQFwcytfMEX5fVTVSVW1qKoWzZs3b5gQJUlDGCZZ3FZV1w3M/5A1X/DTamcs/S/g6qr60MBLZwGHt+nDgTMHyg9NsnmSneg6si9uh6xWJdmnrfOwgTqSpFkwbZ9Fkpe2yRVJzgFOpTv883LgkiHWvS/wGmB5ksta2duB9wOnJjkCuLGtj6pakeRU4Cq6M6mOrqrVrd5RwGeBLYBz20OSNEtm6uB+0cD0rcB+bXol8Ij7Ln5vVfV/mbq/AeCAaeocDxw/RflSYLe+95Qkjca0yaKqXjubgUiSxlfvqbOt/+CNwMLB5TfUIcolSWtvmCHKz6DrqD4buGek0UiSxtIwyeJfq+qEkUciSRpbwySLjyR5J3A+cNdE4cRQHpKkB75hksXudKfAPps1h6GqzUuSNgLDJIuXAI8dHKZckrRxGeYK7suBh484DknSGBumZbEd8P0kl3DvPgtPnZWkjcQwyeKdI49CkjTWhrmfxYWzEYgkaXwNcwX3KtbcP+LBwGbAnVW19SgDkySNj2FaFlsNzic5BNh7VAFJksbPMGdD3UtVnYHXWEjSRmWYw1AvHZh9ELCIaW5rKkl6YBrmbKjB+1rcDdwAHDySaCRJY2mYPgvvayFJG7mZbqv61zPUq6p6zwjikSSNoZlaFndOUfZQ4AjgkYDJQpI2EjPdVvWDE9NJtgKOAV4LnAJ8cLp6kqQHnhn7LJJsA7wFeBWwGHhSVd0+G4FJksbHTH0WHwBeCpwE7F5Vv561qCRJY2Wmi/LeCjwaeAdwc5I72mNVkjtmJzxJ0jiYqc9ira/uliQ9MJkQJEm9TBaSpF4mC0lSL5OFJKmXyUKS1MtkIUnqZbKQJPUyWUiSepksJEm9TBaSpF4mC0lSL5OFJKmXyUKS1GtkySLJZ5LcluTKgbJtknw1ybXt+REDrx2X5Lok1yR53kD5XkmWt9dOSJJRxSxJmtooWxafBQ6cVHYssKSqdgaWtHmS7AIcCuza6nwiySatzonAkcDO7TF5nZKkERtZsqiqbwK/mFR8MN3tWWnPhwyUn1JVd1XV9cB1wN5J5gNbV9VFVVXAyQN1JEmzZLb7LLarqlsA2vOjWvn2wI8HlruplW3fpieXTynJkUmWJlm6cuXK9Rq4JG3MxqWDe6p+iJqhfEpVdVJVLaqqRfPmzVtvwUnSxm62k8Wt7dAS7fm2Vn4TsMPAcguAm1v5ginKJUmzaLaTxVnA4W36cODMgfJDk2yeZCe6juyL26GqVUn2aWdBHTZQR5I0SzYd1YqTfAHYH9g2yU3AO4H3A6cmOQK4EXg5QFWtSHIqcBVwN3B0Va1uqzqK7syqLYBz20OSNItGliyq6pXTvHTANMsfDxw/RflSYLf1GJokaS2NSwe3JGmMmSwkSb1MFpKkXiYLSVIvk4UkqZfJQpLUy2QhSeplspAk9RrZRXmStKH72FvPnusQRuINH3zRWtexZSFJ6mWykCT1MllIknqZLCRJvUwWkqReJgtJUi+ThSSpl8lCktTLZCFJ6mWykCT1MllIknqZLCRJvUwWkqRejjor6V4ufOZ+cx3CSOz3zQvnOoQNmi0LSVIvk4UkqZfJQpLUy2QhSeplspAk9TJZSJJ6mSwkSb1MFpKkXiYLSVIvk4UkqZfJQpLUy2QhSeplspAk9TJZSJJ6bTDJIsmBSa5Jcl2SY+c6HknamGwQySLJJsDHgecDuwCvTLLL3EYlSRuPDSJZAHsD11XVD6vqd8ApwMFzHJMkbTRSVXMdQ68kLwMOrKrXtfnXAE+pqjdMWu5I4Mg2+zjgmlkN9L62BX42xzGMC/fFGu6LNdwXa4zLvnhMVc2bXLih3FY1U5TdJ8tV1UnASaMPZzhJllbVormOYxy4L9ZwX6zhvlhj3PfFhnIY6iZgh4H5BcDNcxSLJG10NpRkcQmwc5KdkjwYOBQ4a45jkqSNxgZxGKqq7k7yBuA8YBPgM1W1Yo7DGsbYHBIbA+6LNdwXa7gv1hjrfbFBdHBLkubWhnIYSpI0h0wWkqReJosmyeoklyW5PMn3kjxtBO+xf5KvrO/1jlqSXw9MvyDJtUl27Ft+bbe3Lb/e9/uoDXx2VrTPz1uSzPi/lWRhkivb9J8m+dg0y52T5OEjCHudJfl3SU5J8oMkV7UYj5zLz3aST8/FqA5JKsk/DMxvmmTl+toXSd6V5G1rWef/rY/3nmyD6OCeJb+tqj0BkjwPeB+w31wGlGTTqrp7LmMYlOQA4KPAc6vqxhG8xf7Ar4GRfNhHaPCz8yjg88DDgHfe3xVX1Qvu7zrWpyQBvgwsrqpDW9mewIvmMq6JC3bnwJ3Abkm2qKrfAn8M/GSOYgGgqkbyg8uWxdS2Bm4HSLJlkiWttbE8ycGtfGGSq5N8qv2iPD/JFu21Jye5IslFST4w8QtyUJJtkpzRlvtOkj1a+buSnJTkfODkJPOSfCnJJe2x7+zthnvF+wzgU8BBVfWDVvaWJFe2x5t76j85yaVJHpvkRUm+2+a/lmS7JAuBPwf+S/uV/oyplhv1dt5fVXUb3SgCb0hnk/YZuKT9rV8/TdVHJ/k/rdX2PyYKk9yQZNtZCX44zwJ+X1V/P1FQVZcB3wK2THJaku8n+VxLLCTZK8mFSZYlOS/J/FZ+QZK/TXJxkn9pn7GJltbp0+yPE5Msbf9z7x4ovyDJXF3Qdi5wUJt+JfCFiRcmtwza/8rC9vh+axFd2fbXc5J8u23z3gPrf0KSr7fyP2vrmfJ7qb32a0ahqnx0Z4StBi4Dvg/8CtirlW8KbN2mtwWuo7uifCFwN7Bne+1U4NVt+krgaW36/cCVbXp/4Ctt+qPAO9v0s4HL2vS7gGXAFm3+88DT2/SOwNVzsG9+D/wC2GOgbC9gOfBQYEtgBfDE9tqvB7cXeFrbph1b+SNYcybe64APDmz72wbeY8rlxu0xsb2Tym4HtqNLHO9oZZsDS4Gd2udn4nPxp8AP6VojDwF+BOzQXrsB2Haut3Fgu94E/N0U5fu3/5sFdD9CLwKeDmxG11Kc15b7E7pT3wEuGPjbvwD42hD7Y5v2vEmrv8fAuhbNxd8e2AM4rcV6Gff+P5/8mb6y/e0X0n1/7N721zLgM3TfLQcDZwzUvxzYgu7758fAo5nme2m6z+P6eHgYao3BQwlPpftVvxvdH++9SZ4J3ANsT/clAHB9db+qoPtjL0x3fHmrqpo4lPJ54IVTvN/Tgf8IUFVfT/LIJA9rr51VXZMW4DnALu1HGsDWSbaqqlX3d4PXwu/p/uGPAI5pZU8HvlxVdwIkOR14BnDppLqPpzt//LlVNXHV/QLgi+0X5oOB66d532GXG0cTf7DnAnukG98Mui/AnYF/mbT8kqr6FUCSq4DH0H0xbEgurqqbAJJcRveF+EtgN+Cr7TO8CXDLQJ3T2/OytvyE6fbHK9KNAbcpMJ9uFOorRrExw6qqK1rL+JXAOWtR9fqqWg6QZAXdNleS5dx7X5zZvg9+m+QbdAOr/jNTfy/99P5uz3RMFlOoqota038e3S+eeXQtjd8nuYHuFwTAXQPVVtNl/6nGsZrKTONd3TlQ9iDgqQPJYy7cA7wC+FqSt1fVexl+O2+h219PZM0QLR8FPlRVZyXZn+7X01SGXW6sJHks3efhNrr99MaqOm/SMgsnVZv8WRrX/80VwMumeW2qbQiwoqqe2lNn8jbfZ11JdgLeBjy5qm5P8lnW/C/OtbOA/0nXqnjkQPnd3Ptw/2C8g9t4z8D8Pdx7X0y+GK6AVzH999JI2GcxhSR/RPcL6Od0vwRva3+QZ9H9wplWVd0OrEqyTys6dJpFv0n3B6d9Ef6squ6YYrnzgf8/um66zsRZV1W/oWshvSrJEXTxH5LkD5I8FHgJ3XHryX5Jdzz3vW07odunE52Ahw8suwrYamB+uuXGVpJ5wN8DH6vumMB5wFFJNmuv/4e2vzZUXwc2nzh2Dl1/FNOfDHINMK+11kmyWZJd1/G9t6b7IfWr1n/1/HVczyh8BvibiZbCgBuAJwEkeRLdIci1dXCShyR5JF0yuoS1/F5aH8b118tc2KI1naH7NXR4Va1O8jng7CRLWdOn0ecI4FNJ7qQ7lvqrKZZ5F/C/k1wB/IbpvwzfBHy8Lbcp3Zf0nw+zQetbVf0iyYEthjcDnwUubi9/uqomH4KaqHdrkhcB5yb5z3Tb/k9JfgJ8hzX/QGcDp7XOujfOsNy4mfjsbEb3S/IfgA+11z5Nd0jhe63DdyVwyOyHuH60wyQvAT6c7o6V/0r3hXjGNMv/rh2CO6EdZt0U+DBdC2Vt3/vyJJe2uj8Evr0u2zAK7fDbR6Z46UvAYe3zcQn3Pfw4jIvpDjvtCLynqm5ex++l+8XhPkYgyZZVNXGtwbHA/Ko6pqeaJI0tWxajcVCS4+j274/ozu6QpA2WLQtJUi87uCVJvUwWkqReJgtJUi+ThbQOkvy3Nj7RFenGsnrKXMckjZJnQ0lrqV1g9kLgSVV1V7va/8H3c51jNcKwNJktC2ntzae74v4ugKr6WbtQ6oB0I+QuT/KZJJvDvUeOTbIoyQVtevIIw9sl+XK6e2JcnnZvjySvTjcy62VJPplkkznZam3UTBbS2jsf2CHdsNqfSLJfkofQXdH+J1W1O12r/agh1rUXcHBV/SfgBODCqnoC3RARK5I8nm6k1n3bQJeracPESLPJZCGtpXZ1/l50w4+vBL4IvJ5uFNGJ4RwWA88cYnWDIww/GzixvcfqNurqAe29LmlDRhwAPHY9bYo0NPsspHVQVavpxv26oA0pPdNAh4Mjj04eGfROZha6u9Idty5xSuuLLQtpLSV5XJKdB4r2BG6lu5/JH7ay1wAXtukb6FoH0O5hMo0ltENX6e6wt3Ure1m627VO3GFx5COMSpOZLKS1tyWwOMlVbTTgXYBjgdfSjZK7nO6eBBO3Hn038JEk36Lrc5jOMcCzWv1lwK5VdRXwDuD89l5fpetgl2aVY0NJknrZspAk9TJZSJJ6mSwkSb1MFpKkXiYLSVIvk4UkqZfJQpLU698AZxHldDq7VKcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.countplot(data = df_flights, x = 'Source')\n",
    "plt.ylabel('Number of Flights',fontsize = 10)\n",
    "plt.xlabel('Source',fontsize = 10)\n",
    "ax.tick_params(labelsize = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1, 2, 3, 4]),\n",
       " [Text(0, 0, 'Banglore'),\n",
       "  Text(1, 0, 'Kolkata'),\n",
       "  Text(2, 0, 'Delhi'),\n",
       "  Text(3, 0, 'Chennai'),\n",
       "  Text(4, 0, 'Mumbai')])"
      ]
     },
     "execution_count": 27,
     "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": [
    "base_color = sn.color_palette()[0]\n",
    "sn.countplot(data = df_flights, x = 'Source', color = base_color)\n",
    "plt.xticks(rotation = 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Source', ylabel='count'>"
      ]
     },
     "execution_count": 28,
     "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": [
    "base_color = sn.color_palette()[1]\n",
    "general_order = df_flights['Source'].value_counts().index\n",
    "sn.countplot(data = df_flights, x = 'Source', color = base_color, order = general_order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11]),\n",
       " [Text(0, 0, 'IndiGo'),\n",
       "  Text(1, 0, 'Air India'),\n",
       "  Text(2, 0, 'Jet Airways'),\n",
       "  Text(3, 0, 'SpiceJet'),\n",
       "  Text(4, 0, 'Multiple carriers'),\n",
       "  Text(5, 0, 'GoAir'),\n",
       "  Text(6, 0, 'Vistara'),\n",
       "  Text(7, 0, 'Air Asia'),\n",
       "  Text(8, 0, 'Vistara Premium economy'),\n",
       "  Text(9, 0, 'Jet Airways Business'),\n",
       "  Text(10, 0, 'Multiple carriers Premium economy'),\n",
       "  Text(11, 0, 'Trujet')])"
      ]
     },
     "execution_count": 38,
     "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": [
    "base_color = sn.color_palette()[2]\n",
    "sn.countplot(data = df_flights, x = 'Airline', color = base_color)\n",
    "plt.xticks(rotation = 270)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11]),\n",
       " [Text(0, 0, 'IndiGo'),\n",
       "  Text(1, 0, 'Air India'),\n",
       "  Text(2, 0, 'Jet Airways'),\n",
       "  Text(3, 0, 'SpiceJet'),\n",
       "  Text(4, 0, 'Multiple carriers'),\n",
       "  Text(5, 0, 'GoAir'),\n",
       "  Text(6, 0, 'Vistara'),\n",
       "  Text(7, 0, 'Air Asia'),\n",
       "  Text(8, 0, 'Vistara Premium economy'),\n",
       "  Text(9, 0, 'Jet Airways Business'),\n",
       "  Text(10, 0, 'Multiple carriers Premium economy'),\n",
       "  Text(11, 0, 'Trujet')])"
      ]
     },
     "execution_count": 40,
     "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": [
    "base_color = sn.color_palette()[3]\n",
    "sn.countplot(data = df_flights, x = 'Airline', color = base_color)\n",
    "plt.xticks(rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Airline               0\n",
       "Date_of_Journey       0\n",
       "Source                0\n",
       "Destination           0\n",
       "Route                16\n",
       "Dep_Time              0\n",
       "Arrival_Time          0\n",
       "Duration(minutes)     0\n",
       "Total_Stops          27\n",
       "Additional_Info       0\n",
       "Price                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_flights.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jaswanthjerripothula/opt/anaconda3/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10]),\n",
       " [Text(0, 0, 'Airline'),\n",
       "  Text(1, 0, 'Date_of_Journey'),\n",
       "  Text(2, 0, 'Source'),\n",
       "  Text(3, 0, 'Destination'),\n",
       "  Text(4, 0, 'Route'),\n",
       "  Text(5, 0, 'Dep_Time'),\n",
       "  Text(6, 0, 'Arrival_Time'),\n",
       "  Text(7, 0, 'Duration(minutes)'),\n",
       "  Text(8, 0, 'Total_Stops'),\n",
       "  Text(9, 0, 'Additional_Info'),\n",
       "  Text(10, 0, 'Price')])"
      ]
     },
     "execution_count": 45,
     "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": [
    "ns_counts = df_flights.isna().sum()\n",
    "base_color = sn.color_palette()[0]\n",
    "sn.barplot(ns_counts.index.values, ns_counts, color = base_color)\n",
    "plt.ylabel('Number of missing values',fontsize = 10)\n",
    "plt.xticks(rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Preprocessing Tweets for removing punctuations(! , '), @ , # , https , special characters\n",
    "def processMessage(tweet):\n",
    "    from string import punctuation\n",
    "    tweet = re.sub(r'\\&\\w*;','',tweet)\n",
    "    tweet = re.sub('@[^\\s]+','',tweet)\n",
    "    tweet = re.sub(r'\\$\\w*','',tweet)\n",
    "    tweet = tweet.lower()\n",
    "    tweet = re.sub(r'https?:\\/\\/.*\\/\\w*','',tweet)\n",
    "    tweet = re.sub(r'#\\w*','',tweet)\n",
    "    tweet = re.sub(r'['+punctuation.replace('@','')+']+','',tweet)\n",
    "    tweet = re.sub(r'\\b\\w{1,2}\\b','',tweet)\n",
    "    tweet = re.sub(r'\\s\\s+',' ',tweet)\n",
    "    tweet = tweet.lstrip(' ')\n",
    "    tweet = ''.join(c for c in tweet if c <= '\\uFFFF')\n",
    "    return tweet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Flight Destination\\n')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sort_counts = df_flights['Destination'].value_counts()\n",
    "plt.pie(sort_counts, labels = sort_counts.index, startangle = 90, counterclock = False);\n",
    "plt.axis('square')\n",
    "plt.title('Flight Destination\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Flight Source\\n')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sort_counts = df_flights['Source'].value_counts()\n",
    "plt.pie(sort_counts, labels = sort_counts.index, startangle = 90, counterclock = False);\n",
    "plt.axis('square')\n",
    "plt.title('Flight Source\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([4.198e+03, 1.988e+03, 1.720e+03, 7.870e+02, 9.310e+02, 8.450e+02,\n",
       "        1.320e+02, 7.000e+01, 1.000e+01, 2.000e+00]),\n",
       " array([  75. ,  353.5,  632. ,  910.5, 1189. , 1467.5, 1746. , 2024.5,\n",
       "        2303. , 2581.5, 2860. ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 60,
     "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": [
    "plt.hist(data = df_flights, x = 'Duration(minutes)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1799., 1775.,  905.,  919.,  545.,  560.,  489.,  361.,  323.,\n",
       "         411.,  265.,  236.,  211.,  202.,  169.,  155.,  139.,  114.,\n",
       "         125.,  113.,  118.,  117.,  102.,   85.,   79.,   83.,   79.,\n",
       "          70.,   71.,   63.]),\n",
       " array([   0. ,   61.6,  123.2,  184.8,  246.4,  308. ,  369.6,  431.2,\n",
       "         492.8,  554.4,  616. ,  677.6,  739.2,  800.8,  862.4,  924. ,\n",
       "         985.6, 1047.2, 1108.8, 1170.4, 1232. , 1293.6, 1355.2, 1416.8,\n",
       "        1478.4, 1540. , 1601.6, 1663.2, 1724.8, 1786.4, 1848. ]),\n",
       " <BarContainer object of 30 artists>)"
      ]
     },
     "execution_count": 65,
     "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": [
    "plt.hist(data = df_flights, x = 'Price', bins = 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Total Stops\\n')"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sort_counts = df_flights['Total_Stops'].value_counts()\n",
    "plt.pie(sort_counts, labels = sort_counts.index, startangle = 90, counterclock = False);\n",
    "plt.axis('square')\n",
    "plt.title('Total Stops\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "********Flight_Data_Project is done successfully**********\n"
     ]
    }
   ],
   "source": [
    "print('********Flight_Data_Project is done successfully**********')"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}