code/ADS_507_Project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing Python Packages:\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pymysql as mysql\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import getpass\n",
    "import seaborn as sn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax. Perhaps you forgot a comma? (2575916973.py, line 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  Cell \u001b[0;32mIn[103], line 2\u001b[0;36m\u001b[0m\n\u001b[0;31m    conn =mysql.connect(host='localhost',port=int(3306),user='root',passwd= getpass.getpass'Jackimo123',db='Airline')\u001b[0m\n\u001b[0m                                                                            ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax. Perhaps you forgot a comma?\n"
     ]
    }
   ],
   "source": [
    "#Connecting to DataBase\n",
    "conn =mysql.connect(host='localhost',port=int(3306),user='root',passwd=getpass.getpass'',db='Airline')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "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>Unnamed: 0</th>\n",
       "      <th>EventId</th>\n",
       "      <th>Type</th>\n",
       "      <th>Severity</th>\n",
       "      <th>StartTime(UTC)</th>\n",
       "      <th>EndTime(UTC)</th>\n",
       "      <th>Precipitation(in)</th>\n",
       "      <th>TimeZone</th>\n",
       "      <th>AirportCode</th>\n",
       "      <th>LocationLat</th>\n",
       "      <th>LocationLng</th>\n",
       "      <th>City</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>ZipCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>W-1</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 23:14:00</td>\n",
       "      <td>2016-01-07 00:34:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>K04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>W-2</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-07 04:14:00</td>\n",
       "      <td>2016-01-07 04:54:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>K04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>W-3</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-07 05:54:00</td>\n",
       "      <td>2016-01-07 15:34:00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>K04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>W-4</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-08 05:34:00</td>\n",
       "      <td>2016-01-08 05:54:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>K04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>W-5</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-08 13:54:00</td>\n",
       "      <td>2016-01-08 15:54:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>K04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 EventId  Type Severity       StartTime(UTC)  \\\n",
       "0           0     W-1  Snow    Light  2016-01-06 23:14:00   \n",
       "1           1     W-2  Snow    Light  2016-01-07 04:14:00   \n",
       "2           2     W-3  Snow    Light  2016-01-07 05:54:00   \n",
       "3           3     W-4  Snow    Light  2016-01-08 05:34:00   \n",
       "4           4     W-5  Snow    Light  2016-01-08 13:54:00   \n",
       "\n",
       "          EndTime(UTC)  Precipitation(in)     TimeZone AirportCode  \\\n",
       "0  2016-01-07 00:34:00               0.00  US/Mountain        K04V   \n",
       "1  2016-01-07 04:54:00               0.00  US/Mountain        K04V   \n",
       "2  2016-01-07 15:34:00               0.03  US/Mountain        K04V   \n",
       "3  2016-01-08 05:54:00               0.00  US/Mountain        K04V   \n",
       "4  2016-01-08 15:54:00               0.00  US/Mountain        K04V   \n",
       "\n",
       "   LocationLat  LocationLng      City    County State  ZipCode  \n",
       "0      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "1      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "2      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "3      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "4      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading weather data csv file\n",
    "weather_data = pd.read_csv(\"/Users/jackieurenda/Desktop/ADS 507/WeatherUS_2016.csv\")\n",
    "weather_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_df = pd.DataFrame(weather_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0              0\n",
       "EventId                 0\n",
       "Type                    0\n",
       "Severity                0\n",
       "StartTime(UTC)          0\n",
       "EndTime(UTC)            0\n",
       "Precipitation(in)       0\n",
       "TimeZone                0\n",
       "AirportCode             0\n",
       "LocationLat             0\n",
       "LocationLng             0\n",
       "City                 1530\n",
       "County                  0\n",
       "State                   0\n",
       "ZipCode              8497\n",
       "dtype: int64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#city and Zipcode are null\n",
    "\n",
    "weather_df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>EventId</th>\n",
       "      <th>Type</th>\n",
       "      <th>Severity</th>\n",
       "      <th>StartTime(UTC)</th>\n",
       "      <th>EndTime(UTC)</th>\n",
       "      <th>Precipitation(in)</th>\n",
       "      <th>TimeZone</th>\n",
       "      <th>AirportCode</th>\n",
       "      <th>LocationLat</th>\n",
       "      <th>LocationLng</th>\n",
       "      <th>City</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>ZipCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>W-1</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 23:14:00</td>\n",
       "      <td>2016-01-07 00:34:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>W-2</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-07 04:14:00</td>\n",
       "      <td>2016-01-07 04:54:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>W-3</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-07 05:54:00</td>\n",
       "      <td>2016-01-07 15:34:00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>W-4</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-08 05:34:00</td>\n",
       "      <td>2016-01-08 05:54:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>W-5</td>\n",
       "      <td>Snow</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-08 13:54:00</td>\n",
       "      <td>2016-01-08 15:54:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Mountain</td>\n",
       "      <td>04V</td>\n",
       "      <td>38.0972</td>\n",
       "      <td>-106.1689</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>Saguache</td>\n",
       "      <td>CO</td>\n",
       "      <td>81149.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 EventId  Type Severity       StartTime(UTC)  \\\n",
       "0           0     W-1  Snow    Light  2016-01-06 23:14:00   \n",
       "1           1     W-2  Snow    Light  2016-01-07 04:14:00   \n",
       "2           2     W-3  Snow    Light  2016-01-07 05:54:00   \n",
       "3           3     W-4  Snow    Light  2016-01-08 05:34:00   \n",
       "4           4     W-5  Snow    Light  2016-01-08 13:54:00   \n",
       "\n",
       "          EndTime(UTC)  Precipitation(in)     TimeZone AirportCode  \\\n",
       "0  2016-01-07 00:34:00               0.00  US/Mountain         04V   \n",
       "1  2016-01-07 04:54:00               0.00  US/Mountain         04V   \n",
       "2  2016-01-07 15:34:00               0.03  US/Mountain         04V   \n",
       "3  2016-01-08 05:54:00               0.00  US/Mountain         04V   \n",
       "4  2016-01-08 15:54:00               0.00  US/Mountain         04V   \n",
       "\n",
       "   LocationLat  LocationLng      City    County State  ZipCode  \n",
       "0      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "1      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "2      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "3      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "4      38.0972    -106.1689  Saguache  Saguache    CO  81149.0  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dropping K values in front of the Airport Code Column\n",
    "\n",
    "weather_df['AirportCode'] = weather_df['AirportCode'].str[1:]\n",
    "\n",
    "weather_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weather_df[\"Type\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.info of          Unnamed: 0    EventId  Type  Severity       StartTime(UTC)  \\\n",
       "0                 0        W-1  Snow     Light  2016-01-06 23:14:00   \n",
       "1                 1        W-2  Snow     Light  2016-01-07 04:14:00   \n",
       "2                 2        W-3  Snow     Light  2016-01-07 05:54:00   \n",
       "3                 3        W-4  Snow     Light  2016-01-08 05:34:00   \n",
       "4                 4        W-5  Snow     Light  2016-01-08 13:54:00   \n",
       "...             ...        ...   ...       ...                  ...   \n",
       "1185986     7476860  W-7574893  Snow     Light  2016-12-25 18:00:00   \n",
       "1185987     7476861  W-7574894  Snow  Moderate  2016-12-25 18:30:00   \n",
       "1185988     7476862  W-7574895  Snow     Light  2016-12-25 20:16:00   \n",
       "1185989     7476863  W-7574896  Snow     Light  2016-12-31 07:53:00   \n",
       "1185990     7476864  W-7574897   Fog    Severe  2016-12-31 16:10:00   \n",
       "\n",
       "                EndTime(UTC)  Precipitation(in)     TimeZone AirportCode  \\\n",
       "0        2016-01-07 00:34:00               0.00  US/Mountain         04V   \n",
       "1        2016-01-07 04:54:00               0.00  US/Mountain         04V   \n",
       "2        2016-01-07 15:34:00               0.03  US/Mountain         04V   \n",
       "3        2016-01-08 05:54:00               0.00  US/Mountain         04V   \n",
       "4        2016-01-08 15:54:00               0.00  US/Mountain         04V   \n",
       "...                      ...                ...          ...         ...   \n",
       "1185986  2016-12-25 18:30:00               0.01  US/Mountain         BVR   \n",
       "1185987  2016-12-25 20:16:00               0.12  US/Mountain         BVR   \n",
       "1185988  2016-12-26 00:53:00               0.16  US/Mountain         BVR   \n",
       "1185989  2016-12-31 08:22:00               0.00  US/Mountain         BVR   \n",
       "1185990  2016-12-31 16:24:00               0.00  US/Mountain         BVR   \n",
       "\n",
       "         LocationLat  LocationLng      City    County State  ZipCode  \n",
       "0            38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "1            38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "2            38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "3            38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "4            38.0972    -106.1689  Saguache  Saguache    CO  81149.0  \n",
       "...              ...          ...       ...       ...   ...      ...  \n",
       "1185986      42.5833    -108.2833    Lander   Fremont    WY  82520.0  \n",
       "1185987      42.5833    -108.2833    Lander   Fremont    WY  82520.0  \n",
       "1185988      42.5833    -108.2833    Lander   Fremont    WY  82520.0  \n",
       "1185989      42.5833    -108.2833    Lander   Fremont    WY  82520.0  \n",
       "1185990      42.5833    -108.2833    Lander   Fremont    WY  82520.0  \n",
       "\n",
       "[1185991 rows x 15 columns]>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df.info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "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>Code</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6385</td>\n",
       "      <td>6385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>6385</td>\n",
       "      <td>6342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>01A</td>\n",
       "      <td>Doha, Qatar: Al Udeid Air Base</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Code                     Description\n",
       "count   6385                            6385\n",
       "unique  6385                            6342\n",
       "top      01A  Doha, Qatar: Al Udeid Air Base\n",
       "freq       1                               3"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airports_df = pd.read_csv(\"/Users/jackieurenda/Desktop/ADS 507/Airport Code.csv\")\n",
    "airports_df.head()\n",
    "\n",
    "airports_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "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>AirportCode</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01A</td>\n",
       "      <td>Afognak Lake, AK: Afognak Lake Airport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>03A</td>\n",
       "      <td>Granite Mountain, AK: Bear Creek Mining Strip</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04A</td>\n",
       "      <td>Lik, AK: Lik Mining Camp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>05A</td>\n",
       "      <td>Little Squaw, AK: Little Squaw Airport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06A</td>\n",
       "      <td>Kizhuyak, AK: Kizhuyak Bay</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  AirportCode                                    Description\n",
       "0         01A         Afognak Lake, AK: Afognak Lake Airport\n",
       "1         03A  Granite Mountain, AK: Bear Creek Mining Strip\n",
       "2         04A                       Lik, AK: Lik Mining Camp\n",
       "3         05A         Little Squaw, AK: Little Squaw Airport\n",
       "4         06A                     Kizhuyak, AK: Kizhuyak Bay"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Renaming Code column to AirportCode\n",
    "airports_df =airports_df.rename(columns={\"Code\": \"AirportCode\"})\n",
    "\n",
    "airports_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>EventId</th>\n",
       "      <th>Type</th>\n",
       "      <th>Severity</th>\n",
       "      <th>StartTime(UTC)</th>\n",
       "      <th>EndTime(UTC)</th>\n",
       "      <th>Precipitation(in)</th>\n",
       "      <th>TimeZone</th>\n",
       "      <th>AirportCode</th>\n",
       "      <th>LocationLat</th>\n",
       "      <th>LocationLng</th>\n",
       "      <th>City</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>ZipCode</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2228</td>\n",
       "      <td>W-2242</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-05 21:45:00</td>\n",
       "      <td>2016-01-05 22:45:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2229</td>\n",
       "      <td>W-2243</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-05 22:53:00</td>\n",
       "      <td>2016-01-05 23:01:00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2230</td>\n",
       "      <td>W-2244</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 00:10:00</td>\n",
       "      <td>2016-01-06 00:20:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2231</td>\n",
       "      <td>W-2245</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 20:37:00</td>\n",
       "      <td>2016-01-06 20:51:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2232</td>\n",
       "      <td>W-2246</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 21:07:00</td>\n",
       "      <td>2016-01-06 22:58:00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 EventId  Type Severity       StartTime(UTC)  \\\n",
       "0        2228  W-2242  Rain    Light  2016-01-05 21:45:00   \n",
       "1        2229  W-2243  Rain    Light  2016-01-05 22:53:00   \n",
       "2        2230  W-2244  Rain    Light  2016-01-06 00:10:00   \n",
       "3        2231  W-2245  Rain    Light  2016-01-06 20:37:00   \n",
       "4        2232  W-2246  Rain    Light  2016-01-06 21:07:00   \n",
       "\n",
       "          EndTime(UTC)  Precipitation(in)    TimeZone AirportCode  \\\n",
       "0  2016-01-05 22:45:00               0.00  US/Central         AXS   \n",
       "1  2016-01-05 23:01:00               0.03  US/Central         AXS   \n",
       "2  2016-01-06 00:20:00               0.00  US/Central         AXS   \n",
       "3  2016-01-06 20:51:00               0.00  US/Central         AXS   \n",
       "4  2016-01-06 22:58:00               0.03  US/Central         AXS   \n",
       "\n",
       "   LocationLat  LocationLng   City   County State  ZipCode  \\\n",
       "0      34.6986     -99.3381  Altus  Jackson    OK  73521.0   \n",
       "1      34.6986     -99.3381  Altus  Jackson    OK  73521.0   \n",
       "2      34.6986     -99.3381  Altus  Jackson    OK  73521.0   \n",
       "3      34.6986     -99.3381  Altus  Jackson    OK  73521.0   \n",
       "4      34.6986     -99.3381  Altus  Jackson    OK  73521.0   \n",
       "\n",
       "                                 Description  \n",
       "0  Altus, OK: Altus/Quartz Mountain Regional  \n",
       "1  Altus, OK: Altus/Quartz Mountain Regional  \n",
       "2  Altus, OK: Altus/Quartz Mountain Regional  \n",
       "3  Altus, OK: Altus/Quartz Mountain Regional  \n",
       "4  Altus, OK: Altus/Quartz Mountain Regional  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merging Datasets (Filtering)\n",
    "\n",
    "weather_data_filtered = pd.merge(weather_df, airports_df, on=\"AirportCode\")\n",
    "\n",
    "weather_data_filtered.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "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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       "    }\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AirportCode</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AXS</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AXS</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AXS</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AXS</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AXS</td>\n",
       "      <td>Altus, OK: Altus/Quartz Mountain Regional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  AirportCode                                Description\n",
       "0         AXS  Altus, OK: Altus/Quartz Mountain Regional\n",
       "1         AXS  Altus, OK: Altus/Quartz Mountain Regional\n",
       "2         AXS  Altus, OK: Altus/Quartz Mountain Regional\n",
       "3         AXS  Altus, OK: Altus/Quartz Mountain Regional\n",
       "4         AXS  Altus, OK: Altus/Quartz Mountain Regional"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airport_df_new = weather_data_filtered[['AirportCode', 'Description']]\n",
    "airport_df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EventId</th>\n",
       "      <th>Type</th>\n",
       "      <th>Severity</th>\n",
       "      <th>StartTime(UTC)</th>\n",
       "      <th>EndTime(UTC)</th>\n",
       "      <th>Precipitation(in)</th>\n",
       "      <th>TimeZone</th>\n",
       "      <th>AirportCode</th>\n",
       "      <th>LocationLat</th>\n",
       "      <th>LocationLng</th>\n",
       "      <th>City</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>ZipCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>W-2242</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-05 21:45:00</td>\n",
       "      <td>2016-01-05 22:45:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>W-2243</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-05 22:53:00</td>\n",
       "      <td>2016-01-05 23:01:00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>W-2244</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 00:10:00</td>\n",
       "      <td>2016-01-06 00:20:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>W-2245</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 20:37:00</td>\n",
       "      <td>2016-01-06 20:51:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>W-2246</td>\n",
       "      <td>Rain</td>\n",
       "      <td>Light</td>\n",
       "      <td>2016-01-06 21:07:00</td>\n",
       "      <td>2016-01-06 22:58:00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>US/Central</td>\n",
       "      <td>AXS</td>\n",
       "      <td>34.6986</td>\n",
       "      <td>-99.3381</td>\n",
       "      <td>Altus</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>OK</td>\n",
       "      <td>73521.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  EventId  Type Severity       StartTime(UTC)         EndTime(UTC)  \\\n",
       "0  W-2242  Rain    Light  2016-01-05 21:45:00  2016-01-05 22:45:00   \n",
       "1  W-2243  Rain    Light  2016-01-05 22:53:00  2016-01-05 23:01:00   \n",
       "2  W-2244  Rain    Light  2016-01-06 00:10:00  2016-01-06 00:20:00   \n",
       "3  W-2245  Rain    Light  2016-01-06 20:37:00  2016-01-06 20:51:00   \n",
       "4  W-2246  Rain    Light  2016-01-06 21:07:00  2016-01-06 22:58:00   \n",
       "\n",
       "   Precipitation(in)    TimeZone AirportCode  LocationLat  LocationLng   City  \\\n",
       "0               0.00  US/Central         AXS      34.6986     -99.3381  Altus   \n",
       "1               0.03  US/Central         AXS      34.6986     -99.3381  Altus   \n",
       "2               0.00  US/Central         AXS      34.6986     -99.3381  Altus   \n",
       "3               0.00  US/Central         AXS      34.6986     -99.3381  Altus   \n",
       "4               0.03  US/Central         AXS      34.6986     -99.3381  Altus   \n",
       "\n",
       "    County State  ZipCode  \n",
       "0  Jackson    OK  73521.0  \n",
       "1  Jackson    OK  73521.0  \n",
       "2  Jackson    OK  73521.0  \n",
       "3  Jackson    OK  73521.0  \n",
       "4  Jackson    OK  73521.0  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#drop description for weather_filtered data\n",
    "\n",
    "weather_data_new = weather_data_filtered.drop(columns=[\"Unnamed: 0\", \"Description\"])\n",
    "\n",
    "weather_data_new.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Data filtering between the weather data and airports code dataset reduced data instances from 1,185,991 to 763,320"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1345\n",
      "1345\n"
     ]
    }
   ],
   "source": [
    "uniqueValues_weather = weather_data_new['AirportCode'].nunique()\n",
    "print(uniqueValues_weather)\n",
    "\n",
    "uniqueValues_airports = airport_df_new['AirportCode'].nunique()\n",
    "print(uniqueValues_airports)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/51/q9hxxxv54rs_ms2xxv3y82fm0000gn/T/ipykernel_10524/957063789.py:1: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  tableNames = pd.read_sql(\"\"\"SHOW TABLES\"\"\", conn)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tables_in_airline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>l_airline_id</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>l_airport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>l_airport_id</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>l_airport_seq_id</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>l_cancellation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>l_city_market_id</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>l_deparrblk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>l_distance_group_250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>l_diversions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>l_months</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>l_ontime_delay_groups</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>l_quarters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>l_state_abr_aviation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>l_state_fips</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>l_unique_carriers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>l_weekdays</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>l_world_area_codes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>l_yesno_resp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>on_time_performance_2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>weatherus_2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Tables_in_airline\n",
       "0               l_airline_id\n",
       "1                  l_airport\n",
       "2               l_airport_id\n",
       "3           l_airport_seq_id\n",
       "4             l_cancellation\n",
       "5           l_city_market_id\n",
       "6                l_deparrblk\n",
       "7       l_distance_group_250\n",
       "8               l_diversions\n",
       "9                   l_months\n",
       "10     l_ontime_delay_groups\n",
       "11                l_quarters\n",
       "12      l_state_abr_aviation\n",
       "13              l_state_fips\n",
       "14         l_unique_carriers\n",
       "15                l_weekdays\n",
       "16        l_world_area_codes\n",
       "17              l_yesno_resp\n",
       "18  on_time_performance_2016\n",
       "19            weatherus_2016"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tableNames = pd.read_sql(\"\"\"SHOW TABLES\"\"\", conn)\n",
    "tableNames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/51/q9hxxxv54rs_ms2xxv3y82fm0000gn/T/ipykernel_10524/3202433327.py:6: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  rename_table = pd.read_sql(\"ALTER TABLE on_time_performance_2016_1 RENAME to on_time_performance_2016\", conn)\n"
     ]
    },
    {
     "ename": "DatabaseError",
     "evalue": "Execution failed on sql 'ALTER TABLE on_time_performance_2016_1 RENAME to on_time_performance_2016': (1146, \"Table 'airline.on_time_performance_2016_1' doesn't exist\")",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mProgrammingError\u001b[0m                          Traceback (most recent call last)",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/io/sql.py:2018\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2017\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 2018\u001b[0m     cur\u001b[39m.\u001b[39;49mexecute(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   2019\u001b[0m     \u001b[39mreturn\u001b[39;00m cur\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/cursors.py:148\u001b[0m, in \u001b[0;36mCursor.execute\u001b[0;34m(self, query, args)\u001b[0m\n\u001b[1;32m    146\u001b[0m query \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmogrify(query, args)\n\u001b[0;32m--> 148\u001b[0m result \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_query(query)\n\u001b[1;32m    149\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_executed \u001b[39m=\u001b[39m query\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/cursors.py:310\u001b[0m, in \u001b[0;36mCursor._query\u001b[0;34m(self, q)\u001b[0m\n\u001b[1;32m    309\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_clear_result()\n\u001b[0;32m--> 310\u001b[0m conn\u001b[39m.\u001b[39;49mquery(q)\n\u001b[1;32m    311\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_do_get_result()\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/connections.py:548\u001b[0m, in \u001b[0;36mConnection.query\u001b[0;34m(self, sql, unbuffered)\u001b[0m\n\u001b[1;32m    547\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_execute_command(COMMAND\u001b[39m.\u001b[39mCOM_QUERY, sql)\n\u001b[0;32m--> 548\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_affected_rows \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_read_query_result(unbuffered\u001b[39m=\u001b[39;49munbuffered)\n\u001b[1;32m    549\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_affected_rows\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/connections.py:775\u001b[0m, in \u001b[0;36mConnection._read_query_result\u001b[0;34m(self, unbuffered)\u001b[0m\n\u001b[1;32m    774\u001b[0m     result \u001b[39m=\u001b[39m MySQLResult(\u001b[39mself\u001b[39m)\n\u001b[0;32m--> 775\u001b[0m     result\u001b[39m.\u001b[39;49mread()\n\u001b[1;32m    776\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_result \u001b[39m=\u001b[39m result\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/connections.py:1156\u001b[0m, in \u001b[0;36mMySQLResult.read\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1155\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 1156\u001b[0m     first_packet \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mconnection\u001b[39m.\u001b[39;49m_read_packet()\n\u001b[1;32m   1158\u001b[0m     \u001b[39mif\u001b[39;00m first_packet\u001b[39m.\u001b[39mis_ok_packet():\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/connections.py:725\u001b[0m, in \u001b[0;36mConnection._read_packet\u001b[0;34m(self, packet_type)\u001b[0m\n\u001b[1;32m    724\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_result\u001b[39m.\u001b[39munbuffered_active \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[0;32m--> 725\u001b[0m     packet\u001b[39m.\u001b[39;49mraise_for_error()\n\u001b[1;32m    726\u001b[0m \u001b[39mreturn\u001b[39;00m packet\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/protocol.py:221\u001b[0m, in \u001b[0;36mMysqlPacket.raise_for_error\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    220\u001b[0m     \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39merrno =\u001b[39m\u001b[39m\"\u001b[39m, errno)\n\u001b[0;32m--> 221\u001b[0m err\u001b[39m.\u001b[39;49mraise_mysql_exception(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_data)\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pymysql/err.py:143\u001b[0m, in \u001b[0;36mraise_mysql_exception\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m    142\u001b[0m     errorclass \u001b[39m=\u001b[39m InternalError \u001b[39mif\u001b[39;00m errno \u001b[39m<\u001b[39m \u001b[39m1000\u001b[39m \u001b[39melse\u001b[39;00m OperationalError\n\u001b[0;32m--> 143\u001b[0m \u001b[39mraise\u001b[39;00m errorclass(errno, errval)\n",
      "\u001b[0;31mProgrammingError\u001b[0m: (1146, \"Table 'airline.on_time_performance_2016_1' doesn't exist\")",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mDatabaseError\u001b[0m                             Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[23], line 6\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39m#Renaming the Table in DataBase\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \n\u001b[1;32m      3\u001b[0m \n\u001b[1;32m      4\u001b[0m   \n\u001b[1;32m      5\u001b[0m \u001b[39m# MySQL query for for renaming a table\u001b[39;00m\n\u001b[0;32m----> 6\u001b[0m rename_table \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39;49mread_sql(\u001b[39m\"\u001b[39;49m\u001b[39mALTER TABLE on_time_performance_2016_1 RENAME to on_time_performance_2016\u001b[39;49m\u001b[39m\"\u001b[39;49m, conn)\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/io/sql.py:564\u001b[0m, in \u001b[0;36mread_sql\u001b[0;34m(sql, con, index_col, coerce_float, params, parse_dates, columns, chunksize)\u001b[0m\n\u001b[1;32m    561\u001b[0m pandas_sql \u001b[39m=\u001b[39m pandasSQL_builder(con)\n\u001b[1;32m    563\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(pandas_sql, SQLiteDatabase):\n\u001b[0;32m--> 564\u001b[0m     \u001b[39mreturn\u001b[39;00m pandas_sql\u001b[39m.\u001b[39;49mread_query(\n\u001b[1;32m    565\u001b[0m         sql,\n\u001b[1;32m    566\u001b[0m         index_col\u001b[39m=\u001b[39;49mindex_col,\n\u001b[1;32m    567\u001b[0m         params\u001b[39m=\u001b[39;49mparams,\n\u001b[1;32m    568\u001b[0m         coerce_float\u001b[39m=\u001b[39;49mcoerce_float,\n\u001b[1;32m    569\u001b[0m         parse_dates\u001b[39m=\u001b[39;49mparse_dates,\n\u001b[1;32m    570\u001b[0m         chunksize\u001b[39m=\u001b[39;49mchunksize,\n\u001b[1;32m    571\u001b[0m     )\n\u001b[1;32m    573\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m    574\u001b[0m     _is_table_name \u001b[39m=\u001b[39m pandas_sql\u001b[39m.\u001b[39mhas_table(sql)\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/io/sql.py:2078\u001b[0m, in \u001b[0;36mSQLiteDatabase.read_query\u001b[0;34m(self, sql, index_col, coerce_float, params, parse_dates, chunksize, dtype)\u001b[0m\n\u001b[1;32m   2066\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mread_query\u001b[39m(\n\u001b[1;32m   2067\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m   2068\u001b[0m     sql,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2074\u001b[0m     dtype: DtypeArg \u001b[39m|\u001b[39m \u001b[39mNone\u001b[39;00m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m,\n\u001b[1;32m   2075\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m DataFrame \u001b[39m|\u001b[39m Iterator[DataFrame]:\n\u001b[1;32m   2077\u001b[0m     args \u001b[39m=\u001b[39m _convert_params(sql, params)\n\u001b[0;32m-> 2078\u001b[0m     cursor \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mexecute(\u001b[39m*\u001b[39;49margs)\n\u001b[1;32m   2079\u001b[0m     columns \u001b[39m=\u001b[39m [col_desc[\u001b[39m0\u001b[39m] \u001b[39mfor\u001b[39;00m col_desc \u001b[39min\u001b[39;00m cursor\u001b[39m.\u001b[39mdescription]\n\u001b[1;32m   2081\u001b[0m     \u001b[39mif\u001b[39;00m chunksize \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/io/sql.py:2030\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2027\u001b[0m     \u001b[39mraise\u001b[39;00m ex \u001b[39mfrom\u001b[39;00m \u001b[39minner_exc\u001b[39;00m\n\u001b[1;32m   2029\u001b[0m ex \u001b[39m=\u001b[39m DatabaseError(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mExecution failed on sql \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00margs[\u001b[39m0\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m: \u001b[39m\u001b[39m{\u001b[39;00mexc\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[0;32m-> 2030\u001b[0m \u001b[39mraise\u001b[39;00m ex \u001b[39mfrom\u001b[39;00m \u001b[39mexc\u001b[39;00m\n",
      "\u001b[0;31mDatabaseError\u001b[0m: Execution failed on sql 'ALTER TABLE on_time_performance_2016_1 RENAME to on_time_performance_2016': (1146, \"Table 'airline.on_time_performance_2016_1' doesn't exist\")"
     ]
    }
   ],
   "source": [
    "#Renaming the Table in DataBase\n",
    "\n",
    "\n",
    "  \n",
    "# MySQL query for for renaming a table\n",
    "rename_table = pd.read_sql(\"ALTER TABLE on_time_performance_2016_1 RENAME to on_time_performance_2016\", conn)\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/51/q9hxxxv54rs_ms2xxv3y82fm0000gn/T/ipykernel_10524/3406315267.py:1: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  on_time_performance = pd.read_sql_query('SELECT * FROM on_time_performance_2016', conn)\n"
     ]
    }
   ],
   "source": [
    "on_time_performance = pd.read_sql_query('SELECT * FROM on_time_performance_2016', conn)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>FlightDate</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>AirlineID</th>\n",
       "      <th>Carrier</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>...</th>\n",
       "      <th>Div1TotalGTime</th>\n",
       "      <th>Div1LongestGTime</th>\n",
       "      <th>Div1WheelsOff</th>\n",
       "      <th>Div1TailNum</th>\n",
       "      <th>Div2Airport</th>\n",
       "      <th>Div2AirportID</th>\n",
       "      <th>Div2AirportSeqID</th>\n",
       "      <th>Div2WheelsOn</th>\n",
       "      <th>Div2TotalGTime</th>\n",
       "      <th>Div2LongestGTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-01-06</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N4YBAA</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>None</td>\n",
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       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-01-07</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N434AA</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2016-01-08</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N541AA</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>2016-01-09</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N489AA</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>2016-01-10</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N439AA</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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>5 rows × 83 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Quarter  Month  DayofMonth  DayOfWeek  FlightDate UniqueCarrier  \\\n",
       "0  2016        1      1           6          3  2016-01-06            AA   \n",
       "1  2016        1      1           7          4  2016-01-07            AA   \n",
       "2  2016        1      1           8          5  2016-01-08            AA   \n",
       "3  2016        1      1           9          6  2016-01-09            AA   \n",
       "4  2016        1      1          10          7  2016-01-10            AA   \n",
       "\n",
       "   AirlineID Carrier TailNum  ...  Div1TotalGTime  Div1LongestGTime  \\\n",
       "0      19805      AA  N4YBAA  ...             NaN               NaN   \n",
       "1      19805      AA  N434AA  ...             NaN               NaN   \n",
       "2      19805      AA  N541AA  ...             NaN               NaN   \n",
       "3      19805      AA  N489AA  ...             NaN               NaN   \n",
       "4      19805      AA  N439AA  ...             NaN               NaN   \n",
       "\n",
       "   Div1WheelsOff  Div1TailNum Div2Airport Div2AirportID Div2AirportSeqID  \\\n",
       "0            NaN         None        None           NaN              NaN   \n",
       "1            NaN         None        None           NaN              NaN   \n",
       "2            NaN         None        None           NaN              NaN   \n",
       "3            NaN         None        None           NaN              NaN   \n",
       "4            NaN         None        None           NaN              NaN   \n",
       "\n",
       "   Div2WheelsOn Div2TotalGTime  Div2LongestGTime  \n",
       "0           NaN            NaN               NaN  \n",
       "1           NaN            NaN               NaN  \n",
       "2           NaN            NaN               NaN  \n",
       "3           NaN            NaN               NaN  \n",
       "4           NaN            NaN               NaN  \n",
       "\n",
       "[5 rows x 83 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "on_time_performance.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dropping Uneccesary columns in on time performance dataset\n",
    "\n",
    "on_time_performance_df2 = on_time_performance[on_time_performance.columns[5:58]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>FlightDate</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>AirlineID</th>\n",
       "      <th>Carrier</th>\n",
       "      <th>TailNum</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>OriginAirportID</th>\n",
       "      <th>OriginAirportSeqID</th>\n",
       "      <th>OriginCityMarketID</th>\n",
       "      <th>Origin</th>\n",
       "      <th>...</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>ActualElapsedTime</th>\n",
       "      <th>AirTime</th>\n",
       "      <th>Flights</th>\n",
       "      <th>Distance</th>\n",
       "      <th>DistanceGroup</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-06</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N4YBAA</td>\n",
       "      <td>43</td>\n",
       "      <td>11298</td>\n",
       "      <td>1129804</td>\n",
       "      <td>30194</td>\n",
       "      <td>DFW</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>986.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-07</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N434AA</td>\n",
       "      <td>43</td>\n",
       "      <td>11298</td>\n",
       "      <td>1129804</td>\n",
       "      <td>30194</td>\n",
       "      <td>DFW</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>986.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-08</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N541AA</td>\n",
       "      <td>43</td>\n",
       "      <td>11298</td>\n",
       "      <td>1129804</td>\n",
       "      <td>30194</td>\n",
       "      <td>DFW</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>986.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-09</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N489AA</td>\n",
       "      <td>43</td>\n",
       "      <td>11298</td>\n",
       "      <td>1129804</td>\n",
       "      <td>30194</td>\n",
       "      <td>DFW</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>986.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-10</td>\n",
       "      <td>AA</td>\n",
       "      <td>19805</td>\n",
       "      <td>AA</td>\n",
       "      <td>N439AA</td>\n",
       "      <td>43</td>\n",
       "      <td>11298</td>\n",
       "      <td>1129804</td>\n",
       "      <td>30194</td>\n",
       "      <td>DFW</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>986.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   FlightDate UniqueCarrier  AirlineID Carrier TailNum  FlightNum  \\\n",
       "0  2016-01-06            AA      19805      AA  N4YBAA         43   \n",
       "1  2016-01-07            AA      19805      AA  N434AA         43   \n",
       "2  2016-01-08            AA      19805      AA  N541AA         43   \n",
       "3  2016-01-09            AA      19805      AA  N489AA         43   \n",
       "4  2016-01-10            AA      19805      AA  N439AA         43   \n",
       "\n",
       "   OriginAirportID  OriginAirportSeqID  OriginCityMarketID Origin  ...  \\\n",
       "0            11298             1129804               30194    DFW  ...   \n",
       "1            11298             1129804               30194    DFW  ...   \n",
       "2            11298             1129804               30194    DFW  ...   \n",
       "3            11298             1129804               30194    DFW  ...   \n",
       "4            11298             1129804               30194    DFW  ...   \n",
       "\n",
       "  CancellationCode Diverted  CRSElapsedTime ActualElapsedTime  AirTime  \\\n",
       "0             None        0           158.0             155.0    132.0   \n",
       "1             None        0           158.0             150.0    126.0   \n",
       "2             None        0           158.0             170.0    135.0   \n",
       "3             None        0           158.0             151.0    129.0   \n",
       "4             None        0           158.0             171.0    137.0   \n",
       "\n",
       "   Flights  Distance  DistanceGroup CarrierDelay WeatherDelay  \n",
       "0      1.0     986.0              4          NaN          NaN  \n",
       "1      1.0     986.0              4          NaN          NaN  \n",
       "2      1.0     986.0              4          NaN          NaN  \n",
       "3      1.0     986.0              4          NaN          NaN  \n",
       "4      1.0     986.0              4          0.0          0.0  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "on_time_performance_df2.head()"
   ]
  }
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