final-project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predicting flight status using supervised learning algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## I. Project Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysis of flight status is important for both flight companies and clients. For companies, sufficent advance preparations before the flight delay high-occurrence seasons are helpful in flight organization and emergence prevention. For clients and customers, an advance estimation about the flight delay or cancellation could give them advice on schdual planning and insurrance purchase. \n",
    "<br>\n",
    "<br>\n",
    "For this project, I plan to use the U.S. flgiht database of year 2008 to predict whether a flight would be on-time or delayed or even cancelled according to the flgiht information such as dates, carriers and schedueled departure time.    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## II. Outline and goals for the project"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 1. Basic information about the flight dataset.\n",
    "* 2. Define the prediction target---the flight status.\n",
    "* 3. Filter out the focused features.\n",
    "* 4. Make prediction about the flight status using supervised learning classifiers.\n",
    "* 5. Analysis how selection of features may affect the selection of models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## III. Basic information about the flight dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) Background of the data\n",
    "\n",
    "\n",
    "* The dataset is published on the open data souce Kaggle.\n",
    "* It is collected by the U.S. Department of Transportation's (DOT) Bureau of Transportation Statistics (BTS). They track the on-time performance of domestic flights operated by large air carriers.\n",
    "* This dataset is only for year 2008.\n",
    "* Summary information on the number of on-time, delayed, canceled and diverted flights appears in DOT's monthly air Traval Consumer Report, published about 30 days after the month's end, as well as in summary tables posted on this website.\n",
    "* BTS began collecting details on the causes of flight delays in June 2003. Summary statistics and raw data are made avaiable to the public at the time the Air Travle Consumer Report is released. \n",
    "* *The above information is from Kaggle. https://www.kaggle.com/giovamata/airlinedelaycauses*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) Links to the Airlines Arrival Delay Dataset\n",
    "* Data Introduction: https://www.kaggle.com/giovamata/airlinedelaycauses\n",
    "* Data Download: https://www.kaggle.com/giovamata/airlinedelaycauses/download"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The direct downloadlink to the Kaggle data set\n",
    "data_url='https://www.kaggle.com/giovamata/airlinedelaycauses/download'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3) Import the eccential modules "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Currently, I only need the _pandas_, _numpy_, _matplotlib_ ,and _seaborn_ .\n",
    "* The _scikitlearn_ et.al. will be imported later "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import PercentFormatter #To make the y-axis(proportion) shown in percentage\n",
    "import seaborn as sns\n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4) Import the local dataset\n",
    "* I've downloaded the dataset in advance to save time;\n",
    "* The name of the dataset is DelayedFlights.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_airline=pd.read_csv('DelayedFlights.csv') #Load the csv file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5) Display the basic information of the dataset.\n",
    "* The dataset contains **1936758** rows and **30** columns\n",
    "* The column names are as listed.\n",
    "* The meaning of each column can be found on the website http://stat-computing.org/dataexpo/2009/the-data.html\n",
    "* Here are some need-to-note details of them:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Column Name       | Details                                                                   |\n",
    "|-------------------|---------------------------------------------------------------------------|\n",
    "| DayOfWeek         | 1 (Monday) - 7 (Sunday)                                                   |\n",
    "| DepTime           | actual departure time (local, hhmm)                                       |\n",
    "| CRSDepTime        | scheduled departure time (local, hhmm)                                    |\n",
    "| ArrTime           | actual arrival time (local, hhmm)                                         |\n",
    "| CRSArrTime        | scheduled arrival time (local, hhmm)                                      |\n",
    "| ActualElapsedTime | in minutes                                                                |\n",
    "| CRSElapsedTime    | in minutes                                                                |\n",
    "| AirTime           | in minutes                                                                |\n",
    "| ArrDelay          | arrival delay, in minutes                                                 |\n",
    "| DepDelay          | departure delay, in minutes                                               |\n",
    "| Distance          | in miles                                                                  |\n",
    "| TaxiIn            | taxi in time, in minutes                                                  |\n",
    "| TaxiOut           | taxi out time in minutes                                                  |\n",
    "| Cancelled         | was the flight cancelled?                                                 |\n",
    "| CancellationCode  | reason for cancellation (A = carrier, B = weather, C = NAS, D = security) |\n",
    "| Diverted          | 1 = yes, 0 = no                                                           |\n",
    "| CarrierDelay      | in minutes                                                                |\n",
    "| WeatherDelay      | in minutes                                                                |\n",
    "| NASDelay          | in minutes                                                                |\n",
    "| SecurityDelay     | in minutes                                                                |\n",
    "| LateAircraftDelay | in minutes                                                                |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are  1936758  rows and  30 columns.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['Unnamed: 0',\n",
       " 'Year',\n",
       " 'Month',\n",
       " 'DayofMonth',\n",
       " 'DayOfWeek',\n",
       " 'DepTime',\n",
       " 'CRSDepTime',\n",
       " 'ArrTime',\n",
       " 'CRSArrTime',\n",
       " 'UniqueCarrier',\n",
       " 'FlightNum',\n",
       " 'TailNum',\n",
       " 'ActualElapsedTime',\n",
       " 'CRSElapsedTime',\n",
       " 'AirTime',\n",
       " 'ArrDelay',\n",
       " 'DepDelay',\n",
       " 'Origin',\n",
       " 'Dest',\n",
       " 'Distance',\n",
       " 'TaxiIn',\n",
       " 'TaxiOut',\n",
       " 'Cancelled',\n",
       " 'CancellationCode',\n",
       " 'Diverted',\n",
       " 'CarrierDelay',\n",
       " 'WeatherDelay',\n",
       " 'NASDelay',\n",
       " 'SecurityDelay',\n",
       " 'LateAircraftDelay']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row_num,col_num=data_airline.shape #Report the shape of the dataset\n",
    "print('There are ',row_num,' rows','and ',col_num,'columns.')\n",
    "list(data_airline.columns) #Print out the column names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1) Examples of the dataset.\n",
    "* Below are **first five rows** of the data, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>...</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>CancellationCode</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>1955</td>\n",
       "      <td>2211.0</td>\n",
       "      <td>2225</td>\n",
       "      <td>WN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>0</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",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>754.0</td>\n",
       "      <td>735</td>\n",
       "      <td>1002.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>WN</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>0</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",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>628.0</td>\n",
       "      <td>620</td>\n",
       "      <td>804.0</td>\n",
       "      <td>750</td>\n",
       "      <td>WN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>0</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",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1829.0</td>\n",
       "      <td>1755</td>\n",
       "      <td>1959.0</td>\n",
       "      <td>1925</td>\n",
       "      <td>WN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1940.0</td>\n",
       "      <td>1915</td>\n",
       "      <td>2121.0</td>\n",
       "      <td>2110</td>\n",
       "      <td>WN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>0</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 × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Year  Month  DayofMonth  DayOfWeek  DepTime  CRSDepTime  \\\n",
       "0           0  2008      1           3          4   2003.0        1955   \n",
       "1           1  2008      1           3          4    754.0         735   \n",
       "2           2  2008      1           3          4    628.0         620   \n",
       "3           4  2008      1           3          4   1829.0        1755   \n",
       "4           5  2008      1           3          4   1940.0        1915   \n",
       "\n",
       "   ArrTime  CRSArrTime UniqueCarrier  ...  TaxiIn TaxiOut  Cancelled  \\\n",
       "0   2211.0        2225            WN  ...     4.0     8.0          0   \n",
       "1   1002.0        1000            WN  ...     5.0    10.0          0   \n",
       "2    804.0         750            WN  ...     3.0    17.0          0   \n",
       "3   1959.0        1925            WN  ...     3.0    10.0          0   \n",
       "4   2121.0        2110            WN  ...     4.0    10.0          0   \n",
       "\n",
       "   CancellationCode  Diverted  CarrierDelay  WeatherDelay NASDelay  \\\n",
       "0                 N         0           NaN           NaN      NaN   \n",
       "1                 N         0           NaN           NaN      NaN   \n",
       "2                 N         0           NaN           NaN      NaN   \n",
       "3                 N         0           2.0           0.0      0.0   \n",
       "4                 N         0           NaN           NaN      NaN   \n",
       "\n",
       "  SecurityDelay  LateAircraftDelay  \n",
       "0           NaN                NaN  \n",
       "1           NaN                NaN  \n",
       "2           NaN                NaN  \n",
       "3           0.0               32.0  \n",
       "4           NaN                NaN  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_airline.head() #First five rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2) Data type information for each columns.\n",
    "* Below are the **information summary** about the data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1936758 entries, 0 to 1936757\n",
      "Data columns (total 30 columns):\n",
      "Unnamed: 0           int64\n",
      "Year                 int64\n",
      "Month                int64\n",
      "DayofMonth           int64\n",
      "DayOfWeek            int64\n",
      "DepTime              float64\n",
      "CRSDepTime           int64\n",
      "ArrTime              float64\n",
      "CRSArrTime           int64\n",
      "UniqueCarrier        object\n",
      "FlightNum            int64\n",
      "TailNum              object\n",
      "ActualElapsedTime    float64\n",
      "CRSElapsedTime       float64\n",
      "AirTime              float64\n",
      "ArrDelay             float64\n",
      "DepDelay             float64\n",
      "Origin               object\n",
      "Dest                 object\n",
      "Distance             int64\n",
      "TaxiIn               float64\n",
      "TaxiOut              float64\n",
      "Cancelled            int64\n",
      "CancellationCode     object\n",
      "Diverted             int64\n",
      "CarrierDelay         float64\n",
      "WeatherDelay         float64\n",
      "NASDelay             float64\n",
      "SecurityDelay        float64\n",
      "LateAircraftDelay    float64\n",
      "dtypes: float64(14), int64(11), object(5)\n",
      "memory usage: 443.3+ MB\n"
     ]
    }
   ],
   "source": [
    "data_airline.info() #Data type for each column"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3) Basic statistical summary for each columns.\n",
    "* The below form is made from the _describe_ method of the dataframe _data_airline_ \n",
    "* It tells us that the dataset only contains the flight information of **year 2008**.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>DayofMonth</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>DepTime</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>ArrTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>FlightNum</th>\n",
       "      <th>...</th>\n",
       "      <th>Distance</th>\n",
       "      <th>TaxiIn</th>\n",
       "      <th>TaxiOut</th>\n",
       "      <th>Cancelled</th>\n",
       "      <th>Diverted</th>\n",
       "      <th>CarrierDelay</th>\n",
       "      <th>WeatherDelay</th>\n",
       "      <th>NASDelay</th>\n",
       "      <th>SecurityDelay</th>\n",
       "      <th>LateAircraftDelay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1936758.0</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.929648e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.929648e+06</td>\n",
       "      <td>1.936303e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.936758e+06</td>\n",
       "      <td>1.247488e+06</td>\n",
       "      <td>1.247488e+06</td>\n",
       "      <td>1.247488e+06</td>\n",
       "      <td>1.247488e+06</td>\n",
       "      <td>1.247488e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>3.341651e+06</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.111106e+00</td>\n",
       "      <td>1.575347e+01</td>\n",
       "      <td>3.984827e+00</td>\n",
       "      <td>1.518534e+03</td>\n",
       "      <td>1.467473e+03</td>\n",
       "      <td>1.610141e+03</td>\n",
       "      <td>1.634225e+03</td>\n",
       "      <td>2.184263e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>7.656862e+02</td>\n",
       "      <td>6.812975e+00</td>\n",
       "      <td>1.823220e+01</td>\n",
       "      <td>3.268348e-04</td>\n",
       "      <td>4.003598e-03</td>\n",
       "      <td>1.917940e+01</td>\n",
       "      <td>3.703571e+00</td>\n",
       "      <td>1.502164e+01</td>\n",
       "      <td>9.013714e-02</td>\n",
       "      <td>2.529647e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>2.066065e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.482546e+00</td>\n",
       "      <td>8.776272e+00</td>\n",
       "      <td>1.995966e+00</td>\n",
       "      <td>4.504853e+02</td>\n",
       "      <td>4.247668e+02</td>\n",
       "      <td>5.481781e+02</td>\n",
       "      <td>4.646347e+02</td>\n",
       "      <td>1.944702e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>5.744797e+02</td>\n",
       "      <td>5.273595e+00</td>\n",
       "      <td>1.433853e+01</td>\n",
       "      <td>1.807562e-02</td>\n",
       "      <td>6.314722e-02</td>\n",
       "      <td>4.354621e+01</td>\n",
       "      <td>2.149290e+01</td>\n",
       "      <td>3.383305e+01</td>\n",
       "      <td>2.022714e+00</td>\n",
       "      <td>4.205486e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>1.517452e+06</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>8.000000e+00</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>1.203000e+03</td>\n",
       "      <td>1.135000e+03</td>\n",
       "      <td>1.316000e+03</td>\n",
       "      <td>1.325000e+03</td>\n",
       "      <td>6.100000e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>3.380000e+02</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>3.242558e+06</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.000000e+00</td>\n",
       "      <td>1.600000e+01</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>1.545000e+03</td>\n",
       "      <td>1.510000e+03</td>\n",
       "      <td>1.715000e+03</td>\n",
       "      <td>1.705000e+03</td>\n",
       "      <td>1.543000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>6.060000e+02</td>\n",
       "      <td>6.000000e+00</td>\n",
       "      <td>1.400000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>4.972467e+06</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>9.000000e+00</td>\n",
       "      <td>2.300000e+01</td>\n",
       "      <td>6.000000e+00</td>\n",
       "      <td>1.900000e+03</td>\n",
       "      <td>1.815000e+03</td>\n",
       "      <td>2.030000e+03</td>\n",
       "      <td>2.014000e+03</td>\n",
       "      <td>3.422000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>9.980000e+02</td>\n",
       "      <td>8.000000e+00</td>\n",
       "      <td>2.100000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.100000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.500000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.300000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>7.009727e+06</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>1.200000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>7.000000e+00</td>\n",
       "      <td>2.400000e+03</td>\n",
       "      <td>2.359000e+03</td>\n",
       "      <td>2.400000e+03</td>\n",
       "      <td>2.400000e+03</td>\n",
       "      <td>9.742000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>4.962000e+03</td>\n",
       "      <td>2.400000e+02</td>\n",
       "      <td>4.220000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.436000e+03</td>\n",
       "      <td>1.352000e+03</td>\n",
       "      <td>1.357000e+03</td>\n",
       "      <td>3.920000e+02</td>\n",
       "      <td>1.316000e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0       Year         Month    DayofMonth     DayOfWeek  \\\n",
       "count  1.936758e+06  1936758.0  1.936758e+06  1.936758e+06  1.936758e+06   \n",
       "mean   3.341651e+06     2008.0  6.111106e+00  1.575347e+01  3.984827e+00   \n",
       "std    2.066065e+06        0.0  3.482546e+00  8.776272e+00  1.995966e+00   \n",
       "min    0.000000e+00     2008.0  1.000000e+00  1.000000e+00  1.000000e+00   \n",
       "25%    1.517452e+06     2008.0  3.000000e+00  8.000000e+00  2.000000e+00   \n",
       "50%    3.242558e+06     2008.0  6.000000e+00  1.600000e+01  4.000000e+00   \n",
       "75%    4.972467e+06     2008.0  9.000000e+00  2.300000e+01  6.000000e+00   \n",
       "max    7.009727e+06     2008.0  1.200000e+01  3.100000e+01  7.000000e+00   \n",
       "\n",
       "            DepTime    CRSDepTime       ArrTime    CRSArrTime     FlightNum  \\\n",
       "count  1.936758e+06  1.936758e+06  1.929648e+06  1.936758e+06  1.936758e+06   \n",
       "mean   1.518534e+03  1.467473e+03  1.610141e+03  1.634225e+03  2.184263e+03   \n",
       "std    4.504853e+02  4.247668e+02  5.481781e+02  4.646347e+02  1.944702e+03   \n",
       "min    1.000000e+00  0.000000e+00  1.000000e+00  0.000000e+00  1.000000e+00   \n",
       "25%    1.203000e+03  1.135000e+03  1.316000e+03  1.325000e+03  6.100000e+02   \n",
       "50%    1.545000e+03  1.510000e+03  1.715000e+03  1.705000e+03  1.543000e+03   \n",
       "75%    1.900000e+03  1.815000e+03  2.030000e+03  2.014000e+03  3.422000e+03   \n",
       "max    2.400000e+03  2.359000e+03  2.400000e+03  2.400000e+03  9.742000e+03   \n",
       "\n",
       "       ...      Distance        TaxiIn       TaxiOut     Cancelled  \\\n",
       "count  ...  1.936758e+06  1.929648e+06  1.936303e+06  1.936758e+06   \n",
       "mean   ...  7.656862e+02  6.812975e+00  1.823220e+01  3.268348e-04   \n",
       "std    ...  5.744797e+02  5.273595e+00  1.433853e+01  1.807562e-02   \n",
       "min    ...  1.100000e+01  0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "25%    ...  3.380000e+02  4.000000e+00  1.000000e+01  0.000000e+00   \n",
       "50%    ...  6.060000e+02  6.000000e+00  1.400000e+01  0.000000e+00   \n",
       "75%    ...  9.980000e+02  8.000000e+00  2.100000e+01  0.000000e+00   \n",
       "max    ...  4.962000e+03  2.400000e+02  4.220000e+02  1.000000e+00   \n",
       "\n",
       "           Diverted  CarrierDelay  WeatherDelay      NASDelay  SecurityDelay  \\\n",
       "count  1.936758e+06  1.247488e+06  1.247488e+06  1.247488e+06   1.247488e+06   \n",
       "mean   4.003598e-03  1.917940e+01  3.703571e+00  1.502164e+01   9.013714e-02   \n",
       "std    6.314722e-02  4.354621e+01  2.149290e+01  3.383305e+01   2.022714e+00   \n",
       "min    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   0.000000e+00   \n",
       "25%    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   0.000000e+00   \n",
       "50%    0.000000e+00  2.000000e+00  0.000000e+00  2.000000e+00   0.000000e+00   \n",
       "75%    0.000000e+00  2.100000e+01  0.000000e+00  1.500000e+01   0.000000e+00   \n",
       "max    1.000000e+00  2.436000e+03  1.352000e+03  1.357000e+03   3.920000e+02   \n",
       "\n",
       "       LateAircraftDelay  \n",
       "count       1.247488e+06  \n",
       "mean        2.529647e+01  \n",
       "std         4.205486e+01  \n",
       "min         0.000000e+00  \n",
       "25%         0.000000e+00  \n",
       "50%         8.000000e+00  \n",
       "75%         3.300000e+01  \n",
       "max         1.316000e+03  \n",
       "\n",
       "[8 rows x 25 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_airline.describe() #Summary pf the count,mean, std,min,max,25,50,75 quantile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6) Handle the missing observations for each column of the dataset\n",
    "* First, check the proportion of the missing values for each column. The column names are listed by descending order of the proportion of the missing obeservations.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Proportion of missing value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>LateAircraftDelay</td>\n",
       "      <td>0.355889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SecurityDelay</td>\n",
       "      <td>0.355889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NASDelay</td>\n",
       "      <td>0.355889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>WeatherDelay</td>\n",
       "      <td>0.355889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CarrierDelay</td>\n",
       "      <td>0.355889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ActualElapsedTime</td>\n",
       "      <td>0.004330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AirTime</td>\n",
       "      <td>0.004330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ArrDelay</td>\n",
       "      <td>0.004330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ArrTime</td>\n",
       "      <td>0.003671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TaxiIn</td>\n",
       "      <td>0.003671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TaxiOut</td>\n",
       "      <td>0.000235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CRSElapsedTime</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TailNum</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CRSArrTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Month</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DayofMonth</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DayOfWeek</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DepTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Diverted</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CancellationCode</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Cancelled</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Distance</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>UniqueCarrier</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Dest</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Origin</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DepDelay</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Year</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CRSDepTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>FlightNum</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Unnamed: 0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Proportion of missing value\n",
       "LateAircraftDelay                     0.355889\n",
       "SecurityDelay                         0.355889\n",
       "NASDelay                              0.355889\n",
       "WeatherDelay                          0.355889\n",
       "CarrierDelay                          0.355889\n",
       "ActualElapsedTime                     0.004330\n",
       "AirTime                               0.004330\n",
       "ArrDelay                              0.004330\n",
       "ArrTime                               0.003671\n",
       "TaxiIn                                0.003671\n",
       "TaxiOut                               0.000235\n",
       "CRSElapsedTime                        0.000102\n",
       "TailNum                               0.000003\n",
       "CRSArrTime                            0.000000\n",
       "Month                                 0.000000\n",
       "DayofMonth                            0.000000\n",
       "DayOfWeek                             0.000000\n",
       "DepTime                               0.000000\n",
       "Diverted                              0.000000\n",
       "CancellationCode                      0.000000\n",
       "Cancelled                             0.000000\n",
       "Distance                              0.000000\n",
       "UniqueCarrier                         0.000000\n",
       "Dest                                  0.000000\n",
       "Origin                                0.000000\n",
       "DepDelay                              0.000000\n",
       "Year                                  0.000000\n",
       "CRSDepTime                            0.000000\n",
       "FlightNum                             0.000000\n",
       "Unnamed: 0                            0.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create a dataframe indicating the proportion of missing values for each column\n",
    "PropOfMissingValue=pd.DataFrame(np.sum(pd.isnull(data_airline))/row_num,columns=['Proportion of missing value'])\n",
    "# Display the columns according to descending missing value proportion order\n",
    "PropOfMissingValue.sort_values(by=['Proportion of missing value'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* The parameters named _LateAircraftDelay_ , _SecurityDelay_, _NASDelay_, _WeatherDelay_, _CarrierDelay_ contains the largest proprotion of missing values. But this is acceptable,because only the flights which were delayed or canceled contains these five parameters.\n",
    "* Some values in _ArrTime_, _DepTime_, et.al are also missing, but this may be due to the cancellation of the flights. Thus this is also acceptable. \n",
    "* But the schedualed arrival elapsed time is one of my interested features, thus the rows whose **_CRSElapsedTime_** contains missing values will be removed.\n",
    "* The following is to remove the rows containing missing values in specific columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "InTorlerantColumn=['CRSElapsedTime']\n",
    "#Delete rows whose columns in InTorlerantColumn contain missing values\n",
    "data_airline = data_airline.dropna(axis=0, subset=InTorlerantColumn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Next step: Remeasure the dataset size and the proporiton of the missing value to ensure that all the unrequried datasets are successfully removed. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The row number changes into  1936560 from  1936758  after removing nulls.\n",
      " 198  rows has been removed.\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Proportion of missing value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>LateAircraftDelay</td>\n",
       "      <td>0.355786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>SecurityDelay</td>\n",
       "      <td>0.355786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NASDelay</td>\n",
       "      <td>0.355786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>WeatherDelay</td>\n",
       "      <td>0.355786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CarrierDelay</td>\n",
       "      <td>0.355786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ActualElapsedTime</td>\n",
       "      <td>0.004228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>AirTime</td>\n",
       "      <td>0.004228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ArrDelay</td>\n",
       "      <td>0.004228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TaxiIn</td>\n",
       "      <td>0.003569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ArrTime</td>\n",
       "      <td>0.003569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TaxiOut</td>\n",
       "      <td>0.000235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TailNum</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CRSArrTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Month</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DayofMonth</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DayOfWeek</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DepTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Diverted</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CancellationCode</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Cancelled</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Distance</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>UniqueCarrier</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Dest</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Origin</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DepDelay</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Year</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CRSDepTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>CRSElapsedTime</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>FlightNum</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Unnamed: 0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Proportion of missing value\n",
       "LateAircraftDelay                     0.355786\n",
       "SecurityDelay                         0.355786\n",
       "NASDelay                              0.355786\n",
       "WeatherDelay                          0.355786\n",
       "CarrierDelay                          0.355786\n",
       "ActualElapsedTime                     0.004228\n",
       "AirTime                               0.004228\n",
       "ArrDelay                              0.004228\n",
       "TaxiIn                                0.003569\n",
       "ArrTime                               0.003569\n",
       "TaxiOut                               0.000235\n",
       "TailNum                               0.000003\n",
       "CRSArrTime                            0.000000\n",
       "Month                                 0.000000\n",
       "DayofMonth                            0.000000\n",
       "DayOfWeek                             0.000000\n",
       "DepTime                               0.000000\n",
       "Diverted                              0.000000\n",
       "CancellationCode                      0.000000\n",
       "Cancelled                             0.000000\n",
       "Distance                              0.000000\n",
       "UniqueCarrier                         0.000000\n",
       "Dest                                  0.000000\n",
       "Origin                                0.000000\n",
       "DepDelay                              0.000000\n",
       "Year                                  0.000000\n",
       "CRSDepTime                            0.000000\n",
       "CRSElapsedTime                        0.000000\n",
       "FlightNum                             0.000000\n",
       "Unnamed: 0                            0.000000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row_new,col_new= data_airline.shape\n",
    "print('The row number changes into ',row_new, 'from ',row_num,' after removing nulls.\\n',row_num-row_new,' rows has been removed.')\n",
    "#Remeasure the proportion of missing values for each column\n",
    "PropOfMissingValue=pd.DataFrame(np.sum(pd.isnull(data_airline))/row_num,columns=['Proportion of missing value'])\n",
    "# ReDisplay the columns according to descending missing value proportion order\n",
    "PropOfMissingValue.sort_values(by=['Proportion of missing value'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IV.Defintion of the prediction target--y: flight status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) The distribution of the raw arrival delay\n",
    "* The dataset has informed about the cancellation, but not the arrival delay. Thus the first step is to set a criterium about the state of delay.\n",
    "* Here I think for the travellers, the arrival time to the destination is more important than the departure time. Thus the overal flight delay is mainly based on the arrival time.\n",
    "* First, I roughly plot the distribution of the raw arrival delay time separately for delay<0 and delay>0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of advance arrival cases is 177916 \n",
      "Number of delayed arrival cases is 1723415\n",
      "Propotion of advance arrival cases is 0.09190222565210361 \n",
      "Propotion of delayed arrival cases is 0.8902272658008282\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Load the arrival delay of all the not cancelled flights \n",
    "ArrDelay_NotCancelled=data_airline[data_airline.Cancelled==0]['ArrDelay'];\n",
    "NumberOfTotalFlights_NotCancelled=np.size(ArrDelay_NotCancelled);\n",
    "#First measure the proportion of flights iwth arrival delay<0 and the proportion of flights iwth arrival delay>0\n",
    "NumOfNegativeArrDelay=np.sum(ArrDelay_NotCancelled<0)\n",
    "NumOfPositiveArrDelay= np.sum(ArrDelay_NotCancelled>0)\n",
    "PropOfNegativeArrDelay=NumOfNegativeArrDelay/NumberOfTotalFlights_NotCancelled\n",
    "PropOfPositiveArrDelay=NumOfPositiveArrDelay/NumberOfTotalFlights_NotCancelled\n",
    "print('Number of advance arrival cases is', NumOfNegativeArrDelay,'\\nNumber of delayed arrival cases is',NumOfPositiveArrDelay)\n",
    "print('Propotion of advance arrival cases is', PropOfNegativeArrDelay,'\\nPropotion of delayed arrival cases is',PropOfPositiveArrDelay)\n",
    "\n",
    "# (a) Make a bar plot of the number of flights arrived in advance   \n",
    "plt.subplot(1,4,1)\n",
    "sns.set()\n",
    "plt.bar([1,2],[PropOfNegativeArrDelay,PropOfPositiveArrDelay],color=['g','r'],alpha=0.75);\n",
    "plt.xticks([1,2],['Advance','Delay'],rotation=45,fontsize=12);\n",
    "plt.yticks(fontsize=12);\n",
    "plt.xlabel('Arrival Delay(min)',fontsize=15,x=0.5,y=-0.5);\n",
    "plt.ylabel('Proportion of Flights(%)',fontsize=15,x=-10,y=0.5);\n",
    "plt.subplots_adjust(bottom=0.2) # make room for x-axis labels\n",
    "plt.title('(a) Arrival Delay Separation',fontsize=15,x=0.5,y=1.1);\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))\n",
    "plt.grid(True)\n",
    "\n",
    "# (b) Plot the distribution of those flights arrived in advance\n",
    "AdvanceTime=ArrDelay_NotCancelled[ArrDelay_NotCancelled<0];\n",
    "Advance_Min=np.min(AdvanceTime)\n",
    "BinWidth_Advance=5 #Width of the bin for the histogram \n",
    "Bin_Advance=np.arange(Advance_Min,BinWidth_Advance,BinWidth_Advance)\n",
    "histAdvance,bins=np.histogram(AdvanceTime,bins=Bin_Advance)\n",
    "plotedge=bins[:-1]\n",
    "histAdvance=histAdvance/NumberOfTotalFlights_NotCancelled #Change the number of cases into the propotion\n",
    "\n",
    "plt.subplot(1,4,2)\n",
    "sns.set()\n",
    "plt.bar(plotedge, histAdvance, align='edge', width=BinWidth_Advance,color='g',alpha=0.75)\n",
    "plt.xlim([Advance_Min,0])\n",
    "plt.xticks(rotation=45,fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xlabel('\\n Distribution of arrival delay (in min)',fontsize=15,x=0.5,y=-0.5)\n",
    "label='Bin Width:'+str(BinWidth_Advance)\n",
    "plt.legend([label],fontsize=12)\n",
    "plt.title('(b) Advance Time Distribution',fontsize=15,x=0.45,y=1.1)\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))\n",
    "plt.subplots_adjust(left=-1.8) # make room for yticks \n",
    "\n",
    "# (c) Plot the distribution of those flights arrived delayed \n",
    "DelayTime=ArrDelay_NotCancelled[ArrDelay_NotCancelled>0];\n",
    "Delay_Max=np.max(DelayTime)\n",
    "BinWidth_Delay=60 #Width of the bin for the histogram \n",
    "Bin_Delay=np.arange(0,Delay_Max+BinWidth_Delay,BinWidth_Delay)\n",
    "histDelay,bins=np.histogram(DelayTime,bins=Bin_Delay)\n",
    "plotedge=bins[:-1]\n",
    "histDelay=histDelay/NumberOfTotalFlights_NotCancelled #Change the number of cases into the propotion\n",
    "\n",
    "plt.subplot(1,4,3)\n",
    "sns.set()\n",
    "plt.bar(plotedge, histDelay, align='edge',log=True, width=BinWidth_Delay,color='r',alpha=0.75)\n",
    "plt.xticks(rotation=45,fontsize=12);\n",
    "plt.yticks(fontsize=12);\n",
    "plt.xlabel('\\n Distribution of arrival delay (in min)',fontsize=15,x=0.5,y=-0.5);\n",
    "label='Bin Width:'+str(BinWidth_Delay)\n",
    "plt.legend([label],fontsize=12);\n",
    "plt.title('(c) Delay time distribution',fontsize=15,x=0.45,y=1.1);\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))\n",
    "\n",
    "# (d) Plot the distribution of those flight delayed within one hour\n",
    "DelayTimeWithinOneHour=DelayTime[DelayTime<60.1]\n",
    "Bin_Delay_Short=np.arange(0,65,5)\n",
    "histDelayShort,bins=np.histogram(DelayTimeWithinOneHour,bins=Bin_Delay_Short)\n",
    "histDelayShort=histDelayShort/NumberOfTotalFlights_NotCancelled\n",
    "plotedge=bins[:-1]\n",
    "plt.subplot(1,4,4)\n",
    "sns.set()\n",
    "plt.bar(plotedge, histDelayShort, align='edge', width=5,color='r',alpha=0.75)\n",
    "plt.xticks(rotation=45,fontsize=12);\n",
    "plt.yticks(fontsize=12);\n",
    "plt.xlabel('\\n Distribution of arrival delay (in min)',fontsize=15,x=0.5,y=-0.5);\n",
    "plt.legend(['Bin width: 5'],fontsize=12);\n",
    "plt.title('(d) Delay time distribution(Delay<1h)',fontsize=15,x=0.45,y=1.1);\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* According to the above figure\n",
    "<br>\n",
    "* **(a)** Among all the flights which were not cancelled, the proportion of advance arrival cases is small, only occupies ~9% of the whole cases.\n",
    "* **(b)** The advanced time is limited, the majority is ranging from 35 minutes to 0, with most cases distributed within 15 minutes. This advance distribution around zero can be used as a reference to determin the time period considered as normal on-time.  \n",
    "* **(c)** The delayed time is broadly distributed, while the most frequent cases show a delay within 60 minutes.\n",
    "* **(d)** To take a detail look at the delay time distribution within one hour, the most cases have a delay within 20minutes.\n",
    "> **It seems that flgiht arrival delay is quite normal distributed within the rage [-20min to 20min].**\n",
    "> **But there is one problem, the arrival delay may be related to the _full flight duration_.**\n",
    ">* **For example, if the total flight duration is only one hour, and the arrival delay of half an hour becomes more serious compared to the condition where the total flight duraiton is 4-5 hours.**\n",
    ">* **Therefore, for the next step, I'll first check the relationship between the regular flight duration (_CRSElapsedTime_) and the arrival delay.**\n",
    ">* **Then, the arrival-delay will be normalized by the CRSEElapsedTime.** "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) The distribution of the arrival delay percentage relative to the duration of the whole journey"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* As mentioned above, it's more resonable to define the arrival delay of the flight relative to the whole flight duration. It's more unacceptable for longer delays if the flight journel is too short.\n",
    "* **First**, take a brief look at the relationship between the _**CRSElapsedTime**_ and the _**DelayTime**_ for those uncancelled flights.\n",
    "* **Then**, normalize the _**Arrival Delay**_ by the _**CRSElapsedTime**_."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Load the arrival delay and crselapstime into a dataframe for scatter plot\n",
    "ExamineArrDelAndCRSElapse=data_airline.loc[data_airline.Cancelled==0,['ArrDelay','CRSElapsedTime']] \n",
    "\n",
    "#Scatter plot for CRSElapsed Time v.s. Arrival Advance and Delay respectively\n",
    "plt.subplot(1,2,1)\n",
    "sns.set()\n",
    "plt.scatter(ExamineArrDelAndCRSElapse.loc[ExamineArrDelAndCRSElapse['ArrDelay']<0]['ArrDelay'],ExamineArrDelAndCRSElapse.loc[ExamineArrDelAndCRSElapse['ArrDelay']<0]['CRSElapsedTime'],color='g',edgecolors='w',alpha=0.75)\n",
    "plt.xlabel('Arrival Delay(min)',fontsize=12)\n",
    "plt.ylabel('CRSElapsed Time(min)',fontsize=12)\n",
    "plt.title('(a) CRSElapsedTime \\n   v.s \\nArrival Advance',fontsize=15);\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "sns.set()\n",
    "plt.scatter(ExamineArrDelAndCRSElapse.loc[ExamineArrDelAndCRSElapse['ArrDelay']>0]['ArrDelay'],ExamineArrDelAndCRSElapse.loc[ExamineArrDelAndCRSElapse['ArrDelay']>0]['CRSElapsedTime'],color='r',edgecolors='w',alpha=0.75)\n",
    "plt.xlabel('Arrival Delay(min)',fontsize=12)\n",
    "plt.title('(b) CRSElapsedTime \\n   v.s \\nArrival Delay',fontsize=15);\n",
    "plt.subplots_adjust(left=-1.8) # make room for yticks "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **From the above figure, it's apparent that the dots distributed on the right down corner are more severious condition.**\n",
    "<br>\n",
    "> **Next, normalize the arrival delay by the CRSElapsedTime**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add a new column called the relative delay to store the relative arrival delay\n",
    "data_airline['RelativeArrDel']=data_airline['ArrDelay']/data_airline['CRSElapsedTime']\n",
    "#Replot the distribution of the Relative Arrival Delay again\n",
    "RelativeArrDel=data_airline[data_airline.Cancelled==0]['RelativeArrDel']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Histograme for advance\n",
    "AdvanceTimeRel=RelativeArrDel[ArrDelay_NotCancelled<0];\n",
    "AdvanceRel_Min=round(np.min(AdvanceTimeRel),1)\n",
    "BinWidth_AdvanceRel=0.1\n",
    "Bin_AdvanceRel=np.arange(AdvanceRel_Min-BinWidth_AdvanceRel,BinWidth_AdvanceRel,BinWidth_AdvanceRel)\n",
    "histAdvanceRel,bins=np.histogram(AdvanceTimeRel,bins=Bin_AdvanceRel)\n",
    "histAdvanceRel=histAdvanceRel/NumberOfTotalFlights_NotCancelled\n",
    "\n",
    "#Histograme for delay with refdelay\n",
    "DelayTimeRel=RelativeArrDel[ArrDelay_NotCancelled>0];\n",
    "DelayRel_Max=np.max(DelayTimeRel)\n",
    "BinWidth_DelayRel=1\n",
    "Bin_DelayRelAbove1=np.arange(1,DelayRel_Max+BinWidth_DelayRel,BinWidth_DelayRel)\n",
    "histDelayRel,bins=np.histogram(DelayTimeRel,bins=Bin_DelayRelAbove1)\n",
    "histDelayRel=histDelayRel/NumberOfTotalFlights_NotCancelled\n",
    "plotedge_Fig2=Bin_DelayRelAbove1[:-1]\n",
    "\n",
    "#Histograme for delay with refdelay<1\n",
    "DelayTimeRelWithin1=DelayTimeRel[DelayTimeRel<1]\n",
    "Bin_DelayRelWithin1=np.arange(0,1+BinWidth_AdvanceRel,BinWidth_AdvanceRel)\n",
    "histDelayRelWithin1,bins=np.histogram(DelayTimeRelWithin1,bins=Bin_DelayRelWithin1)\n",
    "histDelayRelWithin1=histDelayRelWithin1/NumberOfTotalFlights_NotCancelled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#First put the histogram of Advance and Delay<1 together\n",
    "plotedge_Fig1=np.concatenate((Bin_AdvanceRel[:-1],Bin_DelayRelWithin1[:-1]))\n",
    "histDelayRelWithin1All=np.concatenate((histAdvanceRel,histDelayRelWithin1))\n",
    "# Make a bar plot\n",
    "Color=['g']*np.size(Bin_AdvanceRel[:-1])+['r']*np.size(Bin_DelayRelWithin1[:-1])\n",
    "plt.subplot(1,2,1)\n",
    "sns.set()\n",
    "plt.bar(plotedge_Fig1,histDelayRelWithin1All, align='edge', width=BinWidth_AdvanceRel,color=Color,alpha=0.75);\n",
    "plt.xlabel('\\nArrival Delay/CRSElaspedTime',fontsize=15)\n",
    "plt.ylabel('Proportion of flights',fontsize=15)\n",
    "plt.title('(a) Relative Arrival Delay<1',fontsize=15);\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))\n",
    "\n",
    "#Plot the rest relative delays\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "sns.set()\n",
    "plt.bar(plotedge_Fig2,histDelayRel, align='edge',width=BinWidth_DelayRel,color='r',alpha=0.75);\n",
    "plt.xlim(1,DelayRel_Max+BinWidth_AdvanceRel)\n",
    "plt.xlabel('\\nArrival Delay/CRSElaspedTime',fontsize=15)\n",
    "plt.title('(b) Relative Arrival Delay>1',fontsize=15);\n",
    "plt.xscale('log')\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))\n",
    "plt.subplots_adjust(left=-1) # make room for yticks \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* According to (a), it seems that most flight delayed within 0.2 times the whole schedualed flight duration.\n",
    "* Longer delays above 1 only occpupied a small proportion of the flight population.\n",
    "* According to (b), among all the delayed flights, there are still rare cases which arrival delay can be longer that 2 times the whole flgiht duration. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " >**Therefore, in the following, the flights whose arrival delay within _0.15_ times schedualed flight duration will be defined as on-time flights.** \n",
    " <br>\n",
    " >**The rest will be defined as delayed flights**  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Add a new column to indicate flight status\n",
    "* Flight state: **0--On time; 1--Delayed; 2--Cancelled**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_airline['FlightState']=data_airline.RelativeArrDel>0.15 #Assign value 1 to indicate Delayed flight\n",
    "data_airline['FlightState']=data_airline['FlightState'].astype(int)\n",
    "data_airline.loc[data_airline['Cancelled']==1,'FlightState']=2 #Assign value 2 to indicate Cancelled flight"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **7.2) Overview of the parameters related to each flight status**\n",
    "#### 7.2.1) Distribution of each flight status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Donut chart of the flight status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Status=data_airline['FlightState'].value_counts()\n",
    "#To make a donut char plot to show the proportion of data for each status\n",
    "plt.title('Donut chart of the flight status\\n',fontsize=15, fontweight='bold')\n",
    "plt.pie(Status, explode=(0, 0, 0.2)  , labels=['Delayed', 'On-Time', 'Cancelled'], autopct='%1.3f%%',\n",
    "        shadow=True, startangle=90,colors=['tomato','limegreen','k'],textprops={'fontsize': 15});\n",
    "centre_circle = plt.Circle((0,0),0.6,fc='white');\n",
    "plt.gca().add_artist(centre_circle);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Overall, according to our criteria, almost half of the flights are arrived on-time."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3) Re-examination of the arrival delay for the on-time flights and the delayed flights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Proportion of flights \\nfor each flight state')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mEhgYyIcffqjMhMzJlS3atWunDPl169ZN2W5iYsKyZcvQaDQ8efKE8PBwJk+eTPHixbl165bRU78nTpzIgAEDMDMz4+bNm/Tt2zdNT2Xw4MFMnToVBwcH/P39KVasGGPGjOGzzz4zWGabNm0YOXIktra2XL16lXfeeYfhw4cD6M3gK1OmjPIAc+PGjXnnnXeMf2OKGJXIzp1fSZIkySjJycm0b9+eBw8esGDBAmWCjJSWHLKTJEnKJRMmTODu3bs8ePAAOzs72rdvn99VKtDkkJ0kSVIuuXv3Lvfu3cPJyYlVq1YZfGxCekkO2UmSJEkFguwhSZIkSQWCDEhSvrlz5w49e/akbt26NG3alNOnT+d3lbJMt8hqVlew/uGHH5TFQj/88ENOnz6No6Mj//rXv5RjspPfKL2FaV8XHR3N+vXrs1TnvLRq1SocHR2VdfgMvT+FNSeUlD45qUHKN6tWrSIgIIAyZcpQq1atdFcLeNvExcUxf/58kpOT9ZbIeV1Wc04Z6/79+/Tp0wdLS0uGDBmSo2XnFhsbG7y8vLC3t1e2GcoJlVvvmZQ3ZECS8o0uC+0nn3yi9+zJ2+7Zs2ckJyejVqv56aefMDExMdg7zK28QWFhYYSHh1OhQoVcKT83aDSaNO+HoZxQMtdS4SaH7KR80apVK+VDePr06bRq1QpIXQpn8+bNdOjQgXr16tGiRQsWLFig9+S7Ln/Rhg0b8PT0pEWLFgYfcs0s948QgpUrV9KqVSvq1q1L48aNGT16NI8ePVKOiYyMZPr06Xh4eNCgQQO6dOnC77//bvBaM2bMwMXFBU9PT3x9fQ22+/Tp08pDqFqtljp16qTJZ6Tz+vBTYmIi8+fPV/JBffXVVyxcuNBgGm6tVsuiRYto3Lgxbm5ufPnll6SkpBAUFES/fv2A1HQijo6O6Q6VPnr0iI8//ljJcdW7d2/OnDmjd8z+/fvp2rUrDRo0oEmTJkyfPp2IiAhl/4ABA3B0dOTIkSN89NFHODs707ZtW7Zu3apXzoYNG2jZsiUNGjRg4sSJvHjxIs379uqQXXo5oQwN2eVUHaXcJwOSlC88PT2VlR+cnJzw9PQEUlcSmDt3LkFBQbi4uJCSksKGDRsYPny48gGks2jRIipXrkydOnUMriKRWe4fPz8/VqxYQXR0NO7u7lhZWXHkyBHmz58PpH6oDx8+nJ07d2JhYYGLiwu3bt3i448/5uTJk3rXWr9+PadOnaJq1ao8ffqUb7/91uAK2jY2NkpbVSoVXl5eafIZpefbb79l48aNxMfHU6dOHX7++We2b99u8Nj9+/ezZ88eqlevTlRUFH5+fhw8eBArKytlmSBLS0u8vLwMpm6Pjo6mf//+/Pbbb9ja2uLk5MTFixfx8fFRFtvdsmULn376KTdv3qR+/fpYWVmxc+dO+vTpk2b1iKlTp/Lo0SMcHBy4d+8eX3zxhbJK+/79+1mwYAEhISE4OTkREBCAn59fhu9FZjmhdHKqjlIeyfOEF5L0j/79+wuNRiN2794thBAiJCRE1K5dW9SuXVtcunRJCCHE8+fPlXxF+/fvF0K8zF/01VdfpVu2Mbl/Tp8+LZYvXy5u374thBDi0qVLSl4nIYT4888/hUajEc2bNxcxMTFCCCG2bt0qhg8fLvbu3SuEeJkXqVevXiI5OVkIIUSPHj308im9zlD+nlOnTgmNRiNat26tbHs1L1JsbKySv+fMmTPK+9WwYUO9nD66XFLvv/++iIuLE0IIMWHCBL0cPGfPnlWOSc+PP/4oNBqN6Nq1q0hKSlLKHjVqlDh27JiIj48Xbm5uQqPRiEOHDgkhUnMb6dru6+srhHj5Ox4+fLgQQoj4+Hjh6ekpNBqNOHDggBBCiG7dugmNRiNWr16tHOPt7S00Go2YMmVKuu9PRjmhHj9+nKN1lPKGvIckFRgBAQGkpKTg5OSkrIxdsmRJ2rRpw/r16zl37hwdOnRQjs8oz87ruX9evw6krismhGDnzp0EBAQoC7bqUg3oVoN2dXVVMs326tWLXr16pbmeu7u7stp1lSpVCAgIyNZ6fel58OABSUlJ2NraKmvJOTg40LhxYyVV/KtcXFyUNBS61ct16d6NoWt706ZNlfUAx40bp+y/evUqz58/p3Tp0kqOJHNzczp16kRAQICS+0lHNyRrYWFBpUqVCAsLU1YOv3//PoBSjoWFBS1atOD27dtG19eQ27dv51gdpbwhA5JUYGQ1X1BGeZSMyf2zcuVKVqxYQePGjenSpQsjRoxgxIgRaa77aq4c3c+vL9r66qwuXWASOfjMuW648vUy03vPdMEou/Ux1PbExERMTU1Rq9U5mjfKUFk5kRsqN3NbSblD3kOSCoy6deuiUqm4ceOGkssoKiqKQ4cOAWl7RBnl2jEm98/3338PwLRp0+jRo0ealaN107HPnTun3G/Ytm0bzs7OzJ49+w1bmzWVK1fGwsKCZ8+eKStJh4SEZOvZrcxyQsHLth8/flxJ0bBkyRKcnZ3x9fWlevXqFC9enMjISA4fPgykBqz9+/cDWcsb9e677wIvs6rGx8fzxx9/GN2O9IJGTtZRyhuyhyQVGOXLl1dSXfTr1w9nZ2du377N06dPady4sZJS2hjG5P6pWLEigYGBjBw5kmrVqinpFHR5djw9PXFycuLq1au0b9+eGjVq4O/vT3JyssGsormpRIkS9OjRg82bN+Pj40ODBg24fv16miy6xtDlpnr8+DH9+/dn7NixeHh46B3TsWNHfH19uXnzJu3bt6d8+fKcPXsWc3Nz3nvvPSwtLRk1ahTffPMNH3/8MQ0bNlTyAVWvXj3TLMGvGjFiBCNHjmTFihUcO3aM0NBQJXNsRjLLCZWTdZTyhuwhSQXK559/zrRp06hUqRLnz59HrVYzZMgQ1qxZYzAjaUYyy/2zaNEinJ2diYqK4uHDh/j4+FC1alUiIyO5ffs2arWa77//nq5du5KYmMiFCxeoWbMmS5YsoXnz5rnR/AxNnjyZPn36YGpqyo0bN+jXr5/Slqwk96tatSp9+/alRIkS3Lp1y+C9pRIlSrBp0ybatGnDs2fPuHr1Ki4uLvj6+uLo6AikBhLdtPOAgABiY2Pp1q0bW7ZsyVLivvfee4+5c+dSvnx5bty4QYMGDQwmTnydMTmhcqqOUt6Qi6tKUiGxbNkybGxscHd3x9HRESEEffr04cKFC/j5+aXp5UhSYSOH7CSpkPD39+fMmTOULFkSFxcXHj9+TGBgIGXKlMHZ2Tm/qydJb0z2kCSpkAgJCeHLL7/kzJkzREVFYWVlhbOzM5999lm66+FJUmEiA5IkSZJUIMhJDZIkSVKBIAOSJEmSVCDIgCRJkiQVCDIgSZIkSQWCDEiSJElSgSADkiRJklQgyIAkSZIkFQgyIEmSJEkFggxIkiRJUoEgA5IkSZJUIMiAJEmSJBUIMiBJkiRJBYIMSJIkSVKBIAOSJEmSVCDIgCRJkiQVCDIgSZIkSQWCDEiSJElSgSADkiRJklQgyIAkSZIkFQim+V2BwujZsxi0WpEn17KzK0F4eHSeXKsgKErtlW19exWl9hrTVrVahY1N8UzLkgEpG7RakWcBSXe9oqQotVe29e1VlNqbU22VQ3aSJElSgSADkiRJklQgyCE7SSpChBA8exZGYmI8kHdDSqGharRabZ5dL78Vpfa+bKsKc3NLbGzsUalU2SpLBiRJKkKio5+jUqlwcKiISpV3AySmpmqSk4vGBzQUrfbq2iqElsjIp0RHP8faunS2ypJDdpJUhMTFRWNtXTpPg5FUNKhUaqytbYiLy/7sQvlXKUlFiFabgomJHBiRcoeJiSlabUq2z5cBSZKKmOyO70tSZt70b0t+VSoE9kTtonPJrvldDektZPogEFVcTI6XK6yKk1xZk+PlSm832UMqBE7EHcvvKkhvKVVcDKJEyRz/Z2yQi42N5ZtvFtKrVxcGDerD6NHD8fc/k6U2nD59ksGD+zJ4cF/+9a/m9OrVhcGD+zJt2mc8fRrGZ5+Nz85bk6GUlBSmT59EfHw88+fPpmvXDgwe3JdBg3rj4zOIW7cCAbhx4xpffTU33XLCwkJp374VQqTOeBRC0LHjv1i4cJ5e+8aOHZFuWY8fP6J7904AHD9+jK1bNwPw/fe+fP+9b7baN3fuLH79dZ/e67Cw0GyVlRWyh1TAXYq+RGjyk/yuhiTlOCEEU6ZMpGZNDZs3/4SZmRmBgTeYNGkCn38+j4YNXY0qx929Ce7uTQAYO3YEQ4eO0Dt38eLlOV733bt30LixB5aWlgAMHz4Kb+/UoPDnn/9jwYK5rFnjR61adZg6tU665djbl6V06dL8/fddqlevwc2bN6hRoyb+/meVYwICLuDm5p5pWZAaAN/E06dhfP31l5w7d4ZGjdyU7f37D2b58m+ZO/erNyo/MzIgFXDBCcHEaGO5nnCV2hZO+V0dScoxFy6cIyQkhOXLVyv3HjSaWgwaNAw/v+9p2NCVsWNHUKeOEwEBF4mMfMaECZNo0sTT6Gs8fvyIceNGsmPHPubPn42lpRWBgTeIjn7BiBFjOHjwV27fDqR58/cYN24iKSkprFq1jAsXzpGSosXbuyO9evXTK1MIwY4d21i7dqPBa8bERGNjYwvA+fP+rFu3hpUr16TblkaNGnP5cgDVq9fgzJmTtGz5PgcP/sq9e39TtWo1Ll26yJgxH+uVFRh4Q+ktvftu6tDo33/fZc+eXQCUK1cegOvXrzJq1FDCwkLx9u7EsGEj2blzO/v27darc8OGjRg//lN+//0AzZu3pFSpUnr7q1WrTkjII4KDg6hQoaLR739WyYBUwAUnBCMQPE56JAOS9Fa5ceMatWrVTnMj3NnZhdWrVyqvk5KS8fVdz19//cnatf+XpYD0uqdPw/D1Xc+BA/tZsGAOP/64CwsLC7p08WbIEB8OH/4NgHXrtpCYmMgnn4ylVq06NGjgopRx+3YgJUqUoESJEsq2//xnNdu3/0h8fBxPnoSwaNESg9c31JZGjVw5fvwYnTt35cyZU0ybNotnzyI4c+Yk77xTgaCghzg61ubixfNKOfPmfc64cRNxc/Ngw4b/cP68P9WqVadz59R7zR06fMD33/sSERHB6tXriI2NpXv3jvTp059u3XrSrVtPg/Xr23cgAJcuXUyzr359Z44fP0bPnn2y+K4bTwakAi5amzqn/4WIyueaSFJOU5GSknaKcFJSMq/GKN1wXPXqNXjx4s3+P/DwaAqAg0M5qlWrofRkSpYsyYsXUfj7n+HWrUDOnfMHIC4uljt3busFpIcPH2Jv76BX7qtDdpcvB/Dpp+PZsOGHNNc31JaGDV3x9V1FbGwMERHhVKhQEVdXd7Zu3YSjYx3q1WuAWv3ydn9kZCRPnz7Fzc0DgPbtO7J//55022tubo65uTmlSpUmKiqKAwd+SbeHlBEHh/IEBT3I8Jg3JQNSARenjQMgRls0lrKXig4np7rs2LGV5ORkTE1ffhRduXKJWrVe3isxNzcHUqcU627+Dx7cV9lv6IM/PWZmZsrPJiYmafanpGgZPXo8LVu2AlI//K2srPSOUanQq+/r6tVrQMWKFbl58zqlSumvWGCoLaVKlaZYMSv++99Dyr0vJ6e63Lv3N5cupd4/ev36unNT25F+XV5to+6aGfWQMmJiYqIXGHODnGVXwEUkRQAQq43N55pIUs5q0MCFatVqsGzZNyQnJwNw48Z1Nm78nkGDhmV47oYNPyj/clKjRq7s3bub5ORkYmNjGT16GFevXtY7pmLFSjx+/CjdMkJCHvPoUbByb8cYDRu6sXXrD0qvx9TUlCpVqnLo0G80buyhd2ypUqUpV64cJ078BcChQ78p+0xMTAz2OnNCSMhjKlSolCtl68geUgGXoE0AXvaUJCknCaviqKJzfjhYWGWejA3gyy+/Zs2aVQwY0BMTExOsrUvy73/PNXqGXU7r0qU7QUEPGTKkLykpKXh7d0pTl3ff1fD8eSTR0dHKfSTdPSS1Wk1iYiLjxk2kUqXKRk+VbtTIjZ9++lFvZpubmwc//bRVmaDwqn//ey4LFsxh7dpVODnVV7Y7Ozdk/vzZ2NraZqf5Gbp48Rxz5izI8XJfpQ78mLEAACAASURBVBKv9v0ko4SHR+dZ8q2Zzz7jZvQtGljWZ6Z9+s8zvC3s7a0JC3uR39XIE/nR1pCQ+5QrVyVPrwlv32KjP/20FbVaRbduvQzuf9vae+tWIH5+3zNv3sI0+15vq6G/MbVahZ1diddPTUMO2RVwSSIJgASRmM81kSRJ58MPu3P27Gni4+Pzuyp54ocfNjJ27MRcv44csivgElNSA1GiDEiSVGCYmpry1Vff5nc18sznn8/L/KAcIHtIBVwSqT0kXU9JkiTpbSUDUgGX8s9S7jIgSZL0tpMBqYDT9ZDiRdEYq5YkqeiSAakAu55wlURt6r2jFHLn2QJJkqSCQk5qKMBitNFoSZ1OmaBNIPDBb9ShuswzI+WY6wlXc2UVkOLqEpmuvfj48SP69OlK1arVAUhIiKdevQaMGjUWW1u7DM/TLZiaG15dxPR1f/11lMePH9OsWQul7kIIkpOTaN78PUaMGI1arWb+/C/o3Lmr3ooTr1q4cB7VqlWnZ8/UFSd27tzGkiWL+PnnX7G3LwvAyJFDGDlyDL//foAuXbqlKWv+/Nm4uDTC27sT48aNZMWK1FQTzZq58tdf/llu9507t/n88+ls3rxd2fbjj5vZt+9ntFrBRx+NpWXLVoSGPmHNmlXMnDkny9fIjAxIhYU2kbjQW6isHTI/VpKMFKONppRJ6cwPzKLnKZFGHVemjL2y2oIQAl/f75g5cwqrVv0nx+v0phITE9m82Y+VK9cQFhaqV/fk5GQ++mgop08706RJM2bMmJXhc0gNG7py9OgfSkA6ffoUjRt7cPr0STp27ExCQjz379+jXr0GRj0kfOHCuTdq24ED+/H1/U5vSaTr16/y+++/sn79D8TGxjBy5BBcXBpRtqwDtra2nDz5F02aNHuj675ODtkVYFHaV56gT9YSlfw8/yojSblMpVIxbNhI7t69w+3btwDYtGkDQ4f2Y9CgPqxatYzXn+O/e/c248aNZPjwgXTr1pHdu3eg1Wrp3r0TDx7cByAuLo6uXTuQkJDAqVMn8PEZyJAhfZk+fRLPn6cGzjNnTtG/f0+GDu2fZuFRnd9/P0CDBi4G17FLTEwgKSmZ0qVtAPjoIx/On/fn/Hl/Jk4cw7Rpn9KnT1dmzpxMUlISjRq5ceXKJQCSkpK4f/9vevbsy5kzpwC4evUK9erVx8zMjLFjR3D+vD9CCFas+JbevbsyduwIgoODAFi6dBEAPj6DlPosWvQlgwb1YdCgPgQFPSQlJUVJYvjqvwcP7hEdHc1ffx1l9uz5em06efI4LVu2wsLCAhsbW1xcGnH8eGqy0HbtOrBli+H0G2+i0AWk6OhoOnbsSFBQUJp9169fp2vXrrRt25YZM2Yo62P5+fnRunVrhg4dSmJi6j2ZgIAAFi9enKd1z6oXWv0lXaJM4lGHBmH6IDCfaiRJucvMzIxKlSpx//49Tp06wc2b11m7diPr128hLCyM338/oHf8vn17GDRoGP/5z0aWL1/Nd98tR61W0759R+XY//3vCE2bNiM2NpbVq1fyzTcrWb/+Bxo39uD//m8FiYmJzJ//OfPmLWTdus1YWFgYrNvx43/i7Pxy1e+nT8P+yRLbhw8/9MbGxoYaNWqmOe/KlUtMnDiZLVt28ORJCKdPn8TW1g5ra2sePQrm8uUA6tath4tLQy5duohWq+XixfNpFlX93/+OEBh4k82btzN37kKCgx8CMGHCJADWrvVTjnV1bYyf34+4ubmzZ88uTExM9Nb/0/2rXLkqJUqUYP78RTg4lNO73tOnYdjZlVFe29mVUZZCql79Xe7du0tUVM5+SS5UASkgIIA+ffpw7949g/snTZrErFmzOHjwIEIItm9PHQv18/PjwIEDVKlShWPHUiO8r68vPj4+eVX1bIlJ0U8DHa1OQJWYYHR6aEkqnFRYWFjg73+Ga9euMGzYAIYO7c+NG9f4+++7ekeOHTuBxMRENm1az9q1/0dcXOoixN7enZRFR3/77Rfat+/EtWtXePIkhPHjRzF4cF927dpOUNBD7t69jZ2dPVWrVgNS0zkY8nraCd2QnZ/fj+zffxgrq2JKb+VV1arVoGxZB9RqNVWqVFPSTugS850+fRI3Nw8sLCypUqUad+7cIiDgorLQqs6FC+do2fJ9TE1NsbGxwcMj/bxQzZu/98+1q/P8eWSGPaT0CCH00oCkvn4ZMuzty/LoUXC652dHobqHtH37dj7//HMmT56cZl9wcDDx8fE4OzsD0LVrV5YvX07fvn0xNTUlPj6e2NhYzMzMOHz4MK6urmmyIhY0sUI/8MSq5bNI0tstKSmJhw/vU61adc6fP0vPnn3o3bs/AC9evMDExEQZZgOYNWsq1tYl8fRsjpdXGw4fPghA+fLvUK5ceY4e/S8REeE4OdXl2LH/Ub9+AxYuTE2el5CQQFxcHCEhj4FX0zmkTUsBGaedMDMzo337DqxZsyrNPl3KidQyXqadaNTIlTNnTnP16mUl6V3jxu5cunSR0NAQqlWr/tr1Vbw6YplePeFlPXXX0/WQssLevixPnz5VXkdEhFO58ss16kxMTPUCVE4oVAFp/vz56e4LDQ3F3t5eeW1vb8+TJ08AGDNmDL1796Zu3bp4eHgwevRoVq1K+4djLGMWCcwRcSkQDyZqFSozNckWWqxLWEDcU3hyE6yKQ43aeVOXPGRvb53fVcgzed3W0FA1pqYvP0TUJmpMTHJ+oESN/nWANK9119Vt12q1rF+/hrp161GlSmXc3Bqzdu1qunbtjrm5OdOnf0aHDi9X3zY1VXP27Bm2bduFvb09O3akjoioVKkfwJ06dWbp0sX06NEbU1M19evXZ+HCeTx69JDKlauwdu33hIWFMX36TJ49i+Dvv29Ts6aGI0d+R6VSpalvpUqVCQ0N4d13a6SpO6T2YGrVqq1s0x3zalkqlQq1OvW1m5sba9f+H6amZjg4pM6s8/BowhdfzKJ+/QZ655iYqHF392Dz5o1069ad+Ph4zpw5qRyXGpy0SiDSnatWqwy2xZDX2+Tp2YyFC+fTv/8A4uLiOXfuLCNHjlb2h4WFUqlSxTTvg1qtzvbfdaEKSBnRarV6qZBTu5eprzt37kznzp0B2Lp1Kx07duTSpUv4+vpiY2PDnDlz0iThykherfYdEZM6PpuiFZgkaQlNieZFdAJEJ5Bsb4rqcRhJJXMvv31+kKt95y6tVqs3+8tKFCMiMSLHr1NcXULvOoZWv05J0fL0aRj9+/f+p24p1KzpyKxZ80lO1tKkSXNu3rzJ0KED0WpTcHdvStu2Hf7p0UByspahQ30YMWIoFhbm1KhRk/Ll3+HhwyAqVqxE8+bvsWDBXNq0aU9yspZSpWyZOnUW06dPQatNwd7egVmzvgBM+Pzz+cyePRMTExM0mlr/TOXWr2/Tps3w9z9D48ZN9OquUqW+rw4O5ZkyZYZyXkpK6n9fLUsIgVab+trSsjgWFpY4OzdU9levXpOIiAgaNXLXOyclRUvTpi24cuUKffv2wNbWjipVqitlNWvWgv79e/P995uU9yb1PRUG22KIrr66Yx0d6/Cvf7Vn8OABpKQkM3z4KGxty5CcrOXu3dtUrlyFYsVK6J2Tek1tmr9rY1f7LpTpJ1q1asXGjRupWPHlh3FwcDCDBw/m0KFDAPj7+7N8+XI2bnw5EyQ2NpZx48axdu1aevfuzYoVK9i9ezelS5emVy/Dy8gbklcB6eun87mUdIGE5CTMk7S8G2fDwpAPAEiu5YIqOookR5dMSilcZEDKXUUl/YQQglOnjrN7905liO5NJSQkMHr0cHx912eYMRbevvQTr1u+/BtcXd1p2rSZTD9hSIUKFbCwsODcudT5+Hv27KFFixZ6x6xbt47BgwejVqtJSkrC1NQUlUpFQkJCflQ5U4miYNZLkgq65cu/ZcmSRYwZMyHHyrSwsGDgwKHs2vVTjpVZGD15EkJ4eDhNm+bsM0jwFgQkHx8fLl9OTTG8ePFiFixYQLt27YiNjWXgwIHKceHh4Vy7do3mzZsr5/Xq1YvDhw/TqVOnfKl7ZuJfC0iJqmS913IKuCQZ9vHHn7J9+x69m/A5oWXL95UJCEWVg0M55sz5MlfKLpRDdvktr4bspj6ZQJA2SBmyK59QnJWPugOpQ3amNy6QUrHGWzVsJ4fscldRGbLLb0WpvXLIrohIeC3lRJJKLrAqvTn5HVTKLW/6tyUDUiGSrEr7jUsO20lZYWpqTkxMlAxKUo4TQhATE4WpqXnmB6fjrZn2/TZKFvr3jAwFJLlyg5QVNjb2PHsWRnS0cYuf5hS1Wo1WWzSGsKBotffVtpqammNjY5/JGemTAakAS0Z/yC6FovEHLuUeExNTypQpn+fXLUr3BqFotTcn2yqH7AqwZKF/zyhBlcxVi5B8qo0kSVLukgGpAEt5bchOIIhWp01lLu8jSZL0NpABqZCJMhCQ5H0kSZLeBjIgFWAppJ3mHWWSNiBJkiS9DWRAKsBeH7KD1JxIhshhO0mSCjsZkAqo6wlXSTIQkMJNYw0eL4ftJEkq7IwOSPHx8Ur67zt37vD999/j7+9v9IXOnj3LsGHDaNWqFcHBwcpK25JhMdpotP8kDVOJFFQidcp3nEom6ZMk6e1kVEA6deoUzZo149y5c4SGhtK/f3/WrFnDoEGD2Lt3b6bnHz16lOHDh/POO+/w9OlTJXfRjBkz2Llz5xs34q2XLOCftfPiVWl7TTrq0CDMbl6QQ3eSJBVKRgWkJUuW0LFjR5ydndm9ezeWlpYcO3aM2bNns3bt2kzPX7lyJZMnT2bu3LlK2t2xY8cyZcoU1q1b92YteEtFaaMMbk9Upx+QVIkJiBIl5dCdJEmFklEB6fr16wwfPhwrKyuOHTvGe++9h7m5OZ6enty/fz/T82/fvp0mNxHA+++/z8OHD7Ne6yLgRToByRhygoMkSYWRUQHJ2tqamJgYoqOjuXDhAp6engAEBQVRunTpTM+3sbExGHiuXLlCmTJlsljloiEmxXAvJyadWXavkhMcJEkqjIxay65FixbMmjWL4sWLU7x4cZo3b86JEyeYM2cO77//fqbn9+zZkzlz5jB9+nQAHjx4wOnTp/n222/p06doJ7tKT6wwHFDiMhiykyRJKsyMCkizZs1i2bJlPHjwgFWrVmFhYcGFCxdo1KgRU6dOzfT8kSNH8uLFC8aNG0diYiLDhg3D1NSUIUOGMHr06DduxNsoThie3m1oxW9D1KFBmFoVJ7myJierJUmSlGuMCkgHDx5k4sSJWFhYKNvGjBlDbGws27ZtY/DgwRmer1KpmDRpEmPGjOHOnTuYmZlRtWpVLC0tCQ8Px87O7o0a8TaK0xpekcHYFb/lsJ0kSYWNUfeQpk2bRkxM2g+3u3fv8s0332R6fu3atYmIiKBYsWLUq1ePWrVqYWlpyaNHj2jdunXWa12EyRQUkiS9rdLtIfn5+fHVV18BqZkAdRMZXufq6mpw+6+//sqxY8eU8+fNm6fXw4LUSRHFixfPVsWLqjh1agoKRyOOlcN2kiQVJukGpP79+2Nra4tWq2XKlCnMnDkTa2trZb9KpaJ48eK4u7sbPL9hw4bs2LFDSZUcGhqKmZmZ3vmlS5dm0aJFOdWWt0qiMDybLr0UFIbIYTtJkgqTdAOSiYkJnTp1AqB8+fI0bNgQU1PjE8yWK1dOeeh12rRpzJgxgxIlSrxhdYuO+HQCkiRJ0tvKqAjTuHFj/P39uXLlCgkJCUqvR2fUqFEZnr9gwQKSk5N58uQJKSmpKRWEECQmJnL58mU++OCDbFb/7ZWcQUAylBMpPXLYTpKkwsKogOTr68uSJUuwtrbWG7aD1KG3zALSX3/9xZQpU4iIiEizz8rKSgYkAxJE+ouoZiUnkhy2kySpsDAqIG3atIlPPvmEESNGZOsiixcvpn79+gwaNIiPPvqIJUuWEBISwpIlS5g7d262ypSMJ3tJkiQVBkYFpOjoaDp06JDti9y5c4evv/4ajUZDnTp1MDMzo3fv3lhZWbFu3TratGmT7bLfVskGciHphJq+yFJZspckSVJhYNRzSE2aNOH48ePZvoipqakyvbtKlSoEBqYu/Onm5sadO3eMLmffvn14e3vTpk0btmzZku5xkydPZteuXcprPz8/WrduzdChQ5WcTgEBASxevDg7zckTyaQ/ZBdhEpeHNZEkScob6faQVq9erfzs4ODA3Llz8ff3p0qVKkoKCZ3M7iHVrVuXnTt3Mn78eDQaDSdOnGDIkCHcu3cPtdq4HIFPnjxhyZIl7Nq1C3Nzc3r37o27uzvvvvuu3jGff/45J0+exMPDQ9nu5+fHwYMH+fLLLzl27BheXl74+vqyYMECo65d0GSUEyk96tAgzAAhh+4kSSqg0g1I27dv13ttb2+Pv79/miyxxkxqGDt2LCNGjMDa2prOnTuzatUqunTpQnBwsNErNZw4cQIPDw9ldfG2bdvy22+/MXbsWOWYffv24eXllWYFclNTU+Lj44mNjcXMzIzDhw/j6upKqVKljLp2fkgWKenuyygnUnqUXEnR2U9rIUmSlJvSDUj//e9/c+wi7u7uHDx4kKSkJGxtbdmyZQs///wztra2DBw40KgyQkNDsbe3V16XLVuWS5cu6R0zfPhwAM6dO6e3fcyYMfTu3Zu6devi4eHB6NGjWbVqVbbbY2eXu89TXYq+RIIqDhO1CgC1mYp/spmjUkGKmRab0sWhhEXak9PbrtsXdheigqBG7Vyq/Zuzt7fO/KC3hGzr26sotTen2mrUpIZHjx4Z3K5SqTAzM8PW1jbDobfXH4ytWbMmkydPJjIykk8//ZQVK1ZkWgdd2nMdIYTe64x07tyZzp07A7B161Y6duzIpUuX8PX1xcbGhjlz5mBlZWVUWQDh4dFotSLzA7MpOC6U5BQtKUJgqgZt0ssU5kIF8SnJPIuMwTQ67bNKyelsV/aFPyfFKoykkhVzrf5vwt7emrCwrE3aKKxkW99eRam9xrRVrVYZ9UXeqIDUqlWrDD/8zc3N8fb2Zvbs2cp6dXfu3FGeO9q9ezdeXl5phshu3ryprHeXmXLlyukNF4aFhVG2bFmjztWJjY3l0KFDrF27lt69e7NixQp2797N3r176dWrV5bKyk9JqvSH8yRJkgorowLSvHnzWLx4MePGjaNRo0YAXLx4keXLl9O3b1+qVavGihUrWLp0KVOmTAFSF04dOXIkkNqTevVez6v69+9vVEWbNm3KihUriIiIwMrKit9//z3LzzCtW7eOwYMHo1arSUpKwtTUFJVKRUJCwVqmJyqT9OXG5kRKj3wuSZKkgsiogLR+/Xq++OILveeFatWqhb29PUuXLmXfvn3Y29szadIkJSC1bNmSo0ePIoTgvffeU+4Zvap48eJGr2/n4ODAxIkTGThwIElJSXTv3p369evj4+PD+PHjqVevXobnh4eHc+3aNSUw+vj40KtXL2xtbfH19TWqDnnlRS4HJPlckiRJBZFRASkoKEhverVOtWrVuH//PgCVKlUiMjJSb7+DgwMAN27cSHNuRERElhdb7dSpk7Lgq87atWvTHKdLm/EqOzs7vYkM3t7eeHt7Z+n6BUVO5ESSvSRJkgoaox4Cql27Nhs2bNBbVFUIwYYNG5RAdeHCBcqXL2/w/KioKGbMmMHNmzfRarWMGjUKT09P2rZtqwQ06aWYlIx7LwmqZK5pb7/RNWQvSZKkgsbojLG//PILbdq04ZNPPmHChAm0adOG/fv3M336dC5evMjUqVMZMGCAwfPnzZvHhQsXMDMz48CBA5w8eZJvv/0WjUZTaB9OzU2xIuNAIRA8IiyPaiNJkpQ3jApIDRo04Ndff6VTp07ExsaSnJzMBx98wKFDh3B1dcXa2ppVq1bRr18/g+cfPXqUr776iurVq/Pf//6XZs2a0b59eyZMmMDZs2dztEFvgzgRm+kxL3jz3o06NAjTB4FvXI4kSVJOMDrjnoODA+PHjze4r0aNGtSoUSPdcxMTE5WHWk+cOMG4ceOA1Nl3xi4dVJTEaTNPLxFDLGD3RteRw3aSJBUk6QakoUOHsmzZMqytrRk6dGiGhegyw6anVq1a7Ny5Ezs7O549e8Z7771HYmIi//nPf6hVq1b2al7EPSUSqPTG5cg17iRJKijSDUgODg7Kw7Bly5Y1elUEQ6ZMmcLo0aN59uwZw4YN45133mH27NkcOXLE4Cy5oi7RiPTl8eTMs1NyjTtJkgqKdAPSq5MNDE2jzgpnZ2f++usvXrx4oazWMGzYMD777LMsT/0uCuKNCEiSJElvm3QD0r59+4wqQKVS0bFjx0yPU6vVeksHVar05sNNRVkCiTlannwuSZKk/JZuQJo0aZJRBRgbkCTjJRvRQ8rpgCQnOEiSlN/SDUgrV66kWbNmWFpa5mV9JCBGKzPCSpJU9KQ753rSpEnKUkBeXl5plgWSck9G6ct1Eo04Jqvkc0mSJOWndHtIxYsXZ8WKFbi6uhIcHMz+/fvTnYDQpUuXDC/i5eXFjh07sLGx0dseGhpK586dOXnyZDaq/vbKKFusThJZzxqbGTlsJ0lSfko3IH322WcsXLiQPXv2oFKp0l3iR6VSGQxIR48e5fLlywAEBwezdu1aihUrpnfMvXv3SEmRuX1elyJyPtgYS05ukCQpv6QbkLp06aIEmlq1avHnn39iZ2f8ygAVK1bkyy+/VBZkPXjwICYmJsp+lUpF8eLFmTlzZnbrXqTlRg8JZC9JkqT8Y9TSQUeOHEmTyygzNWrU4ODBgwAMGDCAlStXpskYK2VfMrnXs5S9JEmS8oNRAalChQpvdJFNmza90flFyfWEq0at1JCbZC9JkqT8YPTiqm/iwYMHzJo1iytXrhAfn3bh0CtXruRFNQqFGG00ySIZtSpPfjXpkmvcSZKU1/LkU2/GjBmEh4czduxYOWxnhBSEcXlBcpFc406SpLyWbkBq0aIFP/30Ew4ODqxcuZJhw4ZhZWWVrYtcunSJrVu3Urt27WxXVNIXn8MrNUiSJOW3dL+IR0VFcfPmTQC+++474uKyv3qAnZ3dG60WLqUVQxxXLUJy/TryYVlJkvJKuj2k999/nxEjRqBSqRBC4OnpmW4h169fz/AiH330EfPnz+fLL7+Ui6rmEIEgWp15Ir83JSc4SJKUV9INSIsWLaJLly48f/6cyZMnM3PmTKytrY0u2MnJSa9XlJycTJs2bQxmiZWTGl6K0hp/zyYqDwISyGngkiTljXQDkqmpKS1btgRSZ8l17do1S/eQ5s6dK4fpsiEk6bHRx0aZ5E1Akr0kSZLyglGz7MaOHculS5dYt24dt27dwtTUlHfffZdBgwZRv359g+d07do1RytaVMSKgvnBL3tJkiTlNqMC0smTJ/Hx8cHJyYmWLVui1Wo5f/48ffv2Zd26dTRu3DjD86dNm2Zwu0qlwszMjHLlytGuXTuqVauW9RZIeUL2kiRJym1GPe6yZMkS+vTpw7Zt25g8eTJTp05l+/bt9OvXj6VLl2Z6fmJiIrt37+b48eNERUURFRXFqVOn+Pnnn7l58yZ79+6lc+fOnD17NsNy9u3bh7e3N23atGHLli1p9l+/fp2uXbvStm1bZsyYQXJy6npvfn5+tG7dmqFDh5KYmDpdOiAggMWLFxvTfEmSJCkPGBWQbty4Qd++fdNs79WrV6Yz7AAsLCzw9vbm8OHDfPfdd3z33XccOnSILl26oNFoOHDgAEOHDmXJkiXplvHkyROWLFnCDz/8wO7du9m2bRu3b9/WO2bSpEnMmjWLgwcPIoRg+/btQGpAOnDgAFWqVOHYsWMA+Pr64uPjY0zzC6xodd4uMSSngEuSlJuMCkhlypTh8eO0N9sfP36cJqWEIQcPHmT06NGYm5sr20xNTRk+fDi//PILkHrPKaPgduLECTw8PChdujTFihWjbdu2/Pbbb8r+4OBg4uPjcXZ2VsrT7Tc1NSU+Pp7Y2FjMzMw4fPgwrq6uBXLViGcpz4w+Nlad80n6MqJKTMDk/k0ZlCRJyhVGBSRvb28+//xzTp48SXx8PHFxcRw/fpzZs2fTtm3bTM+3tLQkKCgozfagoCBMTVNvYyUkJOgFrNeFhoZib2+vvC5btixPnjxJd7+9vb2yf8yYMfTu3RsADw8Ptm7dSv/+/TOtd354rn2e31XIkLyXJElSbjF6lt3t27cZMmSI3lRub29vJk2alOn5Xbp0YcaMGXz66ac0aNAAIQQBAQEsXbqUTp068fz5c7755htcXV3TLUOr1epdWwih9zqj/Z07d6Zz584AbN26lY4dO3Lp0iV8fX2xsbFhzpw5WZrSbmdnOHNuTrCINMUkSYVaDSba1PqrzVSQmlYKlQoQKtSoMDc3xbqEhX4BpYvD69sy25fl7cXA3vhn0rLKPhfLLmhkW99eRam9OdVWowKSpaUlq1ev5s6dOwQGBmJhYUHNmjWNXnXhk08+ISUlhTlz5pCQkIAQAktLS/r27cvEiRM5evQokZGRGU4yKFeuHP7+/srrsLAwypYtq7c/LCxMef306VO9/QCxsbEcOnSItWvX0rt3b1asWMHu3bvZu3cvvXr1MqotAOHh0Wi1wujjsyImIYYUrUAtIEUITNWgTRLwz/WEChACLYLnyXG8iNa/j5QcGYNptOF7S+nty+p2ERiINjI2V1YCt7e3JizsRY6WWVDJtr69ilJ7jWmrWq0y6ot8llb7rlGjBjVq1MjKKQCYmJgwdepUJkyYwJ07dzAxMaFq1apYWloC0Lp1a1q3bp1hGU2bNmXFihVERERgZWXF77//zty5c5X9FSpUwMLCgnPnztGoUSP27NlDixYt9MpYt24dgwcPRq1Wk5SUhKmpKSqVioSE/M0/9KoEYfx9oWfq7K8v+CbkSuCSJOWGXEs/cf78eRo0aICJiQnnz59Ps//acFwHJAAAIABJREFUtWvKzw0bNsy0PAcHByZOnMjAgQNJSkqie/fu1K9fHx8fH8aPH0+9evVYvHgxM2fOJDo6GicnJwYOHKicHx4ezrVr1xg7diwAPj4+9OrVC1tbW3x9fXOgxTkjWRifmjxRnTtpzI0lH5aVJCknqYQQuTL2VKtWLY4fP46dnR21atVSFmlNUwGVyqip4wVJbg7Z+TwaRGRKJGYqM5JEEhamZiTGxWGeknq9JJUWM6Em0VJN7ShbFoZ8oHd+ci0XTG9cMFh2evuyuv3VfcLcgpQqjjkWlORQx9upKLUVilZ7823ILiuOHDmCjY2N8rNknJQs9JAKAjnrTpKknJJrAalChQoGf5YkSZIkQ4wKSHfv3mXevHlcuHCBpKS0N90NpY/QpZowxsGDB4067m13PeEqiaLgTLAwlryXJElSTjAqIM2ZM4dHjx4xYcIESpYsaVTBH3zwQeYHSXpitNFo87sS2SCH7SRJyglGBaTLly+zfv16GjRoYHTBx44dY+XKldjb27N79268vb0zXIlBylpyPoBEVeG63yRJkpQRo5YOKl26dJaDyfXr1wkNDQVS009ER0dnvXZFzIssBqQkVcHpT8mFVyVJelNG9ZBGjRrFl19+yRdffEGVKlXSpCA3pFGjRvTp04cyZcoghKBbt27pnidn4RV+uoVXVXExubKCgyRJbz+jAtL69et5+PAh3t7eqFSqNIHF0KSGZcuWsW/fPqKioli2bBkdO3Y0amVwyXhJqpT8roIeuYKDJElvwqiANGLEiCwXXLJkSfr16wfAgwcPGDlyJCVK5N6ipEVRcgEasnuVnHUnSVJ2GBWQPvzwQ+XniIgITE1NjZ5tB7BgwYKs10wqtOSsO0mSssOoSQ0AGzZswNPTE09PT9zd3WnevDnr16/PzbpJkiRJRYhRPaQtW7awZMkSBgwYgJubGykpKfj7+7N06VKKFSuWpdQNUvpiUrLWqyioQ3Ygh+0kSco6owKSn58fM2bMoGfPnsq2Vq1aUbVqVfz8/GRAyiHh2rDMD3pFSgF+jFY36w6QQUmSJKMYNWT35MkTPDw80mz38PDg4cOHRl8sKiqK0NBQnjx5ovdPSvU8pWCnL88qeS9JkqSsMKqHVLlyZc6ePUvlypX1tp8+fZpy5cplev6lS5f49NNPCQoK0tuuSzNe2NJP5JboLD4Ym6BK5qpFCE4Jmf8OJEmSCjqjAtKgQYOYO3cuDx8+xMXFBUhNwLdx40YmTpyY6fmzZ8/GwcGBKVOmZGl2XlGTlWyxAAJBtDo+l2ojSZKUt4wKSN27d+fFixd8//33rF69GoBy5coxdepUo+4f3bp1i927d2cr/blUuMnJDZIkGcvofEhDhgxhyJAhREREYG5unqWHXCtVqkRUlHx6vyiSSwpJkmSsdAPSvn37aNu2Lebm5uzbty/DQjp16pRm26uTFfr168esWbOYPn06VatWTbP0kIODQ1brLRUickkhSZKMkW5AmjRpEk2bNsXOzo5JkyalW4BKpTIYkFq2bKmXoE8IwZAhQ9Jsk5Maig51aBDmz8PRlqsse0qSJKWRbkC6ceOGwZ+NtXHjxuzVqAhLFm93fiNVYkJqb6mUXX5XRZKkAsio55AGDhxo8B5QREQEXbt2NXhO48aN9f7Z2dlhaWmpvL5y5Qp2dnY0btz4zVrwlriecJVobdZzRkXJWXaSJL0l0u0hnT9/ngcPHgBw5swZ9u7dm2Yiw+3bt7l3716mFzl69Cjjxo1jxIgR1K9fH4A//viD5cuXs3r1aoMP3RY1qenLs55O4rFZ4bwvo0vmJ4fuJEnSSTcgqdVqZs6ciRACSLtit0qlonjx4owePTrTiyxdupTRo0czatQoZdumTZtYtWoV33zzDT/99FN261/kxagT87sKWaYODUKlUpFiXyG/qyJJUgGSbkBydnZWEu81b96cvXv3YmNjk62L/P3333To0CHN9k6dOrFmzZpslfk2ShEFK+FeblElJuR3FSRJKoCMuodkbW1NSEhIti/i4ODAhQsX0my/fPkytra22S73baNF5HcVJEn6//buPSzKal/g+HeGGQgEL+CgpkhpBV5CLZ40O6LZ3mBcRN2eNC9kHrFST2Vpx0tlpOXOOEdLt4q2e7ykKdutouYFzdPelVppKZwtKVlpYMLIxeQ6M8x7/sCZGJmR4eoAv8/z+DjvWu9a71rzKj/e913vWuK2cerF2MLCQu644446H+TJJ5/kzTff5JdffuH+++8HKpc937BhA9OmTXO6nr1797JmzRpMJhNPPfWUdUVai4yMDBYuXEhxcTGhoaEkJCSg0WjYuHEjmzdvpnv37qxduxZ3d3fOnDnD4cOHmTNnTp371ZCyTdm3uwlNTmZxEEJU5fRcdi+88AKTJ0+mW7dueHh42OQ/8MADtyw/ZcoUDAYDmzdvZuXKlQDodDpmzpxJXFycUw3Nyclh+fLl7Ny5E3d3d8aPH8/AgQO55557rPvMnTuXJUuW0L9/fxYsWEBycjITJkxg48aNHDp0iLfffpvPP/+cxx57jKSkJJdayVZvan2znsssDkKIqpwKSMuXLwfgtddeq5bn7Iut06dPZ/r06RQUFKDVams19RDAsWPHGDRoEO3btwcgIiKCgwcPMmvWLACys7MpKyujf//+AIwZM4b333+fCRMmoNFoKCsro6SkBK1Wy5EjRwgNDaVdu3a1aoNoeDKLgxDCwqmA9Omnn9b7QPn5+fz000+YzZWLyimKgsFgID09neeee67G8rm5ueh0Ouu2v78/aWlpDvN1Op11+qKZM2cyfvx4+vbty6BBg5gxYwarV6+uc1/8/GoXTJ3hWe6O5ZUiN7MKtbrybwC1VoXl8ZJKBSgq1KhArcLkYcbHu8oVa/s24G17BVtjXm3TG6MujQl0PgDobvzdGkhfW67W1N+G6qtTAalr18rhuRcuXOD8+fNotVp69OhBjx49nDrI7t27ef311zEYDKhUKuuUQVC51pIzAclsNtuddsiZ/NjYWGJjYwHYtm0b0dHRpKWlkZSURIcOHUhISMDT09OpvgDk5RVhNjfsAITSEgPmG4PsKhQFtVL5t0YNZqMCN46nqABFqRwAYVb4zVTG9aLfR62ZCovRFNkfxeYor7bpjVGXqqgEo/46Op0Pev11u/u1NNLXlqs19deZvqrVKqd+kXdqlF1ZWRnPPfccUVFRzJ49m1mzZhEVFcWzzz5LeXnNQ3jXrl3LqFGjOHz4MG3btmXnzp2sW7eOLl268MwzzzjTBDp37oxe//sS33q9Hn9/f4f5V69etckHKCkp4fDhw4wcOZJly5axZMkSevbsyZ49e5xqg2hcmkvn4YLMayhEa+VUQEpMTOTcuXOsW7eOb7/9llOnTrF27VoyMzNZsWJFjeWzsrJ4+umnCQgIIDg4mNzcXIYMGcLChQudnvNu8ODBHD9+nPz8fEpLS0lNTSUsLMya37VrVzw8PDh16hQAKSkpNvkAH374IVOmTEGtVmM0GtFoNKhUKqeCqmh8qtJikCXPhWi1nApIBw4cICEhgbCwMLy8vGjTpg1Dhw7ljTfe4JNPPqmxvKenp3XJicDAQM6fr5w2plevXly8eNGphnbq1InZs2cTFxfHqFGjiI6OJiQkhPj4eNLT04HKwLl06VJGjBhBSUmJzQi+vLw8zp49y5AhQwCIj49n3LhxHDlyxO5s5U2toKKgTuXKVC1jQlZ1bhZu+tY39F0I8TunniGVlpbSrVu3aundunWjsLCwxvIDBgzgr3/9KwsXLqR3796kpKQwffp0zpw5Q5s2bZxubExMTLXgsX79euvn4OBgduzYYbesn5+fzUCGyMhIIiMjnT52Y7tmvlancgZ1ywhI1tkbfr2EplwlQ8CFaIWcukLq06eP3R/0ycnJBAUF1Vj+pZde4tNPP2Xz5s1ER0dz5coVBg4cyNy5cxk5cmTtWy1arvKyylt3N2gunbdOxCqEaNmcukJ64YUXmDJlCt9++631Jdhvv/2W9PR0kpKSaiwfHBzMkSNHKC0txdvbm+TkZFJTU/H19eXxxx+vXw9aCKNSt+dY+W4lfOn1E4+U3N3ALbp9LAv5Ke38cNNnyySsQrQSTl0hhYaGsmXLFvz9/fnss884fvw4AQEB7Nq1i0ceecSpA3l6emI2m/nqq6/w8fFhxIgREoyqMCjGupVTm7iiqdvtPlelMpSjvl6I4t0WymW9JyFaC6eukAD69evHe++9V6eDGAwG3njjDXbu3IlarebQoUP8+c9/pqioiFWrVuHj03peIBNCCGGfU1dIAPv372f8+PE88MADhIaGMnnyZP7xj384VXbVqlWkp6ezdetW6zx406ZN48qVK7z77rt1a3kLkldxtc7Ll5erKihSt+xh6+rcLHmOJEQr4FRA2rZtG3PnziUwMJA5c+bw4osv4u/vz8yZMzlw4ECN5Q8cOMCrr75qMwnrgAEDWLx4MUePHq1761uI/Io8TNTtlp2JCkrUdSvbXKgM5ahKi2WAgxAtnFO37D744AMWLFhgs9zDpEmT6NevH6tWrarxWVBubi533nlntfSOHTty/XrrmF5D1I+sMitEy+fUFZJer2fw4MHV0sPCwsjKyqqxfK9evexO0JqcnExwcLAzTRCtnMpQDuVlqHOz0J77Dvevj8jVkhAtjFNXSEOHDmX79u3MmzfPJj01NdU688GtzJkzh2nTpnH69GlMJhPr16/nwoULnDlzRpYwF7ViWa7CLesCSju/290cIUQDciogBQQEsHnzZr755hseeughNBoN//rXvzh+/Dh//OMfbdZJWrx4cbXyoaGhfPzxx3z44YcEBgaSnp7OPffcw6JFi7jvPnkjH8CoVNS57K8aWUtICNH8ORWQ0tLS6NevH1C59LhFaGgoBQUFFBRUzsNWdfmHm/Xq1UtG1N2CuY6j7ADyNSUN2JLmxXLbTqYaEqL5cyogbd68ubHbIUStyUAHIVoWp1+MvXz5Mlu2bCEzMxONRsO9997LE088YV28T4imZpmQVZ2bhcazjVwlCdHMOTXKLiMjg5iYGPbv34+npydubm6kpKQwcuRIvv/++8ZuoxC3ZHlPSQjRvDkVkN555x3CwsJITU3lvffeY+XKlRw+fJhhw4Y59VxoxYoVZGfLWjdCCCEccyognT59mhkzZqDVaq1pWq2WZ555hu+++67G8ps3b8ZsNte9lS1YXsVVTpQeo1QprXdd591zG6BFzZM6Nwv3r4+gPfeddaCDzOwgRPPiVEBq27YtxcXVb4kUFRWh0dT8GOqRRx7hb3/7GwaDofYtbOHyK/L41XgZUz2GfVv87JHfAC1qnqrOEF51miG5lSdE8+HUoIZhw4bx5ptvsmLFCrp37w7Azz//zFtvvcXQoUNrLF9YWMi6dev44IMP0Ol03HHHHTb5hw4dqkPThXBMVVpsXbrCEpgUGfgghEtzKiC99NJLPP3000RERNChQwcACgoK6NevH/Pnz6+x/EMPPcRDDz1Uv5YK4STLcPCqn01390JVVPkCsebSedRXLmHu3L3OAUrefxKi4TkVkCoqKvj73//O559/TmZmJh4eHtxzzz08/PDDTh1k1qxZ9WqkELVhGQ5+82drWmkx6uuFqMpLq1053RxoHAUeuRUoRMNzKiD96U9/YuXKlQwdOtSpW3T2HD58mHXr1lnfY7rnnnuYOnUq4eHhdapPiPqyzItX9cpJc+m8zYu2EniEaDpODWpQFAV3d/c6H+TAgQM8//zzdOvWjblz5/LCCy/QqVMnZs+eTWpqap3rFaKhWEfkyZLpQtw2Tl8hTZs2jTFjxtCtW7dqgxJiYmJuWX716tW8+OKLPPPMM9a0yZMns27dOtauXStXSeK2sj5zqhKMLAMh3PTZ1ismR7fv5HmSEA3DqYC0evVqAJKSkqrlqVSqGgPSxYsXGTFiRLX0iIgI/vKXvzjTBCEajaPnTIp3W8i6YJOmzs2qFqjqe1tPApoQlZwKSPWdHqhLly6cP3+ewMDAavVaRu0J0dgsc945s59KpcLk3bZanuW5U9VAVV/ynEqISrcMSCUlJZw4cQIPDw/69+9PmzY1/2e2Z+zYsSxatIjCwkIeeOABAE6dOsWKFSsYN25cnepsjvIqruLn1tEm7ZuSr8g3Xa1XvfnqEhL8D9LG7M7wetXUsjk75529KyZHNJfO21wt2csHufoRwhkOA9L333/PtGnTuHq18oelv78/q1atIiQkpNYHmTp1Kjk5OSQkJFBRUYGiKGi1Wp5++ulaDQnfu3cva9aswWQy8dRTTzFx4kSb/IyMDBYuXEhxcTGhoaEkJCSg0WjYuHEjmzdvpnv37qxduxZ3d3fOnDnD4cOHmTNnTq37U1f5FXnVAtIFYybXlGv1qtegNvGjx1U6G6v/Ri8aV9UXcME2ANkbtSeEcMzhKLv//u//JiAggG3btpGcnMzdd99NQkKC0xUvW7aMa9cqf9Dm5OSwYMECTpw4wfbt20lJSeHkyZO89NJLuLm5OVVfTk4Oy5cvZ+vWrezevZvt27fzww8/2Owzd+5cXn/9dQ4dOoSiKCQnJwOwceNGDhw4QGBgIJ9//jlQ+TwsPj7e6f4IcTN1bhZu+mzrZ8s8eparsJuDlRDi1hwGpNOnT/P666/Tv39/QkJCWLJkCRkZGZSUOLc66UcffcT169cBeOyxxygsLMTb25uQkBCCgoLw8PCoVUOPHTvGoEGDaN++PV5eXkRERHDw4EFrfnZ2NmVlZfTv3x+AMWPGWPM1Gg1lZWWUlJSg1Wo5cuQIoaGhtGvXrlZtEM1f1SBSmzL2JmlVGcqtAcf6bKnKdEX2jiMTvgrhmMNbdsXFxXTs+PvtpYCAANzc3CgsLMTLy6vGirt168asWbPo1asXiqKwZMkSh0Fo6dKlNdaXm5uLTqezbvv7+5OWluYwX6fTkZOTA8DMmTMZP348ffv2ZdCgQcyYMcM6crAu/Py861TuakkbdF4+Nmke17W4lalxM6tQ3/j1wPLZzXxj+hutCpTKPJUKUFSoUYH69yXj1WYVGo2aDu3bgLeDYO8or7bpjVyXj+Vzo7VLAW0Nx7g5L/9i5Tnw9qj5GO29bhzjxnHae4HuxnnPUeDXSzfSeqHT+UCOV2Xab1nQs5f9trQAOp1PzTu1IK2pvw3VV4cByWw2o1bbXkBpNBoqKpyblToxMZGkpCRycnJQqVTk5ubaLF9RW2az2To/GVS+rFt1+1b5sbGxxMbGArBt2zaio6NJS0sjKSmJDh06kJCQgKenp9NtycsrwmxWat2HAkMx+uLrNmnlZUYqTGYqzArqG1VWKJWfKxQFjRrMRgVuHE9RAYqCmd/TAMyKgslkpqCwGE2R/YfyJgd5tU1vzLp8vD24fuOzK7WLKvvUVFdFYeVdBLcb+1QUlmDUV553bWEJbnnXqPDU075nL/T66zZpxrbd7LaludPpfNDrr9e8YwvRmvrrTF/VapVTv8g7vYR5bfXu3Zv33nsPgOHDh7Ny5cp6DfHu3LkzJ0+etG7r9Xr8/f1t8vV6vXX76tWrNvlQOWrw8OHDrF+/nvHjx7Ny5Up2797Nnj17WtVoPyGEcEW3DEibNm2yuXKoqKhg69at1Z69PPvss7c8yNGjR+vRxEqDBw9m5cqV5Ofn4+npSWpqKosXL7bmd+3aFQ8PD06dOsWDDz5ISkoKYWFhNnV8+OGHTJkyBbVajdFoRKPRoFKpKC93fpivEA3mQgbaX/U1PtOSGSJEa+EwIN15553s3bvXJq1jx47V1i5SqVQ1BqSGYJn7Li4uDqPRyNixYwkJCSE+Pp7nn3+e+++/n8TERF599VWKioro06cPcXFx1vJ5eXmcPXvWOsw8Pj6ecePG4evra3cGCiEanZ3ZIOxx9O6UvFArWhqHAakhrmoaWkxMTLVpitavX2/9HBwczI4dO+yW9fPzsxnIEBkZSWRkZOM0VLRqVddjsmxrAcWJWSIsazUp7fxkQUHR6jg127cQwnlVh4Nbti1Lq9dY9sZaTc7uL0RLIgFJiCZy84u0XL5Uq7JV319y9J6TEM1Zo42yE0LYqraSraF2ZateMcksEKIlkoAkRDOhzs3C/VoeSju/W14dyeg70VzJLTshmgmVodz6fOlWV0eq0mJ5/iSaJQlIQgghXILcshPCRdw8XBxqHrxQddFBVWmxdWi5Jd2Z23Zyi0+4CglIQrgIR0up3/L2XJXBDop3W1RFv1VLr/G4cntPuAi5ZSeEEMIlSEASQgjhEiQgCdGKyAKBwpXJMyQhWhF5XiRcmVwhCSGEcAkSkIQQQrgEuWUnhIuy917SrfYzebd1WMaZ50b23keyLIdh7txd3lMSjU4CkhAuyt57STXt56iMs0tf2EtTXy9EaefnVFuEqA+5ZSeEEMIlSEASQgjhEiQgCSGEcAkSkIQQQrgEGdQgRCtjWeiv6sg5y+i8Cl1Xp+qQGcJFY5CAJEQrozKUozKU24ycc3ZEn3V/mfFBNAK5ZSeEEMIlSEASQgjhEiQgCSGEcAnNKiDt3buXyMhIwsPD2bJlS7X8jIwMxowZQ0REBAsXLsRkMgGwceNG/vCHPzB16lQMBgMAZ86cITExsUnbL4QQwrFmE5BycnJYvnw5W7duZffu3Wzfvp0ffvjBZp+5c+fy+uuvc+jQIRRFITk5GagMSAcOHCAwMJDPP/8cgKSkJOLj45u8H0IIIexrNgHp2LFjDBo0iPbt2+Pl5UVERAQHDx605mdnZ1NWVkb//v0BGDNmjDVfo9FQVlZGSUkJWq2WI0eOEBoaSrt27W5LX4QQQlTXbIZ95+bmotPprNv+/v6kpaU5zNfpdOTk5AAwc+ZMxo8fT9++fRk0aBAzZsxg9erVdW6Ln593ncpdLWmDzsvHJs3juha3MjVuZhXqG78eWD67mStnbVZrVaBU5qlUgKJCjQrUv8/qrDar0GjUdGjfBrw97DfAUV5t0xu5Lh/LZxdrV2PU5fB8NUS72nuB7sa/txyv39MLPWzzc7yqp1lY8uylg21aDXS12LclaE39bai+NpuAZDabbabVVxTFZvtW+bGxscTGxgKwbds2oqOjSUtLIykpiQ4dOpCQkICnp6fTbcnLK8JsVmrdhwJDMfri6zZp5WVGKkxmKswK6htVViiVnysUBY0azEYFbhxPUQGKgpnf0wDMioLJZKagsBhNkf13SkwO8mqb3ph1+Xh7cP3GZ1dqV2PU5ePt4fB8NUS7KgpLMOor/71pC0us6W439rHkawtLqqVZWPLspQM2abei0/mgd3LflqA19deZvqrVKqd+kW82Aalz586cPHnSuq3X6/H397fJ1+v11u2rV6/a5AOUlJRw+PBh1q9fz/jx41m5ciW7d+9mz549jBs3rvE7IUQTsszIoLTzw02fXe2XOHVuFlrATZ9tt4zqWh5qQ5nD9Apd1xpnbNBcOl/5Eu1vOjRVgqL6yiWUdn4onm2sZZ2d/cHRfk09e0Rrmq3Cch6rnq/G0GyeIQ0ePJjjx4+Tn59PaWkpqamphIWFWfO7du2Kh4cHp06dAiAlJcUmH+DDDz9kypQpqNVqjEYjGo0GlUpFeXnt3lIXojlQGcor1zLybgvlZZWzMZSX2eRb8uyVUV8vtOY5TC8tvuWsDarS4spj3NjP8sdSV9WyNdVV037Olm8oTX2828lyHhu7v80mIHXq1InZs2cTFxfHqFGjiI6OJiQkhPj4eNLT0wFITExk6dKljBgxgpKSEuLi4qzl8/LyOHv2LEOGDAEgPj6ecePGceTIEWJiYm5Ln4QQQvyu2dyyA4iJiakWPNavX2/9HBwczI4dO+yW9fPzsxnIEBkZSWRkZOM0VAghRK01myskIYQQLZsEJCGEEC5BApIQQgiXIAFJCCGES5CAJIQQwiU0q1F2rkJdZcqe2vBwc69W1lfri1FlQKPWoFFpATApRjQqLSbFiLubFkNFGe43ZmUwqsxoFTUGdzXuitlaj6eixdfNG7W7O6o29t+IdpRX2/RGrcvTHZWidb12NUZdnu6u2S4n09Uev09T5Oj/hNrDA8XdHdzUqD0qrOmqNjf+rXp4WMta6qvp/5ej/Zwt31BqOl5TtaMpWM5j1fNlk1/TOXPyu1ApilL7OXCEEEKIBia37IQQQrgECUhCCCFcggQkIYQQLkECkhBCCJcgAUkIIYRLkIAkhBDCJUhAEkII4RIkIAkhhHAJEpCEEEK4BAlIQgghXIIEJBe2d+9eIiMjCQ8PZ8uWLbe7OQ1i8uTJREVFERsbS2xsLGfOnHHYz2PHjhETE0N4eDjLly+/ja2unaKiIqKjo8nKygIc9yMjI4MxY8YQERHBwoULMZlMAFy+fJmJEycyYsQInnvuOYqLi29LP5xxc1/nz59PeHi49fwePnwYqP134IpWrVpFVFQUUVFRLFu2DGi559ZeX5vk3CrCJV25ckV59NFHlYKCAqW4uFiJiYlRMjMzb3ez6sVsNiv/9m//phiNRmuao36WlpYqQ4cOVS5duqQYjUZl6tSpymeffXYbW++c06dPK9HR0UqfPn2UX3755Zb9iIqKUr777jtFURRl/vz5ypYtWxRFUZTp06cr+/btUxRFUVatWqUsW7bs9nSmBjf3VVEUJTo6WsnJybHZry7fgav58ssvlXHjxinl5eWKwWBQ4uLilL1797bIc2uvr6mpqU1ybuUKyUUdO3aMQYMG0b59e7y8vIiIiODgwYO3u1n18uOPPwIwdepURo4cyUcffeSwn2lpaQQGBhIQEIBGoyEmJqZZ9D85OZlFixbh7+8P4LAf2dnZlJWV0b9/fwDGjBnDwYMHMRqNfPPNN0RERNiku6Kb+1paWsrly5dZsGABMTExvP/++5jN5lp/B65Ip9Mxb9483N3d0Wq19OzZk59//rlFnlt7fb18+XKTnFv0KrgXAAALtUlEQVRZfsJF5ebmotPprNv+/v6kpaXdxhbV32+//cbDDz/Ma6+9htFoJC4ujscff9xuP+31Pycn53Y0u1beeustm21H/bg5XafTkZOTQ0FBAd7e3mg0Gpt0V3RzX69evcqgQYNYtGgRPj4+PPPMM+zYsQMvL69afQeu6N5777V+/vnnnzlw4ACTJk1qkefWXl+3bNnC119/3ejnVq6QXJTZbEal+n0NEUVRbLabowEDBrBs2TJ8fHzw9fVl7NixvP/++3b72VL676gfjtLt9bO59DsgIIC//OUv+Pv74+npyeTJk/nHP/5R6+/AlWVmZjJ16lReeeUVAgICWvS5rdrXHj16NMm5lYDkojp37oxer7du6/V6662R5urkyZMcP37cuq0oCl27drXbz5bSf0f9uDn96tWr+Pv74+vry/Xr16moqLDZvzk4d+4chw4dsm4rioJGo6n1d+CqTp06xZQpU3j55ZcZPXp0iz63N/e1qc6tBCQXNXjwYI4fP05+fj6lpaWkpqYSFhZ2u5tVL9evX2fZsmWUl5dTVFTErl27ePfdd+32s1+/fvz0009cvHiRiooK9u3b1yz776gfXbt2xcPDg1OnTgGQkpJCWFgYWq2W0NBQ9u/fD8Du3bubTb8VReHtt9/m2rVrGI1Gtm/fzh//+Mdafweu6Ndff2XmzJkkJiYSFRUFtNxza6+vTXVuZcVYF7Z3716SkpIwGo2MHTuW+Pj4292keluxYgWHDh3CbDYzYcIEnnrqKYf9PH78OEuXLqW8vJyhQ4cyf/58l77FUdXw4cPZtGkT3bp1c9iP77//nldffZWioiL69OnD0qVLcXd3Jzs7m3nz5pGXl0eXLl34n//5H9q1a3e7u+RQ1b5u2bKFLVu2YDKZCA8PZ86cOYDjc+noO3A1S5Ys4e9//zvdu3e3po0fP5677rqrxZ1bR301m82Nfm4lIAkhhHAJcstOCCGES5CAJIQQwiVIQBJCCOESJCAJIYRwCRKQhBBCuAQJSKJV0Ov19O7dm8jIyDrXERQUREpKSoO0Z/jw4axevdpu3ldffUVQUJD1T3BwMAMGDOCJJ57gk08+qdVxLHVduXKlIZptl8FgIDY21jpXYW3t3LmT3r17O73/xx9/zOLFi+t0LOHaZC470SqkpKQQEBDAhQsXOHnyJKGhobWu44svvqBt27aN0Dr7du3ahU6nw2w2U1BQwCeffMLLL79MYWEhEydObLJ21GTNmjU88MAD9OjRo07lIyMja/WC6BNPPEFMTEydz6NwXXKFJFqF3bt3ExkZSe/evdm+fXud6tDpdHh4eDRwyxzz9fVFp9PRqVMngoODefnll5k0aRKJiYnk5+c3WTtupbCwkA0bNvD000/XuY477riDjh07Or2/m5sbkydPblZrZAnnSEASLV5aWhqZmZkMHjyY8PBwDh06xLVr16z5QUFBvPfee4SFhREWFoZer3eYlpKSwokTJwgKCuKXX36xOU5UVJT1h+RXX33FpEmTGDBgAH379iU2NpZ//vOf9e7LU089RUlJCZ999pk1LTk5mYiICEJCQoiJiWHXrl0Oy2dlZfH8888zcOBA+vTpw/Dhw/nggw8AOHv2LEFBQdVmlZ8wYQJvv/223fq2b9/O3XffbfNWf1BQEPv27ePJJ5/k/vvvJzIyktOnT7N161aGDh3Kgw8+yEsvvYTBYACq37ILCgpix44dTJw4kZCQEEaMGFHtl4jw8HC+++67Zj8DvrAlAUm0eLt27aJjx448+OCDPP7445SXl7N7926bff72t7+RlJTEqlWrrNPm20sDGDhwIF27drXOSQaVq2P+8MMPjBo1il9//ZX4+HgefPBB9uzZw44dO+jSpQv/9V//Zf0hXFcBAQF4enpy/vx5ALZu3cry5cuZPXs2+/btY9q0abz11lsOg9Jzzz2HwWBg06ZN7N+/n9jYWN59910yMjLo3bs3wcHB7Nmzx7p/VlYW3377LaNHj7Zb39GjRxk6dGi19KVLlxIfH09KSgre3t5Mnz6do0ePsn79et5++21SU1PZsWOHw34mJiYyceJEdu3aRWhoKG+88QbZ2dnWfD8/P/r27cv//u//OvW9ieZBApJo0QwGA/v37yc8PBy1Ws1dd91Fnz59SE5Ottlv9OjR9OrVi5CQkFumQeWSASNHjmTfvn3WtD179tC/f3/uvvtujEYjL7zwAi+++CIBAQEEBwczZcoU8vPzycvLq3ef2rZtS1FREQBr165l1qxZjBgxgu7duxMbG8t//Md/sHbt2mrlysrKGD16NAkJCQQFBREYGMisWbNQq9WcO3fO2uf9+/dbl5ves2cP9913H7169apWn9ls5v/+7/9s1s+xGDt2LMOHD6dHjx7ExsZy7do1Fi1axH333UdERAS9evUiMzPTYR//9Kc/ERkZSc+ePXnllVesi8FVde+993LmzBnnvzjh8mRQg2jRPv30UwoLCxkxYoQ17fHHHycxMdHmoXhAQEC1svbSLEaPHs2aNWvIzMykZ8+e7N+/n2effRaA7t27M2rUKDZu3Mi5c+e4ePEiGRkZANalB+qjqKgIHx8f8vPzycnJ4Z133iExMdGabzKZqKioqHY1dscddzBp0iT2799PWlqatV1msxmz2QzAyJEjSUxM5Msvv2To0KHs2bOH8ePH221HYWEhJpOJDh06VMuregvP09MTtVpNt27dbNpyq6vFu+66y/rZMpDEaDTa7OPr60t6errDOkTzIwFJtGiWW1dVH7pb5hNOTk62BiR7gxVuNYAhMDCQAQMGsG/fPgYPHkx+fr51SHlmZiYTJkygX79+PPzww0RGRmIymawBqz4uXrxIcXExffr0QavVAvDaa6/x0EMPVdvXsjKpRUlJCRMmTKCiooKIiAgGDhxIv379ePTRR637+Pr6MmTIEPbt20eHDh345ZdfiImJuWWbLMHsVsdWqVS1mqnd3qzQN88DbTKZcHNzc7pO4fokIIkWS6/X88UXXzBhwgSefPJJm7x33nmHgwcPsnDhwjrXP3r0aDZs2MC1a9d49NFHrcsI7Ny5ky5dulgHCwBs27YNqP5Dtba2bt2Kt7c3w4YNw9vbm06dOpGVlcW///u/W/f5+OOPycjI4M0337Qp+/XXX5ORkcFXX31F+/btAfjxxx8xm8027RozZgwLFiygY8eODBkyBD8/P7tt6dChA1qt9raN+CssLLR5tieaP3mGJFqslJQUFEVh2rRp3HfffTZ/pk2bRnl5eb1edI2MjCQ7O5s9e/YwatQoa7qvry/Z2dl8+eWXZGdnk5KSYh19V5tBDfn5+ej1enJycvj+++9ZunQpmzZtYt68eXh7ewOVgxQ2bNjA9u3buXTpEnv37uXPf/6z3R/Uvr6+QOU6W9nZ2Rw/fpwXX3yxWruGDRuGm5sbW7duZcyYMQ7bp1Kp6Nu3L2fPnnW6Tw3pX//6V7Xne6J5kysk0WLt3r2bYcOG0bVr12p5Dz/8MMHBwdUGN9SGj48Pjz32GCdOnLB5sTMuLo4LFy4we/ZsKioq6NmzJwkJCcyfP5/09HR69uzpVP2WkW0qlQo/Pz+CgoJYu3atzai2J598EoPBwF//+lcWL15Mp06dmDFjBtOnT69WX0hICK+88grr16/n3Xff5c4772Ts2LH885//JD093XoVqdVqiYqKYt++fQwbNuyWbRw+fDgHDx50qj8NqaCggMzMTJYtW9bkxxaNRxboE0JU8/zzz+Pv78+rr756y/3y8/N57LHHSE5OtjvarrFs2LCBI0eO8NFHHzXZMUXjk1t2QgirL774gg8++ICjR49We+5mj6+vL3FxcWzatKkJWlfJZDLx8ccf85//+Z9NdkzRNCQgCSGskpOTWbNmDfPmzXP61uKMGTM4ffo0Fy5caOTWVdq+fTuDBg1i4MCBTXI80XTklp0QQgiXIFdIQgghXIIEJCGEEC5BApIQQgiXIAFJCCGES5CAJIQQwiX8P7vPUzDd7PNlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Re-examination of the raw arrival delays and the depature delays\n",
    "Delay_Status=data_airline[['ArrDelay','FlightState']];\n",
    "Delayed=Delay_Status[Delay_Status['FlightState']==1]['ArrDelay'];\n",
    "On_Time=Delay_Status[Delay_Status['FlightState']==0]['ArrDelay'];\n",
    "Hist_Bin_Delayed=np.arange(np.min(Delayed),np.max(Delayed),10);\n",
    "\n",
    "#Re-plot the histogram for the distribution of arrival-delay for on-time and delay respectively.\n",
    "plt.title('Distribution of the arrival delay \\nfor each flight condition\\n',fontsize=15, fontweight='bold')\n",
    "plt.hist(Delayed,bins=Hist_Bin_Delayed,density=True,log=True,color='tomato',edgecolor='tomato',alpha=0.2);\n",
    "plt.yscale('log')\n",
    "Hist_Bin_OnTime=np.arange(np.min(On_Time),np.max(On_Time),1);\n",
    "plt.hist(On_Time,bins=Hist_Bin_OnTime,density=True,log=True,color='limegreen',edgecolor='limegreen',alpha=0.2);\n",
    "plt.legend(['On-Time (BinWidth=1)','Delayed (BinWidth=10)']);\n",
    "plt.gca().yaxis.set_major_formatter(PercentFormatter(1))\n",
    "plt.xlabel('Arrival Delay (min)',fontsize=15)\n",
    "plt.ylabel('Proportion of flights \\nfor each flight state',fontsize=15)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Re-examination of the arrival delay distribution for on-time and delayed flights respectively indicates a clear seperation between the status.\n",
    "* The criterium seperating the on-time flight and the delayed flight is valid."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4) Factors leading to a flight delay or cancellation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1) Factors leading to a flight delay "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* The dataset provides five factors that may affect the flight:\n",
    "<br>\n",
    "CarrierDelay, WeatherDelay, NASDelay,SecurityDelay, LateAircraftDelay.\n",
    "<br>\n",
    "* The definition of these delay reasons can be found https://aspmhelp.faa.gov/index.php/Types_of_Delay\n",
    "* Here are a few examples: \n",
    "* **Carrier Delay:**\n",
    "<br>\n",
    "  Examples of occurrences that may determine carrier delay are: aircraft cleaning, aircraft damage, awaiting the arrival of connecting passengers or crew, et.al.\n",
    "* **Late Arrival Delay:**\n",
    "<br>\n",
    "  Arrival delay at an airport due to the late arrival of the same aircraft at a previous airport. The ripple effect of an earlier delay at downstream airports is referred to as delay propagation.\n",
    "* **NAS (National Airspace System) Delay:**\n",
    "<br>\n",
    " For example, non-extreme weather conditions, airport operations, heavy traffic volume, air traffic control, etc. \n",
    "* **Security Delay:** \n",
    "<br>\n",
    "Security delay is caused by evacuation of a terminal or concourse, re-boarding of aircraft because of security breach, inoperative screening equipment and/or long lines in excess of 29 minutes at screening areas.\n",
    "* **Weather Delay:** \n",
    "<br>\n",
    "Weather delay is caused by extreme or hazardous weather conditions that are forecasted or manifest themselves on point of departure, enroute, or on point of arrival.\n",
    "* In the following, how much those factors would lead to flight delayes will be explored. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select the delay reason columns for the delayed flights \n",
    "DelayLabels=['CarrierDelay',\n",
    "       'WeatherDelay', 'NASDelay', 'SecurityDelay', 'LateAircraftDelay']\n",
    "DelayedInformation=data_airline.loc[data_airline['FlightState']==1,DelayLabels]\n",
    "#Remove the null values\n",
    "DelayedInformation.dropna()\n",
    "# Count the non-zero value for each delay reasons\n",
    "DelayReasonCount=DelayedInformation.astype(bool).sum(axis=0)\n",
    "#Figure 1, a pie char plot about the proportion of delayed flights caused by each delay reason\n",
    "plt.subplot(1,2,1)\n",
    "explode=(0.2, 0.2, 0.2,0.2,0.2) #Separate each pie\n",
    "colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99','mediumorchid']\n",
    "\n",
    "plt.title('(a) Pie chart of proportion of delayed flight \\ncaused by each delay reason\\n\\n\\n',fontsize=15, fontweight='bold')\n",
    "plt.pie(DelayReasonCount, explode=explode, labels=DelayLabels, autopct='%1.2f%%',\n",
    "        shadow=True, colors=colors,startangle=90,textprops={'fontsize': 15},radius=1.5);\n",
    "#Figure 2, average time delayed due to each delay reasons\n",
    "DelayReasonTime_mean=DelayedInformation.mean()\n",
    "DelayReasonTime_sem=DelayedInformation.std()/np.sqrt(DelayReasonCount)\n",
    "plt.subplot(1,2,2)\n",
    "sns.set()\n",
    "plt.title('(b) Time of delay \\ncaused by each delay reason\\n\\n\\n',fontsize=15, fontweight='bold')\n",
    "colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99','mediumorchid']\n",
    "plt.xticks(rotation=45,fontsize=15)\n",
    "#plt.box(DelayLabels,DelayReasonTime_mean)\n",
    "plt.bar(DelayLabels,DelayReasonTime_mean,yerr=DelayReasonTime_sem,color=colors)\n",
    "plt.ylabel('Time of Delay (min)',fontsize=15)\n",
    "plt.subplots_adjust(left=-1.5) # make room for yticks "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* For the delayed flights, Late aircraft delay, carrier and the NAS are the three important factors that needs consideration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2) Factors leading to a flight cancellation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B    307\n",
      "A    246\n",
      "C     80\n",
      "Name: CancellationCode, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#Count the proportion of callellation due to each reason revealed by the cancellation code\n",
    "CancellationCode=data_airline['CancellationCode'].value_counts()\n",
    "print(CancellationCode[1:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* The cancel reasons are provided by the cancellation code.\n",
    "* **A = carrier, B = weather, C = NAS, D = security**\n",
    "* The current dataset only contains the former three"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Load the cancellation code counts \n",
    "CancellationCodeCounts=CancellationCode[1:]\n",
    "explode=(0.2, 0.2, 0.2)\n",
    "colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99','mediumorchid']\n",
    "\n",
    "#Pie plot of the proportion\n",
    "plt.title('Pie chart of proportion of cancelled flights \\ncaused by each cancellation reason\\n\\n\\n',fontsize=15, fontweight='bold')\n",
    "plt.pie(CancellationCodeCounts, explode=explode, labels=['CarrierCancel','WeatherCancel','NASCancel'], autopct='%1.2f%%',\n",
    "        shadow=True, colors=colors,startangle=90,textprops={'fontsize': 15},radius=1.5);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Compared to the delay flights, carrier and the weather issue is the major factor that led to the cancellation. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IV. The features related to the flight status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) Pre-screen the features "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'Year', 'Month', 'DayofMonth', 'DayOfWeek', 'DepTime',\n",
       "       'CRSDepTime', 'ArrTime', 'CRSArrTime', 'UniqueCarrier', 'FlightNum',\n",
       "       'TailNum', 'ActualElapsedTime', 'CRSElapsedTime', 'AirTime', 'ArrDelay',\n",
       "       'DepDelay', 'Origin', 'Dest', 'Distance', 'TaxiIn', 'TaxiOut',\n",
       "       'Cancelled', 'CancellationCode', 'Diverted', 'CarrierDelay',\n",
       "       'WeatherDelay', 'NASDelay', 'SecurityDelay', 'LateAircraftDelay',\n",
       "       'RelativeArrDel', 'FlightState'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_airline.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* There are 30 columns in the original datasets, which means there are 30 features at most, but some of them are useless for the classifier and can be removed.\n",
    "* I. The label column _Unnamed: 0_ and the _Year_ appaarently need to be removed.\n",
    "* II. the _ArrDelay_ and _RelativeArrDel_ which were used for state classification can also be removed.\n",
    "* III. Other irrelavent factors like _FlightNum_ , _TailNum_, _Diverted_(no insteret for a moment) also need removal.\n",
    "* IV. As we have defined a new column _FlightState_ , columns like _Cancelled_, _CancellationCode_, _CarrierDelay_, _WeatherDelay_, _NASDelay_, _SecurityDelay_, _LateAircraftDelay_,  _RelativeArrDel_ can also be removed.\n",
    "* V. As we wish to predict the flight status in advance of the flight set off, the actual _Deptime_, _DepDelay_,_ArrTime_, _ActualElapsedTime_, _AirTime_,_TaxiIn_, _TaxiOut_ are not useful, and can be removed.\n",
    "* VI. The _month_ and the _DayofMonth_ can be integrated\n",
    "* VII. **Last, drop the flight state from the feature, as it is the _y_**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>DayOfWeek</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>1955</td>\n",
       "      <td>2225</td>\n",
       "      <td>WN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>IAD</td>\n",
       "      <td>TPA</td>\n",
       "      <td>810</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>735</td>\n",
       "      <td>1000</td>\n",
       "      <td>WN</td>\n",
       "      <td>145.0</td>\n",
       "      <td>IAD</td>\n",
       "      <td>TPA</td>\n",
       "      <td>810</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>620</td>\n",
       "      <td>750</td>\n",
       "      <td>WN</td>\n",
       "      <td>90.0</td>\n",
       "      <td>IND</td>\n",
       "      <td>BWI</td>\n",
       "      <td>515</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1755</td>\n",
       "      <td>1925</td>\n",
       "      <td>WN</td>\n",
       "      <td>90.0</td>\n",
       "      <td>IND</td>\n",
       "      <td>BWI</td>\n",
       "      <td>515</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1915</td>\n",
       "      <td>2110</td>\n",
       "      <td>WN</td>\n",
       "      <td>115.0</td>\n",
       "      <td>IND</td>\n",
       "      <td>JAX</td>\n",
       "      <td>688</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   DayOfWeek  CRSDepTime  CRSArrTime UniqueCarrier  CRSElapsedTime Origin  \\\n",
       "0          4        1955        2225            WN           150.0    IAD   \n",
       "1          4         735        1000            WN           145.0    IAD   \n",
       "2          4         620         750            WN            90.0    IND   \n",
       "3          4        1755        1925            WN            90.0    IND   \n",
       "4          4        1915        2110            WN           115.0    IND   \n",
       "\n",
       "  Dest  Distance  Date  \n",
       "0  TPA       810   103  \n",
       "1  TPA       810   103  \n",
       "2  BWI       515   103  \n",
       "3  BWI       515   103  \n",
       "4  JAX       688   103  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flight_features=data_airline #First load all the features\n",
    "#Use a list to define the useless features \n",
    "drop_features=['Unnamed: 0','Year','ArrDelay','RelativeArrDel','FlightNum' , 'TailNum', 'DepDelay','Diverted','Cancelled', 'CancellationCode', 'CarrierDelay', 'WeatherDelay', 'NASDelay', 'SecurityDelay', 'LateAircraftDelay', 'RelativeArrDel', 'ArrTime','DepTime', 'ActualElapsedTime', 'AirTime','TaxiIn', 'TaxiOut'  ]  #Use a list to store the feature name not needed\n",
    "flight_features= flight_features.drop(drop_features, axis=1) # Delete all columns with the label \n",
    "flight_features['Date']=flight_features['Month']*100+flight_features['DayofMonth'] #Use a four digits number to represent date\n",
    "flight_features= flight_features.drop(['Month','DayofMonth'], axis=1) # the dayofmonth and month\n",
    "flight_features=flight_features.dropna() #Now remove all the rows which contains null value\n",
    "y=flight_features['FlightState'] #Define the y\n",
    "flight_features= flight_features.drop(['FlightState'], axis=1) # drop y from the original datasets\n",
    "flight_features.head() #Show the remained features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, there are  9  features left for the following modeling\n"
     ]
    }
   ],
   "source": [
    "# Display the final feature library we have chosen\n",
    "Rows,NumberOfFeatures=flight_features.shape\n",
    "print('Now, there are ',NumberOfFeatures,' features left for the following modeling')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) Handle the categorial features \n",
    "* For this section, I'll first check the basic properties of those non-numeric categorical features such as the _UniqueCarrier_, _Origin_, _Dest_, .\n",
    "* And examin whether and how those features differ under different flight states. \n",
    "* Then I'll transform those features into unique values. \n",
    "\n",
    "### 2.1) How cancellation, delay, ontime rate differed in different carriers, flight origins, and the destinations "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Compare between UniqueCarriers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>OnTime</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Cancel</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9E</th>\n",
       "      <td>32.085510</td>\n",
       "      <td>67.802283</td>\n",
       "      <td>0.112207</td>\n",
       "      <td>9E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA</th>\n",
       "      <td>44.144581</td>\n",
       "      <td>55.831444</td>\n",
       "      <td>0.023975</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AQ</th>\n",
       "      <td>39.600000</td>\n",
       "      <td>60.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>AQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <td>48.769501</td>\n",
       "      <td>51.202504</td>\n",
       "      <td>0.027995</td>\n",
       "      <td>AS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B6</th>\n",
       "      <td>43.090357</td>\n",
       "      <td>56.891565</td>\n",
       "      <td>0.018079</td>\n",
       "      <td>B6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>56.577674</td>\n",
       "      <td>43.384400</td>\n",
       "      <td>0.037926</td>\n",
       "      <td>CO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DL</th>\n",
       "      <td>48.279031</td>\n",
       "      <td>51.702586</td>\n",
       "      <td>0.018383</td>\n",
       "      <td>DL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EV</th>\n",
       "      <td>30.383380</td>\n",
       "      <td>69.581201</td>\n",
       "      <td>0.035419</td>\n",
       "      <td>EV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F9</th>\n",
       "      <td>57.094344</td>\n",
       "      <td>42.898581</td>\n",
       "      <td>0.007075</td>\n",
       "      <td>F9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>40.365299</td>\n",
       "      <td>59.624881</td>\n",
       "      <td>0.009820</td>\n",
       "      <td>FL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HA</th>\n",
       "      <td>30.587450</td>\n",
       "      <td>69.372497</td>\n",
       "      <td>0.040053</td>\n",
       "      <td>HA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MQ</th>\n",
       "      <td>29.578140</td>\n",
       "      <td>70.348579</td>\n",
       "      <td>0.073281</td>\n",
       "      <td>MQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NW</th>\n",
       "      <td>39.864489</td>\n",
       "      <td>60.115285</td>\n",
       "      <td>0.020226</td>\n",
       "      <td>NW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>28.520425</td>\n",
       "      <td>71.456786</td>\n",
       "      <td>0.022789</td>\n",
       "      <td>OH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OO</th>\n",
       "      <td>30.633080</td>\n",
       "      <td>69.299716</td>\n",
       "      <td>0.067204</td>\n",
       "      <td>OO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>44.432424</td>\n",
       "      <td>55.534343</td>\n",
       "      <td>0.033233</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>49.654051</td>\n",
       "      <td>50.319533</td>\n",
       "      <td>0.026416</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WN</th>\n",
       "      <td>47.213203</td>\n",
       "      <td>52.782824</td>\n",
       "      <td>0.003972</td>\n",
       "      <td>WN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XE</th>\n",
       "      <td>34.261019</td>\n",
       "      <td>65.694607</td>\n",
       "      <td>0.044375</td>\n",
       "      <td>XE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YV</th>\n",
       "      <td>22.035996</td>\n",
       "      <td>77.884974</td>\n",
       "      <td>0.079030</td>\n",
       "      <td>YV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       OnTime      Delay    Cancel UniqueCarrier\n",
       "9E  32.085510  67.802283  0.112207            9E\n",
       "AA  44.144581  55.831444  0.023975            AA\n",
       "AQ  39.600000  60.400000  0.000000            AQ\n",
       "AS  48.769501  51.202504  0.027995            AS\n",
       "B6  43.090357  56.891565  0.018079            B6\n",
       "CO  56.577674  43.384400  0.037926            CO\n",
       "DL  48.279031  51.702586  0.018383            DL\n",
       "EV  30.383380  69.581201  0.035419            EV\n",
       "F9  57.094344  42.898581  0.007075            F9\n",
       "FL  40.365299  59.624881  0.009820            FL\n",
       "HA  30.587450  69.372497  0.040053            HA\n",
       "MQ  29.578140  70.348579  0.073281            MQ\n",
       "NW  39.864489  60.115285  0.020226            NW\n",
       "OH  28.520425  71.456786  0.022789            OH\n",
       "OO  30.633080  69.299716  0.067204            OO\n",
       "UA  44.432424  55.534343  0.033233            UA\n",
       "US  49.654051  50.319533  0.026416            US\n",
       "WN  47.213203  52.782824  0.003972            WN\n",
       "XE  34.261019  65.694607  0.044375            XE\n",
       "YV  22.035996  77.884974  0.079030            YV"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Grouping the data according to unique carrier\n",
    "CarrierGroup_Total=pd.DataFrame(data_airline.groupby(data_airline['UniqueCarrier']).UniqueCarrier.count())\n",
    "CarrierGroup_OnTime=pd.DataFrame(data_airline[data_airline.FlightState==0].groupby(data_airline['UniqueCarrier']).UniqueCarrier.count())\n",
    "CarrierGroup_Delay=pd.DataFrame(data_airline[data_airline.FlightState==1].groupby(data_airline['UniqueCarrier']).UniqueCarrier.count())\n",
    "CarrierGroup_Cancel=pd.DataFrame(data_airline[data_airline.FlightState==2].groupby(data_airline['UniqueCarrier']).UniqueCarrier.count())\n",
    "\n",
    "CarrierGroup=pd.concat([CarrierGroup_Total, CarrierGroup_OnTime,CarrierGroup_Delay,CarrierGroup_Cancel],axis = 1,sort=False)\n",
    "CarrierGroup.columns = ['Total','OnTime','Delay','Cancel']\n",
    "UniqueCarrier=CarrierGroup_Total.index\n",
    "CarrierGroup['UniqueCarrier']=UniqueCarrier\n",
    "CarrierGroup['OnTime']=CarrierGroup['OnTime']/CarrierGroup['Total']*100\n",
    "CarrierGroup['Delay']=CarrierGroup['Delay']/CarrierGroup['Total']*100\n",
    "CarrierGroup['Cancel']=CarrierGroup['Cancel']/CarrierGroup['Total']*100\n",
    "CarrierGroup['Cancel'].fillna(0,inplace=True)\n",
    "CarrierGroup.drop(['Total'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Grouping the data according to Origin\n",
    "Origin_Total=pd.DataFrame(data_airline.groupby(data_airline['Origin']).Origin.count())\n",
    "Origin_OnTime=pd.DataFrame(data_airline[data_airline.FlightState==0].groupby(data_airline['Origin']).UniqueCarrier.count())\n",
    "Origin_Delay=pd.DataFrame(data_airline[data_airline.FlightState==1].groupby(data_airline['Origin']).UniqueCarrier.count())\n",
    "Origin_Cancel=pd.DataFrame(data_airline[data_airline.FlightState==2].groupby(data_airline['Origin']).UniqueCarrier.count())\n",
    "\n",
    "OriginGroup=pd.concat([Origin_Total, Origin_OnTime,Origin_Delay,Origin_Cancel],axis = 1,sort=False)\n",
    "OriginGroup.columns = ['Total','OnTime','Delay','Cancel']\n",
    "UniqueOrigin=Origin_Total.index\n",
    "OriginGroup['Origin']=UniqueOrigin\n",
    "OriginGroup['OnTime']=OriginGroup['OnTime']/OriginGroup['Total']*100\n",
    "OriginGroup['Delay']=OriginGroup['Delay']/OriginGroup['Total']*100\n",
    "OriginGroup['Cancel']=OriginGroup['Cancel']/OriginGroup['Total']*100\n",
    "OriginGroup['Cancel'].fillna(0,inplace=True)\n",
    "OriginGroup.drop(['Total'],axis=1);\n",
    "\n",
    "#Grouping the data according to Destination\n",
    "Dest_Total=pd.DataFrame(data_airline.groupby(data_airline['Dest']).Origin.count())\n",
    "Dest_OnTime=pd.DataFrame(data_airline[data_airline.FlightState==0].groupby(data_airline['Dest']).UniqueCarrier.count())\n",
    "Dest_Delay=pd.DataFrame(data_airline[data_airline.FlightState==1].groupby(data_airline['Dest']).UniqueCarrier.count())\n",
    "Dest_Cancel=pd.DataFrame(data_airline[data_airline.FlightState==2].groupby(data_airline['Dest']).UniqueCarrier.count())\n",
    "\n",
    "DestGroup=pd.concat([Dest_Total, Dest_OnTime,Dest_Delay,Dest_Cancel],axis = 1,sort=False)\n",
    "DestGroup.columns = ['Total','OnTime','Delay','Cancel']\n",
    "UniqueDest=Dest_Total.index\n",
    "DestGroup['Dest']=UniqueDest\n",
    "DestGroup['OnTime']=DestGroup['OnTime']/DestGroup['Total']*100\n",
    "DestGroup['Delay']=DestGroup['Delay']/DestGroup['Total']*100\n",
    "DestGroup['Cancel']=DestGroup['Cancel']/DestGroup['Total']*100\n",
    "DestGroup['Cancel'].fillna(0,inplace=True)\n",
    "DestGroup.drop(['Total'],axis=1);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x1080 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Initialize the matplotlib figure\n",
    "#plt.subplot(1,3,1)\n",
    "plt.subplots(figsize=(6, 15))\n",
    "plt.subplot(1,3,1)\n",
    "# Load the example car crash dataset\n",
    "CarrierGroup_plots= CarrierGroup.sort_values(\"OnTime\", ascending=False)\n",
    "#CarrierGroup_plots['Total']=CarrierGroup_plots['Delay']+CarrierGroup_plots['OnTime']+CarrierGroup_plots['Cancel']\n",
    "CarrierGroup_plots['Total']=1\n",
    "CarrierGroup_plots['Delay']=CarrierGroup_plots['Delay']+CarrierGroup_plots['OnTime']\n",
    "\n",
    "# Plot the total crashes\n",
    "sns.set_color_codes(\"pastel\")\n",
    "\n",
    "sns.barplot(x=\"Cancel\", y=\"UniqueCarrier\", data=CarrierGroup_plots,\n",
    "             label=\"Cancel\",color=\"k\");\n",
    "sns.barplot(x=\"Delay\", y=\"UniqueCarrier\", data=CarrierGroup_plots,\n",
    "            label=\"Delay\", color=\"r\");\n",
    "#sns.set_color_codes(\"muted\")\n",
    "sns.barplot(x=\"OnTime\", y=\"UniqueCarrier\", data=CarrierGroup_plots,\n",
    "            label=\"OnTime\", color=\"g\");\n",
    "plt.ylabel('Unique Carrier',fontsize=15)\n",
    "plt.xlabel('On-Time v.s. Delay v.s. Cancelled',fontsize=15)\n",
    "\n",
    "\n",
    "plt.subplot(1,3,2)\n",
    "\n",
    "#OriginGroup_plots= OriginGroup\n",
    "OriginGroup_plots= OriginGroup.sort_values(\"OnTime\", ascending=False)\n",
    "#CarrierGroup_plots['Total']=CarrierGroup_plots['Delay']+CarrierGroup_plots['OnTime']+CarrierGroup_plots['Cancel']\n",
    "OriginGroup_plots['Total']=1\n",
    "OriginGroup_plots['Delay']=OriginGroup_plots['Delay']+OriginGroup_plots['OnTime']\n",
    "\n",
    "# Plot the total crashes\n",
    "sns.set_color_codes(\"pastel\")\n",
    "\n",
    "sns.barplot(x=\"Cancel\", y=\"Origin\", data=OriginGroup_plots,\n",
    "             label=\"Cancel\",color=\"k\");\n",
    "sns.barplot(x=\"Delay\", y=\"Origin\", data=OriginGroup_plots,\n",
    "            label=\"Delay\", color=\"r\");\n",
    "#sns.set_color_codes(\"muted\")\n",
    "sns.barplot(x=\"OnTime\", y=\"Origin\", data=OriginGroup_plots,\n",
    "            label=\"OnTime\", color=\"g\");\n",
    "plt.ylabel('Origin',fontsize=15)\n",
    "plt.xlabel('On-Time v.s. Delay v.s. Cancelled',fontsize=15)\n",
    "plt.subplots_adjust(left=-1.5) # make room for yticks \n",
    "\n",
    "\n",
    "# Plot the total crashes\n",
    "plt.subplot(1,3,3)\n",
    "\n",
    "#DestGroup_plots= DestGroup\n",
    "DestGroup_plots= DestGroup.sort_values(\"OnTime\", ascending=False)\n",
    "#CarrierGroup_plots['Total']=CarrierGroup_plots['Delay']+CarrierGroup_plots['OnTime']+CarrierGroup_plots['Cancel']\n",
    "DestGroup_plots['Total']=1\n",
    "DestGroup_plots['Delay']=DestGroup_plots['Delay']+DestGroup_plots['OnTime']\n",
    "\n",
    "\n",
    "sns.set_color_codes(\"pastel\")\n",
    "\n",
    "sns.barplot(x=\"Cancel\", y=\"Dest\", data=DestGroup_plots,\n",
    "             label=\"Cancel\",color=\"k\");\n",
    "sns.barplot(x=\"Delay\", y=\"Dest\", data=DestGroup_plots,\n",
    "            label=\"Delay\", color=\"r\");\n",
    "#sns.set_color_codes(\"muted\")\n",
    "sns.barplot(x=\"OnTime\", y=\"Dest\", data=DestGroup_plots,\n",
    "            label=\"OnTime\", color=\"g\");\n",
    "plt.ylabel('Dest',fontsize=15)\n",
    "plt.xlabel('On-Time v.s. Delay v.s. Cancelled',fontsize=15)\n",
    "plt.subplots_adjust(left=-1.5) # make room for yticks "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2) Deplace the category data with numbers "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Replace the cateogory data with numbers using _.cat.codes_ methods of pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DayOfWeek', 'CRSDepTime', 'CRSArrTime', 'UniqueCarrier',\n",
       "       'CRSElapsedTime', 'Origin', 'Dest', 'Distance', 'Date'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flight_features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change the symbols into numbers\n",
    "flight_features['UniqueCarrier']=flight_features['UniqueCarrier'].astype('category')\n",
    "flight_features['UniqueCarrier']=flight_features['UniqueCarrier'].cat.codes\n",
    "\n",
    "flight_features['Origin']=flight_features['Origin'].astype('category')\n",
    "flight_features['Origin']=flight_features['Origin'].cat.codes\n",
    "\n",
    "flight_features['Dest']=flight_features['Dest'].astype('category')\n",
    "flight_features['Dest']=flight_features['Dest'].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>DayOfWeek</th>\n",
       "      <th>CRSDepTime</th>\n",
       "      <th>CRSArrTime</th>\n",
       "      <th>UniqueCarrier</th>\n",
       "      <th>CRSElapsedTime</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Dest</th>\n",
       "      <th>Distance</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>1955</td>\n",
       "      <td>2225</td>\n",
       "      <td>17</td>\n",
       "      <td>150.0</td>\n",
       "      <td>135</td>\n",
       "      <td>286</td>\n",
       "      <td>810</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>735</td>\n",
       "      <td>1000</td>\n",
       "      <td>17</td>\n",
       "      <td>145.0</td>\n",
       "      <td>135</td>\n",
       "      <td>286</td>\n",
       "      <td>810</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>620</td>\n",
       "      <td>750</td>\n",
       "      <td>17</td>\n",
       "      <td>90.0</td>\n",
       "      <td>140</td>\n",
       "      <td>48</td>\n",
       "      <td>515</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1755</td>\n",
       "      <td>1925</td>\n",
       "      <td>17</td>\n",
       "      <td>90.0</td>\n",
       "      <td>140</td>\n",
       "      <td>48</td>\n",
       "      <td>515</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1915</td>\n",
       "      <td>2110</td>\n",
       "      <td>17</td>\n",
       "      <td>115.0</td>\n",
       "      <td>140</td>\n",
       "      <td>150</td>\n",
       "      <td>688</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   DayOfWeek  CRSDepTime  CRSArrTime  UniqueCarrier  CRSElapsedTime  Origin  \\\n",
       "0          4        1955        2225             17           150.0     135   \n",
       "1          4         735        1000             17           145.0     135   \n",
       "2          4         620         750             17            90.0     140   \n",
       "3          4        1755        1925             17            90.0     140   \n",
       "4          4        1915        2110             17           115.0     140   \n",
       "\n",
       "   Dest  Distance  Date  \n",
       "0   286       810   103  \n",
       "1   286       810   103  \n",
       "2    48       515   103  \n",
       "3    48       515   103  \n",
       "4   150       688   103  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flight_features.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Now the non-numerical features have been transformed to numbers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3)  Examine the co-linearities of the features "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrmat = flight_features.corr() #Correlation matrix for all the chosen features\n",
    "f, ax = plt.subplots(figsize=(12, 9)) \n",
    "sns.heatmap(corrmat, vmax=1, square=True,linewidths=.5);\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## V. Predict flight status using superveised learning algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## _Here, I want to focus on one technical quesition:_\n",
    "##  <ins>How does selection of features affect the selection of models?<ins>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* ### I propose four scenarios for feature selection:\n",
    "> ### 1. Selection single feature and fit the models by each features\n",
    "> ### 2. Use all features for model fitting\n",
    "> ### 3. Use PCA(Principle Component Analysis) to reduce feature dimensions\n",
    "> ### 4. Use a supervised algorithm---LDA(Linear Discriminant Analysis) to reduce feature dimensions\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) Instantiation of the models\n",
    "* ### I choose four commonly used classifiers.\n",
    "**1. K-nearest neighbor classifier**\n",
    "**2. Ridge classifer**\n",
    "**3. Decision Tree**\n",
    "**4. Linear Support Vector Machine**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import modules\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.svm import LinearSVC\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.linear_model import RidgeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn=KNeighborsClassifier(n_neighbors = 5)#KNN\n",
    "svc=LinearSVC(multi_class='crammer_singer') #\"crammer_singer\" optimizes a joint objective over all classes\n",
    "dtc=DecisionTreeClassifier(max_depth=5)\n",
    "rdg=RidgeClassifier(alpha=0.1, tol=0.001) #Ridge regression with internal cross-validation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3) Preprocessing of the features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **1.Standardize the features.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.preprocessing import scale\n",
    "\n",
    "X = StandardScaler().fit_transform(flight_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **2. Instatiate the feature selection scenarios**\n",
    "* 1. Selection single feature and fit the models by each features\n",
    "* 2. Use all features for model fitting\n",
    "* 3. Use PCA(Principle Component Analysis) to reduce feature dimensions into 2\n",
    "* 4. Use LDA(Linear Discriminant Analysis) to reduce feature dimensions into 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#1.Selection single feature and fit the models by each features\n",
    "# Just to use each column in X_train and X_test \n",
    "#2.Use all features for model fitting\n",
    "# Just to use the whole X_train and X_test \n",
    "#3.Use PCA(Principle Component Analysis) to reduce feature dimensions\n",
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(n_components=2) #Instantiate PCA\n",
    "X_PCA = pca.fit(X).transform(X) #Transform the features\n",
    "\n",
    "#4.Use LDA(Linear Discriminant Analysis)  to reduce feature dimensions\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis  \n",
    "lda = LinearDiscriminantAnalysis(n_components=2)#Instantiate LDA\n",
    "X_LDA = lda.fit(X, y).transform(X)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **3. Split dataset into training set and test set.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* As the original dataset is too large to test all the models, I only use 2% (38732 rows as a sample) of the original dataset to save time.\n",
    "* For the next step, I'll separate the sample dataset into train-test group for model fitting \n",
    "* Here, the test set size is set as 0.2.\n",
    "* For the purpose of illustration, I fixed the random state to 42 here. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "SampleSize=0.02\n",
    "X_Remain, X_Sample, y_Remain, y_Sample = train_test_split(X, y, test_size=SampleSize, random_state=42)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_Sample, y_Sample, test_size=0.2, random_state=42) #For scenario 1 and 2\n",
    "#For PCA\n",
    "X_Remain_PCA, X_Sample_PCA, y_Remain_PCA, y_Sample_PCA = train_test_split(X_PCA, y, test_size=SampleSize, random_state=42)\n",
    "X_train_PCA, X_test_PCA, y_train_PCA, y_test_PCA = train_test_split(X_Sample_PCA, y_Sample_PCA, test_size=0.2, random_state=42) #For scenario 3\n",
    "#For LDA\n",
    "X_Remain_LDA, X_Sample_LDA, y_Remain_LDA, y_Sample_LDA = train_test_split(X_LDA, y, test_size=SampleSize, random_state=42)\n",
    "X_train_LDA, X_test_LDA, y_train_LDA, y_test_LDA = train_test_split(X_Sample_LDA, y_Sample_LDA, test_size=0.2, random_state=42) #For scenario 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4) Fit the models with each of the freature selection scenarios and score their performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_knn=[]\n",
    "result_svc=[]\n",
    "result_rdg=[]\n",
    "result_dtc=[]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Scenario 1: Use single features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yuxue\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:929: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n",
      "C:\\Users\\yuxue\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:929: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n",
      "C:\\Users\\yuxue\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:929: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Scenario 1: Fit each model using each feature\n",
    "for i in range(NumberOfFeatures): \n",
    "    knn_model = knn.fit(X_train[:,i].reshape(-1, 1) , y_train)\n",
    "    SVC_model=svc.fit(X_train[:,i].reshape(-1, 1) , y_train)\n",
    "    Rdg_model=rdg.fit(X_train[:,i].reshape(-1, 1) , y_train)\n",
    "    dtc_model=dtc.fit(X_train[:,i].reshape(-1, 1) , y_train)\n",
    "    \n",
    "    knn_score=knn_model.score(X_test[:,i].reshape(-1, 1) , y_test)\n",
    "    svc_score=SVC_model.score(X_test[:,i].reshape(-1, 1) , y_test)\n",
    "    rdg_score=Rdg_model.score(X_test[:,i].reshape(-1, 1) , y_test)\n",
    "    dtc_score=dtc_model.score(X_test[:,i].reshape(-1, 1) , y_test)\n",
    "    \n",
    "    result_knn.append(knn_score)\n",
    "    result_svc.append(svc_score)\n",
    "    result_rdg.append(rdg_score)\n",
    "    result_dtc.append(dtc_score)\n",
    "    \n",
    "     \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Scenario 2: Use all features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yuxue\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:929: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "knn_model = knn.fit(X_train, y_train)\n",
    "SVC_model=svc.fit(X_train, y_train)\n",
    "Rdg_model=rdg.fit(X_train, y_train)\n",
    "dtc_model=dtc.fit(X_train, y_train)\n",
    "    \n",
    "knn_score=knn_model.score(X_test, y_test)\n",
    "svc_score=SVC_model.score(X_test, y_test)\n",
    "rdg_score=Rdg_model.score(X_test, y_test)\n",
    "dtc_score=dtc_model.score(X_test, y_test)\n",
    "result_knn.append(knn_score)\n",
    "result_svc.append(svc_score)\n",
    "result_rdg.append(rdg_score)\n",
    "result_dtc.append(dtc_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Scenario 3: Use the first two components of PCA**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yuxue\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:929: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "knn_model = knn.fit(X_train_PCA, y_train_PCA)\n",
    "SVC_model=svc.fit(X_train_PCA, y_train_PCA)\n",
    "Rdg_model=rdg.fit(X_train_PCA, y_train_PCA)\n",
    "dtc_model=dtc.fit(X_train_PCA, y_train_PCA)\n",
    "    \n",
    "knn_score=knn_model.score(X_test_PCA, y_test_PCA)\n",
    "svc_score=SVC_model.score(X_test_PCA, y_test_PCA)\n",
    "rdg_score=Rdg_model.score(X_test_PCA, y_test_PCA)\n",
    "dtc_score=dtc_model.score(X_test_PCA, y_test_PCA)\n",
    "result_knn.append(knn_score)\n",
    "result_svc.append(svc_score)\n",
    "result_rdg.append(rdg_score)\n",
    "result_dtc.append(dtc_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **Scenario 4: Use the first two components of LDA**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yuxue\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:929: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "knn_model = knn.fit(X_train_LDA, y_train_LDA)\n",
    "SVC_model=svc.fit(X_train_LDA, y_train_LDA)\n",
    "Rdg_model=rdg.fit(X_train_LDA, y_train_LDA)\n",
    "dtc_model=dtc.fit(X_train_LDA, y_train_LDA)\n",
    "    \n",
    "knn_score=knn_model.score(X_test_LDA, y_test_LDA)\n",
    "svc_score=SVC_model.score(X_test_LDA, y_test_LDA)\n",
    "rdg_score=Rdg_model.score(X_test_LDA, y_test_LDA)\n",
    "dtc_score=dtc_model.score(X_test_LDA, y_test_LDA)\n",
    "result_knn.append(knn_score)\n",
    "result_svc.append(svc_score)\n",
    "result_rdg.append(rdg_score)\n",
    "result_dtc.append(dtc_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5) Compare the model performance between feature selection scenarios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Store all the feature selection scenarios\n",
    "columns=flight_features.columns\n",
    "columns_final=columns.append(pd.Index(['All Features','PCA Features','LDA Features']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "#{'knn','svc','rdg','dtc'}\n",
    "dataForPlot=pd.DataFrame([result_knn,result_svc,result_rdg,result_dtc],columns=columns_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(12, 9))\n",
    "xticklabels =['KNN','SVC','RDG','DTC']\n",
    "ax=sns.heatmap(dataForPlot.T,vmin=0, vmax=1,annot=True,xticklabels=xticklabels)\n",
    "plt.xlabel('Models',FontSize=20);\n",
    "plt.ylabel('Feature selections',FontSize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6) Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Comparing across the features, it seems the selecting more features for this case does not imporve the model performance significantly.\n",
    "### 2. Using PCA(principle component analysis) or LDA(linear determinant analysis) to reduce dimentionality is not very effective in overall model performance, maybe due to a low co-linearity among features.\n",
    "### 3. Comparing across the models, performance of LinearSVC(Linear support vector machine), RDG(RidgeClassifier), DTC(Decision Tree Classifier) didn't differ much, whereas KNN(K-Nearest Neighbor) behaved the poorest."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## VI. Discussion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <ins> 1.) Is ArrDelay/CTRSElapsedTime a good delay indicator?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " * ### Alternative status definations: \n",
    " >### 1. Using raw arrival delay: eg. ArrDelay>15min as a delayed condition \n",
    " >### 2. All the datas containing the delayed reasons could be defined as delayed conditions \n",
    " >### 3. Use a unsupervised algorithm to separate on-time with delay with features of flight information such as Depature Delay, Taxi-in,Taxi-out, AirTime,et.al\n",
    " >### 4. Directly use the ArrDelay as the regression target and change it into a regression problem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <ins> 2.) Are non-numeric category features handled right?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* ### Currently, we use artificial numbers to replace symbols, e.g. IAD=1,PSD=7, but this assignments are artifical and may introduce bias to larger numbers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* ### Alternative category handle methods: \n",
    ">#### Change into binary numbers: e.g. IAD_Yes: 1/0\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <ins>3.) The hyperparameters in those models are not tuned to optimise the model performance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* ### Grid search, et.al"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <ins>4.) Is score a good measurement for model performance?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* ### Not likely, the distribution of on-time, delayed and cancellation is highly screwed towards the on-time and delayed states. If the model never report the cancellation, is still can acheive high score on on-time or delay.  \n",
    "* ### For a better estimation of the model performance, other evaluation methods such as ROC, precision, et.al need to be included."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <ins>5.) Include more useful features, such as the weather, temperature, height, et.al."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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