eda_task4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.options.mode.chained_assignment = None  # default='warn'\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#drop the unnamed columns that was created\n",
    "flights_no_outlier = pd.read_csv('data/flights_no_outlier_iqr.csv')\\\n",
    "                    .drop(columns=['Unnamed: 0','Unnamed: 0.1'],axis=1)\n",
    "passengers = pd.read_csv('data/passengers_cleaned.csv').drop(columns=['Unnamed: 0'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#function to change integer time to standard time in string\n",
    "def time_row(row):\n",
    "    row_int = int(row)\n",
    "    row_str = str(row_int)\n",
    "    len_row = len(row_str)\n",
    "    if len_row == 1:\n",
    "        minute = '00'\n",
    "        hour = row_str\n",
    "        row = hour + ':' + minute\n",
    "    if len_row == 2:\n",
    "        minute =  '0'+ row_str[1]\n",
    "        hour = row_str[0]\n",
    "        row = hour + ':' + minute\n",
    "    if len_row == 3:\n",
    "        minute = row_str[1]+row_str[2]\n",
    "        hour = row_str[0]\n",
    "        row = hour + ':' + minute\n",
    "    elif len_row == 4:\n",
    "        minute = row_str[2] + row_str[3]\n",
    "        hour = row_str[0] + row_str[1]\n",
    "        row = hour + ':' + minute\n",
    "        if row == '24:00':\n",
    "            row = '23:59'\n",
    "    return str(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#applyting the function and changing to format to date and time\n",
    "flights_no_outlier['dep_time_format'] = flights_no_outlier['dep_time'].apply(time_row)\n",
    "\n",
    "flights_no_outlier['dep_time_format'] = pd.to_datetime(\\\n",
    "                                                       flights_no_outlier['dep_time_format'],\\\n",
    "                                                       format='%H:%M').dt.time\n",
    "\n",
    "taxi_out_mean_hour = flights_no_outlier.groupby(by=[flights_no_outlier\\\n",
    "                                                    .dep_time_format.map(\\\n",
    "                                                    lambda x : (x.hour))])['taxi_out'].mean()\n",
    "number_of_departures = flights_no_outlier.groupby(by=[flights_no_outlier.dep_time_format.map(lambda x : (x.hour))])['taxi_out'].count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "fig.suptitle('Average Taxi-out(left), Number Of Departures(right)')\n",
    "\n",
    "#average departures\n",
    "sns.barplot(ax=axes[0], x=taxi_out_mean_hour.index, y=taxi_out_mean_hour.values,color='b')\n",
    "axes[0].set_title('Average Taxi-out Time For Different Hours')\n",
    "axes[0].set_xlabel('Hours Of the Day')\n",
    "axes[0].set_ylabel('Average Time(min)')\n",
    "#number of flights\n",
    "sns.barplot(ax=axes[1], x=number_of_departures.index, y=number_of_departures.values,color='b')\n",
    "axes[1].set_title('Number Of Departures For Different Hours')\n",
    "axes[1].set_xlabel('Hours Of The Day')\n",
    "axes[1].set_ylabel('Number Of Flights')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Applying the function for arrival times and changing the format to date and time\n",
    "flights_no_outlier['arrival_time_format'] = flights_no_outlier['arr_time'].apply(time_row)\n",
    "\n",
    "flights_no_outlier['arrival_time_format'] = pd.to_datetime(\\\n",
    "                                            flights_no_outlier['arrival_time_format'],\\\n",
    "                                            format='%H:%M').dt.time\n",
    "\n",
    "taxi_in_mean_hour = flights_no_outlier.groupby(by=[flights_no_outlier\\\n",
    "                                                   .arrival_time_format.map(\\\n",
    "                                                    lambda x : (x.hour))])['taxi_in'].mean()\n",
    "number_of_arrivals = flights_no_outlier.groupby(by=[flights_no_outlier.arrival_time_format.map(lambda x : (x.hour))])['taxi_in'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "fig.suptitle('Average Taxi-in(left), Number Of Arrivals(right)')\n",
    "\n",
    "#average departures\n",
    "sns.barplot(ax=axes[0], x=taxi_in_mean_hour.index, y=taxi_in_mean_hour.values,color='b')\n",
    "axes[0].set_title('Average Taxi-in Time For Different Hours')\n",
    "axes[0].set_xlabel('Hours Of the Day')\n",
    "axes[0].set_ylabel('Average Time(min)')\n",
    "#number of flights\n",
    "sns.barplot(ax=axes[1], x=number_of_arrivals.index, y=number_of_arrivals.values,color='b')\n",
    "axes[1].set_title('Number Of Arrivals For Different Hours')\n",
    "axes[1].set_xlabel('Hours Of The Daye')\n",
    "axes[1].set_ylabel('Number Of Flights')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 774,
   "metadata": {},
   "outputs": [],
   "source": [
    "#exporting the data frame which contains time\n",
    "#flights_no_outlier.to_csv('data/flights_no_outlier_iqr_time.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "flights_no_outlier.loc[flights_no_outlier.dep_time == 614]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "bootcamp",
   "language": "python",
   "name": "bootcamp"
  },
  "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
}