Visualisation_Flight_Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Programing for Data Science project\n",
    "\n",
    "\n",
    "by: Sawan Aich\n",
    "    Shashwata Mandal\n",
    "    Sourav Bhattacharjee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "#PDS PROJECT BDA FIRST SEMESTER PYTHON PORTION\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mp\n",
    "import seaborn as sb\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "from numpy import math\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"working_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>Dest</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>107.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>156.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>349.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>135.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>295.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>297.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>306.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ItinID         MktID  MktCoupons  Quarter Origin  OriginWac  \\\n",
       "0       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "1       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "2       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "3       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "4       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "...              ...           ...         ...      ...    ...        ...   \n",
       "124869  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124870  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124871  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124872  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124873  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "\n",
       "       Dest  DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       DFW       74    936              2                  1             AA   \n",
       "1       DFW       74    936              2                  1             AA   \n",
       "2       DFW       74    936              2                  1             AA   \n",
       "3       DFW       74    936              2                  1             AA   \n",
       "4       DFW       74    936              2                  1             AA   \n",
       "...     ...      ...    ...            ...                ...            ...   \n",
       "124869  LAS       85    226              2                  1             WN   \n",
       "124870  LAS       85    226              2                  1             WN   \n",
       "124871  LAS       85    226              2                  1             WN   \n",
       "124872  LAS       85    226              2                  1             WN   \n",
       "124873  LAS       85    226              2                  1             WN   \n",
       "\n",
       "        PricePerTicket  \n",
       "0               107.80  \n",
       "1               156.44  \n",
       "2               191.18  \n",
       "3               349.66  \n",
       "4               135.13  \n",
       "...                ...  \n",
       "124869          295.50  \n",
       "124870          297.50  \n",
       "124871          306.00  \n",
       "124872          113.28  \n",
       "124873           80.33  \n",
       "\n",
       "[124874 rows x 13 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=df.PricePerTicket.groupby(df.AirlineCompany)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AirlineCompany\n",
       "AA    275.104201\n",
       "AS    149.475873\n",
       "B6    200.927241\n",
       "DL    240.789827\n",
       "UA    259.785438\n",
       "Name: PricePerTicket, dtype: float64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gk2=df1.mean()\n",
    "gk2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "##avarage price ticket of every airline company...\n",
    "\n",
    "gk2.plot(kind=\"bar\",color=\"red\",xlabel=\"Airline Company\",ylabel=\"Ticket price\")\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg1.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        672.87\n",
       "1        367.68\n",
       "2        417.94\n",
       "3        247.10\n",
       "4        276.35\n",
       "          ...  \n",
       "41280    133.52\n",
       "44441    295.00\n",
       "45156     83.30\n",
       "45738     61.19\n",
       "48851    127.26\n",
       "Name: PricePerTicket, Length: 337, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sb.histplot(df[\"Miles\"],color=\"red\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "##### frequency/count of \"no of tickets\" ordered\n",
    "\n",
    "\n",
    "sb.histplot(df[\"NumTicketsOrdered\"],color=\"blue\")\n",
    "\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2=df.Miles.groupby(df.Origin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Origin\n",
       "ABQ     328.000000\n",
       "ATL    1377.791878\n",
       "AUS     961.645503\n",
       "BDL     196.000000\n",
       "BNA     443.666667\n",
       "          ...     \n",
       "SNA     347.435146\n",
       "STL    1166.547297\n",
       "TPA    1132.122481\n",
       "TUL     237.000000\n",
       "VPS     641.000000\n",
       "Name: Miles, Length: 76, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PHL    9479\n",
       "PIT    1922\n",
       "Name: Origin, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.value_counts(df[df[\"OriginWac\"]==23][\"Origin\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "76"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Origin\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.FacetGrid(df,col=\"Origin\",col_wrap=4).map(plt.hist,\"PricePerTicket\")\n",
    "\n",
    "\n",
    "\n",
    "#origin wise ticket price variety.....\n",
    "plt.savefig(\"save_as_a_jpeg2.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PHX    14330\n",
       "PHL     9479\n",
       "RDU     2518\n",
       "SAN     2062\n",
       "PIT     1922\n",
       "       ...  \n",
       "BDL        1\n",
       "SAV        1\n",
       "TUL        1\n",
       "VPS        1\n",
       "ORF        1\n",
       "Name: Origin, Length: 76, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.value_counts(df[df[\"Quarter\"]==1][\"Origin\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Quarter\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3=df.NumTicketsOrdered.groupby(df.Origin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1\n",
       "1        1\n",
       "2        1\n",
       "3        1\n",
       "4        1\n",
       "        ..\n",
       "41280    1\n",
       "44441    1\n",
       "45156    1\n",
       "45738    1\n",
       "48851    1\n",
       "Name: NumTicketsOrdered, Length: 337, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>Dest</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20181767585</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>672.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20181767586</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>367.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20181767587</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>417.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20181767636</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>247.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20181767637</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>276.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49995</th>\n",
       "      <td>20181881433</td>\n",
       "      <td>2.018190e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SAN</td>\n",
       "      <td>91</td>\n",
       "      <td>ORD</td>\n",
       "      <td>41</td>\n",
       "      <td>1723</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>AA</td>\n",
       "      <td>190.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49996</th>\n",
       "      <td>20181881433</td>\n",
       "      <td>2.018190e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>ORD</td>\n",
       "      <td>41</td>\n",
       "      <td>SAN</td>\n",
       "      <td>91</td>\n",
       "      <td>1723</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>AA</td>\n",
       "      <td>190.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49997</th>\n",
       "      <td>20181881434</td>\n",
       "      <td>2.018190e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SAN</td>\n",
       "      <td>91</td>\n",
       "      <td>ORD</td>\n",
       "      <td>41</td>\n",
       "      <td>1723</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49998</th>\n",
       "      <td>20181881434</td>\n",
       "      <td>2.018190e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>ORD</td>\n",
       "      <td>41</td>\n",
       "      <td>SAN</td>\n",
       "      <td>91</td>\n",
       "      <td>1723</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49999</th>\n",
       "      <td>20181881435</td>\n",
       "      <td>2.018190e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SAN</td>\n",
       "      <td>91</td>\n",
       "      <td>ORD</td>\n",
       "      <td>41</td>\n",
       "      <td>1723</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>AA</td>\n",
       "      <td>193.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50000 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ItinID         MktID  MktCoupons  Quarter Origin  OriginWac Dest  \\\n",
       "0      20181767585  2.018180e+12           1        1    PHL         23  LAX   \n",
       "1      20181767586  2.018180e+12           1        1    PHL         23  LAX   \n",
       "2      20181767587  2.018180e+12           1        1    PHL         23  LAX   \n",
       "3      20181767636  2.018180e+12           1        1    PHL         23  LAX   \n",
       "4      20181767637  2.018180e+12           1        1    PHL         23  LAX   \n",
       "...            ...           ...         ...      ...    ...        ...  ...   \n",
       "49995  20181881433  2.018190e+12           1        1    SAN         91  ORD   \n",
       "49996  20181881433  2.018190e+12           1        1    ORD         41  SAN   \n",
       "49997  20181881434  2.018190e+12           1        1    SAN         91  ORD   \n",
       "49998  20181881434  2.018190e+12           1        1    ORD         41  SAN   \n",
       "49999  20181881435  2.018190e+12           1        1    SAN         91  ORD   \n",
       "\n",
       "       DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0           91   2402              2                  1             AA   \n",
       "1           91   2402              2                  1             AA   \n",
       "2           91   2402              2                  1             AA   \n",
       "3           91   2402              2                  1             AA   \n",
       "4           91   2402              2                  1             AA   \n",
       "...        ...    ...            ...                ...            ...   \n",
       "49995       41   1723              2                  3             AA   \n",
       "49996       91   1723              2                  3             AA   \n",
       "49997       41   1723              2                  3             AA   \n",
       "49998       91   1723              2                  3             AA   \n",
       "49999       41   1723              2                  3             AA   \n",
       "\n",
       "       PricePerTicket  \n",
       "0              672.87  \n",
       "1              367.68  \n",
       "2              417.94  \n",
       "3              247.10  \n",
       "4              276.35  \n",
       "...               ...  \n",
       "49995          190.00  \n",
       "49996          190.00  \n",
       "49997          191.00  \n",
       "49998          191.00  \n",
       "49999          193.50  \n",
       "\n",
       "[50000 rows x 13 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#HOW MANY FLIGHTS ARE AVAILABLE??\n",
    "df3=df.groupby(df.AirlineCompany)\n",
    "\n"
   ]
  },
  {
   "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>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>Dest</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20181767585</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>672.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20181767586</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>367.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20181767587</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>417.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20181767636</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>247.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20181767637</td>\n",
       "      <td>2.018180e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>PHL</td>\n",
       "      <td>23</td>\n",
       "      <td>LAX</td>\n",
       "      <td>91</td>\n",
       "      <td>2402</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>276.35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ItinID         MktID  MktCoupons  Quarter Origin  OriginWac Dest  \\\n",
       "0  20181767585  2.018180e+12           1        1    PHL         23  LAX   \n",
       "1  20181767586  2.018180e+12           1        1    PHL         23  LAX   \n",
       "2  20181767587  2.018180e+12           1        1    PHL         23  LAX   \n",
       "3  20181767636  2.018180e+12           1        1    PHL         23  LAX   \n",
       "4  20181767637  2.018180e+12           1        1    PHL         23  LAX   \n",
       "\n",
       "   DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       91   2402              2                  1             AA   \n",
       "1       91   2402              2                  1             AA   \n",
       "2       91   2402              2                  1             AA   \n",
       "3       91   2402              2                  1             AA   \n",
       "4       91   2402              2                  1             AA   \n",
       "\n",
       "   PricePerTicket  \n",
       "0          672.87  \n",
       "1          367.68  \n",
       "2          417.94  \n",
       "3          247.10  \n",
       "4          276.35  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "###no of flights in each airline company.\n",
    "\n",
    "\n",
    "\n",
    "sb.countplot(x=\"AirlineCompany\",data=df,palette=\"CMRmap\")\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg3.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "df4=df[[\"Dest\",\"Origin\",\"PricePerTicket\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "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>Dest</th>\n",
       "      <th>Origin</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DFW</td>\n",
       "      <td>CLT</td>\n",
       "      <td>107.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DFW</td>\n",
       "      <td>CLT</td>\n",
       "      <td>156.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DFW</td>\n",
       "      <td>CLT</td>\n",
       "      <td>191.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DFW</td>\n",
       "      <td>CLT</td>\n",
       "      <td>349.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DFW</td>\n",
       "      <td>CLT</td>\n",
       "      <td>135.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>LAS</td>\n",
       "      <td>SNA</td>\n",
       "      <td>295.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>LAS</td>\n",
       "      <td>SNA</td>\n",
       "      <td>297.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>LAS</td>\n",
       "      <td>SNA</td>\n",
       "      <td>306.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>LAS</td>\n",
       "      <td>SNA</td>\n",
       "      <td>113.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>LAS</td>\n",
       "      <td>SNA</td>\n",
       "      <td>80.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Dest Origin  PricePerTicket\n",
       "0       DFW    CLT          107.80\n",
       "1       DFW    CLT          156.44\n",
       "2       DFW    CLT          191.18\n",
       "3       DFW    CLT          349.66\n",
       "4       DFW    CLT          135.13\n",
       "...     ...    ...             ...\n",
       "124869  LAS    SNA          295.50\n",
       "124870  LAS    SNA          297.50\n",
       "124871  LAS    SNA          306.00\n",
       "124872  LAS    SNA          113.28\n",
       "124873  LAS    SNA           80.33\n",
       "\n",
       "[124874 rows x 3 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "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></th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">CLT</th>\n",
       "      <th>DFW</th>\n",
       "      <td>275.900484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</th>\n",
       "      <td>346.703333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>249.827927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>173.646353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>266.266935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SNA</th>\n",
       "      <th>MCO</th>\n",
       "      <td>330.124433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>290.226170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>277.945202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>178.667157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <td>62.830000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             PricePerTicket\n",
       "Origin Dest                \n",
       "CLT    DFW       275.900484\n",
       "       LAS       346.703333\n",
       "       LAX       249.827927\n",
       "       LGA       173.646353\n",
       "       MCO       266.266935\n",
       "...                     ...\n",
       "SNA    MCO       330.124433\n",
       "       MIA       290.226170\n",
       "       ORD       277.945202\n",
       "       PHX       178.667157\n",
       "       SFO        62.830000\n",
       "\n",
       "[125 rows x 1 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gk = df4.groupby(['Origin','Dest']).mean()\n",
    "gk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "##### origin destination combo with price of ticket\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "fp=gk.pivot_table(index='Dest',columns='Origin',values='PricePerTicket')\n",
    "pp=sb.heatmap(fp)\n",
    "pp.set(ylabel=\"Destination\")\n",
    "\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg4.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7DEwvBm6Zo7FI0kZpvgfJt4CdkuyY5KHAMuCsOR6TJG1U5vWuraq6N8kbgPOATYFPVdXKMXXXa9eY/dnfb0hf9md/a5nXB9slSXNvvu/akiTNMYNEktSLQTIgyeOSnJrk+0muTnJOkicnuarN3zrJ5e324yQ/Gph+6Ajt39eWXZnku0nekmSTNm+vJD8baO+fkjw6yU+SpC3z7CSVZHGbflSSOyfaWEe/v1jHvKPaemwyULZtkrPbGK9Ocs5oj+C0+3tLkhMGpl+e5Et9+0vyiiRXDDzen0zy6IH5C5P8W5LXjdhPJTllYHpBkjVJzh4o2y/JiiTXJLk2yYcG5i1vZdcmuTTJb89Ev0leneRjk+p8N8nnRml/Ur3FSb6Y5Pr2OjgqyUMHnp/fGbJer27j+U6rd16S52xAnxOvi6uS/EOSLVr5LyYt9+v1TPKeJH82jfWbTl9HJ/kfA/PeleSYDejzXe05eEXr+7eSXJju0k4Tr/eD2rJDH/8Z6GvFwDJLk1w4qd5ar8sNUlXeuuNEAS4G/ttA2W7A84Crhiz/HuDPNrCPXwzcfyzwT8Bftem9gLOH1FkJ7Nzu/ynwbeClbXof4NwN6XdS+SbATcD/A/YaKP874I0D08+Y7nqO2N8C4HLgucCjgRuAJ/TpD9gXuAxY1KY3BV4LPGVgmdcDXwcuHLUf4DvA5m16vzbus9v0rsD3gacOrNfr2/0Xt/Fs06af1R6Lx81Av68GPjaw/NOAK4EfAQ/fwNfApcBrBh6zE4APDj4/gc2Ba4HnTtH/84EfA0+bxuviM8Bbhv1fB/thGq+/Hn1tCfwAeAKwY3t+PnrE/p5N976yWZveBtgeuBBYOurjPwN93QTs18qXMvCcZ4rX5Ybc3CK53/OBf6uqj08UVNXlwM3j6Kyqbqf7tv0bkgz7YuWEbwITn+6eA3xk0vRFPYbxfOAq4DjgkIHy7ei+ozMx1it69LHe/qrqXro39WOAD9CdffeDnn29i+6N5ketj/uq6lNVNXhVg0PownlxkkUjtnsu8PsD9Qc/9f85cGRVXdv6vLeqjm3z3ga8taruaPO+DZwEHDED/U72X4BTgC8Dfzhi+wAvAO6uqk+3Md4HvJkugLeYWKiqfkUXZEMfs6r6Kt2ZQcuHzV+PrwNPmka96Ripr6r6Od3z6WN0z9G/rKp/HrGP7YA7quqe1tYdVTXVd92mfPwntpx69PVB4C+mqDfV+8DIDJL77Ur3iXHWtDfLTei2TgCeN7Cp+65WdhH3B8cTgH+g+0RBK/9mjyFMvCGdCbw4yUNa+THACUm+2jaVt+/Rxyj9UVUXAdcA/5kuTPrahW7rbagkO9BtDVwKnA68bMR2TwWWJXkY8AzgkoF563oO7TJk3opW3rffyV4GnEb3WG/IG8NaY2xvojcx8IabZCtgJ+Br62jr28BTN6Bvkiyg29q6shVtPvB6uBx474a0N5N9VdXngK2ALavqFEb3ZWCHJN9LcmyS3x2Y95mBPrdmxMd/mn1dDNyT5PlD6k35uhyVQTL3BrdGvl5Vu7Xbka3sm8BzkuwI3FhVdwNJ8ghgd7pN4Q3vtNvv+iLgC+3JegnwQoCqOo8utD5B92bwnSRDr7EzE/21+Y+gC8iHAL36GtL309uL9ftJJgJjGV2AQPcmPdIbbts6W9KW36BjR8OGxpBL+vTpN8l/AtZU1Q+B84FntTf+PuOZKH9ekivodludXVU/Xk9bo9q8vXmvoHvTnDhe9quB18NuwF9uQJsz2le645KPA7Zvz9WRVNUv6F6ny4E1wGlJXt1mv3ygz5+w/se/T18A/5NJWyXre12Oal5/IXGGrQQOms0OkzwBuA+4nW6/9lqq6vr2RvAHdJ8qoPvU8hrghvbkmY59gUcBV7Y9a1sA/wJ8qfV7J/BZ4LPpDur+DvD5afa13v6AvwL+HriNbvfdwT36gu7/+Szgq1V1JbBbO3i6eZt/CLBtkpe36e2T7FRV14/Q9lnAh+iOG2w9qc/dge8OqXN1m3fBQNmzWvmopup30CHAU5Pc2Ka3BF4CfHKE9le2ZX8tyZZ0lyH6Pt0HnRcneTLwjSRntt2/wzyTbgtzFL9qb96zYbp9HUV3XOZpwLuBt45ase2iuhC4MMmVwKFTLLq+x79XX1V1QZL3AXsOVFnf63IkbpHc7wJgsyT/daKgfbp7/Dg6a5/wP053QG99nzYuBt7I/UFyMfAm+h0fOQT446paUlVL6A4ivjDJFkleMHA2yyOBJ9J9eutjXf09nW7///vp9q0/Psnv9ezvr4EPtU+SEzYHSPIUuoPQiwbG89d0Wymj+BTw3hZQgz4IvLO90ZJkkyRvafM+ALy/7cIgyW50B3SPZXRT9ctEf3QB/IyB9dqf0XdvnQ9skeRVrb1NgQ8DJ9K9uQBQVd+je7zeNsU4fpfuU/EnRuz3QS3JfnS7n08G3gccmBF/9yjJU5LsNFC0G/DDKRaf8vGvqn+Zos6G9nUk3bG8CVO+LtfX3yCDpGlv5gcCv9d2gayk+wRyC/CUJKsHbtP9tDyxH3Yl3RlbX6b7JL4+36T7VDJxCt/FdLueRg2SLSaN/510Z3z9+lNHVf0S+Abdls/uwIq2G+Ni4JNV9a0R+5pOf8cBb66qu6vq3+kOvB+V0U97nNzfW6rqHOBo4Nx0pzBfRLf1dx7di+fMSW18ntF3b62uqqOGlF9BF/CfS3IN3QHM7dq8s+iC4KIk19K9yb6iqm4dcR2n7HfA7wA/mjjBoPkasHOS7UZof+I1cHCS64HvAXcD7xyy+MeB32m7XAFe1p7b32vLv6SqRt0ima6/GPy/j6ODdkzqb+nOvqv2vP1zugPvo3gEcFJ7Dl5B9wN87xm24AY+/tPqq70u1rR124J1vy5H5iVSJEm9uEUiSerFIJEk9WKQSJJ6MUgkSb0YJJKkXgwSaQwy4lVck2yf5IwR2jsnA1culh5MPP1XmmHpviJ8CXBcVX26fbHseODOqnrrwHIL2gUrpXnNS6RIM2+tq7gmeTNwQ5Ib6K62+jDg4UleS3fdql3bF8ROpLu+2TV019Y6oqpWtEueLKX70tm5dF8aew7dpeL3b1fkleaEu7akmbeuq7guoPvdiEOr6gWT6r0e+GlVPYPuUhy7T9H+TsAxVbUL8M9Muj6TNNsMEmnmre8qrl9pF8Wc7LfprkRMVV0FTPU7MDcMXCzxMrotF2nOGCTSzFvJ/b8ZAzzgKq73Ab+cot6ol16/Z+D+fbiLWnPMIJFm3khX0R3iG8BLW52dgaePd5jSzDBIpBnW4yquxwIL25Vb30a3a+tn4xyrNBM8/Vd6kGhbLg+pqruTPJFuy+bJVfWvczw0aZ3ctyo9eGwBfDXdb2YHONwQ0XzgFokkqRePkUiSejFIJEm9GCSSpF4MEklSLwaJJKmX/w+fV6CufdymAQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(x=\"Origin\",data=df)\n",
    "\n",
    "## no of flights from every origin\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg5.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "### no of flights coming  to every destination\n",
    "\n",
    "\n",
    "plot=sb.countplot(x=\"Dest\",data=df,)\n",
    "plot.set(xlabel=\"Destination\")\n",
    "\n",
    "plt.savefig(\"save_as_a_plot.jpeg\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>Dest</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>107.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>156.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>349.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>135.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>295.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>297.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>306.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ItinID         MktID  MktCoupons  Quarter Origin  OriginWac  \\\n",
       "0       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "1       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "2       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "3       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "4       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "...              ...           ...         ...      ...    ...        ...   \n",
       "124869  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124870  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124871  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124872  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124873  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "\n",
       "       Dest  DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       DFW       74    936              2                  1             AA   \n",
       "1       DFW       74    936              2                  1             AA   \n",
       "2       DFW       74    936              2                  1             AA   \n",
       "3       DFW       74    936              2                  1             AA   \n",
       "4       DFW       74    936              2                  1             AA   \n",
       "...     ...      ...    ...            ...                ...            ...   \n",
       "124869  LAS       85    226              2                  1             WN   \n",
       "124870  LAS       85    226              2                  1             WN   \n",
       "124871  LAS       85    226              2                  1             WN   \n",
       "124872  LAS       85    226              2                  1             WN   \n",
       "124873  LAS       85    226              2                  1             WN   \n",
       "\n",
       "        PricePerTicket  \n",
       "0               107.80  \n",
       "1               156.44  \n",
       "2               191.18  \n",
       "3               349.66  \n",
       "4               135.13  \n",
       "...                ...  \n",
       "124869          295.50  \n",
       "124870          297.50  \n",
       "124871          306.00  \n",
       "124872          113.28  \n",
       "124873           80.33  \n",
       "\n",
       "[124874 rows x 13 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x203e41a5760>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#### airlinecompany wise price ticket...\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "sb.FacetGrid(df,col=\"AirlineCompany\",col_wrap=4).map(plt.hist,\"PricePerTicket\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>Dest</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>107.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>156.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>349.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>135.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>295.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>297.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>306.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ItinID         MktID  MktCoupons  Quarter Origin  OriginWac  \\\n",
       "0       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "1       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "2       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "3       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "4       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "...              ...           ...         ...      ...    ...        ...   \n",
       "124869  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124870  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124871  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124872  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124873  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "\n",
       "       Dest  DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       DFW       74    936              2                  1             AA   \n",
       "1       DFW       74    936              2                  1             AA   \n",
       "2       DFW       74    936              2                  1             AA   \n",
       "3       DFW       74    936              2                  1             AA   \n",
       "4       DFW       74    936              2                  1             AA   \n",
       "...     ...      ...    ...            ...                ...            ...   \n",
       "124869  LAS       85    226              2                  1             WN   \n",
       "124870  LAS       85    226              2                  1             WN   \n",
       "124871  LAS       85    226              2                  1             WN   \n",
       "124872  LAS       85    226              2                  1             WN   \n",
       "124873  LAS       85    226              2                  1             WN   \n",
       "\n",
       "        PricePerTicket  \n",
       "0               107.80  \n",
       "1               156.44  \n",
       "2               191.18  \n",
       "3               349.66  \n",
       "4               135.13  \n",
       "...                ...  \n",
       "124869          295.50  \n",
       "124870          297.50  \n",
       "124871          306.00  \n",
       "124872          113.28  \n",
       "124873           80.33  \n",
       "\n",
       "[124874 rows x 13 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Dest</th>\n",
       "      <th>AirlineCompany</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Dest AirlineCompany\n",
       "0       DFW             AA\n",
       "1       DFW             AA\n",
       "2       DFW             AA\n",
       "3       DFW             AA\n",
       "4       DFW             AA\n",
       "...     ...            ...\n",
       "124869  LAS             WN\n",
       "124870  LAS             WN\n",
       "124871  LAS             WN\n",
       "124872  LAS             WN\n",
       "124873  LAS             WN\n",
       "\n",
       "[124874 rows x 2 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5=df[[\"Dest\",\"AirlineCompany\"]];df5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='AirlineCompany'>"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df6=df.groupby([\"Dest\",\"AirlineCompany\"])\n",
    "df7=df6['Origin'].count()\n",
    "df8=pd.DataFrame(df7)\n",
    "df8['Origin']['LAS'].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='AirlineCompany'>"
      ]
     },
     "execution_count": 61,
     "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": [
    "df8=pd.DataFrame(df7);df8\n",
    "df8[\"Origin\"][\"DFW\"].plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dest</th>\n",
       "      <th>AirlineCompany</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">CLT</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DFW</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">LAS</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">LAX</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">LGA</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">MCO</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">MIA</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">ORD</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">PHL</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PHX</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SFO</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">SNA</th>\n",
       "      <th>AA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [(CLT, AA), (CLT, UA), (CLT, WN), (DFW, AA), (DFW, DL), (DFW, UA), (LAS, AA), (LAS, AS), (LAS, DL), (LAS, UA), (LAS, WN), (LAX, AA), (LAX, AS), (LAX, B6), (LAX, DL), (LAX, UA), (LAX, WN), (LGA, AA), (LGA, B6), (LGA, DL), (LGA, UA), (LGA, WN), (MCO, AA), (MCO, B6), (MCO, DL), (MCO, UA), (MCO, WN), (MIA, AA), (MIA, DL), (MIA, UA), (ORD, AA), (ORD, UA), (PHL, AA), (PHL, UA), (PHL, WN), (PHX, AA), (PHX, AS), (PHX, DL), (PHX, UA), (PHX, WN), (SFO, AA), (SFO, AS), (SFO, DL), (SFO, UA), (SFO, WN), (SNA, AA), (SNA, UA), (SNA, WN)]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df9=df5.groupby([\"Dest\",\"AirlineCompany\"]).count()\n",
    "df9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
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       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
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       "      <td>74</td>\n",
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       "      <td>2.018183e+10</td>\n",
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       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
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       "      <td>936</td>\n",
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       "      <td>156.44</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
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       "      <td>CLT</td>\n",
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       "      <td>191.18</td>\n",
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       "      <td>2.018200e+10</td>\n",
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       "      <td>CLT</td>\n",
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       "      <td>349.66</td>\n",
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       "    <tr>\n",
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       "      <td>CLT</td>\n",
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       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>135.13</td>\n",
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       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>295.50</td>\n",
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       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>297.50</td>\n",
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       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
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       "      <td>1</td>\n",
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       "      <td>91</td>\n",
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       "      <td>306.00</td>\n",
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       "      <th>124872</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
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       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ItinID         MktID  MktCoupons  Quarter Origin  OriginWac  \\\n",
       "0       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "1       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "2       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "3       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "4       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "...              ...           ...         ...      ...    ...        ...   \n",
       "124869  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124870  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124871  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124872  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124873  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "\n",
       "       Dest  DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       DFW       74    936              2                  1             AA   \n",
       "1       DFW       74    936              2                  1             AA   \n",
       "2       DFW       74    936              2                  1             AA   \n",
       "3       DFW       74    936              2                  1             AA   \n",
       "4       DFW       74    936              2                  1             AA   \n",
       "...     ...      ...    ...            ...                ...            ...   \n",
       "124869  LAS       85    226              2                  1             WN   \n",
       "124870  LAS       85    226              2                  1             WN   \n",
       "124871  LAS       85    226              2                  1             WN   \n",
       "124872  LAS       85    226              2                  1             WN   \n",
       "124873  LAS       85    226              2                  1             WN   \n",
       "\n",
       "        PricePerTicket  \n",
       "0               107.80  \n",
       "1               156.44  \n",
       "2               191.18  \n",
       "3               349.66  \n",
       "4               135.13  \n",
       "...                ...  \n",
       "124869          295.50  \n",
       "124870          297.50  \n",
       "124871          306.00  \n",
       "124872          113.28  \n",
       "124873           80.33  \n",
       "\n",
       "[124874 rows x 13 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>173.646353</td>\n",
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       "      <th rowspan=\"5\" valign=\"top\">SNA</th>\n",
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       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>290.226170</td>\n",
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       "      <th>ORD</th>\n",
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       "      <th>PHX</th>\n",
       "      <td>178.667157</td>\n",
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       "      <th>SFO</th>\n",
       "      <td>62.830000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>125 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             PricePerTicket\n",
       "Origin Dest                \n",
       "CLT    DFW       275.900484\n",
       "       LAS       346.703333\n",
       "       LAX       249.827927\n",
       "       LGA       173.646353\n",
       "       MCO       266.266935\n",
       "...                     ...\n",
       "SNA    MCO       330.124433\n",
       "       MIA       290.226170\n",
       "       ORD       277.945202\n",
       "       PHX       178.667157\n",
       "       SFO        62.830000\n",
       "\n",
       "[125 rows x 1 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gk\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>297.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>306.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
       "      <td>91</td>\n",
       "      <td>LAS</td>\n",
       "      <td>85</td>\n",
       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ItinID         MktID  MktCoupons  Quarter Origin  OriginWac  \\\n",
       "0       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "1       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "2       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "3       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "4       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "...              ...           ...         ...      ...    ...        ...   \n",
       "124869  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124870  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124871  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124872  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124873  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "\n",
       "       Dest  DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       DFW       74    936              2                  1             AA   \n",
       "1       DFW       74    936              2                  1             AA   \n",
       "2       DFW       74    936              2                  1             AA   \n",
       "3       DFW       74    936              2                  1             AA   \n",
       "4       DFW       74    936              2                  1             AA   \n",
       "...     ...      ...    ...            ...                ...            ...   \n",
       "124869  LAS       85    226              2                  1             WN   \n",
       "124870  LAS       85    226              2                  1             WN   \n",
       "124871  LAS       85    226              2                  1             WN   \n",
       "124872  LAS       85    226              2                  1             WN   \n",
       "124873  LAS       85    226              2                  1             WN   \n",
       "\n",
       "        PricePerTicket  \n",
       "0               107.80  \n",
       "1               156.44  \n",
       "2               191.18  \n",
       "3               349.66  \n",
       "4               135.13  \n",
       "...                ...  \n",
       "124869          295.50  \n",
       "124870          297.50  \n",
       "124871          306.00  \n",
       "124872          113.28  \n",
       "124873           80.33  \n",
       "\n",
       "[124874 rows x 13 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Origin</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dest</th>\n",
       "      <th>AirlineCompany</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">CLT</th>\n",
       "      <th>AA</th>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "      <td>3785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DFW</th>\n",
       "      <th>AA</th>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "      <td>11917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "      <td>649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "      <td>799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">LAS</th>\n",
       "      <th>AA</th>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "      <td>3610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "      <td>471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "      <td>1488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "      <td>1427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">LAX</th>\n",
       "      <th>AA</th>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "      <td>6754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "      <td>318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "      <td>1636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "      <td>2908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "      <td>1250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">LGA</th>\n",
       "      <th>AA</th>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "      <td>5472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "      <td>901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "      <td>3105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "      <td>1705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">MCO</th>\n",
       "      <th>AA</th>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "      <td>6011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "      <td>1238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "      <td>2772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "      <td>2129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "      <td>330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">MIA</th>\n",
       "      <th>AA</th>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "      <td>9146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "      <td>1759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "      <td>702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">ORD</th>\n",
       "      <th>AA</th>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "      <td>11728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "      <td>9269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">PHL</th>\n",
       "      <th>AA</th>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "      <td>7954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "      <td>904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</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>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PHX</th>\n",
       "      <th>AA</th>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "      <td>6853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "      <td>204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "      <td>1188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "      <td>708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SFO</th>\n",
       "      <th>AA</th>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "      <td>5005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "      <td>209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "      <td>4202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "      <td>591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">SNA</th>\n",
       "      <th>AA</th>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "      <td>2562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "      <td>562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     ItinID  MktID  MktCoupons  Quarter  Origin  OriginWac  \\\n",
       "Dest AirlineCompany                                                          \n",
       "CLT  AA                3785   3785        3785     3785    3785       3785   \n",
       "     UA                  39     39          39       39      39         39   \n",
       "     WN                  62     62          62       62      62         62   \n",
       "DFW  AA               11917  11917       11917    11917   11917      11917   \n",
       "     DL                 649    649         649      649     649        649   \n",
       "     UA                 799    799         799      799     799        799   \n",
       "LAS  AA                3610   3610        3610     3610    3610       3610   \n",
       "     AS                   4      4           4        4       4          4   \n",
       "     DL                 471    471         471      471     471        471   \n",
       "     UA                1488   1488        1488     1488    1488       1488   \n",
       "     WN                1427   1427        1427     1427    1427       1427   \n",
       "LAX  AA                6754   6754        6754     6754    6754       6754   \n",
       "     AS                   7      7           7        7       7          7   \n",
       "     B6                 318    318         318      318     318        318   \n",
       "     DL                1636   1636        1636     1636    1636       1636   \n",
       "     UA                2908   2908        2908     2908    2908       2908   \n",
       "     WN                1250   1250        1250     1250    1250       1250   \n",
       "LGA  AA                5472   5472        5472     5472    5472       5472   \n",
       "     B6                 901    901         901      901     901        901   \n",
       "     DL                3105   3105        3105     3105    3105       3105   \n",
       "     UA                1705   1705        1705     1705    1705       1705   \n",
       "     WN                  40     40          40       40      40         40   \n",
       "MCO  AA                6011   6011        6011     6011    6011       6011   \n",
       "     B6                1238   1238        1238     1238    1238       1238   \n",
       "     DL                2772   2772        2772     2772    2772       2772   \n",
       "     UA                2129   2129        2129     2129    2129       2129   \n",
       "     WN                 330    330         330      330     330        330   \n",
       "MIA  AA                9146   9146        9146     9146    9146       9146   \n",
       "     DL                1759   1759        1759     1759    1759       1759   \n",
       "     UA                 702    702         702      702     702        702   \n",
       "ORD  AA               11728  11728       11728    11728   11728      11728   \n",
       "     UA                9269   9269        9269     9269    9269       9269   \n",
       "PHL  AA                7954   7954        7954     7954    7954       7954   \n",
       "     UA                 904    904         904      904     904        904   \n",
       "     WN                 194    194         194      194     194        194   \n",
       "PHX  AA                6853   6853        6853     6853    6853       6853   \n",
       "     AS                 204    204         204      204     204        204   \n",
       "     DL                  20     20          20       20      20         20   \n",
       "     UA                1188   1188        1188     1188    1188       1188   \n",
       "     WN                 708    708         708      708     708        708   \n",
       "SFO  AA                5005   5005        5005     5005    5005       5005   \n",
       "     AS                 209    209         209      209     209        209   \n",
       "     DL                   8      8           8        8       8          8   \n",
       "     UA                4202   4202        4202     4202    4202       4202   \n",
       "     WN                 591    591         591      591     591        591   \n",
       "SNA  AA                2562   2562        2562     2562    2562       2562   \n",
       "     UA                 562    562         562      562     562        562   \n",
       "     WN                 279    279         279      279     279        279   \n",
       "\n",
       "                     DestWac  Miles  ContiguousUSA  NumTicketsOrdered  \\\n",
       "Dest AirlineCompany                                                     \n",
       "CLT  AA                 3785   3785           3785               3785   \n",
       "     UA                   39     39             39                 39   \n",
       "     WN                   62     62             62                 62   \n",
       "DFW  AA                11917  11917          11917              11917   \n",
       "     DL                  649    649            649                649   \n",
       "     UA                  799    799            799                799   \n",
       "LAS  AA                 3610   3610           3610               3610   \n",
       "     AS                    4      4              4                  4   \n",
       "     DL                  471    471            471                471   \n",
       "     UA                 1488   1488           1488               1488   \n",
       "     WN                 1427   1427           1427               1427   \n",
       "LAX  AA                 6754   6754           6754               6754   \n",
       "     AS                    7      7              7                  7   \n",
       "     B6                  318    318            318                318   \n",
       "     DL                 1636   1636           1636               1636   \n",
       "     UA                 2908   2908           2908               2908   \n",
       "     WN                 1250   1250           1250               1250   \n",
       "LGA  AA                 5472   5472           5472               5472   \n",
       "     B6                  901    901            901                901   \n",
       "     DL                 3105   3105           3105               3105   \n",
       "     UA                 1705   1705           1705               1705   \n",
       "     WN                   40     40             40                 40   \n",
       "MCO  AA                 6011   6011           6011               6011   \n",
       "     B6                 1238   1238           1238               1238   \n",
       "     DL                 2772   2772           2772               2772   \n",
       "     UA                 2129   2129           2129               2129   \n",
       "     WN                  330    330            330                330   \n",
       "MIA  AA                 9146   9146           9146               9146   \n",
       "     DL                 1759   1759           1759               1759   \n",
       "     UA                  702    702            702                702   \n",
       "ORD  AA                11728  11728          11728              11728   \n",
       "     UA                 9269   9269           9269               9269   \n",
       "PHL  AA                 7954   7954           7954               7954   \n",
       "     UA                  904    904            904                904   \n",
       "     WN                  194    194            194                194   \n",
       "PHX  AA                 6853   6853           6853               6853   \n",
       "     AS                  204    204            204                204   \n",
       "     DL                   20     20             20                 20   \n",
       "     UA                 1188   1188           1188               1188   \n",
       "     WN                  708    708            708                708   \n",
       "SFO  AA                 5005   5005           5005               5005   \n",
       "     AS                  209    209            209                209   \n",
       "     DL                    8      8              8                  8   \n",
       "     UA                 4202   4202           4202               4202   \n",
       "     WN                  591    591            591                591   \n",
       "SNA  AA                 2562   2562           2562               2562   \n",
       "     UA                  562    562            562                562   \n",
       "     WN                  279    279            279                279   \n",
       "\n",
       "                     PricePerTicket  \n",
       "Dest AirlineCompany                  \n",
       "CLT  AA                        3785  \n",
       "     UA                          39  \n",
       "     WN                          62  \n",
       "DFW  AA                       11917  \n",
       "     DL                         649  \n",
       "     UA                         799  \n",
       "LAS  AA                        3610  \n",
       "     AS                           4  \n",
       "     DL                         471  \n",
       "     UA                        1488  \n",
       "     WN                        1427  \n",
       "LAX  AA                        6754  \n",
       "     AS                           7  \n",
       "     B6                         318  \n",
       "     DL                        1636  \n",
       "     UA                        2908  \n",
       "     WN                        1250  \n",
       "LGA  AA                        5472  \n",
       "     B6                         901  \n",
       "     DL                        3105  \n",
       "     UA                        1705  \n",
       "     WN                          40  \n",
       "MCO  AA                        6011  \n",
       "     B6                        1238  \n",
       "     DL                        2772  \n",
       "     UA                        2129  \n",
       "     WN                         330  \n",
       "MIA  AA                        9146  \n",
       "     DL                        1759  \n",
       "     UA                         702  \n",
       "ORD  AA                       11728  \n",
       "     UA                        9269  \n",
       "PHL  AA                        7954  \n",
       "     UA                         904  \n",
       "     WN                         194  \n",
       "PHX  AA                        6853  \n",
       "     AS                         204  \n",
       "     DL                          20  \n",
       "     UA                        1188  \n",
       "     WN                         708  \n",
       "SFO  AA                        5005  \n",
       "     AS                         209  \n",
       "     DL                           8  \n",
       "     UA                        4202  \n",
       "     WN                         591  \n",
       "SNA  AA                        2562  \n",
       "     UA                         562  \n",
       "     WN                         279  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['Dest','AirlineCompany']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>AA</th>\n",
       "      <th>AS</th>\n",
       "      <th>B6</th>\n",
       "      <th>DL</th>\n",
       "      <th>UA</th>\n",
       "      <th>WN</th>\n",
       "      <th>NewCol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dest</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>CLT</th>\n",
       "      <td>3785.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>CLT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DFW</th>\n",
       "      <td>11917.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>649.0</td>\n",
       "      <td>799.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DFW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</th>\n",
       "      <td>3610.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>471.0</td>\n",
       "      <td>1488.0</td>\n",
       "      <td>1427.0</td>\n",
       "      <td>LAS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>6754.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>1636.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>LAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>5472.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>901.0</td>\n",
       "      <td>3105.0</td>\n",
       "      <td>1705.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>LGA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>6011.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>2772.0</td>\n",
       "      <td>2129.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>MCO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>9146.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1759.0</td>\n",
       "      <td>702.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>11728.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9269.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ORD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHL</th>\n",
       "      <td>7954.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>904.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>PHL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>6853.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1188.0</td>\n",
       "      <td>708.0</td>\n",
       "      <td>PHX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <td>5005.0</td>\n",
       "      <td>209.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4202.0</td>\n",
       "      <td>591.0</td>\n",
       "      <td>SFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNA</th>\n",
       "      <td>2562.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>562.0</td>\n",
       "      <td>279.0</td>\n",
       "      <td>SNA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AirlineCompany       AA     AS      B6      DL      UA      WN NewCol\n",
       "Dest                                                                 \n",
       "CLT              3785.0    NaN     NaN     NaN    39.0    62.0    CLT\n",
       "DFW             11917.0    NaN     NaN   649.0   799.0     NaN    DFW\n",
       "LAS              3610.0    4.0     NaN   471.0  1488.0  1427.0    LAS\n",
       "LAX              6754.0    7.0   318.0  1636.0  2908.0  1250.0    LAX\n",
       "LGA              5472.0    NaN   901.0  3105.0  1705.0    40.0    LGA\n",
       "MCO              6011.0    NaN  1238.0  2772.0  2129.0   330.0    MCO\n",
       "MIA              9146.0    NaN     NaN  1759.0   702.0     NaN    MIA\n",
       "ORD             11728.0    NaN     NaN     NaN  9269.0     NaN    ORD\n",
       "PHL              7954.0    NaN     NaN     NaN   904.0   194.0    PHL\n",
       "PHX              6853.0  204.0     NaN    20.0  1188.0   708.0    PHX\n",
       "SFO              5005.0  209.0     NaN     8.0  4202.0   591.0    SFO\n",
       "SNA              2562.0    NaN     NaN     NaN   562.0   279.0    SNA"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl1 = df[['Dest','AirlineCompany']].value_counts().unstack()\n",
    "pl1['NewCol']=pl1.index\n",
    "pl1\n",
    "#np.sort(df['Dest'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "sb.countplot(x=\"AirlineCompany\",data=df,palette=\"Dark2\")\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg6.jpeg\")\n",
    "### no of flights in every airline company....\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "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></th>\n",
       "      <th>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>OriginWac</th>\n",
       "      <th>DestWac</th>\n",
       "      <th>Miles</th>\n",
       "      <th>ContiguousUSA</th>\n",
       "      <th>NumTicketsOrdered</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">CLT</th>\n",
       "      <th>DFW</th>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "      <td>475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</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",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "      <td>186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SNA</th>\n",
       "      <th>MCO</th>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "      <td>967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "      <td>626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</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",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>125 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             ItinID  MktID  MktCoupons  Quarter  OriginWac  DestWac  Miles  \\\n",
       "Origin Dest                                                                  \n",
       "CLT    DFW      475    475         475      475        475      475    475   \n",
       "       LAS        6      6           6        6          6        6      6   \n",
       "       LAX       82     82          82       82         82       82     82   \n",
       "       LGA      266    266         266      266        266      266    266   \n",
       "       MCO      186    186         186      186        186      186    186   \n",
       "...             ...    ...         ...      ...        ...      ...    ...   \n",
       "SNA    MCO       97     97          97       97         97       97     97   \n",
       "       MIA       47     47          47       47         47       47     47   \n",
       "       ORD      967    967         967      967        967      967    967   \n",
       "       PHX      626    626         626      626        626      626    626   \n",
       "       SFO        3      3           3        3          3        3      3   \n",
       "\n",
       "             ContiguousUSA  NumTicketsOrdered  AirlineCompany  PricePerTicket  \n",
       "Origin Dest                                                                    \n",
       "CLT    DFW             475                475             475             475  \n",
       "       LAS               6                  6               6               6  \n",
       "       LAX              82                 82              82              82  \n",
       "       LGA             266                266             266             266  \n",
       "       MCO             186                186             186             186  \n",
       "...                    ...                ...             ...             ...  \n",
       "SNA    MCO              97                 97              97              97  \n",
       "       MIA              47                 47              47              47  \n",
       "       ORD             967                967             967             967  \n",
       "       PHX             626                626             626             626  \n",
       "       SFO               3                  3               3               3  \n",
       "\n",
       "[125 rows x 11 columns]"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10=df.groupby([\"Origin\",\"Dest\",]).count()\n",
    "df10\n",
    "#sb.countplot(x=\"AirlineCompany\",data=df10,palette=\"Blues\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "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>AirlineCompany</th>\n",
       "      <th>AA</th>\n",
       "      <th>AS</th>\n",
       "      <th>B6</th>\n",
       "      <th>DL</th>\n",
       "      <th>UA</th>\n",
       "      <th>WN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dest</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>CLT</th>\n",
       "      <td>3785.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DFW</th>\n",
       "      <td>11917.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>649.0</td>\n",
       "      <td>799.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</th>\n",
       "      <td>3610.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>471.0</td>\n",
       "      <td>1488.0</td>\n",
       "      <td>1427.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>6754.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>1636.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>1250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>5472.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>901.0</td>\n",
       "      <td>3105.0</td>\n",
       "      <td>1705.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>6011.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>2772.0</td>\n",
       "      <td>2129.0</td>\n",
       "      <td>330.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>9146.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1759.0</td>\n",
       "      <td>702.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>11728.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9269.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHL</th>\n",
       "      <td>7954.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>904.0</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>6853.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1188.0</td>\n",
       "      <td>708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <td>5005.0</td>\n",
       "      <td>209.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4202.0</td>\n",
       "      <td>591.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNA</th>\n",
       "      <td>2562.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>562.0</td>\n",
       "      <td>279.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AirlineCompany       AA     AS      B6      DL      UA      WN\n",
       "Dest                                                          \n",
       "CLT              3785.0    NaN     NaN     NaN    39.0    62.0\n",
       "DFW             11917.0    NaN     NaN   649.0   799.0     NaN\n",
       "LAS              3610.0    4.0     NaN   471.0  1488.0  1427.0\n",
       "LAX              6754.0    7.0   318.0  1636.0  2908.0  1250.0\n",
       "LGA              5472.0    NaN   901.0  3105.0  1705.0    40.0\n",
       "MCO              6011.0    NaN  1238.0  2772.0  2129.0   330.0\n",
       "MIA              9146.0    NaN     NaN  1759.0   702.0     NaN\n",
       "ORD             11728.0    NaN     NaN     NaN  9269.0     NaN\n",
       "PHL              7954.0    NaN     NaN     NaN   904.0   194.0\n",
       "PHX              6853.0  204.0     NaN    20.0  1188.0   708.0\n",
       "SFO              5005.0  209.0     NaN     8.0  4202.0   591.0\n",
       "SNA              2562.0    NaN     NaN     NaN   562.0   279.0"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pl1['AA'].plot(kind='bar')\n",
    "pl1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "##no of flights coming to every destinaion point based on airline company...\n",
    "\n",
    "\n",
    "pl2 = pl1.plot(kind='bar',figsize=(20,20),xlabel='Destination',ylabel='Count')\n",
    "\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg7.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "##no of flights coming from every origin point based on airline company...\n",
    "\n",
    "\n",
    "pl4 = pl3.plot(kind='bar',figsize=(20,20),xlabel='ORIGIN',ylabel='Count')\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg8.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"10\" halign=\"left\">ContiguousUSA</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Quarter</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Origin</th>\n",
       "      <th>CLT</th>\n",
       "      <th>DFW</th>\n",
       "      <th>LAS</th>\n",
       "      <th>LAX</th>\n",
       "      <th>LGA</th>\n",
       "      <th>MCO</th>\n",
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       "      <th>ORD</th>\n",
       "      <th>PHL</th>\n",
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       "      <th>LAS</th>\n",
       "      <th>LAX</th>\n",
       "      <th>LGA</th>\n",
       "      <th>MCO</th>\n",
       "      <th>MIA</th>\n",
       "      <th>ORD</th>\n",
       "      <th>PHL</th>\n",
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       "      <th>SFO</th>\n",
       "      <th>SNA</th>\n",
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       "    <tr>\n",
       "      <th>Dest</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CLT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DFW</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHL</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 120 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ContiguousUSA                                               ...  \\\n",
       "Origin           CLT  DFW  LAS  LAX  LGA  MCO  MIA  ORD  PHL  PHX  ...   \n",
       "Dest                                                               ...   \n",
       "CLT              NaN  2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  ...   \n",
       "DFW              2.0  NaN  2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  ...   \n",
       "LAS              2.0  2.0  NaN  2.0  2.0  2.0  2.0  2.0  2.0  2.0  ...   \n",
       "LAX              2.0  2.0  2.0  NaN  2.0  2.0  2.0  2.0  2.0  2.0  ...   \n",
       "LGA              2.0  2.0  2.0  2.0  NaN  2.0  2.0  2.0  2.0  NaN  ...   \n",
       "MCO              2.0  2.0  2.0  2.0  2.0  NaN  2.0  2.0  2.0  2.0  ...   \n",
       "MIA              2.0  2.0  2.0  2.0  2.0  2.0  NaN  2.0  2.0  2.0  ...   \n",
       "ORD              2.0  2.0  2.0  2.0  2.0  2.0  2.0  NaN  2.0  2.0  ...   \n",
       "PHL              2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  NaN  2.0  ...   \n",
       "PHX              2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  NaN  ...   \n",
       "SFO              2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  2.0  ...   \n",
       "SNA              NaN  2.0  2.0  NaN  2.0  2.0  2.0  2.0  2.0  2.0  ...   \n",
       "\n",
       "       Quarter                                               \n",
       "Origin     LAS  LAX  LGA  MCO  MIA  ORD  PHL  PHX  SFO  SNA  \n",
       "Dest                                                         \n",
       "CLT        1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  NaN  \n",
       "DFW        1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  \n",
       "LAS        NaN  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  \n",
       "LAX        1.0  NaN  1.0  1.0  1.0  1.0  1.0  1.0  1.0  NaN  \n",
       "LGA        1.0  1.0  NaN  1.0  1.0  1.0  1.0  NaN  1.0  NaN  \n",
       "MCO        1.0  1.0  1.0  NaN  1.0  1.0  1.0  1.0  1.0  1.0  \n",
       "MIA        1.0  1.0  1.0  1.0  NaN  1.0  1.0  1.0  1.0  1.0  \n",
       "ORD        1.0  1.0  1.0  1.0  1.0  NaN  1.0  1.0  1.0  1.0  \n",
       "PHL        1.0  1.0  1.0  1.0  1.0  1.0  NaN  1.0  1.0  NaN  \n",
       "PHX        1.0  1.0  1.0  1.0  1.0  1.0  1.0  NaN  1.0  1.0  \n",
       "SFO        1.0  1.0  1.0  1.0  1.0  1.0  1.0  1.0  NaN  1.0  \n",
       "SNA        1.0  NaN  1.0  1.0  1.0  1.0  1.0  1.0  1.0  NaN  \n",
       "\n",
       "[12 rows x 120 columns]"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.pivot_table(index='Dest',columns='Origin',values=df.groupby(['AirlineCompany']).count())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "124874"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['AirlineCompany'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pp=[]\n",
    "\n",
    "\n",
    "## no of flights in every origin-destination combo\n",
    "df11=pd.crosstab(df['Origin'],df['Dest'])\n",
    "sb.heatmap(df11,cmap='coolwarm',).set(xlabel=\"Destination\",ylabel=\"Origin\")\n",
    "\n",
    "plt.savefig(\"save_as_a_jpeg9.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>AirlineCompany</th>\n",
       "      <th>AA</th>\n",
       "      <th>AS</th>\n",
       "      <th>B6</th>\n",
       "      <th>DL</th>\n",
       "      <th>UA</th>\n",
       "      <th>WN</th>\n",
       "      <th>NewCol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dest</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>CLT</th>\n",
       "      <td>3785.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>CLT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DFW</th>\n",
       "      <td>11917.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>649.0</td>\n",
       "      <td>799.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DFW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</th>\n",
       "      <td>3610.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>471.0</td>\n",
       "      <td>1488.0</td>\n",
       "      <td>1427.0</td>\n",
       "      <td>LAS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>6754.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>1636.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>LAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>5472.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>901.0</td>\n",
       "      <td>3105.0</td>\n",
       "      <td>1705.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>LGA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>6011.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>2772.0</td>\n",
       "      <td>2129.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>MCO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>9146.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1759.0</td>\n",
       "      <td>702.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>11728.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9269.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ORD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHL</th>\n",
       "      <td>7954.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>904.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>PHL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>6853.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1188.0</td>\n",
       "      <td>708.0</td>\n",
       "      <td>PHX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <td>5005.0</td>\n",
       "      <td>209.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4202.0</td>\n",
       "      <td>591.0</td>\n",
       "      <td>SFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNA</th>\n",
       "      <td>2562.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>562.0</td>\n",
       "      <td>279.0</td>\n",
       "      <td>SNA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AirlineCompany       AA     AS      B6      DL      UA      WN NewCol\n",
       "Dest                                                                 \n",
       "CLT              3785.0    NaN     NaN     NaN    39.0    62.0    CLT\n",
       "DFW             11917.0    NaN     NaN   649.0   799.0     NaN    DFW\n",
       "LAS              3610.0    4.0     NaN   471.0  1488.0  1427.0    LAS\n",
       "LAX              6754.0    7.0   318.0  1636.0  2908.0  1250.0    LAX\n",
       "LGA              5472.0    NaN   901.0  3105.0  1705.0    40.0    LGA\n",
       "MCO              6011.0    NaN  1238.0  2772.0  2129.0   330.0    MCO\n",
       "MIA              9146.0    NaN     NaN  1759.0   702.0     NaN    MIA\n",
       "ORD             11728.0    NaN     NaN     NaN  9269.0     NaN    ORD\n",
       "PHL              7954.0    NaN     NaN     NaN   904.0   194.0    PHL\n",
       "PHX              6853.0  204.0     NaN    20.0  1188.0   708.0    PHX\n",
       "SFO              5005.0  209.0     NaN     8.0  4202.0   591.0    SFO\n",
       "SNA              2562.0    NaN     NaN     NaN   562.0   279.0    SNA"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        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>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>AirlineCompany</th>\n",
       "      <th>PricePerTicket</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CLT</td>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "      <td>107.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CLT</td>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "      <td>156.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CLT</td>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CLT</td>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "      <td>349.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CLT</td>\n",
       "      <td>DFW</td>\n",
       "      <td>AA</td>\n",
       "      <td>135.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>SNA</td>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "      <td>295.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>SNA</td>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "      <td>297.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>SNA</td>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "      <td>306.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124872</th>\n",
       "      <td>SNA</td>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124873</th>\n",
       "      <td>SNA</td>\n",
       "      <td>LAS</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124874 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Origin Dest AirlineCompany  PricePerTicket\n",
       "0         CLT  DFW             AA          107.80\n",
       "1         CLT  DFW             AA          156.44\n",
       "2         CLT  DFW             AA          191.18\n",
       "3         CLT  DFW             AA          349.66\n",
       "4         CLT  DFW             AA          135.13\n",
       "...       ...  ...            ...             ...\n",
       "124869    SNA  LAS             WN          295.50\n",
       "124870    SNA  LAS             WN          297.50\n",
       "124871    SNA  LAS             WN          306.00\n",
       "124872    SNA  LAS             WN          113.28\n",
       "124873    SNA  LAS             WN           80.33\n",
       "\n",
       "[124874 rows x 4 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df15=df[[\"Origin\",\"Dest\",\"AirlineCompany\",\"PricePerTicket\"]];df15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sb.lmplot(x=\"total_bill\",y=\"tip\",col=\"time\",hue=\"smoker\",row=\"sex\",data=tips)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th colspan=\"10\" halign=\"left\">ItinID</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">NumTicketsOrdered</th>\n",
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       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>PricePerTicket</th>\n",
       "      <th>50.00</th>\n",
       "      <th>50.12</th>\n",
       "      <th>50.20</th>\n",
       "      <th>50.22</th>\n",
       "      <th>50.24</th>\n",
       "      <th>50.27</th>\n",
       "      <th>50.32</th>\n",
       "      <th>50.34</th>\n",
       "      <th>50.40</th>\n",
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       "      <th>...</th>\n",
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       "      <th>Origin</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">CLT</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SNA</th>\n",
       "      <th>MIA</th>\n",
       "      <th>UA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">ORD</th>\n",
       "      <th>AA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <th>AA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <th>UA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>246 rows × 138753 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            ItinID                                          \\\n",
       "PricePerTicket             50.00   50.12   50.20   50.22   50.24   50.27     \n",
       "Origin Dest AirlineCompany                                                   \n",
       "CLT    DFW  AA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "       LAS  AA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "            WN                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "       LAX  AA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "            WN                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "...                            ...     ...     ...     ...     ...     ...   \n",
       "SNA    MIA  UA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "       ORD  AA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "            UA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "       PHX  AA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "       SFO  UA                 NaN     NaN     NaN     NaN     NaN     NaN   \n",
       "\n",
       "                                                            ...  \\\n",
       "PricePerTicket             50.32   50.34   50.40   50.50    ...   \n",
       "Origin Dest AirlineCompany                                  ...   \n",
       "CLT    DFW  AA                 NaN     NaN     NaN     NaN  ...   \n",
       "       LAS  AA                 NaN     NaN     NaN     NaN  ...   \n",
       "            WN                 NaN     NaN     NaN     NaN  ...   \n",
       "       LAX  AA                 NaN     NaN     NaN     NaN  ...   \n",
       "            WN                 NaN     NaN     NaN     NaN  ...   \n",
       "...                            ...     ...     ...     ...  ...   \n",
       "SNA    MIA  UA                 NaN     NaN     NaN     NaN  ...   \n",
       "       ORD  AA                 NaN     NaN     NaN     NaN  ...   \n",
       "            UA                 NaN     NaN     NaN     NaN  ...   \n",
       "       PHX  AA                 NaN     NaN     NaN     NaN  ...   \n",
       "       SFO  UA                 NaN     NaN     NaN     NaN  ...   \n",
       "\n",
       "                           NumTicketsOrdered                                  \\\n",
       "PricePerTicket                       995.50  995.78  996.00  996.50  997.00    \n",
       "Origin Dest AirlineCompany                                                     \n",
       "CLT    DFW  AA                           NaN     NaN     NaN     NaN     NaN   \n",
       "       LAS  AA                           NaN     NaN     NaN     NaN     NaN   \n",
       "            WN                           NaN     NaN     NaN     NaN     NaN   \n",
       "       LAX  AA                           NaN     NaN     NaN     NaN     NaN   \n",
       "            WN                           NaN     NaN     NaN     NaN     NaN   \n",
       "...                                      ...     ...     ...     ...     ...   \n",
       "SNA    MIA  UA                           NaN     NaN     NaN     NaN     NaN   \n",
       "       ORD  AA                           NaN     NaN     NaN     NaN     NaN   \n",
       "            UA                           NaN     NaN     NaN     NaN     NaN   \n",
       "       PHX  AA                           NaN     NaN     NaN     NaN     NaN   \n",
       "       SFO  UA                           NaN     NaN     NaN     NaN     NaN   \n",
       "\n",
       "                                                                    \n",
       "PricePerTicket             997.70  998.00  998.50  999.00  1000.00  \n",
       "Origin Dest AirlineCompany                                          \n",
       "CLT    DFW  AA                 NaN     NaN     NaN     NaN     NaN  \n",
       "       LAS  AA                 NaN     NaN     NaN     NaN     NaN  \n",
       "            WN                 NaN     NaN     NaN     NaN     NaN  \n",
       "       LAX  AA                 NaN     NaN     NaN     NaN     NaN  \n",
       "            WN                 NaN     NaN     NaN     NaN     NaN  \n",
       "...                            ...     ...     ...     ...     ...  \n",
       "SNA    MIA  UA                 NaN     NaN     NaN     NaN     NaN  \n",
       "       ORD  AA                 NaN     NaN     NaN     NaN     NaN  \n",
       "            UA                 NaN     NaN     NaN     NaN     NaN  \n",
       "       PHX  AA                 NaN     NaN     NaN     NaN     NaN  \n",
       "       SFO  UA                 NaN     NaN     NaN     NaN     NaN  \n",
       "\n",
       "[246 rows x 138753 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df16=df.groupby([\"Origin\",\"Dest\",\"AirlineCompany\",\"PricePerTicket\"])\n",
    "df16.mean().unstack()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "pd.crosstab(df[\"Origin\"],df[\"Dest\"],df[\"PricePerTicket\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ItinID</th>\n",
       "      <th>MktID</th>\n",
       "      <th>MktCoupons</th>\n",
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       "      <th>Origin</th>\n",
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       "      <th>DestWac</th>\n",
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       "      <th>0</th>\n",
       "      <td>2.018183e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
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       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>191.18</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.018200e+10</td>\n",
       "      <td>2.020000e+12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CLT</td>\n",
       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>349.66</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>2.020000e+12</td>\n",
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       "      <td>36</td>\n",
       "      <td>DFW</td>\n",
       "      <td>74</td>\n",
       "      <td>936</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>AA</td>\n",
       "      <td>135.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>124869</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
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       "      <td>LAS</td>\n",
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       "      <td>295.50</td>\n",
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       "    <tr>\n",
       "      <th>124870</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SNA</td>\n",
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       "    <tr>\n",
       "      <th>124871</th>\n",
       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>2.020000e+11</td>\n",
       "      <td>2.020000e+13</td>\n",
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       "      <td>1</td>\n",
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       "      <td>226</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>113.28</td>\n",
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       "      <td>2.020000e+11</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>WN</td>\n",
       "      <td>80.33</td>\n",
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       "  </tbody>\n",
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       "<p>124874 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ItinID         MktID  MktCoupons  Quarter Origin  OriginWac  \\\n",
       "0       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "1       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "2       2.018183e+10  2.020000e+12           1        1    CLT         36   \n",
       "3       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "4       2.018200e+10  2.020000e+12           1        1    CLT         36   \n",
       "...              ...           ...         ...      ...    ...        ...   \n",
       "124869  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124870  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124871  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124872  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "124873  2.020000e+11  2.020000e+13           1        1    SNA         91   \n",
       "\n",
       "       Dest  DestWac  Miles  ContiguousUSA  NumTicketsOrdered AirlineCompany  \\\n",
       "0       DFW       74    936              2                  1             AA   \n",
       "1       DFW       74    936              2                  1             AA   \n",
       "2       DFW       74    936              2                  1             AA   \n",
       "3       DFW       74    936              2                  1             AA   \n",
       "4       DFW       74    936              2                  1             AA   \n",
       "...     ...      ...    ...            ...                ...            ...   \n",
       "124869  LAS       85    226              2                  1             WN   \n",
       "124870  LAS       85    226              2                  1             WN   \n",
       "124871  LAS       85    226              2                  1             WN   \n",
       "124872  LAS       85    226              2                  1             WN   \n",
       "124873  LAS       85    226              2                  1             WN   \n",
       "\n",
       "        PricePerTicket  \n",
       "0               107.80  \n",
       "1               156.44  \n",
       "2               191.18  \n",
       "3               349.66  \n",
       "4               135.13  \n",
       "...                ...  \n",
       "124869          295.50  \n",
       "124870          297.50  \n",
       "124871          306.00  \n",
       "124872          113.28  \n",
       "124873           80.33  \n",
       "\n",
       "[124874 rows x 13 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>AS</th>\n",
       "      <th>B6</th>\n",
       "      <th>DL</th>\n",
       "      <th>UA</th>\n",
       "      <th>WN</th>\n",
       "      <th>NewCol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Origin</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>CLT</th>\n",
       "      <td>2141.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>CLT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DFW</th>\n",
       "      <td>12900.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>506.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DFW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS</th>\n",
       "      <td>2832.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>385.0</td>\n",
       "      <td>1879.0</td>\n",
       "      <td>1916.0</td>\n",
       "      <td>LAS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAX</th>\n",
       "      <td>6401.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>331.0</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>3557.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>LAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGA</th>\n",
       "      <td>6413.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>907.0</td>\n",
       "      <td>3446.0</td>\n",
       "      <td>1672.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>LGA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCO</th>\n",
       "      <td>6018.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1219.0</td>\n",
       "      <td>2676.0</td>\n",
       "      <td>2283.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>MCO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIA</th>\n",
       "      <td>8993.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1810.0</td>\n",
       "      <td>812.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORD</th>\n",
       "      <td>12315.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10366.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ORD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHL</th>\n",
       "      <td>7996.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>PHL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHX</th>\n",
       "      <td>7340.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1352.0</td>\n",
       "      <td>481.0</td>\n",
       "      <td>PHX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SFO</th>\n",
       "      <td>4922.0</td>\n",
       "      <td>205.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2167.0</td>\n",
       "      <td>477.0</td>\n",
       "      <td>SFO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNA</th>\n",
       "      <td>2526.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>287.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>SNA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AirlineCompany       AA     AS      B6      DL       UA      WN NewCol\n",
       "Origin                                                                \n",
       "CLT              2141.0    NaN     NaN     NaN      8.0    64.0    CLT\n",
       "DFW             12900.0    NaN     NaN   150.0    506.0     NaN    DFW\n",
       "LAS              2832.0    6.0     NaN   385.0   1879.0  1916.0    LAS\n",
       "LAX              6401.0   22.0   331.0  1926.0   3557.0  1460.0    LAX\n",
       "LGA              6413.0    NaN   907.0  3446.0   1672.0     3.0    LGA\n",
       "MCO              6018.0    NaN  1219.0  2676.0   2283.0   256.0    MCO\n",
       "MIA              8993.0    NaN     NaN  1810.0    812.0     NaN    MIA\n",
       "ORD             12315.0    NaN     NaN     NaN  10366.0     NaN    ORD\n",
       "PHL              7996.0    NaN     NaN     NaN   1006.0    60.0    PHL\n",
       "PHX              7340.0  191.0     NaN    26.0   1352.0   481.0    PHX\n",
       "SFO              4922.0  205.0     NaN     1.0   2167.0   477.0    SFO\n",
       "SNA              2526.0    NaN     NaN     NaN    287.0   164.0    SNA"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl3 = df[['Origin','AirlineCompany']].value_counts().unstack()\n",
    "pl3['NewCol']=pl3.index\n",
    "pl3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl4 = pl3.plot(kind='bar',figsize=(20,20),xlabel='ORIGIN',ylabel='Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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
}