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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\wipar\\AppData\\Local\\Temp\\ipykernel_16160\\3701237280.py:1: DtypeWarning: Columns (77,84) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  raw_airport_dataset = pd.read_csv(os.path.join(\"data_cleaning/flight_data_raw/2021/On_Time_Reporting_Carrier_On_Time_Performance_(1987_present)_2021_1.csv\"))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Year                  int64\n",
      "Quarter               int64\n",
      "Month                 int64\n",
      "DayofMonth            int64\n",
      "DayOfWeek             int64\n",
      "                     ...   \n",
      "Div5TotalGTime      float64\n",
      "Div5LongestGTime    float64\n",
      "Div5WheelsOff       float64\n",
      "Div5TailNum         float64\n",
      "Unnamed: 109        float64\n",
      "Length: 110, dtype: object\n"
     ]
    }
   ],
   "source": [
    "raw_airport_dataset = pd.read_csv(os.path.join(\"data_cleaning/flight_data_raw/2021/On_Time_Reporting_Carrier_On_Time_Performance_(1987_present)_2021_1.csv\"))\n",
    "\n",
    "print(raw_airport_dataset.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time                   object\n",
      "Origin                 object\n",
      "Dest                   object\n",
      "Carrier                object\n",
      "Cancelled                bool\n",
      "CancellationReason     object\n",
      "Delayed                  bool\n",
      "DepDelayMinutes       float64\n",
      "CarrierDelay          float64\n",
      "WeatherDelay          float64\n",
      "NASDelay              float64\n",
      "SecurityDelay         float64\n",
      "LateAircraftDelay     float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "clean_airport_dataset = pd.read_csv(os.path.join(\"data_cleaning/flight_data_with_time/2021/On_Time_Reporting_Carrier_On_Time_Performance_(1987_present)_2021_1.csv\"))\n",
    "\n",
    "print(clean_airport_dataset.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "station               object\n",
      "valid                 object\n",
      "tmpf                  object\n",
      "dwpf                  object\n",
      "relh                  object\n",
      "drct                  object\n",
      "sknt                  object\n",
      "p01i                  object\n",
      "alti                 float64\n",
      "mslp                  object\n",
      "vsby                  object\n",
      "gust                  object\n",
      "skyc1                 object\n",
      "skyc2                 object\n",
      "skyc3                 object\n",
      "skyc4                 object\n",
      "skyl1                 object\n",
      "skyl2                 object\n",
      "skyl3                 object\n",
      "skyl4                 object\n",
      "wxcodes               object\n",
      "ice_accretion_1hr     object\n",
      "ice_accretion_3hr     object\n",
      "ice_accretion_6hr     object\n",
      "peak_wind_gust        object\n",
      "peak_wind_drct        object\n",
      "peak_wind_time        object\n",
      "feel                  object\n",
      "metar                 object\n",
      "snowdepth             object\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "raw_weather_dataset = pd.read_csv(os.path.join(\"data_cleaning/weather_raw/ATL.csv\"))\n",
    "\n",
    "print(raw_weather_dataset.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time                       object\n",
      "Origin                     object\n",
      "Temperature               float64\n",
      "Feels_Like_Temperature    float64\n",
      "Altimeter_Pressure        float64\n",
      "Sea_Level_Pressure        float64\n",
      "Visibility                float64\n",
      "Wind_Speed                float64\n",
      "Wind_Gust                 float64\n",
      "Precipitation             float64\n",
      "Ice_Accretion_3hr         float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "combined_weather_dataset = pd.read_csv(os.path.join(\"data_cleaning/combined_weather.csv\"))\n",
    "\n",
    "print(combined_weather_dataset.dtypes)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
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 },
 "nbformat": 4,
 "nbformat_minor": 2
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