Computing For Analytics - Airlines Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "raw",
   "id": "5439225b",
   "metadata": {},
   "source": [
    "Notebook Prepared By:\n",
    "    Akanksha Singh\n",
    "    Chinmay Gidwani\n",
    "    Harshraj Jadeja\n",
    "    Keertana Madan"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "201fdf39",
   "metadata": {},
   "source": [
    "# 1. Predicting Flight Arrival Delays (Machine Learning)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "794507a1",
   "metadata": {},
   "source": [
    "#### Importing Necessary Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "160fc66d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import networkx as nx\n",
    "import pulp\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.metrics import accuracy_score, roc_auc_score, confusion_matrix, classification_report\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from imblearn.over_sampling import SMOTE\n",
    "from imblearn.pipeline import Pipeline as ImblearnPipeline\n",
    "from sklearn.cluster import KMeans\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c34d886",
   "metadata": {},
   "source": [
    "#### Importing Input Data Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7a851d09",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('filtered_flight_data.csv')\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c90962b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9ce94d28",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FL_DATE</th>\n",
       "      <th>OP_CARRIER_AIRLINE_ID</th>\n",
       "      <th>TAIL_NUM</th>\n",
       "      <th>OP_CARRIER_FL_NUM</th>\n",
       "      <th>ORIGIN_AIRPORT_ID</th>\n",
       "      <th>ORIGIN_AIRPORT_SEQ_ID</th>\n",
       "      <th>ORIGIN_CITY_MARKET_ID</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST_AIRPORT_ID</th>\n",
       "      <th>DEST_AIRPORT_SEQ_ID</th>\n",
       "      <th>DEST_CITY_MARKET_ID</th>\n",
       "      <th>DEST</th>\n",
       "      <th>CRS_DEP_TIME</th>\n",
       "      <th>DEP_TIME</th>\n",
       "      <th>DEP_DELAY</th>\n",
       "      <th>DEP_DELAY_NEW</th>\n",
       "      <th>ARR_TIME</th>\n",
       "      <th>ARR_DELAY</th>\n",
       "      <th>ARR_DELAY_NEW</th>\n",
       "      <th>CANCELLED</th>\n",
       "      <th>CANCELLATION_CODE</th>\n",
       "      <th>CRS_ELAPSED_TIME</th>\n",
       "      <th>ACTUAL_ELAPSED_TIME</th>\n",
       "      <th>CARRIER_DELAY</th>\n",
       "      <th>WEATHER_DELAY</th>\n",
       "      <th>NAS_DELAY</th>\n",
       "      <th>SECURITY_DELAY</th>\n",
       "      <th>LATE_AIRCRAFT_DELAY</th>\n",
       "      <th>Unnamed: 28</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N201NN</td>\n",
       "      <td>6005</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>700</td>\n",
       "      <td>653.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>824.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N201NN</td>\n",
       "      <td>6005</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>900</td>\n",
       "      <td>851.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1038.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N218NN</td>\n",
       "      <td>6010</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>1110</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>-13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N218NN</td>\n",
       "      <td>6010</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>1310</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1436.0</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N209NN</td>\n",
       "      <td>6011</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>14831</td>\n",
       "      <td>1483106</td>\n",
       "      <td>32457</td>\n",
       "      <td>SJC</td>\n",
       "      <td>705</td>\n",
       "      <td>704.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>816.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "      FL_DATE  OP_CARRIER_AIRLINE_ID TAIL_NUM  OP_CARRIER_FL_NUM  \\\n",
       "0  2018-08-01                  21167   N201NN               6005   \n",
       "1  2018-08-01                  21167   N201NN               6005   \n",
       "2  2018-08-01                  21167   N218NN               6010   \n",
       "3  2018-08-01                  21167   N218NN               6010   \n",
       "4  2018-08-01                  21167   N209NN               6011   \n",
       "\n",
       "   ORIGIN_AIRPORT_ID  ORIGIN_AIRPORT_SEQ_ID  ORIGIN_CITY_MARKET_ID ORIGIN  \\\n",
       "0              12892                1289208                  32575    LAX   \n",
       "1              14893                1489302                  33192    SMF   \n",
       "2              12892                1289208                  32575    LAX   \n",
       "3              14893                1489302                  33192    SMF   \n",
       "4              12892                1289208                  32575    LAX   \n",
       "\n",
       "   DEST_AIRPORT_ID  DEST_AIRPORT_SEQ_ID  DEST_CITY_MARKET_ID DEST  \\\n",
       "0            14893              1489302                33192  SMF   \n",
       "1            12892              1289208                32575  LAX   \n",
       "2            14893              1489302                33192  SMF   \n",
       "3            12892              1289208                32575  LAX   \n",
       "4            14831              1483106                32457  SJC   \n",
       "\n",
       "   CRS_DEP_TIME  DEP_TIME  DEP_DELAY  DEP_DELAY_NEW  ARR_TIME  ARR_DELAY  \\\n",
       "0           700     653.0       -7.0            0.0     824.0       -4.0   \n",
       "1           900     851.0       -9.0            0.0    1038.0       -8.0   \n",
       "2          1110    1104.0       -6.0            0.0    1227.0      -13.0   \n",
       "3          1310    1305.0       -5.0            0.0    1436.0      -12.0   \n",
       "4           705     704.0       -1.0            0.0     816.0        0.0   \n",
       "\n",
       "   ARR_DELAY_NEW  CANCELLED CANCELLATION_CODE  CRS_ELAPSED_TIME  \\\n",
       "0            0.0        0.0               NaN              88.0   \n",
       "1            0.0        0.0               NaN             106.0   \n",
       "2            0.0        0.0               NaN              90.0   \n",
       "3            0.0        0.0               NaN              98.0   \n",
       "4            0.0        0.0               NaN              71.0   \n",
       "\n",
       "   ACTUAL_ELAPSED_TIME  CARRIER_DELAY  WEATHER_DELAY  NAS_DELAY  \\\n",
       "0                 91.0            NaN            NaN        NaN   \n",
       "1                107.0            NaN            NaN        NaN   \n",
       "2                 83.0            NaN            NaN        NaN   \n",
       "3                 91.0            NaN            NaN        NaN   \n",
       "4                 72.0            NaN            NaN        NaN   \n",
       "\n",
       "   SECURITY_DELAY  LATE_AIRCRAFT_DELAY  Unnamed: 28  \n",
       "0             NaN                  NaN          NaN  \n",
       "1             NaN                  NaN          NaN  \n",
       "2             NaN                  NaN          NaN  \n",
       "3             NaN                  NaN          NaN  \n",
       "4             NaN                  NaN          NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
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   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cc9afcb",
   "metadata": {},
   "source": [
    "<hr style=\"border:0.5px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2da52d46",
   "metadata": {},
   "source": [
    "#### Filtering to keep only Relevant Input Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "96ccb2e9",
   "metadata": {
    "scrolled": true
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   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FL_DATE</th>\n",
       "      <th>OP_CARRIER_AIRLINE_ID</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST</th>\n",
       "      <th>DEP_TIME</th>\n",
       "      <th>ARR_TIME</th>\n",
       "      <th>ARR_DELAY</th>\n",
       "      <th>CANCELLED</th>\n",
       "      <th>CANCELLATION_CODE</th>\n",
       "      <th>CARRIER_DELAY</th>\n",
       "      <th>WEATHER_DELAY</th>\n",
       "      <th>NAS_DELAY</th>\n",
       "      <th>SECURITY_DELAY</th>\n",
       "      <th>LATE_AIRCRAFT_DELAY</th>\n",
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       "      <th>0</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>LAX</td>\n",
       "      <td>SMF</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>1</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>SMF</td>\n",
       "      <td>LAX</td>\n",
       "      <td>851.0</td>\n",
       "      <td>1038.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>LAX</td>\n",
       "      <td>SMF</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>-13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>3</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>SMF</td>\n",
       "      <td>LAX</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>1436.0</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>LAX</td>\n",
       "      <td>SJC</td>\n",
       "      <td>704.0</td>\n",
       "      <td>816.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "      FL_DATE  OP_CARRIER_AIRLINE_ID ORIGIN DEST  DEP_TIME  ARR_TIME  \\\n",
       "0  2018-08-01                  21167    LAX  SMF     653.0     824.0   \n",
       "1  2018-08-01                  21167    SMF  LAX     851.0    1038.0   \n",
       "2  2018-08-01                  21167    LAX  SMF    1104.0    1227.0   \n",
       "3  2018-08-01                  21167    SMF  LAX    1305.0    1436.0   \n",
       "4  2018-08-01                  21167    LAX  SJC     704.0     816.0   \n",
       "\n",
       "   ARR_DELAY  CANCELLED CANCELLATION_CODE  CARRIER_DELAY  WEATHER_DELAY  \\\n",
       "0       -4.0        0.0               NaN            NaN            NaN   \n",
       "1       -8.0        0.0               NaN            NaN            NaN   \n",
       "2      -13.0        0.0               NaN            NaN            NaN   \n",
       "3      -12.0        0.0               NaN            NaN            NaN   \n",
       "4        0.0        0.0               NaN            NaN            NaN   \n",
       "\n",
       "   NAS_DELAY  SECURITY_DELAY  LATE_AIRCRAFT_DELAY  \n",
       "0        NaN             NaN                  NaN  \n",
       "1        NaN             NaN                  NaN  \n",
       "2        NaN             NaN                  NaN  \n",
       "3        NaN             NaN                  NaN  \n",
       "4        NaN             NaN                  NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Uncomment the next lines and modify the list of relevant columns as needed\n",
    "relevant_columns = [\n",
    "    'FL_DATE', \n",
    "    'OP_CARRIER_AIRLINE_ID', \n",
    "#    'TAIL_NUM', \n",
    "#    'OP_CARRIER_FL_NUM',\n",
    "#    'ORIGIN_AIRPORT_ID', \n",
    "#    'ORIGIN_AIRPORT_SEQ_ID', \n",
    "#    'ORIGIN_CITY_MARKET_ID', \n",
    "    'ORIGIN',\n",
    "#    'DEST_AIRPORT_ID', \n",
    "#     'DEST_AIRPORT_SEQ_ID', \n",
    "#     'DEST_CITY_MARKET_ID', \n",
    "    'DEST',\n",
    "#    'CRS_DEP_TIME', \n",
    "    'DEP_TIME', \n",
    "#    'DEP_DELAY', \n",
    "#     'DEP_DELAY_NEW', \n",
    "    'ARR_TIME',\n",
    "    'ARR_DELAY', \n",
    "#    'ARR_DELAY_NEW', \n",
    "    'CANCELLED', \n",
    "    'CANCELLATION_CODE', \n",
    "#    'CRS_ELAPSED_TIME',\n",
    "#    'ACTUAL_ELAPSED_TIME', \n",
    "    'CARRIER_DELAY', \n",
    "    'WEATHER_DELAY', \n",
    "    'NAS_DELAY',\n",
    "    'SECURITY_DELAY', \n",
    "    'LATE_AIRCRAFT_DELAY'\n",
    "]\n",
    "data = data[relevant_columns]\n",
    "\n",
    "# To check the reduced dataframe\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54cdeb60",
   "metadata": {},
   "source": [
    "<hr style=\"border:0.5px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98fbb08a",
   "metadata": {},
   "source": [
    "#### Null Treatment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b6b53c0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20311"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b0f1c11f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CANCELLATION_CODE        19841\n",
      "CARRIER_DELAY            16225\n",
      "WEATHER_DELAY            16225\n",
      "NAS_DELAY                16225\n",
      "SECURITY_DELAY           16225\n",
      "LATE_AIRCRAFT_DELAY      16225\n",
      "ARR_DELAY                  480\n",
      "ARR_TIME                   477\n",
      "DEP_TIME                   466\n",
      "FL_DATE                      0\n",
      "OP_CARRIER_AIRLINE_ID        0\n",
      "ORIGIN                       0\n",
      "DEST                         0\n",
      "CANCELLED                    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "null_counts = data.isnull().sum().sort_values(ascending=False)\n",
    "print(null_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d51f2ae1",
   "metadata": {},
   "source": [
    "#### Dropping the fields with a higher proportion of null records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9eee4eca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of columns to drop\n",
    "columns_to_drop = ['CANCELLATION_CODE', 'LATE_AIRCRAFT_DELAY', 'SECURITY_DELAY', \n",
    "                   'NAS_DELAY', 'WEATHER_DELAY', 'CARRIER_DELAY']\n",
    "\n",
    "# Dropping the specified columns\n",
    "data = data.drop(columns=columns_to_drop)\n",
    "\n",
    "# Dropping rows with any null values\n",
    "data = data.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "20621386",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FL_DATE                  0\n",
      "OP_CARRIER_AIRLINE_ID    0\n",
      "ORIGIN                   0\n",
      "DEST                     0\n",
      "DEP_TIME                 0\n",
      "ARR_TIME                 0\n",
      "ARR_DELAY                0\n",
      "CANCELLED                0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "null_counts = data.isnull().sum().sort_values(ascending=False)\n",
    "print(null_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d30021ba",
   "metadata": {},
   "source": [
    "<hr style=\"border:0.5px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01b9b5e1",
   "metadata": {},
   "source": [
    "#### Correlation Check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c3964c3c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/48/3359jr0n34v6fd5jftvl2dn00000gn/T/ipykernel_62474/2497433749.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  corr = data.corr()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate the correlation matrix\n",
    "corr = data.corr()\n",
    "\n",
    "# Plot the heatmap with smaller annotation font size\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(corr, annot=True, fmt=\".2f\", cmap='coolwarm', vmin=-1, vmax=1, annot_kws={\"size\": 5})\n",
    "plt.title('Correlation Matrix Heatmap')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "47ae5586",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pairs of fields with a correlation greater than 0.8:\n",
      "DEP_TIME  ARR_TIME    True\n",
      "dtype: bool\n"
     ]
    }
   ],
   "source": [
    "# Find pairs of fields with high correlation\n",
    "high_corr = (corr.abs() > 0.8) & (corr.abs() < 1.0)\n",
    "high_corr_pairs = high_corr.unstack().dropna()\n",
    "\n",
    "# Filter out lower/upper triangular duplicates by sorting\n",
    "unique_corr_pairs = high_corr_pairs.sort_values(ascending=False).drop_duplicates()\n",
    "\n",
    "print(\"Pairs of fields with a correlation greater than 0.8:\")\n",
    "print(unique_corr_pairs[unique_corr_pairs > 0.8])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2135c2b9",
   "metadata": {},
   "source": [
    "Departure time and arrival time show the highest correlation which aligns well with the business context as well."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3e730e7",
   "metadata": {},
   "source": [
    "<hr style=\"border:0.5px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35e631d8",
   "metadata": {},
   "source": [
    "#### Analyzing variability of Arrival Delays "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "66bb0beb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum ARR_DELAY: -44.0\n",
      "Maximum ARR_DELAY: 1298.0\n",
      "Range of ARR_DELAY: 1342.0\n",
      "Mean ARR_DELAY: 7.400685794967475\n",
      "Median ARR_DELAY: -4.0\n",
      "Mode ARR_DELAY: -8.0\n",
      "Standard Deviation of ARR_DELAY: 40.99176463708514\n"
     ]
    }
   ],
   "source": [
    "# Display the minimum value of 'ARR_DELAY'\n",
    "min_ARR_DELAY = data['ARR_DELAY'].min()\n",
    "print(f\"Minimum ARR_DELAY: {min_ARR_DELAY}\")\n",
    "\n",
    "# Display the maximum value of 'ARR_DELAY'\n",
    "max_ARR_DELAY = data['ARR_DELAY'].max()\n",
    "print(f\"Maximum ARR_DELAY: {max_ARR_DELAY}\")\n",
    "\n",
    "# Display the range of 'ARR_DELAY'\n",
    "range_ARR_DELAY = max_ARR_DELAY - min_ARR_DELAY\n",
    "print(f\"Range of ARR_DELAY: {range_ARR_DELAY}\")\n",
    "\n",
    "# Display the mean value of 'ARR_DELAY'\n",
    "mean_ARR_DELAY = data['ARR_DELAY'].mean()\n",
    "print(f\"Mean ARR_DELAY: {mean_ARR_DELAY}\")\n",
    "\n",
    "# Display the median value of 'ARR_DELAY'\n",
    "median_ARR_DELAY = data['ARR_DELAY'].median()\n",
    "print(f\"Median ARR_DELAY: {median_ARR_DELAY}\")\n",
    "\n",
    "# Display the mode value of 'ARR_DELAY' (Note: mode() returns a Series, so we extract the value)\n",
    "mode_ARR_DELAY = data['ARR_DELAY'].mode()[0]\n",
    "print(f\"Mode ARR_DELAY: {mode_ARR_DELAY}\")\n",
    "\n",
    "# Display the standard deviation of 'ARR_DELAY'\n",
    "std_dev_ARR_DELAY = data['ARR_DELAY'].std()\n",
    "print(f\"Standard Deviation of ARR_DELAY: {std_dev_ARR_DELAY}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d96fc16",
   "metadata": {},
   "source": [
    "<hr style=\"border:0.5px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efabfb44",
   "metadata": {},
   "source": [
    "### Feature Engineering, Data Preprocessing and Model Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8a550696",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 192 candidates, totalling 576 fits\n",
      "Updated Accuracy: 0.7101083942525838\n",
      "Updated ROC AUC: 0.768515976002607\n",
      "Updated Confusion Matrix:\n",
      "[[1822  598]\n",
      " [ 552  995]]\n",
      "\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.77      0.75      0.76      2420\n",
      "           1       0.62      0.64      0.63      1547\n",
      "\n",
      "    accuracy                           0.71      3967\n",
      "   macro avg       0.70      0.70      0.70      3967\n",
      "weighted avg       0.71      0.71      0.71      3967\n",
      "\n",
      "Updated CV Accuracy: 0.6754583754684443 ± 0.01070218415118806\n",
      "Updated CV ROC AUC: 0.7264861496878314 ± 0.010291304054470166\n"
     ]
    }
   ],
   "source": [
    "# 'data' is the DataFrame loaded with flight data\n",
    "df = data\n",
    "\n",
    "# Feature Engineering: Creating new features based on existing data\n",
    "# Function to categorize departure time into parts of the day\n",
    "def get_time_of_day(hour):\n",
    "    if 5 <= hour < 12:\n",
    "        return 'Morning'\n",
    "    elif 12 <= hour < 18:\n",
    "        return 'Afternoon'\n",
    "    else:\n",
    "        return 'Evening'\n",
    "\n",
    "# Extract hour from DEP_TIME and apply the function to categorize time of day\n",
    "df['DEP_HOUR'] = (df['DEP_TIME'] // 100).astype(int)  # Extract hour from HHMM format\n",
    "df['TIME_OF_DAY'] = df['DEP_HOUR'].apply(get_time_of_day)\n",
    "\n",
    "# Extract the month from the flight date for capturing seasonal effects\n",
    "df['MONTH'] = pd.to_datetime(df['FL_DATE']).dt.month\n",
    "\n",
    "# Create a binary target variable for delay (1 if there's a delay, 0 otherwise)\n",
    "df['Delay'] = (df['ARR_DELAY'] > 0).astype(int)\n",
    "\n",
    "# Prepare feature matrix and target vector\n",
    "# Including newly created features and categorical features\n",
    "feature_columns = ['OP_CARRIER_AIRLINE_ID', 'DEP_HOUR', 'CANCELLED', 'TIME_OF_DAY', 'MONTH', 'ORIGIN', 'DEST']\n",
    "categorical_features = ['ORIGIN', 'DEST', 'TIME_OF_DAY', 'MONTH']\n",
    "df[categorical_features] = df[categorical_features].apply(LabelEncoder().fit_transform)\n",
    "\n",
    "# Define X and y for model training\n",
    "X = df[feature_columns]\n",
    "y = df['Delay']\n",
    "\n",
    "# Data preprocessing and ML pipeline\n",
    "# Configure preprocessing to scale numerical data\n",
    "preprocessor = ColumnTransformer(transformers=[('scaler', StandardScaler(), feature_columns)], remainder='passthrough')\n",
    "\n",
    "# Setup the machine learning pipeline with SMOTE for handling class imbalance\n",
    "pipeline = ImblearnPipeline(steps=[\n",
    "    ('preprocessor', preprocessor),\n",
    "    ('smote', SMOTE(random_state=42)),  # SMOTE for synthetic minority oversampling\n",
    "    ('classifier', GradientBoostingClassifier(random_state=42))  # Gradient Boosting Classifier\n",
    "])\n",
    "\n",
    "# Split data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Setup grid search to find the best hyperparameters\n",
    "param_grid = {\n",
    "    'classifier__n_estimators': [100, 150, 200],\n",
    "    'classifier__learning_rate': [0.01, 0.05, 0.1, 0.15],\n",
    "    'classifier__max_depth': [3, 5, 7, 10],\n",
    "    'classifier__subsample': [0.75, 0.8, 0.9, 1.0]\n",
    "}\n",
    "grid_search = GridSearchCV(pipeline, param_grid=param_grid, cv=3, scoring='accuracy', verbose=1)\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "# Evaluate the model using test data\n",
    "y_pred = grid_search.predict(X_test)\n",
    "y_proba = grid_search.predict_proba(X_test)[:, 1]\n",
    "\n",
    "# Performance metrics\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "roc_auc = roc_auc_score(y_test, y_proba)\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "# Print results\n",
    "print(f\"Updated Accuracy: {accuracy}\")\n",
    "print(f\"Updated ROC AUC: {roc_auc}\")\n",
    "print(\"Updated Confusion Matrix:\")\n",
    "print(cm)\n",
    "print(\"\\nClassification Report:\")\n",
    "print(classification_report(y_test, y_pred))\n",
    "\n",
    "# Cross-validation metrics for model robustness\n",
    "cv_accuracy = cross_val_score(grid_search.best_estimator_, X, y, scoring='accuracy', cv=3)\n",
    "cv_roc_auc = cross_val_score(grid_search.best_estimator_, X, y, scoring='roc_auc', cv=3)\n",
    "\n",
    "print(f\"Updated CV Accuracy: {np.mean(cv_accuracy)} ± {np.std(cv_accuracy)}\")\n",
    "print(f\"Updated CV ROC AUC: {np.mean(cv_roc_auc)} ± {np.std(cv_roc_auc)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11a6b0d4",
   "metadata": {},
   "source": [
    "#### Model Performance Overview:"
   ]
  },
  {
   "cell_type": "raw",
   "id": "ac137727",
   "metadata": {},
   "source": [
    "Updated Accuracy: 71.01% - This indicates that the model correctly predicts whether a flight will be delayed or not about 71% of the time.\n",
    "\n",
    "Updated ROC AUC: 76.85% - The ROC AUC value is quite good, suggesting that the model has a strong ability to differentiate between delayed and non-delayed flights."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ce20618",
   "metadata": {},
   "source": [
    "#### Confusion Matrix Analysis:"
   ]
  },
  {
   "cell_type": "raw",
   "id": "a11f9555",
   "metadata": {},
   "source": [
    "True Positives (TP): 995 - The model correctly predicted 995 flights as delayed.\n",
    "\n",
    "True Negatives (TN): 1822 - The model correctly predicted 1822 flights as not delayed.\n",
    "\n",
    "False Positives (FP): 598 - The model incorrectly predicted 598 flights as delayed when they were not.\n",
    "\n",
    "False Negatives (FN): 552 - The model failed to identify 552 flights that were delayed."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58f94c29",
   "metadata": {},
   "source": [
    "#### Classification Report Insights:"
   ]
  },
  {
   "cell_type": "raw",
   "id": "a2cd1409",
   "metadata": {},
   "source": [
    "Precision for Non-Delayed Flights (0): 0.77 - When it predicts a flight is not delayed, it is correct 77% of the time.\n",
    "\n",
    "Recall for Non-Delayed Flights (0): 0.75 - It correctly identifies 75% of all non-delayed flights.\n",
    "\n",
    "Precision for Delayed Flights (1): 0.62 - When it predicts a flight is delayed, it is correct 62% of the time.\n",
    "\n",
    "Recall for Delayed Flights (1): 0.64 - It correctly identifies 64% of all delayed flights.\n",
    "\n",
    "F1-Score: Indicates the balance between precision and recall. For non-delayed flights, the F1-score is 0.76, and for delayed flights, it is 0.63, showing better performance for non-delayed flight predictions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2237e402",
   "metadata": {},
   "source": [
    "#### Cross-Validation Metrics:"
   ]
  },
  {
   "cell_type": "raw",
   "id": "d38d7227",
   "metadata": {},
   "source": [
    "CV Accuracy: 67.55% ± 1.07% - The model's accuracy varies slightly less around this mean across different subsets of the data, indicating moderate stability.\n",
    "\n",
    "CV ROC AUC: 72.65% ± 1.03% - There is some variation in how well the model discriminates between classes across different folds, suggesting potential overfitting to the training set or a need for better generalization."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13d926b9",
   "metadata": {},
   "source": [
    "#### Looking at the Feature Importance Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "44fadc14",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Retrieve the best estimator from the grid search\n",
    "best_model = grid_search.best_estimator_\n",
    "\n",
    "# Extract the Gradient Boosting Classifier from the pipeline (assuming it's the last step)\n",
    "gb_classifier = best_model.named_steps['classifier']\n",
    "\n",
    "# Get feature importances\n",
    "importances = gb_classifier.feature_importances_\n",
    "\n",
    "# Create a DataFrame to view the feature importances alongside their corresponding feature names\n",
    "feature_importance_df = pd.DataFrame({\n",
    "    'Feature': feature_columns,\n",
    "    'Importance': importances\n",
    "}).sort_values(by='Importance', ascending=False)\n",
    "\n",
    "# Plotting the feature importances\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.barplot(x='Importance', y='Feature', data=feature_importance_df, palette='viridis')\n",
    "plt.title('Feature Importances')\n",
    "plt.xlabel('Importance')\n",
    "plt.ylabel('Features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "470efcf1",
   "metadata": {},
   "source": [
    "Insight:\n",
    "\n",
    "The \"DEP_HOUR\" feature holds the most significant influence on predicting delays in the model, suggesting that the time of departure is crucial in determining flight delays."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74e30137",
   "metadata": {},
   "source": [
    "<hr style=\"border:4px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4ee64b3",
   "metadata": {},
   "source": [
    "# 2. Airport Profiling Using Clustering (Machine Learning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0a50f77a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/48/3359jr0n34v6fd5jftvl2dn00000gn/T/ipykernel_62474/996812784.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  flights_data_filtered.fillna(0, inplace=True)  # Handling missing values by assuming no delay if data is missing\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           DEP_DELAY  ARR_DELAY  CARRIER_DELAY  WEATHER_DELAY  NAS_DELAY  \\\n",
      "Cluster 1   7.623173   3.470134       2.716481       0.012409   1.076798   \n",
      "Cluster 2  13.748206   9.374012       2.046459       0.027709   6.042333   \n",
      "Cluster 3  10.943730   7.856789       2.773639       0.009061   4.465110   \n",
      "Cluster 4  15.472027  11.501827       4.757380       0.008153   1.849873   \n",
      "\n",
      "           SECURITY_DELAY  LATE_AIRCRAFT_DELAY  CANCELLED  \n",
      "Cluster 1        0.021894             4.716132   0.015052  \n",
      "Cluster 2        0.016447             5.767643   0.014493  \n",
      "Cluster 3        0.007552             5.518349   0.024198  \n",
      "Cluster 4        0.000000             9.765252   0.040484  \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/48/3359jr0n34v6fd5jftvl2dn00000gn/T/ipykernel_62474/996812784.py:56: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  date_cluster_group = flights_with_date.groupby(['FL_DATE', 'Cluster']).mean().reset_index()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load the data\n",
    "file_path = 'filtered_flight_data.csv'\n",
    "flights_data = pd.read_csv(file_path)\n",
    "\n",
    "# Clean and prepare the data\n",
    "flights_data['FL_DATE'] = pd.to_datetime(flights_data['FL_DATE'])\n",
    "relevant_columns = [\n",
    "    'FL_DATE', 'ORIGIN', 'OP_CARRIER_AIRLINE_ID', 'DEP_DELAY', 'ARR_DELAY',\n",
    "    'CARRIER_DELAY', 'WEATHER_DELAY', 'NAS_DELAY', 'SECURITY_DELAY', 'LATE_AIRCRAFT_DELAY', 'CANCELLED'\n",
    "]\n",
    "flights_data_filtered = flights_data[relevant_columns]\n",
    "flights_data_filtered.fillna(0, inplace=True)  # Handling missing values by assuming no delay if data is missing\n",
    "\n",
    "# Calculate average delays and cancellation rates for each airport\n",
    "airport_delays = flights_data_filtered.groupby('ORIGIN').agg({\n",
    "    'DEP_DELAY': 'mean',\n",
    "    'ARR_DELAY': 'mean',\n",
    "    'CARRIER_DELAY': 'mean',\n",
    "    'WEATHER_DELAY': 'mean',\n",
    "    'NAS_DELAY': 'mean',\n",
    "    'SECURITY_DELAY': 'mean',\n",
    "    'LATE_AIRCRAFT_DELAY': 'mean',\n",
    "    'CANCELLED': 'mean'\n",
    "}).reset_index()\n",
    "\n",
    "# Clustering with K-means and determining the optimal number of clusters using the elbow method\n",
    "sse = []\n",
    "for k in range(1, 11):\n",
    "    kmeans = KMeans(n_clusters=k, random_state=42)\n",
    "    kmeans.fit(airport_delays.iloc[:, 1:])\n",
    "    sse.append(kmeans.inertia_)\n",
    "\n",
    "# Plotting the Elbow Curve\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(range(1, 11), sse, marker='o')\n",
    "plt.title('Elbow Method for Optimal Clusters')\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('Sum of squared distances')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Applying K-means clustering with the chosen number of clusters (e.g., 4)\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "airport_delays['Cluster'] = kmeans.fit_predict(airport_delays.iloc[:, 1:])\n",
    "\n",
    "# Analyzing and plotting cluster characteristics\n",
    "cluster_centers = kmeans.cluster_centers_\n",
    "columns = airport_delays.columns[1:-1]  # Exclude 'ORIGIN' and 'Cluster'\n",
    "cluster_summary = pd.DataFrame(cluster_centers, columns=columns, index=[f'Cluster {i+1}' for i in range(4)])\n",
    "\n",
    "# Printing cluster centers for insight\n",
    "print(cluster_summary)\n",
    "\n",
    "# Preparing area charts for delays over time by cluster\n",
    "flights_with_date = flights_data_filtered.merge(airport_delays[['ORIGIN', 'Cluster']], on='ORIGIN', how='left')\n",
    "date_cluster_group = flights_with_date.groupby(['FL_DATE', 'Cluster']).mean().reset_index()\n",
    "\n",
    "# Area Chart for each cluster\n",
    "fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(15, 12), sharex=True)\n",
    "clusters = sorted(date_cluster_group['Cluster'].unique())\n",
    "\n",
    "for ax, cluster in zip(axes.flatten(), clusters):\n",
    "    subset = date_cluster_group[date_cluster_group['Cluster'] == cluster]\n",
    "    ax.stackplot(subset['FL_DATE'], subset['CARRIER_DELAY'], subset['WEATHER_DELAY'], subset['NAS_DELAY'], subset['SECURITY_DELAY'], subset['LATE_AIRCRAFT_DELAY'],\n",
    "                 labels=['Carrier Delay', 'Weather Delay', 'NAS Delay', 'Security Delay', 'Late Aircraft Delay'],\n",
    "                 alpha=0.8)\n",
    "    ax.set_title(f'Cluster {cluster} Delays Over Time')\n",
    "    ax.set_ylabel('Average Delay (minutes)')\n",
    "    ax.legend(loc='upper left')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "511957a4",
   "metadata": {},
   "source": [
    "### Cluster 1: \"High Efficiency, Low Impact\""
   ]
  },
  {
   "cell_type": "raw",
   "id": "c2074e26",
   "metadata": {},
   "source": [
    "Lowest Delays: This cluster features the lowest average departure and arrival delays, suggesting efficient operations and minimal disruptions.\n",
    "\n",
    "Minimal Weather and NAS Delays: Both weather and NAS delays are extremely low, indicating that these airports are less affected by external environmental factors and airspace system issues.\n",
    "\n",
    "Low Cancellations: The cancellation rate is also low, enhancing its reputation for reliability.\n",
    "\n",
    "Insight: Airports in this cluster are likely smaller or exceptionally well-managed, with streamlined operations that rarely face significant delays or cancellations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ffca7f1",
   "metadata": {},
   "source": [
    "### Cluster 2: \"Moderate Delays, Controlled Impact\""
   ]
  },
  {
   "cell_type": "raw",
   "id": "c9227d30",
   "metadata": {},
   "source": [
    "Higher Delays: Exhibits moderate levels of departure and arrival delays. Not as efficient as Cluster 1 but still manages to keep delays under control.\n",
    "\n",
    "Higher NAS Delays: Indicates more significant impact from the National Airspace System, possibly due to higher traffic volumes or strategic location.\n",
    "\n",
    "Low Carrier and Security Delays: Shows effective management of carrier operations and security, contributing to fewer delays in these areas despite higher overall delays.\n",
    "\n",
    "Insight: These airports might be busier than those in Cluster 1 but have effective delay management strategies in place, particularly concerning carrier and security operations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9ff5c61",
   "metadata": {},
   "source": [
    "### Cluster 3: \"Average Performance\""
   ]
  },
  {
   "cell_type": "raw",
   "id": "cfb77bdf",
   "metadata": {},
   "source": [
    "Intermediate Delays: Delays are higher than Cluster 1 but lower than Cluster 4, placing them in the middle in terms of operational efficiency.\n",
    "\n",
    "Moderate Cancellation Rates: Has a higher cancellation rate compared to Clusters 1 and 2, which might indicate more frequent issues or challenges.\n",
    "\n",
    "Balanced Delay Types: No particular type of delay dominates, suggesting a balanced spread of delay causes.\n",
    "\n",
    "Insight: Airports in this cluster have average delay and cancellation rates, likely reflecting a mix of traffic volumes and operational challenges."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee4a03b3",
   "metadata": {},
   "source": [
    "### Cluster 4: \"High Delays and Cancellations\""
   ]
  },
  {
   "cell_type": "raw",
   "id": "488b2139",
   "metadata": {},
   "source": [
    "Highest Delays: This cluster experiences the highest average departure and arrival delays.\n",
    "\n",
    "Significant Late Aircraft Delays: The highest late aircraft delays, possibly indicating issues with scheduling, airline efficiency, or knock-on effects from earlier delays.\n",
    "\n",
    "Highest Cancellations: Also features the highest cancellation rate, underscoring potential issues with reliability.\n",
    "\n",
    "Insight: Airports in this cluster may struggle with operational efficiency and face the most significant challenges regarding managing delays and cancellations. They could benefit from targeted improvements in scheduling and operational coordination."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8de7121",
   "metadata": {},
   "source": [
    "<hr style=\"border:4px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbdae9e4",
   "metadata": {},
   "source": [
    "# 3. Shortest Path Analysis (Graph Algorithms)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "44cbc85f",
   "metadata": {},
   "source": [
    "Key Components\n",
    "\n",
    "Data Reading: The script reads from a CSV file using pandas.\n",
    "\n",
    "Graph Construction: It constructs a directed graph using networkx, where nodes represent airports and edges represent direct flights with weights as the actual flying time.\n",
    "\n",
    "Path Finding: The code attempts to find the shortest paths from JFK to LAX based on the total flying time, printing the top three shortest paths."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1313de09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shortest path 1: ['JFK', 'LAX']\n",
      "Total flying time: 354.0 minutes\n",
      "Difference in time from shortest path for path 2: 30.0 minutes\n",
      "Shortest path 2: ['JFK', 'IND', 'LAX']\n",
      "Total flying time: 384.0 minutes\n",
      "Difference in time from shortest path for path 3: 30.0 minutes\n",
      "Shortest path 3: ['JFK', 'CLE', 'LAX']\n",
      "Total flying time: 384.0 minutes\n"
     ]
    }
   ],
   "source": [
    "# Load data from the CSV file\n",
    "df = pd.read_csv('August 2018 Nationwide.csv')\n",
    "\n",
    "# Create a directed graph\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# Add edges to the graph from DataFrame. Each edge has a weight, which is the actual flying time.\n",
    "for idx, row in df.iterrows():\n",
    "    if pd.notna(row['ACTUAL_ELAPSED_TIME']):  # Ensure there's a valid flying time\n",
    "        G.add_edge(row['ORIGIN'], row['DEST'], weight=row['ACTUAL_ELAPSED_TIME'])\n",
    "\n",
    "# Define the airports for the route calculation\n",
    "airport_a = 'JFK'  # Example starting airport\n",
    "airport_b = 'LAX'  # Example destination airport\n",
    "\n",
    "# Initialize a counter and path generator\n",
    "try:\n",
    "    path_generator = nx.shortest_simple_paths(G, source=airport_a, target=airport_b, weight='weight')\n",
    "    shortest_time = None  # To store the shortest path time for reference\n",
    "    for i in range(3):  # Fetch the top three shortest paths\n",
    "        path = next(path_generator)\n",
    "        total_time = sum(G[u][v]['weight'] for u, v in zip(path[:-1], path[1:]))\n",
    "        if i == 0:\n",
    "            shortest_time = total_time  # Set the first path time as the shortest\n",
    "        else:\n",
    "            time_difference = total_time - shortest_time\n",
    "            print(f\"Difference in time from shortest path for path {i+1}: {time_difference} minutes\")\n",
    "        print(f\"Shortest path {i+1}: {path}\")\n",
    "        print(\"Total flying time:\", total_time, \"minutes\")\n",
    "except StopIteration:\n",
    "    print(\"Less than three paths were found.\")\n",
    "except nx.NetworkXNoPath:\n",
    "    print(f\"No path found between {airport_a} and {airport_b}\")"
   ]
  },
  {
   "cell_type": "raw",
   "id": "5cfe22e4",
   "metadata": {},
   "source": [
    "Direct Efficiency: The direct flight from JFK to LAX is the most time-efficient route, taking 354 minutes.\n",
    "\n",
    "Common Time Increase: Both alternative routes via IND and CLE increase travel time by exactly 30 minutes compared to the direct flight.\n",
    "\n",
    "Routing Variability: Despite different midpoints (IND and CLE), the total travel time for the alternative routes remains identical, highlighting a possible consistency in layover or flight speeds for these paths.\n",
    "\n",
    "Optimal Choice: For time-sensitive travel, choosing the direct route between JFK and LAX is clearly the best option.\n",
    "\n",
    "Layover Impact: The layovers at IND and CLE have an equal impact on travel time, suggesting that either layover might be due to scheduling rather than distance."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da1c0531",
   "metadata": {},
   "source": [
    "<hr style=\"border:4px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b3c317d",
   "metadata": {},
   "source": [
    "# 4. Connect all airports in a State (California) with Carrier Delay as weights using Minimum Spanning Tree (Kruskal's)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f36939ba",
   "metadata": {},
   "source": [
    "## (Graph Algorithms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7d98adeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading the dataset\n",
    "flights = pd.read_csv('August 2018 Nationwide.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dadb915",
   "metadata": {},
   "source": [
    "#### Filter the data to include only California airports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "68d19b56",
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of airport codes to filter by\n",
    "airport_codes = ['BUR', 'LGB', 'LAX', 'OAK', 'ONT', 'SMF', 'SAN', 'SFO', 'SJC', 'SNA']\n",
    " \n",
    "# Filter data where either the origin or destination airport is in the airport_codes list\n",
    "filtered_df = flights[flights['ORIGIN'].isin(airport_codes) & flights['DEST'].isin(airport_codes)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "89afa1de",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FL_DATE</th>\n",
       "      <th>OP_CARRIER_AIRLINE_ID</th>\n",
       "      <th>TAIL_NUM</th>\n",
       "      <th>OP_CARRIER_FL_NUM</th>\n",
       "      <th>ORIGIN_AIRPORT_ID</th>\n",
       "      <th>ORIGIN_AIRPORT_SEQ_ID</th>\n",
       "      <th>ORIGIN_CITY_MARKET_ID</th>\n",
       "      <th>ORIGIN</th>\n",
       "      <th>DEST_AIRPORT_ID</th>\n",
       "      <th>DEST_AIRPORT_SEQ_ID</th>\n",
       "      <th>DEST_CITY_MARKET_ID</th>\n",
       "      <th>DEST</th>\n",
       "      <th>CRS_DEP_TIME</th>\n",
       "      <th>DEP_TIME</th>\n",
       "      <th>DEP_DELAY</th>\n",
       "      <th>DEP_DELAY_NEW</th>\n",
       "      <th>ARR_TIME</th>\n",
       "      <th>ARR_DELAY</th>\n",
       "      <th>ARR_DELAY_NEW</th>\n",
       "      <th>CANCELLED</th>\n",
       "      <th>CANCELLATION_CODE</th>\n",
       "      <th>CRS_ELAPSED_TIME</th>\n",
       "      <th>ACTUAL_ELAPSED_TIME</th>\n",
       "      <th>CARRIER_DELAY</th>\n",
       "      <th>WEATHER_DELAY</th>\n",
       "      <th>NAS_DELAY</th>\n",
       "      <th>SECURITY_DELAY</th>\n",
       "      <th>LATE_AIRCRAFT_DELAY</th>\n",
       "      <th>Unnamed: 28</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1087</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N201NN</td>\n",
       "      <td>6005</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>700</td>\n",
       "      <td>653.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>824.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
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       "      <td>21167</td>\n",
       "      <td>N201NN</td>\n",
       "      <td>6005</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>900</td>\n",
       "      <td>851.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1038.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1092</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N218NN</td>\n",
       "      <td>6010</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>1110</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>-13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N218NN</td>\n",
       "      <td>6010</td>\n",
       "      <td>14893</td>\n",
       "      <td>1489302</td>\n",
       "      <td>33192</td>\n",
       "      <td>SMF</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>1310</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1436.0</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1094</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>21167</td>\n",
       "      <td>N209NN</td>\n",
       "      <td>6011</td>\n",
       "      <td>12892</td>\n",
       "      <td>1289208</td>\n",
       "      <td>32575</td>\n",
       "      <td>LAX</td>\n",
       "      <td>14831</td>\n",
       "      <td>1483106</td>\n",
       "      <td>32457</td>\n",
       "      <td>SJC</td>\n",
       "      <td>705</td>\n",
       "      <td>704.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>816.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>701267</th>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>19687</td>\n",
       "      <td>N630QX</td>\n",
       "      <td>2550</td>\n",
       "      <td>14831</td>\n",
       "      <td>1483106</td>\n",
       "      <td>32457</td>\n",
       "      <td>SJC</td>\n",
       "      <td>10800</td>\n",
       "      <td>1080003</td>\n",
       "      <td>32575</td>\n",
       "      <td>BUR</td>\n",
       "      <td>635</td>\n",
       "      <td>631.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>744.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701268</th>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>19687</td>\n",
       "      <td>N622QX</td>\n",
       "      <td>2552</td>\n",
       "      <td>14831</td>\n",
       "      <td>1483106</td>\n",
       "      <td>32457</td>\n",
       "      <td>SJC</td>\n",
       "      <td>10800</td>\n",
       "      <td>1080003</td>\n",
       "      <td>32575</td>\n",
       "      <td>BUR</td>\n",
       "      <td>1923</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2108.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701319</th>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>19687</td>\n",
       "      <td>N630QX</td>\n",
       "      <td>2810</td>\n",
       "      <td>10800</td>\n",
       "      <td>1080003</td>\n",
       "      <td>32575</td>\n",
       "      <td>BUR</td>\n",
       "      <td>14831</td>\n",
       "      <td>1483106</td>\n",
       "      <td>32457</td>\n",
       "      <td>SJC</td>\n",
       "      <td>830</td>\n",
       "      <td>824.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>939.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701321</th>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>19687</td>\n",
       "      <td>N622QX</td>\n",
       "      <td>2812</td>\n",
       "      <td>10800</td>\n",
       "      <td>1080003</td>\n",
       "      <td>32575</td>\n",
       "      <td>BUR</td>\n",
       "      <td>14831</td>\n",
       "      <td>1483106</td>\n",
       "      <td>32457</td>\n",
       "      <td>SJC</td>\n",
       "      <td>2118</td>\n",
       "      <td>2143.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2252.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701333</th>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>19687</td>\n",
       "      <td>N632QX</td>\n",
       "      <td>2897</td>\n",
       "      <td>14771</td>\n",
       "      <td>1477104</td>\n",
       "      <td>32457</td>\n",
       "      <td>SFO</td>\n",
       "      <td>14908</td>\n",
       "      <td>1490803</td>\n",
       "      <td>32575</td>\n",
       "      <td>SNA</td>\n",
       "      <td>1425</td>\n",
       "      <td>1419.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1552.0</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20311 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           FL_DATE  OP_CARRIER_AIRLINE_ID TAIL_NUM  OP_CARRIER_FL_NUM  \\\n",
       "1087    2018-08-01                  21167   N201NN               6005   \n",
       "1088    2018-08-01                  21167   N201NN               6005   \n",
       "1092    2018-08-01                  21167   N218NN               6010   \n",
       "1093    2018-08-01                  21167   N218NN               6010   \n",
       "1094    2018-08-01                  21167   N209NN               6011   \n",
       "...            ...                    ...      ...                ...   \n",
       "701267  2018-08-31                  19687   N630QX               2550   \n",
       "701268  2018-08-31                  19687   N622QX               2552   \n",
       "701319  2018-08-31                  19687   N630QX               2810   \n",
       "701321  2018-08-31                  19687   N622QX               2812   \n",
       "701333  2018-08-31                  19687   N632QX               2897   \n",
       "\n",
       "        ORIGIN_AIRPORT_ID  ORIGIN_AIRPORT_SEQ_ID  ORIGIN_CITY_MARKET_ID  \\\n",
       "1087                12892                1289208                  32575   \n",
       "1088                14893                1489302                  33192   \n",
       "1092                12892                1289208                  32575   \n",
       "1093                14893                1489302                  33192   \n",
       "1094                12892                1289208                  32575   \n",
       "...                   ...                    ...                    ...   \n",
       "701267              14831                1483106                  32457   \n",
       "701268              14831                1483106                  32457   \n",
       "701319              10800                1080003                  32575   \n",
       "701321              10800                1080003                  32575   \n",
       "701333              14771                1477104                  32457   \n",
       "\n",
       "       ORIGIN  DEST_AIRPORT_ID  DEST_AIRPORT_SEQ_ID  DEST_CITY_MARKET_ID DEST  \\\n",
       "1087      LAX            14893              1489302                33192  SMF   \n",
       "1088      SMF            12892              1289208                32575  LAX   \n",
       "1092      LAX            14893              1489302                33192  SMF   \n",
       "1093      SMF            12892              1289208                32575  LAX   \n",
       "1094      LAX            14831              1483106                32457  SJC   \n",
       "...       ...              ...                  ...                  ...  ...   \n",
       "701267    SJC            10800              1080003                32575  BUR   \n",
       "701268    SJC            10800              1080003                32575  BUR   \n",
       "701319    BUR            14831              1483106                32457  SJC   \n",
       "701321    BUR            14831              1483106                32457  SJC   \n",
       "701333    SFO            14908              1490803                32575  SNA   \n",
       "\n",
       "        CRS_DEP_TIME  DEP_TIME  DEP_DELAY  DEP_DELAY_NEW  ARR_TIME  ARR_DELAY  \\\n",
       "1087             700     653.0       -7.0            0.0     824.0       -4.0   \n",
       "1088             900     851.0       -9.0            0.0    1038.0       -8.0   \n",
       "1092            1110    1104.0       -6.0            0.0    1227.0      -13.0   \n",
       "1093            1310    1305.0       -5.0            0.0    1436.0      -12.0   \n",
       "1094             705     704.0       -1.0            0.0     816.0        0.0   \n",
       "...              ...       ...        ...            ...       ...        ...   \n",
       "701267           635     631.0       -4.0            0.0     744.0       -6.0   \n",
       "701268          1923    2003.0       40.0           40.0    2108.0       30.0   \n",
       "701319           830     824.0       -6.0            0.0     939.0       -5.0   \n",
       "701321          2118    2143.0       25.0           25.0    2252.0       20.0   \n",
       "701333          1425    1419.0       -6.0            0.0    1552.0      -10.0   \n",
       "\n",
       "        ARR_DELAY_NEW  CANCELLED CANCELLATION_CODE  CRS_ELAPSED_TIME  \\\n",
       "1087              0.0        0.0                 0              88.0   \n",
       "1088              0.0        0.0                 0             106.0   \n",
       "1092              0.0        0.0                 0              90.0   \n",
       "1093              0.0        0.0                 0              98.0   \n",
       "1094              0.0        0.0                 0              71.0   \n",
       "...               ...        ...               ...               ...   \n",
       "701267            0.0        0.0                 0              75.0   \n",
       "701268           30.0        0.0                 0              75.0   \n",
       "701319            0.0        0.0                 0              74.0   \n",
       "701321           20.0        0.0                 0              74.0   \n",
       "701333            0.0        0.0                 0              97.0   \n",
       "\n",
       "        ACTUAL_ELAPSED_TIME  CARRIER_DELAY  WEATHER_DELAY  NAS_DELAY  \\\n",
       "1087                   91.0            0.0            0.0        0.0   \n",
       "1088                  107.0            0.0            0.0        0.0   \n",
       "1092                   83.0            0.0            0.0        0.0   \n",
       "1093                   91.0            0.0            0.0        0.0   \n",
       "1094                   72.0            0.0            0.0        0.0   \n",
       "...                     ...            ...            ...        ...   \n",
       "701267                 73.0            0.0            0.0        0.0   \n",
       "701268                 65.0            0.0            0.0        0.0   \n",
       "701319                 75.0            0.0            0.0        0.0   \n",
       "701321                 69.0            0.0            0.0        0.0   \n",
       "701333                 93.0            0.0            0.0        0.0   \n",
       "\n",
       "        SECURITY_DELAY  LATE_AIRCRAFT_DELAY  Unnamed: 28  \n",
       "1087               0.0                  0.0          0.0  \n",
       "1088               0.0                  0.0          0.0  \n",
       "1092               0.0                  0.0          0.0  \n",
       "1093               0.0                  0.0          0.0  \n",
       "1094               0.0                  0.0          0.0  \n",
       "...                ...                  ...          ...  \n",
       "701267             0.0                  0.0          0.0  \n",
       "701268             0.0                 30.0          0.0  \n",
       "701319             0.0                  0.0          0.0  \n",
       "701321             0.0                 20.0          0.0  \n",
       "701333             0.0                  0.0          0.0  \n",
       "\n",
       "[20311 rows x 29 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fill missing values with 0 (delays)\n",
    "filtered_df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cc6d4f74",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Take areas where Carrier Delay > 0\n",
    "filtered_df = filtered_df[filtered_df['CARRIER_DELAY']>0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e601cf7",
   "metadata": {},
   "source": [
    "#### Kruskal's algorithm to identify the best method to connect all California airports with Carrier Delay as weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b8d0f286",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Delay in Full Network: 562.0\n",
      "Total Delay in MST: 36.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a graph for the filtered data\n",
    "G_filtered = nx.Graph()\n",
    "for index, row in filtered_df.iterrows():\n",
    "    G_filtered.add_edge(row['ORIGIN'], row['DEST'], weight=abs(row['CARRIER_DELAY']))\n",
    "\n",
    "# Compute the MST using Kruskal's algorithm for the filtered graph\n",
    "mst_filtered = nx.minimum_spanning_tree(G_filtered, algorithm='kruskal')\n",
    "\n",
    "# Calculate total delay in the full filtered network\n",
    "total_delay_full = sum(weight for (u, v, weight) in G_filtered.edges(data='weight'))\n",
    "\n",
    "# Calculate total delay in the MST\n",
    "total_delay_mst = sum(weight for (u, v, weight) in mst_filtered.edges(data='weight'))\n",
    "\n",
    "# Output the total delays for comparison\n",
    "print(f\"Total Delay in Full Network: {total_delay_full}\")\n",
    "print(f\"Total Delay in MST: {total_delay_mst}\")\n",
    "\n",
    "# Plotting the filtered graph with MST\n",
    "pos = nx.spring_layout(G_filtered)  # positions for all nodes\n",
    "nx.draw(G_filtered, pos, with_labels=True, node_color='lightblue', edge_color='#909090', node_size=500)\n",
    "nx.draw_networkx_edges(mst_filtered, pos, edge_color='red', width=2)\n",
    "# plt.title(f'Flight Network with MST for {state}')\n",
    "plt.show()\n",
    "\n",
    "# Plotting the comparison of delays\n",
    "delays = [total_delay_full, total_delay_mst]\n",
    "labels = ['Full Network', 'MST Network']\n",
    "colors = ['blue', 'red']\n",
    "plt.bar(labels, delays, color=colors)\n",
    "plt.ylabel('Total Delay')\n",
    "plt.title('Comparison of Total Delays')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb04351d",
   "metadata": {},
   "source": [
    " **Grey lines:** Current connections between airports (California)\n",
    " \n",
    " **Red lines:** Suggested connections between airports (California) using Kruskal's"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "399c7ab1",
   "metadata": {},
   "source": [
    "**Building the Filtered Graph:**\n",
    "1. A new graph G_filtered is initialized.\n",
    "2. The script iterates through filtered_df, which is presumably a pandas DataFrame containing filtered flight data with columns 'ORIGIN', 'DEST', and 'CARRIER_DELAY'.\n",
    "3. For each row in filtered_df, an edge is added between the origin and destination airports with a weight equal to the absolute value of the carrier delay (abs(row['CARRIER_DELAY'])). This ensures that delay values are positive, which is typical for weights in graph algorithms.\n",
    "\n",
    "**Computing the Minimum Spanning Tree (MST):**\n",
    "1. The Minimum Spanning Tree (MST) of G_filtered is computed using Kruskal's algorithm. Kruskal's algorithm is a greedy algorithm that finds the minimum spanning tree for a connected weighted graph, ensuring that the tree includes every vertex with the minimal possible total edge weight.\n",
    "\n",
    "**Calculating Total Delays:**\n",
    "1. total_delay_full: Calculates the total delay in the full network by summing the weights of all edges in G_filtered.\n",
    "2. total_delay_mst: Calculates the total delay in the MST by summing the weights of all edges in the MST (mst_filtered).\n",
    "\n",
    "**Outputting Total Delays:**\n",
    "1. Prints the total delays for the full network and the MST, providing a comparison to see how much delay is reduced when using the MST instead of the full network.\n",
    "\n",
    "**Plotting the Graph and MST:**\n",
    "Uses nx.spring_layout(G_filtered) to generate positions for all nodes in a visually appealing way.\n",
    "Plots G_filtered using a standard visualization with labels and node colors.\n",
    "Overlays the MST on the same plot with edges colored red to distinguish them from the full network's edges.\n",
    "\n",
    "**Plotting Delay Comparison:**\n",
    "Creates a bar chart comparing the total delays of the full network and the MST. This visual comparison helps to illustrate the effectiveness of the MST in minimizing the total delay across the network."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "550eee12",
   "metadata": {},
   "source": [
    "### Results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e5cacf6",
   "metadata": {},
   "source": [
    "**Significant Reduction in Total Delay:** The total delay in the full network is 562 units, while in the MST it is significantly reduced to only 36 units. This shows a drastic reduction in total delay when the network is optimized to only include the most necessary connections, as represented by the MST.\n",
    "\n",
    "**Efficiency of MST:** The MST effectively minimizes the cumulative weight (in this case, delay) of the edges included in the tree. This optimization demonstrates the strength of using MST in network analysis, particularly in contexts where it's critical to minimize a certain cost (like time or resource expenditure).\n",
    "\n",
    "**Implications for Network Planning:** In practical terms, especially in transportation and logistics (like airline routing), constructing networks according to principles similar to those of MST can lead to significant efficiency gains. By only maintaining essential routes that offer the most direct and least delayed connections, airlines could potentially reduce operational delays and improve overall service quality.\n",
    "\n",
    "**Visualization and Decision Making:** The visual representation provided by the network graph and the bar chart offers clear insights into how network optimization affects performance metrics like delays. This can be extremely useful for decision-makers in planning and optimizing operational networks."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ec9d16d",
   "metadata": {},
   "source": [
    "<hr style=\"border:4px solid #000\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2672b3f-93df-4df2-b0a9-d7d475caa5d9",
   "metadata": {},
   "source": [
    "# 5. Optimization of Flight Schedules to Minimize Delay Penalties (Linear Programming)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c839b6dc-eb9e-41b9-9fc7-eb0358ee9d48",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading the dataset\n",
    "data = pd.read_csv('filtered_flight_data.csv')\n",
    "\n",
    "# Convert FL_DATE to datetime\n",
    "data['FL_DATE'] = pd.to_datetime(data['FL_DATE'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91980086-86eb-4041-a2e7-a45c2e0d855a",
   "metadata": {},
   "source": [
    "#### User Input\n",
    "Here we take the **Origin airport  A as LAX** and **Destinaion Airport B as SFO** for instance. This can be altered if we want to see the optimised schedule for other routes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "906951ce-c648-4157-add2-ba63e638ef10",
   "metadata": {},
   "outputs": [],
   "source": [
    "# User inputs for origin and destination\n",
    "origin_input = 'LAX'\n",
    "destination_input = 'SFO'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4edd85ae-ad91-4092-ba5e-59824df00406",
   "metadata": {},
   "source": [
    "There are delays associated with the flights which are essential in understanding as there is very high costs associated with flight delays for a company. In order to reduce the delays by penalising it, we have created a penalty system according to the delays incurred by a flight.\n",
    "\n",
    "The penalty costs assigned to different types of flight delays quantify the financial impact of inefficiencies. High penalties for carrier and security delays encourage better management and operational efficiency, while moderate penalties for weather and NAS delays recognize partial airline control over these factors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6ce42498-4027-4394-809e-3bdf19b12600",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill missing values and calculate penalties\n",
    "data.fillna({'CARRIER_DELAY': 0, 'WEATHER_DELAY': 0, 'NAS_DELAY': 0, 'SECURITY_DELAY': 0, 'LATE_AIRCRAFT_DELAY': 0}, inplace=True)\n",
    "penalty_costs = {'CARRIER_DELAY': 100, 'WEATHER_DELAY': 75, 'NAS_DELAY': 50, 'SECURITY_DELAY': 200, 'LATE_AIRCRAFT_DELAY': 60}\n",
    "data['TOTAL_PENALTY'] = sum(data[col] * cost for col, cost in penalty_costs.items())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6610413a-cbf8-44d3-913e-b6971dc5bddc",
   "metadata": {},
   "source": [
    "#### Calculating the total penalty before any optimzationa as per current schedule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4d3c9372-9796-4b67-a6f8-fe1bb482e60c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter for the specific route\n",
    "route_data = data[(data['ORIGIN'] == origin_input) & (data['DEST'] == destination_input)]\n",
    "total_penalty_cost_before = route_data['TOTAL_PENALTY'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89cdc5c1-4207-44b9-9352-1a0ab6a7c0ba",
   "metadata": {},
   "source": [
    "Now, we try to optimise the totals schedule of daily flights for a month(August 2018 for instance) to see when airline companies have targets to reduce delay based penalties, what is the best way to created an optimised schedule that will help them achieve their targets.\n",
    "\n",
    "To enhance the efficiency of flight schedules on a specific route for August 2018, we aimed to minimize delay-related penalties by at least 20% while maximizing the number of flights. This strategy helps airlines meet their goals of reducing operational disruptions and costs, maintaining high levels of service. By employing linear programming, we established an optimization model that quantifies and aims to reduce penalties associated with different types of delays, such as those caused by the carrier, weather, or airport systems. Successfully optimizing the schedule not only meets financial and operational objectives but also improves customer satisfaction by ensuring more dependable flights. This refined approach provides airlines with a strategic framework to fine-tune their operations, achieving a more cost-effective and reliable flight schedule.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e1ddc58e-2b49-461e-bd73-541fba2e48fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to the CBC MILP Solver \n",
      "Version: 2.10.3 \n",
      "Build Date: Dec 15 2019 \n",
      "\n",
      "command line - /Users/harsh/anaconda3/lib/python3.11/site-packages/pulp/solverdir/cbc/osx/64/cbc /var/folders/48/3359jr0n34v6fd5jftvl2dn00000gn/T/6dfc537a4b8449aa89da27ee569ec734-pulp.mps -max -timeMode elapsed -branch -printingOptions all -solution /var/folders/48/3359jr0n34v6fd5jftvl2dn00000gn/T/6dfc537a4b8449aa89da27ee569ec734-pulp.sol (default strategy 1)\n",
      "At line 2 NAME          MODEL\n",
      "At line 3 ROWS\n",
      "At line 6 COLUMNS\n",
      "At line 5480 RHS\n",
      "At line 5482 BOUNDS\n",
      "At line 7135 ENDATA\n",
      "Problem MODEL has 1 rows, 1652 columns and 517 elements\n",
      "Coin0008I MODEL read with 0 errors\n",
      "Option for timeMode changed from cpu to elapsed\n",
      "Continuous objective value is 1624.3 - 0.00 seconds\n",
      "Cgl0004I processed model has 1 rows, 258 columns (258 integer (166 of which binary)) and 258 elements\n",
      "Cutoff increment increased from 1e-05 to 0.9999\n",
      "Cbc0038I Initial state - 1 integers unsatisfied sum - 0.298701\n",
      "Cbc0038I Solution found of -1624\n",
      "Cbc0038I Cleaned solution of -1624\n",
      "Cbc0038I Before mini branch and bound, 257 integers at bound fixed and 0 continuous\n",
      "Cbc0038I Mini branch and bound did not improve solution (0.02 seconds)\n",
      "Cbc0038I After 0.02 seconds - Feasibility pump exiting with objective of -1624 - took 0.00 seconds\n",
      "Cbc0012I Integer solution of -1624 found by feasibility pump after 0 iterations and 0 nodes (0.02 seconds)\n",
      "Cbc0001I Search completed - best objective -1624, took 1 iterations and 0 nodes (0.02 seconds)\n",
      "Cbc0035I Maximum depth 0, 165 variables fixed on reduced cost\n",
      "Cuts at root node changed objective from -1624.3 to -1624\n",
      "Probing was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "Gomory was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "Knapsack was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "Clique was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "MixedIntegerRounding2 was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "FlowCover was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "TwoMirCuts was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "ZeroHalf was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
      "\n",
      "Result - Optimal solution found\n",
      "\n",
      "Objective value:                1624.00000000\n",
      "Enumerated nodes:               0\n",
      "Total iterations:               1\n",
      "Time (CPU seconds):             0.00\n",
      "Time (Wallclock seconds):       0.02\n",
      "\n",
      "Option for printingOptions changed from normal to all\n",
      "Total time (CPU seconds):       0.01   (Wallclock seconds):       0.03\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create the LP problem\n",
    "problem = pulp.LpProblem(\"Maximize_Flights_Reduce_Penalties\", pulp.LpMaximize)\n",
    "\n",
    "# Decision Variables\n",
    "flight_vars = {}\n",
    "for date in route_data['FL_DATE'].unique():\n",
    "    daily_flights = route_data[route_data['FL_DATE'] == date]\n",
    "    date_str = pd.Timestamp(date).strftime('%Y-%m-%d')\n",
    "    flight_vars[date] = pulp.LpVariable.dicts(f\"Flight_{date_str}\", daily_flights.index, cat='Binary')\n",
    "\n",
    "# Objective Function\n",
    "problem += pulp.lpSum(flight_vars[date][i] for date in route_data['FL_DATE'].unique() for i in flight_vars[date])\n",
    "\n",
    "# Constraints: Ensure penalty reduction by at least 20%\n",
    "target_penalty = total_penalty_cost_before * 0.8  # 20% reduction\n",
    "problem += pulp.lpSum([flight_vars[date][i] * route_data.at[i, 'TOTAL_PENALTY'] for date in route_data['FL_DATE'].unique() for i in flight_vars[date]]) <= target_penalty\n",
    "\n",
    "# Solve the problem\n",
    "problem.solve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8d64bb4a-c750-4a78-83a4-6a4d35107fc5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solver Status: Optimal\n",
      "--- Flights for 2018-08-01 ---\n",
      "Flight ID 6 included in the schedule with penalty 0.00\n",
      "Flight ID 8 included in the schedule with penalty 0.00\n",
      "Flight ID 12 included in the schedule with penalty 0.00\n",
      "Flight ID 16 included in the schedule with penalty 0.00\n",
      "Flight ID 18 included in the schedule with penalty 0.00\n",
      "Flight ID 25 included in the schedule with penalty 0.00\n",
      "Flight ID 27 included in the schedule with penalty 0.00\n",
      "Flight ID 30 included in the schedule with penalty 0.00\n",
      "Flight ID 39 included in the schedule with penalty 0.00\n",
      "Flight ID 41 included in the schedule with penalty 0.00\n",
      "Flight ID 50 included in the schedule with penalty 0.00\n",
      "Flight ID 51 included in the schedule with penalty 0.00\n",
      "Flight ID 52 included in the schedule with penalty 0.00\n",
      "Flight ID 53 included in the schedule with penalty 0.00\n",
      "Flight ID 58 included in the schedule with penalty 0.00\n",
      "Flight ID 59 included in the schedule with penalty 3500.00\n",
      "Flight ID 62 included in the schedule with penalty 0.00\n",
      "Flight ID 63 included in the schedule with penalty 0.00\n",
      "Flight ID 110 included in the schedule with penalty 0.00\n",
      "Flight ID 129 included in the schedule with penalty 0.00\n",
      "Flight ID 354 included in the schedule with penalty 0.00\n",
      "Flight ID 357 included in the schedule with penalty 0.00\n",
      "Flight ID 358 included in the schedule with penalty 0.00\n",
      "Flight ID 360 included in the schedule with penalty 950.00\n",
      "Flight ID 362 included in the schedule with penalty 0.00\n",
      "Flight ID 364 included in the schedule with penalty 0.00\n",
      "Flight ID 366 included in the schedule with penalty 0.00\n",
      "Flight ID 368 included in the schedule with penalty 0.00\n",
      "Flight ID 370 included in the schedule with penalty 1900.00\n",
      "Flight ID 372 included in the schedule with penalty 0.00\n",
      "Flight ID 374 included in the schedule with penalty 0.00\n",
      "Flight ID 463 included in the schedule with penalty 0.00\n",
      "Flight ID 464 included in the schedule with penalty 0.00\n",
      "Flight ID 465 included in the schedule with penalty 0.00\n",
      "Flight ID 466 included in the schedule with penalty 0.00\n",
      "Flight ID 467 included in the schedule with penalty 3600.00\n",
      "Flight ID 468 included in the schedule with penalty 0.00\n",
      "Flight ID 469 included in the schedule with penalty 0.00\n",
      "Flight ID 470 included in the schedule with penalty 0.00\n",
      "Flight ID 471 included in the schedule with penalty 0.00\n",
      "Flight ID 616 included in the schedule with penalty 0.00\n",
      "Flight ID 627 included in the schedule with penalty 2250.00\n",
      "Flight ID 628 included in the schedule with penalty 0.00\n",
      "Flight ID 635 included in the schedule with penalty 0.00\n",
      "Flight ID 643 included in the schedule with penalty 0.00\n",
      "Flight ID 648 included in the schedule with penalty 0.00\n",
      "Flight ID 656 included in the schedule with penalty 0.00\n",
      "Flight ID 658 included in the schedule with penalty 0.00\n",
      "Flight ID 659 included in the schedule with penalty 0.00\n",
      "Flight ID 660 included in the schedule with penalty 0.00\n",
      "Flight ID 661 included in the schedule with penalty 0.00\n",
      "Flight ID 662 included in the schedule with penalty 0.00\n",
      "Flight ID 664 included in the schedule with penalty 0.00\n",
      "Flight ID 665 included in the schedule with penalty 0.00\n",
      "Flight ID 672 included in the schedule with penalty 2090.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-02 ---\n",
      "Flight ID 924 included in the schedule with penalty 0.00\n",
      "Flight ID 925 included in the schedule with penalty 800.00\n",
      "Flight ID 932 included in the schedule with penalty 0.00\n",
      "Flight ID 940 included in the schedule with penalty 0.00\n",
      "Flight ID 952 included in the schedule with penalty 0.00\n",
      "Flight ID 954 included in the schedule with penalty 0.00\n",
      "Flight ID 955 included in the schedule with penalty 0.00\n",
      "Flight ID 956 included in the schedule with penalty 1760.00\n",
      "Flight ID 957 included in the schedule with penalty 0.00\n",
      "Flight ID 958 included in the schedule with penalty 0.00\n",
      "Flight ID 960 included in the schedule with penalty 0.00\n",
      "Flight ID 961 included in the schedule with penalty 0.00\n",
      "Flight ID 1110 included in the schedule with penalty 0.00\n",
      "Flight ID 1111 included in the schedule with penalty 0.00\n",
      "Flight ID 1112 included in the schedule with penalty 0.00\n",
      "Flight ID 1113 included in the schedule with penalty 950.00\n",
      "Flight ID 1114 included in the schedule with penalty 5660.00\n",
      "Flight ID 1115 included in the schedule with penalty 1550.00\n",
      "Flight ID 1116 included in the schedule with penalty 0.00\n",
      "Flight ID 1117 included in the schedule with penalty 0.00\n",
      "Flight ID 1118 included in the schedule with penalty 0.00\n",
      "Flight ID 1145 included in the schedule with penalty 6250.00\n",
      "Flight ID 1148 included in the schedule with penalty 0.00\n",
      "Flight ID 1149 included in the schedule with penalty 750.00\n",
      "Flight ID 1151 included in the schedule with penalty 0.00\n",
      "Flight ID 1153 included in the schedule with penalty 0.00\n",
      "Flight ID 1155 included in the schedule with penalty 0.00\n",
      "Flight ID 1157 included in the schedule with penalty 0.00\n",
      "Flight ID 1160 included in the schedule with penalty 3150.00\n",
      "Flight ID 1162 included in the schedule with penalty 0.00\n",
      "Flight ID 1166 included in the schedule with penalty 0.00\n",
      "Flight ID 1231 included in the schedule with penalty 0.00\n",
      "Flight ID 1250 included in the schedule with penalty 0.00\n",
      "Flight ID 1280 included in the schedule with penalty 0.00\n",
      "Flight ID 1296 included in the schedule with penalty 0.00\n",
      "Flight ID 1298 included in the schedule with penalty 0.00\n",
      "Flight ID 1302 included in the schedule with penalty 0.00\n",
      "Flight ID 1306 included in the schedule with penalty 0.00\n",
      "Flight ID 1308 included in the schedule with penalty 0.00\n",
      "Flight ID 1315 included in the schedule with penalty 0.00\n",
      "Flight ID 1317 included in the schedule with penalty 0.00\n",
      "Flight ID 1320 included in the schedule with penalty 0.00\n",
      "Flight ID 1329 included in the schedule with penalty 0.00\n",
      "Flight ID 1331 included in the schedule with penalty 0.00\n",
      "Flight ID 1340 included in the schedule with penalty 0.00\n",
      "Flight ID 1341 included in the schedule with penalty 0.00\n",
      "Flight ID 1342 included in the schedule with penalty 0.00\n",
      "Flight ID 1343 included in the schedule with penalty 0.00\n",
      "Flight ID 1348 included in the schedule with penalty 0.00\n",
      "Flight ID 1349 included in the schedule with penalty 0.00\n",
      "Flight ID 1352 included in the schedule with penalty 0.00\n",
      "Flight ID 1353 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-03 ---\n",
      "Flight ID 1362 included in the schedule with penalty 0.00\n",
      "Flight ID 1364 included in the schedule with penalty 0.00\n",
      "Flight ID 1368 included in the schedule with penalty 0.00\n",
      "Flight ID 1372 included in the schedule with penalty 0.00\n",
      "Flight ID 1374 included in the schedule with penalty 0.00\n",
      "Flight ID 1381 included in the schedule with penalty 0.00\n",
      "Flight ID 1383 included in the schedule with penalty 0.00\n",
      "Flight ID 1386 included in the schedule with penalty 0.00\n",
      "Flight ID 1395 included in the schedule with penalty 4700.00\n",
      "Flight ID 1397 included in the schedule with penalty 0.00\n",
      "Flight ID 1404 included in the schedule with penalty 0.00\n",
      "Flight ID 1405 included in the schedule with penalty 0.00\n",
      "Flight ID 1428 included in the schedule with penalty 0.00\n",
      "Flight ID 1451 included in the schedule with penalty 0.00\n",
      "Flight ID 1452 included in the schedule with penalty 2250.00\n",
      "Flight ID 1453 included in the schedule with penalty 0.00\n",
      "Flight ID 1454 included in the schedule with penalty 0.00\n",
      "Flight ID 1459 included in the schedule with penalty 1500.00\n",
      "Flight ID 1460 included in the schedule with penalty 1100.00\n",
      "Flight ID 1547 included in the schedule with penalty 0.00\n",
      "Flight ID 1570 included in the schedule with penalty 0.00\n",
      "Flight ID 1581 included in the schedule with penalty 0.00\n",
      "Flight ID 1582 included in the schedule with penalty 1640.00\n",
      "Flight ID 1589 included in the schedule with penalty 0.00\n",
      "Flight ID 1597 included in the schedule with penalty 2150.00\n",
      "Flight ID 1609 included in the schedule with penalty 0.00\n",
      "Flight ID 1611 included in the schedule with penalty 0.00\n",
      "Flight ID 1612 included in the schedule with penalty 0.00\n",
      "Flight ID 1613 included in the schedule with penalty 0.00\n",
      "Flight ID 1614 included in the schedule with penalty 0.00\n",
      "Flight ID 1615 included in the schedule with penalty 2780.00\n",
      "Flight ID 1617 included in the schedule with penalty 0.00\n",
      "Flight ID 1618 included in the schedule with penalty 0.00\n",
      "Flight ID 1625 included in the schedule with penalty 0.00\n",
      "Flight ID 1697 included in the schedule with penalty 0.00\n",
      "Flight ID 1698 included in the schedule with penalty 7100.00\n",
      "Flight ID 1699 included in the schedule with penalty 4920.00\n",
      "Flight ID 1700 included in the schedule with penalty 7380.00\n",
      "Flight ID 1701 included in the schedule with penalty 6600.00\n",
      "Flight ID 1702 included in the schedule with penalty 0.00\n",
      "Flight ID 1703 included in the schedule with penalty 2610.00\n",
      "Flight ID 1705 included in the schedule with penalty 8640.00\n",
      "Flight ID 1991 included in the schedule with penalty 0.00\n",
      "Flight ID 1993 included in the schedule with penalty 0.00\n",
      "Flight ID 1994 included in the schedule with penalty 0.00\n",
      "Flight ID 1996 included in the schedule with penalty 5400.00\n",
      "Flight ID 1998 included in the schedule with penalty 1700.00\n",
      "Flight ID 2000 included in the schedule with penalty 1700.00\n",
      "Flight ID 2002 included in the schedule with penalty 2050.00\n",
      "Flight ID 2003 included in the schedule with penalty 0.00\n",
      "Flight ID 2006 included in the schedule with penalty 3220.00\n",
      "Flight ID 2009 included in the schedule with penalty 3050.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-04 ---\n",
      "Flight ID 2037 included in the schedule with penalty 2400.00\n",
      "Flight ID 2038 included in the schedule with penalty 0.00\n",
      "Flight ID 2044 included in the schedule with penalty 0.00\n",
      "Flight ID 2046 included in the schedule with penalty 0.00\n",
      "Flight ID 2054 included in the schedule with penalty 0.00\n",
      "Flight ID 2061 included in the schedule with penalty 0.00\n",
      "Flight ID 2070 included in the schedule with penalty 0.00\n",
      "Flight ID 2071 included in the schedule with penalty 0.00\n",
      "Flight ID 2073 included in the schedule with penalty 0.00\n",
      "Flight ID 2078 included in the schedule with penalty 0.00\n",
      "Flight ID 2087 included in the schedule with penalty 0.00\n",
      "Flight ID 2100 included in the schedule with penalty 0.00\n",
      "Flight ID 2138 included in the schedule with penalty 0.00\n",
      "Flight ID 2144 included in the schedule with penalty 0.00\n",
      "Flight ID 2157 included in the schedule with penalty 0.00\n",
      "Flight ID 2158 included in the schedule with penalty 0.00\n",
      "Flight ID 2159 included in the schedule with penalty 0.00\n",
      "Flight ID 2161 included in the schedule with penalty 0.00\n",
      "Flight ID 2162 included in the schedule with penalty 0.00\n",
      "Flight ID 2221 included in the schedule with penalty 0.00\n",
      "Flight ID 2222 included in the schedule with penalty 0.00\n",
      "Flight ID 2223 included in the schedule with penalty 0.00\n",
      "Flight ID 2224 included in the schedule with penalty 0.00\n",
      "Flight ID 2225 included in the schedule with penalty 3700.00\n",
      "Flight ID 2415 included in the schedule with penalty 0.00\n",
      "Flight ID 2418 included in the schedule with penalty 0.00\n",
      "Flight ID 2419 included in the schedule with penalty 0.00\n",
      "Flight ID 2421 included in the schedule with penalty 0.00\n",
      "Flight ID 2423 included in the schedule with penalty 0.00\n",
      "Flight ID 2426 included in the schedule with penalty 0.00\n",
      "Flight ID 2427 included in the schedule with penalty 4000.00\n",
      "Flight ID 2429 included in the schedule with penalty 0.00\n",
      "Flight ID 2431 included in the schedule with penalty 800.00\n",
      "Flight ID 2432 included in the schedule with penalty 0.00\n",
      "Flight ID 2434 included in the schedule with penalty 2000.00\n",
      "Flight ID 2497 included in the schedule with penalty 0.00\n",
      "Flight ID 2499 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-05 ---\n",
      "Flight ID 2616 included in the schedule with penalty 0.00\n",
      "Flight ID 2617 included in the schedule with penalty 0.00\n",
      "Flight ID 2618 included in the schedule with penalty 0.00\n",
      "Flight ID 2619 included in the schedule with penalty 0.00\n",
      "Flight ID 2624 included in the schedule with penalty 0.00\n",
      "Flight ID 2625 included in the schedule with penalty 0.00\n",
      "Flight ID 2628 included in the schedule with penalty 0.00\n",
      "Flight ID 2629 included in the schedule with penalty 0.00\n",
      "Flight ID 2726 included in the schedule with penalty 0.00\n",
      "Flight ID 2727 included in the schedule with penalty 0.00\n",
      "Flight ID 2728 included in the schedule with penalty 0.00\n",
      "Flight ID 2729 included in the schedule with penalty 0.00\n",
      "Flight ID 2730 included in the schedule with penalty 0.00\n",
      "Flight ID 2731 included in the schedule with penalty 6100.00\n",
      "Flight ID 2732 included in the schedule with penalty 3840.00\n",
      "Flight ID 2733 included in the schedule with penalty 3020.00\n",
      "Flight ID 2734 included in the schedule with penalty 1540.00\n",
      "Flight ID 2925 included in the schedule with penalty 0.00\n",
      "Flight ID 2928 included in the schedule with penalty 0.00\n",
      "Flight ID 2929 included in the schedule with penalty 1700.00\n",
      "Flight ID 2931 included in the schedule with penalty 0.00\n",
      "Flight ID 2933 included in the schedule with penalty 0.00\n",
      "Flight ID 2935 included in the schedule with penalty 0.00\n",
      "Flight ID 2936 included in the schedule with penalty 0.00\n",
      "Flight ID 2938 included in the schedule with penalty 0.00\n",
      "Flight ID 2940 included in the schedule with penalty 0.00\n",
      "Flight ID 2942 included in the schedule with penalty 0.00\n",
      "Flight ID 2944 included in the schedule with penalty 0.00\n",
      "Flight ID 3007 included in the schedule with penalty 0.00\n",
      "Flight ID 3024 included in the schedule with penalty 4400.00\n",
      "Flight ID 3062 included in the schedule with penalty 5600.00\n",
      "Flight ID 3069 included in the schedule with penalty 0.00\n",
      "Flight ID 3077 included in the schedule with penalty 0.00\n",
      "Flight ID 3085 included in the schedule with penalty 0.00\n",
      "Flight ID 3087 included in the schedule with penalty 0.00\n",
      "Flight ID 3088 included in the schedule with penalty 0.00\n",
      "Flight ID 3089 included in the schedule with penalty 1130.00\n",
      "Flight ID 3091 included in the schedule with penalty 3700.00\n",
      "Flight ID 3092 included in the schedule with penalty 0.00\n",
      "Flight ID 3112 included in the schedule with penalty 0.00\n",
      "Flight ID 3114 included in the schedule with penalty 0.00\n",
      "Flight ID 3118 included in the schedule with penalty 0.00\n",
      "Flight ID 3122 included in the schedule with penalty 0.00\n",
      "Flight ID 3124 included in the schedule with penalty 0.00\n",
      "Flight ID 3131 included in the schedule with penalty 0.00\n",
      "Flight ID 3133 included in the schedule with penalty 0.00\n",
      "Flight ID 3136 included in the schedule with penalty 0.00\n",
      "Flight ID 3147 included in the schedule with penalty 0.00\n",
      "Flight ID 3149 included in the schedule with penalty 0.00\n",
      "Flight ID 3151 included in the schedule with penalty 0.00\n",
      "Flight ID 3154 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-06 ---\n",
      "Flight ID 3164 included in the schedule with penalty 0.00\n",
      "Flight ID 3166 included in the schedule with penalty 0.00\n",
      "Flight ID 3170 included in the schedule with penalty 0.00\n",
      "Flight ID 3174 included in the schedule with penalty 0.00\n",
      "Flight ID 3176 included in the schedule with penalty 0.00\n",
      "Flight ID 3183 included in the schedule with penalty 0.00\n",
      "Flight ID 3185 included in the schedule with penalty 0.00\n",
      "Flight ID 3188 included in the schedule with penalty 0.00\n",
      "Flight ID 3199 included in the schedule with penalty 0.00\n",
      "Flight ID 3201 included in the schedule with penalty 0.00\n",
      "Flight ID 3203 included in the schedule with penalty 0.00\n",
      "Flight ID 3206 included in the schedule with penalty 0.00\n",
      "Flight ID 3211 included in the schedule with penalty 0.00\n",
      "Flight ID 3212 included in the schedule with penalty 0.00\n",
      "Flight ID 3215 included in the schedule with penalty 0.00\n",
      "Flight ID 3216 included in the schedule with penalty 0.00\n",
      "Flight ID 3239 included in the schedule with penalty 0.00\n",
      "Flight ID 3240 included in the schedule with penalty 0.00\n",
      "Flight ID 3241 included in the schedule with penalty 0.00\n",
      "Flight ID 3242 included in the schedule with penalty 0.00\n",
      "Flight ID 3290 included in the schedule with penalty 0.00\n",
      "Flight ID 3302 included in the schedule with penalty 0.00\n",
      "Flight ID 3303 included in the schedule with penalty 0.00\n",
      "Flight ID 3310 included in the schedule with penalty 0.00\n",
      "Flight ID 3318 included in the schedule with penalty 0.00\n",
      "Flight ID 3330 included in the schedule with penalty 0.00\n",
      "Flight ID 3332 included in the schedule with penalty 0.00\n",
      "Flight ID 3333 included in the schedule with penalty 0.00\n",
      "Flight ID 3334 included in the schedule with penalty 0.00\n",
      "Flight ID 3335 included in the schedule with penalty 0.00\n",
      "Flight ID 3336 included in the schedule with penalty 0.00\n",
      "Flight ID 3338 included in the schedule with penalty 0.00\n",
      "Flight ID 3339 included in the schedule with penalty 0.00\n",
      "Flight ID 3345 included in the schedule with penalty 0.00\n",
      "Flight ID 3399 included in the schedule with penalty 0.00\n",
      "Flight ID 3418 included in the schedule with penalty 0.00\n",
      "Flight ID 3506 included in the schedule with penalty 0.00\n",
      "Flight ID 3507 included in the schedule with penalty 0.00\n",
      "Flight ID 3508 included in the schedule with penalty 0.00\n",
      "Flight ID 3509 included in the schedule with penalty 0.00\n",
      "Flight ID 3510 included in the schedule with penalty 0.00\n",
      "Flight ID 3511 included in the schedule with penalty 0.00\n",
      "Flight ID 3512 included in the schedule with penalty 0.00\n",
      "Flight ID 3513 included in the schedule with penalty 0.00\n",
      "Flight ID 3514 included in the schedule with penalty 0.00\n",
      "Flight ID 3798 included in the schedule with penalty 0.00\n",
      "Flight ID 3800 included in the schedule with penalty 0.00\n",
      "Flight ID 3801 included in the schedule with penalty 0.00\n",
      "Flight ID 3803 included in the schedule with penalty 0.00\n",
      "Flight ID 3805 included in the schedule with penalty 0.00\n",
      "Flight ID 3807 included in the schedule with penalty 0.00\n",
      "Flight ID 3809 included in the schedule with penalty 0.00\n",
      "Flight ID 3810 included in the schedule with penalty 0.00\n",
      "Flight ID 3813 included in the schedule with penalty 900.00\n",
      "Flight ID 3816 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-07 ---\n",
      "Flight ID 3846 included in the schedule with penalty 0.00\n",
      "Flight ID 3848 included in the schedule with penalty 0.00\n",
      "Flight ID 3852 included in the schedule with penalty 2050.00\n",
      "Flight ID 3856 included in the schedule with penalty 1000.00\n",
      "Flight ID 3858 included in the schedule with penalty 0.00\n",
      "Flight ID 3865 included in the schedule with penalty 3190.00\n",
      "Flight ID 3867 included in the schedule with penalty 0.00\n",
      "Flight ID 3870 included in the schedule with penalty 4020.00\n",
      "Flight ID 3881 included in the schedule with penalty 4360.00\n",
      "Flight ID 3883 included in the schedule with penalty 4550.00\n",
      "Flight ID 3885 included in the schedule with penalty 0.00\n",
      "Flight ID 3888 included in the schedule with penalty 0.00\n",
      "Flight ID 3936 included in the schedule with penalty 0.00\n",
      "Flight ID 3972 included in the schedule with penalty 0.00\n",
      "Flight ID 3973 included in the schedule with penalty 0.00\n",
      "Flight ID 3974 included in the schedule with penalty 950.00\n",
      "Flight ID 3975 included in the schedule with penalty 3020.00\n",
      "Flight ID 3976 included in the schedule with penalty 0.00\n",
      "Flight ID 3977 included in the schedule with penalty 0.00\n",
      "Flight ID 3978 included in the schedule with penalty 0.00\n",
      "Flight ID 3979 included in the schedule with penalty 0.00\n",
      "Flight ID 3980 included in the schedule with penalty 2260.00\n",
      "Flight ID 3981 included in the schedule with penalty 0.00\n",
      "Flight ID 4308 included in the schedule with penalty 0.00\n",
      "Flight ID 4310 included in the schedule with penalty 0.00\n",
      "Flight ID 4311 included in the schedule with penalty 0.00\n",
      "Flight ID 4313 included in the schedule with penalty 0.00\n",
      "Flight ID 4315 included in the schedule with penalty 2400.00\n",
      "Flight ID 4317 included in the schedule with penalty 0.00\n",
      "Flight ID 4319 included in the schedule with penalty 0.00\n",
      "Flight ID 4320 included in the schedule with penalty 0.00\n",
      "Flight ID 4323 included in the schedule with penalty 4000.00\n",
      "Flight ID 4327 included in the schedule with penalty 0.00\n",
      "Flight ID 4378 included in the schedule with penalty 4950.00\n",
      "Flight ID 4404 included in the schedule with penalty 0.00\n",
      "Flight ID 4405 included in the schedule with penalty 0.00\n",
      "Flight ID 4406 included in the schedule with penalty 0.00\n",
      "Flight ID 4407 included in the schedule with penalty 0.00\n",
      "Flight ID 4412 included in the schedule with penalty 2850.00\n",
      "Flight ID 4413 included in the schedule with penalty 2400.00\n",
      "Flight ID 4416 included in the schedule with penalty 1450.00\n",
      "Flight ID 4417 included in the schedule with penalty 0.00\n",
      "Flight ID 4464 included in the schedule with penalty 1250.00\n",
      "Flight ID 4475 included in the schedule with penalty 0.00\n",
      "Flight ID 4476 included in the schedule with penalty 4650.00\n",
      "Flight ID 4483 included in the schedule with penalty 0.00\n",
      "Flight ID 4491 included in the schedule with penalty 0.00\n",
      "Flight ID 4503 included in the schedule with penalty 0.00\n",
      "Flight ID 4505 included in the schedule with penalty 0.00\n",
      "Flight ID 4506 included in the schedule with penalty 0.00\n",
      "Flight ID 4507 included in the schedule with penalty 0.00\n",
      "Flight ID 4508 included in the schedule with penalty 4500.00\n",
      "Flight ID 4509 included in the schedule with penalty 0.00\n",
      "Flight ID 4511 included in the schedule with penalty 1000.00\n",
      "Flight ID 4512 included in the schedule with penalty 0.00\n",
      "Flight ID 4519 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-08 ---\n",
      "Flight ID 4587 included in the schedule with penalty 4280.00\n",
      "Flight ID 4606 included in the schedule with penalty 5350.00\n",
      "Flight ID 4632 included in the schedule with penalty 0.00\n",
      "Flight ID 4633 included in the schedule with penalty 0.00\n",
      "Flight ID 4634 included in the schedule with penalty 0.00\n",
      "Flight ID 4640 included in the schedule with penalty 6970.00\n",
      "Flight ID 4641 included in the schedule with penalty 0.00\n",
      "Flight ID 4644 included in the schedule with penalty 2790.00\n",
      "Flight ID 4645 included in the schedule with penalty 0.00\n",
      "Flight ID 4692 included in the schedule with penalty 3250.00\n",
      "Flight ID 4703 included in the schedule with penalty 750.00\n",
      "Flight ID 4704 included in the schedule with penalty 2850.00\n",
      "Flight ID 4711 included in the schedule with penalty 1850.00\n",
      "Flight ID 4719 included in the schedule with penalty 2250.00\n",
      "Flight ID 4730 included in the schedule with penalty 2700.00\n",
      "Flight ID 4732 included in the schedule with penalty 1240.00\n",
      "Flight ID 4733 included in the schedule with penalty 0.00\n",
      "Flight ID 4734 included in the schedule with penalty 2400.00\n",
      "Flight ID 4735 included in the schedule with penalty 2800.00\n",
      "Flight ID 4736 included in the schedule with penalty 0.00\n",
      "Flight ID 4738 included in the schedule with penalty 5850.00\n",
      "Flight ID 4739 included in the schedule with penalty 0.00\n",
      "Flight ID 4817 included in the schedule with penalty 1450.00\n",
      "Flight ID 4818 included in the schedule with penalty 0.00\n",
      "Flight ID 4819 included in the schedule with penalty 1030.00\n",
      "Flight ID 4821 included in the schedule with penalty 7550.00\n",
      "Flight ID 4822 included in the schedule with penalty 0.00\n",
      "Flight ID 4823 included in the schedule with penalty 0.00\n",
      "Flight ID 4825 included in the schedule with penalty 0.00\n",
      "Flight ID 4826 included in the schedule with penalty 8100.00\n",
      "Flight ID 5115 included in the schedule with penalty 1200.00\n",
      "Flight ID 5118 included in the schedule with penalty 0.00\n",
      "Flight ID 5119 included in the schedule with penalty 0.00\n",
      "Flight ID 5121 included in the schedule with penalty 0.00\n",
      "Flight ID 5123 included in the schedule with penalty 3350.00\n",
      "Flight ID 5125 included in the schedule with penalty 2650.00\n",
      "Flight ID 5127 included in the schedule with penalty 0.00\n",
      "Flight ID 5128 included in the schedule with penalty 0.00\n",
      "Flight ID 5129 included in the schedule with penalty 0.00\n",
      "Flight ID 5133 included in the schedule with penalty 1080.00\n",
      "Flight ID 5168 included in the schedule with penalty 0.00\n",
      "Flight ID 5170 included in the schedule with penalty 0.00\n",
      "Flight ID 5174 included in the schedule with penalty 0.00\n",
      "Flight ID 5178 included in the schedule with penalty 5250.00\n",
      "Flight ID 5180 included in the schedule with penalty 0.00\n",
      "Flight ID 5187 included in the schedule with penalty 4500.00\n",
      "Flight ID 5189 included in the schedule with penalty 0.00\n",
      "Flight ID 5192 included in the schedule with penalty 1500.00\n",
      "Flight ID 5203 included in the schedule with penalty 0.00\n",
      "Flight ID 5205 included in the schedule with penalty 0.00\n",
      "Flight ID 5207 included in the schedule with penalty 0.00\n",
      "Flight ID 5210 included in the schedule with penalty 1500.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-09 ---\n",
      "Flight ID 5220 included in the schedule with penalty 0.00\n",
      "Flight ID 5222 included in the schedule with penalty 0.00\n",
      "Flight ID 5226 included in the schedule with penalty 0.00\n",
      "Flight ID 5230 included in the schedule with penalty 2850.00\n",
      "Flight ID 5232 included in the schedule with penalty 0.00\n",
      "Flight ID 5239 included in the schedule with penalty 0.00\n",
      "Flight ID 5241 included in the schedule with penalty 0.00\n",
      "Flight ID 5244 included in the schedule with penalty 0.00\n",
      "Flight ID 5255 included in the schedule with penalty 0.00\n",
      "Flight ID 5257 included in the schedule with penalty 1300.00\n",
      "Flight ID 5259 included in the schedule with penalty 0.00\n",
      "Flight ID 5262 included in the schedule with penalty 950.00\n",
      "Flight ID 5266 included in the schedule with penalty 0.00\n",
      "Flight ID 5267 included in the schedule with penalty 0.00\n",
      "Flight ID 5268 included in the schedule with penalty 1250.00\n",
      "Flight ID 5269 included in the schedule with penalty 0.00\n",
      "Flight ID 5274 included in the schedule with penalty 5260.00\n",
      "Flight ID 5275 included in the schedule with penalty 0.00\n",
      "Flight ID 5278 included in the schedule with penalty 0.00\n",
      "Flight ID 5279 included in the schedule with penalty 0.00\n",
      "Flight ID 5344 included in the schedule with penalty 0.00\n",
      "Flight ID 5363 included in the schedule with penalty 0.00\n",
      "Flight ID 5432 included in the schedule with penalty 4500.00\n",
      "Flight ID 5434 included in the schedule with penalty 0.00\n",
      "Flight ID 5435 included in the schedule with penalty 0.00\n",
      "Flight ID 5436 included in the schedule with penalty 0.00\n",
      "Flight ID 5437 included in the schedule with penalty 2500.00\n",
      "Flight ID 5438 included in the schedule with penalty 0.00\n",
      "Flight ID 5440 included in the schedule with penalty 0.00\n",
      "Flight ID 5441 included in the schedule with penalty 0.00\n",
      "Flight ID 5448 included in the schedule with penalty 0.00\n",
      "Flight ID 5464 included in the schedule with penalty 0.00\n",
      "Flight ID 5475 included in the schedule with penalty 2750.00\n",
      "Flight ID 5476 included in the schedule with penalty 4300.00\n",
      "Flight ID 5483 included in the schedule with penalty 0.00\n",
      "Flight ID 5491 included in the schedule with penalty 1250.00\n",
      "Flight ID 5564 included in the schedule with penalty 0.00\n",
      "Flight ID 5565 included in the schedule with penalty 0.00\n",
      "Flight ID 5566 included in the schedule with penalty 1670.00\n",
      "Flight ID 5567 included in the schedule with penalty 1590.00\n",
      "Flight ID 5568 included in the schedule with penalty 0.00\n",
      "Flight ID 5569 included in the schedule with penalty 0.00\n",
      "Flight ID 5570 included in the schedule with penalty 3610.00\n",
      "Flight ID 5571 included in the schedule with penalty 4080.00\n",
      "Flight ID 5572 included in the schedule with penalty 0.00\n",
      "Flight ID 5573 included in the schedule with penalty 1350.00\n",
      "Flight ID 5866 included in the schedule with penalty 0.00\n",
      "Flight ID 5869 included in the schedule with penalty 0.00\n",
      "Flight ID 5870 included in the schedule with penalty 0.00\n",
      "Flight ID 5872 included in the schedule with penalty 0.00\n",
      "Flight ID 5874 included in the schedule with penalty 1900.00\n",
      "Flight ID 5876 included in the schedule with penalty 0.00\n",
      "Flight ID 5878 included in the schedule with penalty 0.00\n",
      "Flight ID 5879 included in the schedule with penalty 0.00\n",
      "Flight ID 5881 included in the schedule with penalty 0.00\n",
      "Flight ID 5883 included in the schedule with penalty 0.00\n",
      "Flight ID 5885 included in the schedule with penalty 750.00\n",
      "Flight ID 5887 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-10 ---\n",
      "Flight ID 5917 included in the schedule with penalty 0.00\n",
      "Flight ID 5919 included in the schedule with penalty 0.00\n",
      "Flight ID 5923 included in the schedule with penalty 0.00\n",
      "Flight ID 5927 included in the schedule with penalty 0.00\n",
      "Flight ID 5929 included in the schedule with penalty 0.00\n",
      "Flight ID 5936 included in the schedule with penalty 0.00\n",
      "Flight ID 5938 included in the schedule with penalty 0.00\n",
      "Flight ID 5941 included in the schedule with penalty 0.00\n",
      "Flight ID 5952 included in the schedule with penalty 0.00\n",
      "Flight ID 5954 included in the schedule with penalty 0.00\n",
      "Flight ID 5956 included in the schedule with penalty 0.00\n",
      "Flight ID 5959 included in the schedule with penalty 1050.00\n",
      "Flight ID 5967 included in the schedule with penalty 0.00\n",
      "Flight ID 5968 included in the schedule with penalty 0.00\n",
      "Flight ID 5969 included in the schedule with penalty 0.00\n",
      "Flight ID 5970 included in the schedule with penalty 0.00\n",
      "Flight ID 5975 included in the schedule with penalty 0.00\n",
      "Flight ID 5976 included in the schedule with penalty 0.00\n",
      "Flight ID 5979 included in the schedule with penalty 0.00\n",
      "Flight ID 5980 included in the schedule with penalty 0.00\n",
      "Flight ID 5993 included in the schedule with penalty 0.00\n",
      "Flight ID 6012 included in the schedule with penalty 0.00\n",
      "Flight ID 6041 included in the schedule with penalty 0.00\n",
      "Flight ID 6052 included in the schedule with penalty 1600.00\n",
      "Flight ID 6053 included in the schedule with penalty 750.00\n",
      "Flight ID 6060 included in the schedule with penalty 0.00\n",
      "Flight ID 6068 included in the schedule with penalty 0.00\n",
      "Flight ID 6080 included in the schedule with penalty 0.00\n",
      "Flight ID 6082 included in the schedule with penalty 0.00\n",
      "Flight ID 6083 included in the schedule with penalty 0.00\n",
      "Flight ID 6084 included in the schedule with penalty 4360.00\n",
      "Flight ID 6085 included in the schedule with penalty 0.00\n",
      "Flight ID 6086 included in the schedule with penalty 0.00\n",
      "Flight ID 6088 included in the schedule with penalty 0.00\n",
      "Flight ID 6089 included in the schedule with penalty 3400.00\n",
      "Flight ID 6096 included in the schedule with penalty 0.00\n",
      "Flight ID 6170 included in the schedule with penalty 0.00\n",
      "Flight ID 6171 included in the schedule with penalty 0.00\n",
      "Flight ID 6172 included in the schedule with penalty 0.00\n",
      "Flight ID 6173 included in the schedule with penalty 0.00\n",
      "Flight ID 6174 included in the schedule with penalty 0.00\n",
      "Flight ID 6175 included in the schedule with penalty 0.00\n",
      "Flight ID 6176 included in the schedule with penalty 0.00\n",
      "Flight ID 6177 included in the schedule with penalty 0.00\n",
      "Flight ID 6178 included in the schedule with penalty 0.00\n",
      "Flight ID 6179 included in the schedule with penalty 0.00\n",
      "Flight ID 6206 included in the schedule with penalty 0.00\n",
      "Flight ID 6538 included in the schedule with penalty 0.00\n",
      "Flight ID 6539 included in the schedule with penalty 0.00\n",
      "Flight ID 6541 included in the schedule with penalty 0.00\n",
      "Flight ID 6543 included in the schedule with penalty 0.00\n",
      "Flight ID 6545 included in the schedule with penalty 0.00\n",
      "Flight ID 6547 included in the schedule with penalty 1550.00\n",
      "Flight ID 6548 included in the schedule with penalty 0.00\n",
      "Flight ID 6551 included in the schedule with penalty 1900.00\n",
      "Flight ID 6553 included in the schedule with penalty 0.00\n",
      "Flight ID 6555 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-11 ---\n",
      "Flight ID 6644 included in the schedule with penalty 0.00\n",
      "Flight ID 6645 included in the schedule with penalty 0.00\n",
      "Flight ID 6646 included in the schedule with penalty 0.00\n",
      "Flight ID 6647 included in the schedule with penalty 0.00\n",
      "Flight ID 6648 included in the schedule with penalty 0.00\n",
      "Flight ID 6649 included in the schedule with penalty 0.00\n",
      "Flight ID 6832 included in the schedule with penalty 0.00\n",
      "Flight ID 6835 included in the schedule with penalty 0.00\n",
      "Flight ID 6836 included in the schedule with penalty 0.00\n",
      "Flight ID 6838 included in the schedule with penalty 0.00\n",
      "Flight ID 6840 included in the schedule with penalty 6240.00\n",
      "Flight ID 6843 included in the schedule with penalty 0.00\n",
      "Flight ID 6844 included in the schedule with penalty 0.00\n",
      "Flight ID 6845 included in the schedule with penalty 0.00\n",
      "Flight ID 6847 included in the schedule with penalty 4270.00\n",
      "Flight ID 6848 included in the schedule with penalty 7600.00\n",
      "Flight ID 6850 included in the schedule with penalty 3000.00\n",
      "Flight ID 6947 included in the schedule with penalty 2890.00\n",
      "Flight ID 6960 included in the schedule with penalty 0.00\n",
      "Flight ID 6998 included in the schedule with penalty 0.00\n",
      "Flight ID 7004 included in the schedule with penalty 0.00\n",
      "Flight ID 7017 included in the schedule with penalty 0.00\n",
      "Flight ID 7018 included in the schedule with penalty 0.00\n",
      "Flight ID 7019 included in the schedule with penalty 0.00\n",
      "Flight ID 7021 included in the schedule with penalty 0.00\n",
      "Flight ID 7022 included in the schedule with penalty 0.00\n",
      "Flight ID 7030 included in the schedule with penalty 6450.00\n",
      "Flight ID 7045 included in the schedule with penalty 0.00\n",
      "Flight ID 7046 included in the schedule with penalty 0.00\n",
      "Flight ID 7052 included in the schedule with penalty 0.00\n",
      "Flight ID 7054 included in the schedule with penalty 0.00\n",
      "Flight ID 7062 included in the schedule with penalty 0.00\n",
      "Flight ID 7071 included in the schedule with penalty 0.00\n",
      "Flight ID 7073 included in the schedule with penalty 0.00\n",
      "Flight ID 7082 included in the schedule with penalty 0.00\n",
      "Flight ID 7083 included in the schedule with penalty 0.00\n",
      "Flight ID 7085 included in the schedule with penalty 0.00\n",
      "Flight ID 7090 included in the schedule with penalty 0.00\n",
      "Flight ID 7095 included in the schedule with penalty 0.00\n",
      "Flight ID 7097 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-12 ---\n",
      "Flight ID 7105 included in the schedule with penalty 3750.00\n",
      "Flight ID 7107 included in the schedule with penalty 0.00\n",
      "Flight ID 7111 included in the schedule with penalty 0.00\n",
      "Flight ID 7115 included in the schedule with penalty 0.00\n",
      "Flight ID 7117 included in the schedule with penalty 0.00\n",
      "Flight ID 7124 included in the schedule with penalty 0.00\n",
      "Flight ID 7126 included in the schedule with penalty 8700.00\n",
      "Flight ID 7129 included in the schedule with penalty 1560.00\n",
      "Flight ID 7140 included in the schedule with penalty 0.00\n",
      "Flight ID 7142 included in the schedule with penalty 7700.00\n",
      "Flight ID 7144 included in the schedule with penalty 1900.00\n",
      "Flight ID 7147 included in the schedule with penalty 0.00\n",
      "Flight ID 7205 included in the schedule with penalty 0.00\n",
      "Flight ID 7207 included in the schedule with penalty 0.00\n",
      "Flight ID 7208 included in the schedule with penalty 2000.00\n",
      "Flight ID 7210 included in the schedule with penalty 0.00\n",
      "Flight ID 7213 included in the schedule with penalty 0.00\n",
      "Flight ID 7214 included in the schedule with penalty 0.00\n",
      "Flight ID 7217 included in the schedule with penalty 5150.00\n",
      "Flight ID 7218 included in the schedule with penalty 2200.00\n",
      "Flight ID 7220 included in the schedule with penalty 0.00\n",
      "Flight ID 7239 included in the schedule with penalty 1450.00\n",
      "Flight ID 7240 included in the schedule with penalty 0.00\n",
      "Flight ID 7241 included in the schedule with penalty 0.00\n",
      "Flight ID 7242 included in the schedule with penalty 0.00\n",
      "Flight ID 7247 included in the schedule with penalty 0.00\n",
      "Flight ID 7248 included in the schedule with penalty 0.00\n",
      "Flight ID 7251 included in the schedule with penalty 0.00\n",
      "Flight ID 7252 included in the schedule with penalty 0.00\n",
      "Flight ID 7307 included in the schedule with penalty 0.00\n",
      "Flight ID 7352 included in the schedule with penalty 0.00\n",
      "Flight ID 7369 included in the schedule with penalty 0.00\n",
      "Flight ID 7387 included in the schedule with penalty 0.00\n",
      "Flight ID 7395 included in the schedule with penalty 0.00\n",
      "Flight ID 7403 included in the schedule with penalty 0.00\n",
      "Flight ID 7405 included in the schedule with penalty 0.00\n",
      "Flight ID 7406 included in the schedule with penalty 0.00\n",
      "Flight ID 7407 included in the schedule with penalty 0.00\n",
      "Flight ID 7409 included in the schedule with penalty 960.00\n",
      "Flight ID 7410 included in the schedule with penalty 0.00\n",
      "Flight ID 7450 included in the schedule with penalty 0.00\n",
      "Flight ID 7451 included in the schedule with penalty 0.00\n",
      "Flight ID 7452 included in the schedule with penalty 0.00\n",
      "Flight ID 7453 included in the schedule with penalty 0.00\n",
      "Flight ID 7454 included in the schedule with penalty 0.00\n",
      "Flight ID 7455 included in the schedule with penalty 0.00\n",
      "Flight ID 7456 included in the schedule with penalty 1750.00\n",
      "Flight ID 7457 included in the schedule with penalty 0.00\n",
      "Flight ID 7458 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-13 ---\n",
      "Flight ID 7722 included in the schedule with penalty 3500.00\n",
      "Flight ID 7724 included in the schedule with penalty 0.00\n",
      "Flight ID 7728 included in the schedule with penalty 0.00\n",
      "Flight ID 7732 included in the schedule with penalty 0.00\n",
      "Flight ID 7734 included in the schedule with penalty 0.00\n",
      "Flight ID 7741 included in the schedule with penalty 0.00\n",
      "Flight ID 7743 included in the schedule with penalty 0.00\n",
      "Flight ID 7746 included in the schedule with penalty 0.00\n",
      "Flight ID 7757 included in the schedule with penalty 0.00\n",
      "Flight ID 7759 included in the schedule with penalty 0.00\n",
      "Flight ID 7761 included in the schedule with penalty 3100.00\n",
      "Flight ID 7764 included in the schedule with penalty 750.00\n",
      "Flight ID 7858 included in the schedule with penalty 1620.00\n",
      "Flight ID 7877 included in the schedule with penalty 0.00\n",
      "Flight ID 7949 included in the schedule with penalty 0.00\n",
      "Flight ID 7950 included in the schedule with penalty 0.00\n",
      "Flight ID 7951 included in the schedule with penalty 0.00\n",
      "Flight ID 7952 included in the schedule with penalty 5120.00\n",
      "Flight ID 7953 included in the schedule with penalty 0.00\n",
      "Flight ID 7954 included in the schedule with penalty 0.00\n",
      "Flight ID 7955 included in the schedule with penalty 0.00\n",
      "Flight ID 7956 included in the schedule with penalty 3300.00\n",
      "Flight ID 7957 included in the schedule with penalty 0.00\n",
      "Flight ID 7958 included in the schedule with penalty 0.00\n",
      "Flight ID 8247 included in the schedule with penalty 0.00\n",
      "Flight ID 8250 included in the schedule with penalty 0.00\n",
      "Flight ID 8251 included in the schedule with penalty 0.00\n",
      "Flight ID 8253 included in the schedule with penalty 2200.00\n",
      "Flight ID 8255 included in the schedule with penalty 3300.00\n",
      "Flight ID 8257 included in the schedule with penalty 0.00\n",
      "Flight ID 8259 included in the schedule with penalty 0.00\n",
      "Flight ID 8260 included in the schedule with penalty 0.00\n",
      "Flight ID 8262 included in the schedule with penalty 0.00\n",
      "Flight ID 8264 included in the schedule with penalty 4100.00\n",
      "Flight ID 8266 included in the schedule with penalty 1500.00\n",
      "Flight ID 8268 included in the schedule with penalty 0.00\n",
      "Flight ID 8288 included in the schedule with penalty 4400.00\n",
      "Flight ID 8289 included in the schedule with penalty 0.00\n",
      "Flight ID 8290 included in the schedule with penalty 0.00\n",
      "Flight ID 8294 included in the schedule with penalty 900.00\n",
      "Flight ID 8295 included in the schedule with penalty 0.00\n",
      "Flight ID 8296 included in the schedule with penalty 0.00\n",
      "Flight ID 8297 included in the schedule with penalty 0.00\n",
      "Flight ID 8298 included in the schedule with penalty 1550.00\n",
      "Flight ID 8344 included in the schedule with penalty 0.00\n",
      "Flight ID 8356 included in the schedule with penalty 2800.00\n",
      "Flight ID 8357 included in the schedule with penalty 3850.00\n",
      "Flight ID 8364 included in the schedule with penalty 0.00\n",
      "Flight ID 8372 included in the schedule with penalty 0.00\n",
      "Flight ID 8383 included in the schedule with penalty 0.00\n",
      "Flight ID 8385 included in the schedule with penalty 0.00\n",
      "Flight ID 8386 included in the schedule with penalty 0.00\n",
      "Flight ID 8387 included in the schedule with penalty 0.00\n",
      "Flight ID 8388 included in the schedule with penalty 0.00\n",
      "Flight ID 8389 included in the schedule with penalty 0.00\n",
      "Flight ID 8391 included in the schedule with penalty 0.00\n",
      "Flight ID 8392 included in the schedule with penalty 1450.00\n",
      "Flight ID 8399 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-14 ---\n",
      "Flight ID 8431 included in the schedule with penalty 4600.00\n",
      "Flight ID 8522 included in the schedule with penalty 0.00\n",
      "Flight ID 8524 included in the schedule with penalty 0.00\n",
      "Flight ID 8525 included in the schedule with penalty 3640.00\n",
      "Flight ID 8526 included in the schedule with penalty 4480.00\n",
      "Flight ID 8527 included in the schedule with penalty 0.00\n",
      "Flight ID 8528 included in the schedule with penalty 7820.00\n",
      "Flight ID 8530 included in the schedule with penalty 0.00\n",
      "Flight ID 8531 included in the schedule with penalty 0.00\n",
      "Flight ID 8822 included in the schedule with penalty 0.00\n",
      "Flight ID 8825 included in the schedule with penalty 0.00\n",
      "Flight ID 8826 included in the schedule with penalty 0.00\n",
      "Flight ID 8828 included in the schedule with penalty 0.00\n",
      "Flight ID 8830 included in the schedule with penalty 8300.00\n",
      "Flight ID 8832 included in the schedule with penalty 1600.00\n",
      "Flight ID 8834 included in the schedule with penalty 0.00\n",
      "Flight ID 8835 included in the schedule with penalty 0.00\n",
      "Flight ID 8837 included in the schedule with penalty 2900.00\n",
      "Flight ID 8839 included in the schedule with penalty 3240.00\n",
      "Flight ID 8842 included in the schedule with penalty 0.00\n",
      "Flight ID 8861 included in the schedule with penalty 6350.00\n",
      "Flight ID 8862 included in the schedule with penalty 9050.00\n",
      "Flight ID 8867 included in the schedule with penalty 800.00\n",
      "Flight ID 8868 included in the schedule with penalty 6150.00\n",
      "Flight ID 8869 included in the schedule with penalty 3150.00\n",
      "Flight ID 8871 included in the schedule with penalty 4300.00\n",
      "Flight ID 8910 included in the schedule with penalty 3250.00\n",
      "Flight ID 8911 included in the schedule with penalty 3750.00\n",
      "Flight ID 8997 included in the schedule with penalty 5000.00\n",
      "Flight ID 8999 included in the schedule with penalty 7950.00\n",
      "Flight ID 9003 included in the schedule with penalty 7890.00\n",
      "Flight ID 9007 included in the schedule with penalty 1800.00\n",
      "Flight ID 9009 included in the schedule with penalty 0.00\n",
      "Flight ID 9016 included in the schedule with penalty 2050.00\n",
      "Flight ID 9018 included in the schedule with penalty 0.00\n",
      "Flight ID 9021 included in the schedule with penalty 2850.00\n",
      "Flight ID 9032 included in the schedule with penalty 2950.00\n",
      "Flight ID 9036 included in the schedule with penalty 8200.00\n",
      "Flight ID 9039 included in the schedule with penalty 2400.00\n",
      "Flight ID 9051 included in the schedule with penalty 7390.00\n",
      "Flight ID 9062 included in the schedule with penalty 3500.00\n",
      "Flight ID 9063 included in the schedule with penalty 8200.00\n",
      "Flight ID 9070 included in the schedule with penalty 0.00\n",
      "Flight ID 9078 included in the schedule with penalty 0.00\n",
      "Flight ID 9089 included in the schedule with penalty 1450.00\n",
      "Flight ID 9091 included in the schedule with penalty 4740.00\n",
      "Flight ID 9092 included in the schedule with penalty 0.00\n",
      "Flight ID 9093 included in the schedule with penalty 7790.00\n",
      "Flight ID 9095 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-15 ---\n",
      "Flight ID 9102 included in the schedule with penalty 1750.00\n",
      "Flight ID 9104 included in the schedule with penalty 1100.00\n",
      "Flight ID 9108 included in the schedule with penalty 2340.00\n",
      "Flight ID 9112 included in the schedule with penalty 0.00\n",
      "Flight ID 9114 included in the schedule with penalty 1500.00\n",
      "Flight ID 9121 included in the schedule with penalty 0.00\n",
      "Flight ID 9123 included in the schedule with penalty 0.00\n",
      "Flight ID 9126 included in the schedule with penalty 3960.00\n",
      "Flight ID 9137 included in the schedule with penalty 0.00\n",
      "Flight ID 9139 included in the schedule with penalty 0.00\n",
      "Flight ID 9141 included in the schedule with penalty 1250.00\n",
      "Flight ID 9144 included in the schedule with penalty 1380.00\n",
      "Flight ID 9156 included in the schedule with penalty 0.00\n",
      "Flight ID 9167 included in the schedule with penalty 2600.00\n",
      "Flight ID 9168 included in the schedule with penalty 0.00\n",
      "Flight ID 9175 included in the schedule with penalty 0.00\n",
      "Flight ID 9183 included in the schedule with penalty 0.00\n",
      "Flight ID 9194 included in the schedule with penalty 8760.00\n",
      "Flight ID 9196 included in the schedule with penalty 0.00\n",
      "Flight ID 9197 included in the schedule with penalty 0.00\n",
      "Flight ID 9198 included in the schedule with penalty 0.00\n",
      "Flight ID 9199 included in the schedule with penalty 0.00\n",
      "Flight ID 9202 included in the schedule with penalty 0.00\n",
      "Flight ID 9203 included in the schedule with penalty 0.00\n",
      "Flight ID 9211 included in the schedule with penalty 4100.00\n",
      "Flight ID 9277 included in the schedule with penalty 0.00\n",
      "Flight ID 9296 included in the schedule with penalty 0.00\n",
      "Flight ID 9368 included in the schedule with penalty 0.00\n",
      "Flight ID 9369 included in the schedule with penalty 0.00\n",
      "Flight ID 9370 included in the schedule with penalty 0.00\n",
      "Flight ID 9371 included in the schedule with penalty 4430.00\n",
      "Flight ID 9372 included in the schedule with penalty 0.00\n",
      "Flight ID 9373 included in the schedule with penalty 0.00\n",
      "Flight ID 9374 included in the schedule with penalty 2000.00\n",
      "Flight ID 9375 included in the schedule with penalty 800.00\n",
      "Flight ID 9376 included in the schedule with penalty 0.00\n",
      "Flight ID 9377 included in the schedule with penalty 0.00\n",
      "Flight ID 9460 included in the schedule with penalty 0.00\n",
      "Flight ID 9463 included in the schedule with penalty 1850.00\n",
      "Flight ID 9464 included in the schedule with penalty 4200.00\n",
      "Flight ID 9466 included in the schedule with penalty 6200.00\n",
      "Flight ID 9468 included in the schedule with penalty 0.00\n",
      "Flight ID 9470 included in the schedule with penalty 1690.00\n",
      "Flight ID 9472 included in the schedule with penalty 0.00\n",
      "Flight ID 9473 included in the schedule with penalty 0.00\n",
      "Flight ID 9474 included in the schedule with penalty 1250.00\n",
      "Flight ID 9477 included in the schedule with penalty 3600.00\n",
      "Flight ID 9479 included in the schedule with penalty 0.00\n",
      "Flight ID 9500 included in the schedule with penalty 0.00\n",
      "Flight ID 9501 included in the schedule with penalty 0.00\n",
      "Flight ID 9502 included in the schedule with penalty 6900.00\n",
      "Flight ID 9506 included in the schedule with penalty 3950.00\n",
      "Flight ID 9507 included in the schedule with penalty 0.00\n",
      "Flight ID 9508 included in the schedule with penalty 4560.00\n",
      "Flight ID 9509 included in the schedule with penalty 1050.00\n",
      "Flight ID 9510 included in the schedule with penalty 3650.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-16 ---\n",
      "Flight ID 9792 included in the schedule with penalty 0.00\n",
      "Flight ID 9794 included in the schedule with penalty 1050.00\n",
      "Flight ID 9798 included in the schedule with penalty 3540.00\n",
      "Flight ID 9802 included in the schedule with penalty 2100.00\n",
      "Flight ID 9804 included in the schedule with penalty 0.00\n",
      "Flight ID 9811 included in the schedule with penalty 0.00\n",
      "Flight ID 9813 included in the schedule with penalty 4920.00\n",
      "Flight ID 9816 included in the schedule with penalty 0.00\n",
      "Flight ID 9827 included in the schedule with penalty 4780.00\n",
      "Flight ID 9829 included in the schedule with penalty 0.00\n",
      "Flight ID 9831 included in the schedule with penalty 800.00\n",
      "Flight ID 9834 included in the schedule with penalty 1200.00\n",
      "Flight ID 9846 included in the schedule with penalty 4960.00\n",
      "Flight ID 9857 included in the schedule with penalty 1100.00\n",
      "Flight ID 9858 included in the schedule with penalty 0.00\n",
      "Flight ID 9865 included in the schedule with penalty 1300.00\n",
      "Flight ID 9873 included in the schedule with penalty 1500.00\n",
      "Flight ID 9884 included in the schedule with penalty 0.00\n",
      "Flight ID 9886 included in the schedule with penalty 0.00\n",
      "Flight ID 9887 included in the schedule with penalty 0.00\n",
      "Flight ID 9888 included in the schedule with penalty 0.00\n",
      "Flight ID 9889 included in the schedule with penalty 0.00\n",
      "Flight ID 9891 included in the schedule with penalty 2500.00\n",
      "Flight ID 9899 included in the schedule with penalty 1100.00\n",
      "Flight ID 9973 included in the schedule with penalty 0.00\n",
      "Flight ID 9974 included in the schedule with penalty 1100.00\n",
      "Flight ID 9975 included in the schedule with penalty 1610.00\n",
      "Flight ID 9976 included in the schedule with penalty 1750.00\n",
      "Flight ID 9977 included in the schedule with penalty 4210.00\n",
      "Flight ID 9978 included in the schedule with penalty 0.00\n",
      "Flight ID 9979 included in the schedule with penalty 0.00\n",
      "Flight ID 9980 included in the schedule with penalty 0.00\n",
      "Flight ID 9981 included in the schedule with penalty 4800.00\n",
      "Flight ID 9982 included in the schedule with penalty 0.00\n",
      "Flight ID 10137 included in the schedule with penalty 1320.00\n",
      "Flight ID 10156 included in the schedule with penalty 0.00\n",
      "Flight ID 10386 included in the schedule with penalty 2250.00\n",
      "Flight ID 10389 included in the schedule with penalty 800.00\n",
      "Flight ID 10390 included in the schedule with penalty 0.00\n",
      "Flight ID 10392 included in the schedule with penalty 1750.00\n",
      "Flight ID 10394 included in the schedule with penalty 1000.00\n",
      "Flight ID 10396 included in the schedule with penalty 0.00\n",
      "Flight ID 10398 included in the schedule with penalty 0.00\n",
      "Flight ID 10401 included in the schedule with penalty 850.00\n",
      "Flight ID 10403 included in the schedule with penalty 0.00\n",
      "Flight ID 10407 included in the schedule with penalty 0.00\n",
      "Flight ID 10428 included in the schedule with penalty 0.00\n",
      "Flight ID 10429 included in the schedule with penalty 0.00\n",
      "Flight ID 10430 included in the schedule with penalty 1600.00\n",
      "Flight ID 10434 included in the schedule with penalty 0.00\n",
      "Flight ID 10435 included in the schedule with penalty 0.00\n",
      "Flight ID 10436 included in the schedule with penalty 0.00\n",
      "Flight ID 10437 included in the schedule with penalty 0.00\n",
      "Flight ID 10438 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-17 ---\n",
      "Flight ID 10589 included in the schedule with penalty 0.00\n",
      "Flight ID 10590 included in the schedule with penalty 0.00\n",
      "Flight ID 10591 included in the schedule with penalty 0.00\n",
      "Flight ID 10592 included in the schedule with penalty 0.00\n",
      "Flight ID 10593 included in the schedule with penalty 1500.00\n",
      "Flight ID 10594 included in the schedule with penalty 0.00\n",
      "Flight ID 10595 included in the schedule with penalty 0.00\n",
      "Flight ID 10596 included in the schedule with penalty 0.00\n",
      "Flight ID 10597 included in the schedule with penalty 0.00\n",
      "Flight ID 10598 included in the schedule with penalty 0.00\n",
      "Flight ID 10893 included in the schedule with penalty 0.00\n",
      "Flight ID 10895 included in the schedule with penalty 0.00\n",
      "Flight ID 10896 included in the schedule with penalty 0.00\n",
      "Flight ID 10898 included in the schedule with penalty 0.00\n",
      "Flight ID 10900 included in the schedule with penalty 0.00\n",
      "Flight ID 10902 included in the schedule with penalty 1600.00\n",
      "Flight ID 10904 included in the schedule with penalty 1300.00\n",
      "Flight ID 10905 included in the schedule with penalty 0.00\n",
      "Flight ID 10908 included in the schedule with penalty 5450.00\n",
      "Flight ID 10910 included in the schedule with penalty 7650.00\n",
      "Flight ID 10912 included in the schedule with penalty 1200.00\n",
      "Flight ID 10931 included in the schedule with penalty 2500.00\n",
      "Flight ID 10932 included in the schedule with penalty 0.00\n",
      "Flight ID 10933 included in the schedule with penalty 0.00\n",
      "Flight ID 10937 included in the schedule with penalty 0.00\n",
      "Flight ID 10938 included in the schedule with penalty 0.00\n",
      "Flight ID 10939 included in the schedule with penalty 0.00\n",
      "Flight ID 10940 included in the schedule with penalty 0.00\n",
      "Flight ID 10941 included in the schedule with penalty 2900.00\n",
      "Flight ID 10987 included in the schedule with penalty 0.00\n",
      "Flight ID 10998 included in the schedule with penalty 0.00\n",
      "Flight ID 10999 included in the schedule with penalty 0.00\n",
      "Flight ID 11006 included in the schedule with penalty 0.00\n",
      "Flight ID 11041 included in the schedule with penalty 0.00\n",
      "Flight ID 11060 included in the schedule with penalty 0.00\n",
      "Flight ID 11091 included in the schedule with penalty 0.00\n",
      "Flight ID 11093 included in the schedule with penalty 0.00\n",
      "Flight ID 11097 included in the schedule with penalty 0.00\n",
      "Flight ID 11101 included in the schedule with penalty 0.00\n",
      "Flight ID 11103 included in the schedule with penalty 0.00\n",
      "Flight ID 11110 included in the schedule with penalty 0.00\n",
      "Flight ID 11112 included in the schedule with penalty 1980.00\n",
      "Flight ID 11115 included in the schedule with penalty 0.00\n",
      "Flight ID 11126 included in the schedule with penalty 0.00\n",
      "Flight ID 11128 included in the schedule with penalty 0.00\n",
      "Flight ID 11130 included in the schedule with penalty 0.00\n",
      "Flight ID 11133 included in the schedule with penalty 0.00\n",
      "Flight ID 11138 included in the schedule with penalty 0.00\n",
      "Flight ID 11149 included in the schedule with penalty 800.00\n",
      "Flight ID 11151 included in the schedule with penalty 0.00\n",
      "Flight ID 11152 included in the schedule with penalty 0.00\n",
      "Flight ID 11153 included in the schedule with penalty 0.00\n",
      "Flight ID 11154 included in the schedule with penalty 0.00\n",
      "Flight ID 11155 included in the schedule with penalty 0.00\n",
      "Flight ID 11157 included in the schedule with penalty 0.00\n",
      "Flight ID 11158 included in the schedule with penalty 1940.00\n",
      "Flight ID 11166 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-18 ---\n",
      "Flight ID 11178 included in the schedule with penalty 0.00\n",
      "Flight ID 11179 included in the schedule with penalty 6230.00\n",
      "Flight ID 11185 included in the schedule with penalty 0.00\n",
      "Flight ID 11187 included in the schedule with penalty 0.00\n",
      "Flight ID 11195 included in the schedule with penalty 1560.00\n",
      "Flight ID 11204 included in the schedule with penalty 0.00\n",
      "Flight ID 11206 included in the schedule with penalty 0.00\n",
      "Flight ID 11234 included in the schedule with penalty 0.00\n",
      "Flight ID 11247 included in the schedule with penalty 0.00\n",
      "Flight ID 11297 included in the schedule with penalty 0.00\n",
      "Flight ID 11298 included in the schedule with penalty 0.00\n",
      "Flight ID 11299 included in the schedule with penalty 0.00\n",
      "Flight ID 11300 included in the schedule with penalty 0.00\n",
      "Flight ID 11301 included in the schedule with penalty 0.00\n",
      "Flight ID 11302 included in the schedule with penalty 0.00\n",
      "Flight ID 11485 included in the schedule with penalty 0.00\n",
      "Flight ID 11487 included in the schedule with penalty 0.00\n",
      "Flight ID 11495 included in the schedule with penalty 0.00\n",
      "Flight ID 11496 included in the schedule with penalty 0.00\n",
      "Flight ID 11497 included in the schedule with penalty 2500.00\n",
      "Flight ID 11498 included in the schedule with penalty 0.00\n",
      "Flight ID 11543 included in the schedule with penalty 0.00\n",
      "Flight ID 11549 included in the schedule with penalty 0.00\n",
      "Flight ID 11562 included in the schedule with penalty 0.00\n",
      "Flight ID 11563 included in the schedule with penalty 0.00\n",
      "Flight ID 11564 included in the schedule with penalty 0.00\n",
      "Flight ID 11566 included in the schedule with penalty 0.00\n",
      "Flight ID 11567 included in the schedule with penalty 0.00\n",
      "Flight ID 11575 included in the schedule with penalty 0.00\n",
      "Flight ID 11629 included in the schedule with penalty 5100.00\n",
      "Flight ID 11630 included in the schedule with penalty 0.00\n",
      "Flight ID 11634 included in the schedule with penalty 1900.00\n",
      "Flight ID 11637 included in the schedule with penalty 0.00\n",
      "Flight ID 11638 included in the schedule with penalty 0.00\n",
      "Flight ID 11640 included in the schedule with penalty 0.00\n",
      "Flight ID 11642 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-19 ---\n",
      "Flight ID 11670 included in the schedule with penalty 0.00\n",
      "Flight ID 11672 included in the schedule with penalty 0.00\n",
      "Flight ID 11676 included in the schedule with penalty 1500.00\n",
      "Flight ID 11680 included in the schedule with penalty 900.00\n",
      "Flight ID 11682 included in the schedule with penalty 0.00\n",
      "Flight ID 11689 included in the schedule with penalty 0.00\n",
      "Flight ID 11691 included in the schedule with penalty 0.00\n",
      "Flight ID 11694 included in the schedule with penalty 1600.00\n",
      "Flight ID 11705 included in the schedule with penalty 1550.00\n",
      "Flight ID 11707 included in the schedule with penalty 0.00\n",
      "Flight ID 11709 included in the schedule with penalty 0.00\n",
      "Flight ID 11712 included in the schedule with penalty 0.00\n",
      "Flight ID 11720 included in the schedule with penalty 3900.00\n",
      "Flight ID 11721 included in the schedule with penalty 2550.00\n",
      "Flight ID 11722 included in the schedule with penalty 0.00\n",
      "Flight ID 11725 included in the schedule with penalty 1150.00\n",
      "Flight ID 11726 included in the schedule with penalty 0.00\n",
      "Flight ID 11727 included in the schedule with penalty 0.00\n",
      "Flight ID 11728 included in the schedule with penalty 0.00\n",
      "Flight ID 11748 included in the schedule with penalty 4150.00\n",
      "Flight ID 11751 included in the schedule with penalty 0.00\n",
      "Flight ID 11752 included in the schedule with penalty 3000.00\n",
      "Flight ID 11754 included in the schedule with penalty 3150.00\n",
      "Flight ID 11756 included in the schedule with penalty 0.00\n",
      "Flight ID 11758 included in the schedule with penalty 0.00\n",
      "Flight ID 11760 included in the schedule with penalty 0.00\n",
      "Flight ID 11761 included in the schedule with penalty 4250.00\n",
      "Flight ID 11763 included in the schedule with penalty 0.00\n",
      "Flight ID 11765 included in the schedule with penalty 2100.00\n",
      "Flight ID 11767 included in the schedule with penalty 0.00\n",
      "Flight ID 11769 included in the schedule with penalty 1650.00\n",
      "Flight ID 11845 included in the schedule with penalty 0.00\n",
      "Flight ID 11924 included in the schedule with penalty 1220.00\n",
      "Flight ID 11925 included in the schedule with penalty 0.00\n",
      "Flight ID 11926 included in the schedule with penalty 0.00\n",
      "Flight ID 11927 included in the schedule with penalty 4610.00\n",
      "Flight ID 11928 included in the schedule with penalty 3600.00\n",
      "Flight ID 11929 included in the schedule with penalty 2250.00\n",
      "Flight ID 11930 included in the schedule with penalty 2360.00\n",
      "Flight ID 11931 included in the schedule with penalty 2750.00\n",
      "Flight ID 11932 included in the schedule with penalty 2860.00\n",
      "Flight ID 12236 included in the schedule with penalty 0.00\n",
      "Flight ID 12243 included in the schedule with penalty 2250.00\n",
      "Flight ID 12251 included in the schedule with penalty 0.00\n",
      "Flight ID 12259 included in the schedule with penalty 8700.00\n",
      "Flight ID 12261 included in the schedule with penalty 0.00\n",
      "Flight ID 12262 included in the schedule with penalty 850.00\n",
      "Flight ID 12263 included in the schedule with penalty 0.00\n",
      "Flight ID 12265 included in the schedule with penalty 0.00\n",
      "Flight ID 12266 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-20 ---\n",
      "Flight ID 12340 included in the schedule with penalty 0.00\n",
      "Flight ID 12359 included in the schedule with penalty 3840.00\n",
      "Flight ID 12616 included in the schedule with penalty 0.00\n",
      "Flight ID 12617 included in the schedule with penalty 2770.00\n",
      "Flight ID 12618 included in the schedule with penalty 1910.00\n",
      "Flight ID 12619 included in the schedule with penalty 4570.00\n",
      "Flight ID 12620 included in the schedule with penalty 3850.00\n",
      "Flight ID 12621 included in the schedule with penalty 0.00\n",
      "Flight ID 12622 included in the schedule with penalty 0.00\n",
      "Flight ID 12623 included in the schedule with penalty 4200.00\n",
      "Flight ID 12624 included in the schedule with penalty 3780.00\n",
      "Flight ID 12625 included in the schedule with penalty 0.00\n",
      "Flight ID 12771 included in the schedule with penalty 0.00\n",
      "Flight ID 12782 included in the schedule with penalty 0.00\n",
      "Flight ID 12783 included in the schedule with penalty 0.00\n",
      "Flight ID 12790 included in the schedule with penalty 800.00\n",
      "Flight ID 12799 included in the schedule with penalty 0.00\n",
      "Flight ID 12810 included in the schedule with penalty 750.00\n",
      "Flight ID 12812 included in the schedule with penalty 0.00\n",
      "Flight ID 12813 included in the schedule with penalty 0.00\n",
      "Flight ID 12814 included in the schedule with penalty 2160.00\n",
      "Flight ID 12815 included in the schedule with penalty 0.00\n",
      "Flight ID 12816 included in the schedule with penalty 0.00\n",
      "Flight ID 12818 included in the schedule with penalty 0.00\n",
      "Flight ID 12819 included in the schedule with penalty 0.00\n",
      "Flight ID 12827 included in the schedule with penalty 3050.00\n",
      "Flight ID 12848 included in the schedule with penalty 0.00\n",
      "Flight ID 12849 included in the schedule with penalty 0.00\n",
      "Flight ID 12851 included in the schedule with penalty 0.00\n",
      "Flight ID 12853 included in the schedule with penalty 2100.00\n",
      "Flight ID 12855 included in the schedule with penalty 0.00\n",
      "Flight ID 12857 included in the schedule with penalty 0.00\n",
      "Flight ID 12858 included in the schedule with penalty 0.00\n",
      "Flight ID 12861 included in the schedule with penalty 4250.00\n",
      "Flight ID 12863 included in the schedule with penalty 0.00\n",
      "Flight ID 12874 included in the schedule with penalty 0.00\n",
      "Flight ID 12896 included in the schedule with penalty 2150.00\n",
      "Flight ID 12898 included in the schedule with penalty 0.00\n",
      "Flight ID 12902 included in the schedule with penalty 0.00\n",
      "Flight ID 12906 included in the schedule with penalty 3250.00\n",
      "Flight ID 12908 included in the schedule with penalty 0.00\n",
      "Flight ID 12915 included in the schedule with penalty 0.00\n",
      "Flight ID 12917 included in the schedule with penalty 1600.00\n",
      "Flight ID 12920 included in the schedule with penalty 1680.00\n",
      "Flight ID 12931 included in the schedule with penalty 3500.00\n",
      "Flight ID 12933 included in the schedule with penalty 1550.00\n",
      "Flight ID 12935 included in the schedule with penalty 1400.00\n",
      "Flight ID 12938 included in the schedule with penalty 0.00\n",
      "Flight ID 12950 included in the schedule with penalty 1360.00\n",
      "Flight ID 12951 included in the schedule with penalty 0.00\n",
      "Flight ID 12952 included in the schedule with penalty 1250.00\n",
      "Flight ID 12956 included in the schedule with penalty 0.00\n",
      "Flight ID 12957 included in the schedule with penalty 0.00\n",
      "Flight ID 12958 included in the schedule with penalty 0.00\n",
      "Flight ID 12959 included in the schedule with penalty 1300.00\n",
      "Flight ID 12960 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-21 ---\n",
      "Flight ID 12964 included in the schedule with penalty 1100.00\n",
      "Flight ID 12970 included in the schedule with penalty 4500.00\n",
      "Flight ID 12972 included in the schedule with penalty 3200.00\n",
      "Flight ID 12977 included in the schedule with penalty 4500.00\n",
      "Flight ID 12980 included in the schedule with penalty 0.00\n",
      "Flight ID 12984 included in the schedule with penalty 0.00\n",
      "Flight ID 12986 included in the schedule with penalty 0.00\n",
      "Flight ID 12993 included in the schedule with penalty 2600.00\n",
      "Flight ID 12995 included in the schedule with penalty 2250.00\n",
      "Flight ID 12998 included in the schedule with penalty 0.00\n",
      "Flight ID 13005 included in the schedule with penalty 5100.00\n",
      "Flight ID 13007 included in the schedule with penalty 2400.00\n",
      "Flight ID 13022 included in the schedule with penalty 0.00\n",
      "Flight ID 13023 included in the schedule with penalty 2050.00\n",
      "Flight ID 13024 included in the schedule with penalty 2150.00\n",
      "Flight ID 13028 included in the schedule with penalty 1900.00\n",
      "Flight ID 13029 included in the schedule with penalty 0.00\n",
      "Flight ID 13030 included in the schedule with penalty 3170.00\n",
      "Flight ID 13031 included in the schedule with penalty 1650.00\n",
      "Flight ID 13032 included in the schedule with penalty 0.00\n",
      "Flight ID 13137 included in the schedule with penalty 4500.00\n",
      "Flight ID 13138 included in the schedule with penalty 0.00\n",
      "Flight ID 13139 included in the schedule with penalty 0.00\n",
      "Flight ID 13140 included in the schedule with penalty 0.00\n",
      "Flight ID 13141 included in the schedule with penalty 2350.00\n",
      "Flight ID 13142 included in the schedule with penalty 0.00\n",
      "Flight ID 13143 included in the schedule with penalty 0.00\n",
      "Flight ID 13144 included in the schedule with penalty 1100.00\n",
      "Flight ID 13145 included in the schedule with penalty 1060.00\n",
      "Flight ID 13146 included in the schedule with penalty 0.00\n",
      "Flight ID 13437 included in the schedule with penalty 0.00\n",
      "Flight ID 13440 included in the schedule with penalty 0.00\n",
      "Flight ID 13441 included in the schedule with penalty 0.00\n",
      "Flight ID 13443 included in the schedule with penalty 0.00\n",
      "Flight ID 13445 included in the schedule with penalty 1200.00\n",
      "Flight ID 13447 included in the schedule with penalty 0.00\n",
      "Flight ID 13449 included in the schedule with penalty 0.00\n",
      "Flight ID 13450 included in the schedule with penalty 0.00\n",
      "Flight ID 13451 included in the schedule with penalty 0.00\n",
      "Flight ID 13454 included in the schedule with penalty 0.00\n",
      "Flight ID 13456 included in the schedule with penalty 6000.00\n",
      "Flight ID 13544 included in the schedule with penalty 0.00\n",
      "Flight ID 13559 included in the schedule with penalty 0.00\n",
      "Flight ID 13562 included in the schedule with penalty 0.00\n",
      "Flight ID 13568 included in the schedule with penalty 0.00\n",
      "Flight ID 13577 included in the schedule with penalty 1500.00\n",
      "Flight ID 13578 included in the schedule with penalty 0.00\n",
      "Flight ID 13587 included in the schedule with penalty 0.00\n",
      "Flight ID 13596 included in the schedule with penalty 0.00\n",
      "Flight ID 13605 included in the schedule with penalty 950.00\n",
      "Flight ID 13607 included in the schedule with penalty 0.00\n",
      "Flight ID 13608 included in the schedule with penalty 3540.00\n",
      "Flight ID 13609 included in the schedule with penalty 2700.00\n",
      "Flight ID 13610 included in the schedule with penalty 0.00\n",
      "Flight ID 13612 included in the schedule with penalty 0.00\n",
      "Flight ID 13613 included in the schedule with penalty 0.00\n",
      "Flight ID 13621 included in the schedule with penalty 4520.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-22 ---\n",
      "Flight ID 13652 included in the schedule with penalty 0.00\n",
      "Flight ID 13658 included in the schedule with penalty 0.00\n",
      "Flight ID 13660 included in the schedule with penalty 0.00\n",
      "Flight ID 13665 included in the schedule with penalty 0.00\n",
      "Flight ID 13668 included in the schedule with penalty 0.00\n",
      "Flight ID 13672 included in the schedule with penalty 0.00\n",
      "Flight ID 13674 included in the schedule with penalty 0.00\n",
      "Flight ID 13681 included in the schedule with penalty 0.00\n",
      "Flight ID 13683 included in the schedule with penalty 1850.00\n",
      "Flight ID 13686 included in the schedule with penalty 0.00\n",
      "Flight ID 13693 included in the schedule with penalty 5650.00\n",
      "Flight ID 13695 included in the schedule with penalty 0.00\n",
      "Flight ID 13766 included in the schedule with penalty 0.00\n",
      "Flight ID 13781 included in the schedule with penalty 0.00\n",
      "Flight ID 13787 included in the schedule with penalty 0.00\n",
      "Flight ID 13793 included in the schedule with penalty 0.00\n",
      "Flight ID 13802 included in the schedule with penalty 0.00\n",
      "Flight ID 13803 included in the schedule with penalty 0.00\n",
      "Flight ID 13812 included in the schedule with penalty 0.00\n",
      "Flight ID 13821 included in the schedule with penalty 0.00\n",
      "Flight ID 13830 included in the schedule with penalty 0.00\n",
      "Flight ID 13832 included in the schedule with penalty 0.00\n",
      "Flight ID 13833 included in the schedule with penalty 0.00\n",
      "Flight ID 13834 included in the schedule with penalty 0.00\n",
      "Flight ID 13835 included in the schedule with penalty 0.00\n",
      "Flight ID 13837 included in the schedule with penalty 0.00\n",
      "Flight ID 13838 included in the schedule with penalty 0.00\n",
      "Flight ID 13846 included in the schedule with penalty 0.00\n",
      "Flight ID 13948 included in the schedule with penalty 0.00\n",
      "Flight ID 13949 included in the schedule with penalty 0.00\n",
      "Flight ID 13950 included in the schedule with penalty 2800.00\n",
      "Flight ID 13951 included in the schedule with penalty 1920.00\n",
      "Flight ID 13952 included in the schedule with penalty 1700.00\n",
      "Flight ID 13953 included in the schedule with penalty 0.00\n",
      "Flight ID 13954 included in the schedule with penalty 0.00\n",
      "Flight ID 13955 included in the schedule with penalty 4900.00\n",
      "Flight ID 13956 included in the schedule with penalty 1140.00\n",
      "Flight ID 13957 included in the schedule with penalty 0.00\n",
      "Flight ID 14248 included in the schedule with penalty 0.00\n",
      "Flight ID 14251 included in the schedule with penalty 0.00\n",
      "Flight ID 14252 included in the schedule with penalty 0.00\n",
      "Flight ID 14254 included in the schedule with penalty 0.00\n",
      "Flight ID 14256 included in the schedule with penalty 0.00\n",
      "Flight ID 14258 included in the schedule with penalty 1050.00\n",
      "Flight ID 14260 included in the schedule with penalty 0.00\n",
      "Flight ID 14262 included in the schedule with penalty 0.00\n",
      "Flight ID 14264 included in the schedule with penalty 2530.00\n",
      "Flight ID 14267 included in the schedule with penalty 0.00\n",
      "Flight ID 14288 included in the schedule with penalty 0.00\n",
      "Flight ID 14289 included in the schedule with penalty 0.00\n",
      "Flight ID 14290 included in the schedule with penalty 0.00\n",
      "Flight ID 14294 included in the schedule with penalty 0.00\n",
      "Flight ID 14295 included in the schedule with penalty 0.00\n",
      "Flight ID 14296 included in the schedule with penalty 0.00\n",
      "Flight ID 14297 included in the schedule with penalty 5920.00\n",
      "Flight ID 14298 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-23 ---\n",
      "Flight ID 14402 included in the schedule with penalty 0.00\n",
      "Flight ID 14403 included in the schedule with penalty 2100.00\n",
      "Flight ID 14404 included in the schedule with penalty 0.00\n",
      "Flight ID 14405 included in the schedule with penalty 8440.00\n",
      "Flight ID 14406 included in the schedule with penalty 2640.00\n",
      "Flight ID 14407 included in the schedule with penalty 0.00\n",
      "Flight ID 14408 included in the schedule with penalty 1400.00\n",
      "Flight ID 14410 included in the schedule with penalty 3590.00\n",
      "Flight ID 14411 included in the schedule with penalty 0.00\n",
      "Flight ID 14437 included in the schedule with penalty 1850.00\n",
      "Flight ID 14440 included in the schedule with penalty 0.00\n",
      "Flight ID 14441 included in the schedule with penalty 950.00\n",
      "Flight ID 14443 included in the schedule with penalty 0.00\n",
      "Flight ID 14445 included in the schedule with penalty 0.00\n",
      "Flight ID 14447 included in the schedule with penalty 0.00\n",
      "Flight ID 14449 included in the schedule with penalty 4750.00\n",
      "Flight ID 14450 included in the schedule with penalty 0.00\n",
      "Flight ID 14451 included in the schedule with penalty 2600.00\n",
      "Flight ID 14454 included in the schedule with penalty 1200.00\n",
      "Flight ID 14456 included in the schedule with penalty 0.00\n",
      "Flight ID 14477 included in the schedule with penalty 1970.00\n",
      "Flight ID 14478 included in the schedule with penalty 2200.00\n",
      "Flight ID 14479 included in the schedule with penalty 0.00\n",
      "Flight ID 14483 included in the schedule with penalty 0.00\n",
      "Flight ID 14484 included in the schedule with penalty 3510.00\n",
      "Flight ID 14485 included in the schedule with penalty 1600.00\n",
      "Flight ID 14486 included in the schedule with penalty 4000.00\n",
      "Flight ID 14487 included in the schedule with penalty 4050.00\n",
      "Flight ID 14900 included in the schedule with penalty 0.00\n",
      "Flight ID 14906 included in the schedule with penalty 0.00\n",
      "Flight ID 14913 included in the schedule with penalty 0.00\n",
      "Flight ID 14922 included in the schedule with penalty 4820.00\n",
      "Flight ID 14923 included in the schedule with penalty 0.00\n",
      "Flight ID 14933 included in the schedule with penalty 0.00\n",
      "Flight ID 14944 included in the schedule with penalty 0.00\n",
      "Flight ID 14953 included in the schedule with penalty 5100.00\n",
      "Flight ID 14955 included in the schedule with penalty 1460.00\n",
      "Flight ID 14956 included in the schedule with penalty 0.00\n",
      "Flight ID 14957 included in the schedule with penalty 5140.00\n",
      "Flight ID 14958 included in the schedule with penalty 1250.00\n",
      "Flight ID 14960 included in the schedule with penalty 2000.00\n",
      "Flight ID 14961 included in the schedule with penalty 850.00\n",
      "Flight ID 14970 included in the schedule with penalty 850.00\n",
      "Flight ID 14984 included in the schedule with penalty 2450.00\n",
      "Flight ID 14992 included in the schedule with penalty 0.00\n",
      "Flight ID 14997 included in the schedule with penalty 1300.00\n",
      "Flight ID 15000 included in the schedule with penalty 2540.00\n",
      "Flight ID 15004 included in the schedule with penalty 2250.00\n",
      "Flight ID 15006 included in the schedule with penalty 0.00\n",
      "Flight ID 15013 included in the schedule with penalty 0.00\n",
      "Flight ID 15015 included in the schedule with penalty 0.00\n",
      "Flight ID 15018 included in the schedule with penalty 4200.00\n",
      "Flight ID 15025 included in the schedule with penalty 1900.00\n",
      "Flight ID 15027 included in the schedule with penalty 8000.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-24 ---\n",
      "Flight ID 15034 included in the schedule with penalty 2540.00\n",
      "Flight ID 15040 included in the schedule with penalty 1900.00\n",
      "Flight ID 15042 included in the schedule with penalty 0.00\n",
      "Flight ID 15047 included in the schedule with penalty 0.00\n",
      "Flight ID 15050 included in the schedule with penalty 0.00\n",
      "Flight ID 15054 included in the schedule with penalty 0.00\n",
      "Flight ID 15056 included in the schedule with penalty 0.00\n",
      "Flight ID 15063 included in the schedule with penalty 0.00\n",
      "Flight ID 15065 included in the schedule with penalty 0.00\n",
      "Flight ID 15068 included in the schedule with penalty 3550.00\n",
      "Flight ID 15075 included in the schedule with penalty 1950.00\n",
      "Flight ID 15077 included in the schedule with penalty 0.00\n",
      "Flight ID 15089 included in the schedule with penalty 4650.00\n",
      "Flight ID 15090 included in the schedule with penalty 9100.00\n",
      "Flight ID 15091 included in the schedule with penalty 0.00\n",
      "Flight ID 15095 included in the schedule with penalty 1450.00\n",
      "Flight ID 15096 included in the schedule with penalty 4200.00\n",
      "Flight ID 15097 included in the schedule with penalty 2450.00\n",
      "Flight ID 15098 included in the schedule with penalty 4200.00\n",
      "Flight ID 15099 included in the schedule with penalty 0.00\n",
      "Flight ID 15140 included in the schedule with penalty 0.00\n",
      "Flight ID 15156 included in the schedule with penalty 0.00\n",
      "Flight ID 15198 included in the schedule with penalty 0.00\n",
      "Flight ID 15200 included in the schedule with penalty 0.00\n",
      "Flight ID 15201 included in the schedule with penalty 0.00\n",
      "Flight ID 15203 included in the schedule with penalty 2200.00\n",
      "Flight ID 15205 included in the schedule with penalty 0.00\n",
      "Flight ID 15207 included in the schedule with penalty 3350.00\n",
      "Flight ID 15208 included in the schedule with penalty 2850.00\n",
      "Flight ID 15211 included in the schedule with penalty 2150.00\n",
      "Flight ID 15213 included in the schedule with penalty 800.00\n",
      "Flight ID 15215 included in the schedule with penalty 0.00\n",
      "Flight ID 15260 included in the schedule with penalty 0.00\n",
      "Flight ID 15266 included in the schedule with penalty 0.00\n",
      "Flight ID 15275 included in the schedule with penalty 0.00\n",
      "Flight ID 15276 included in the schedule with penalty 0.00\n",
      "Flight ID 15332 included in the schedule with penalty 0.00\n",
      "Flight ID 15343 included in the schedule with penalty 0.00\n",
      "Flight ID 15352 included in the schedule with penalty 850.00\n",
      "Flight ID 15354 included in the schedule with penalty 0.00\n",
      "Flight ID 15355 included in the schedule with penalty 0.00\n",
      "Flight ID 15356 included in the schedule with penalty 0.00\n",
      "Flight ID 15357 included in the schedule with penalty 0.00\n",
      "Flight ID 15359 included in the schedule with penalty 0.00\n",
      "Flight ID 15360 included in the schedule with penalty 0.00\n",
      "Flight ID 15369 included in the schedule with penalty 1500.00\n",
      "Flight ID 15409 included in the schedule with penalty 0.00\n",
      "Flight ID 15410 included in the schedule with penalty 3820.00\n",
      "Flight ID 15411 included in the schedule with penalty 7860.00\n",
      "Flight ID 15412 included in the schedule with penalty 8480.00\n",
      "Flight ID 15413 included in the schedule with penalty 1150.00\n",
      "Flight ID 15414 included in the schedule with penalty 0.00\n",
      "Flight ID 15415 included in the schedule with penalty 6040.00\n",
      "Flight ID 15416 included in the schedule with penalty 0.00\n",
      "Flight ID 15417 included in the schedule with penalty 3990.00\n",
      "Flight ID 15418 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-25 ---\n",
      "Flight ID 15724 included in the schedule with penalty 1300.00\n",
      "Flight ID 15725 included in the schedule with penalty 0.00\n",
      "Flight ID 15732 included in the schedule with penalty 0.00\n",
      "Flight ID 15736 included in the schedule with penalty 1100.00\n",
      "Flight ID 15738 included in the schedule with penalty 0.00\n",
      "Flight ID 15745 included in the schedule with penalty 0.00\n",
      "Flight ID 15748 included in the schedule with penalty 0.00\n",
      "Flight ID 15755 included in the schedule with penalty 0.00\n",
      "Flight ID 15757 included in the schedule with penalty 0.00\n",
      "Flight ID 15762 included in the schedule with penalty 0.00\n",
      "Flight ID 15770 included in the schedule with penalty 0.00\n",
      "Flight ID 15771 included in the schedule with penalty 0.00\n",
      "Flight ID 15772 included in the schedule with penalty 0.00\n",
      "Flight ID 15773 included in the schedule with penalty 0.00\n",
      "Flight ID 15822 included in the schedule with penalty 0.00\n",
      "Flight ID 15823 included in the schedule with penalty 0.00\n",
      "Flight ID 15825 included in the schedule with penalty 0.00\n",
      "Flight ID 15826 included in the schedule with penalty 0.00\n",
      "Flight ID 15827 included in the schedule with penalty 0.00\n",
      "Flight ID 16004 included in the schedule with penalty 0.00\n",
      "Flight ID 16020 included in the schedule with penalty 0.00\n",
      "Flight ID 16109 included in the schedule with penalty 960.00\n",
      "Flight ID 16112 included in the schedule with penalty 0.00\n",
      "Flight ID 16113 included in the schedule with penalty 0.00\n",
      "Flight ID 16115 included in the schedule with penalty 1350.00\n",
      "Flight ID 16117 included in the schedule with penalty 0.00\n",
      "Flight ID 16120 included in the schedule with penalty 0.00\n",
      "Flight ID 16121 included in the schedule with penalty 0.00\n",
      "Flight ID 16123 included in the schedule with penalty 0.00\n",
      "Flight ID 16125 included in the schedule with penalty 0.00\n",
      "Flight ID 16131 included in the schedule with penalty 0.00\n",
      "Flight ID 16135 included in the schedule with penalty 0.00\n",
      "Flight ID 16165 included in the schedule with penalty 0.00\n",
      "Flight ID 16172 included in the schedule with penalty 0.00\n",
      "Flight ID 16173 included in the schedule with penalty 0.00\n",
      "Flight ID 16178 included in the schedule with penalty 0.00\n",
      "Flight ID 16189 included in the schedule with penalty 750.00\n",
      "Flight ID 16190 included in the schedule with penalty 0.00\n",
      "Flight ID 16191 included in the schedule with penalty 0.00\n",
      "Flight ID 16193 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-26 ---\n",
      "Flight ID 16288 included in the schedule with penalty 0.00\n",
      "Flight ID 16304 included in the schedule with penalty 0.00\n",
      "Flight ID 16351 included in the schedule with penalty 0.00\n",
      "Flight ID 16352 included in the schedule with penalty 0.00\n",
      "Flight ID 16353 included in the schedule with penalty 0.00\n",
      "Flight ID 16354 included in the schedule with penalty 0.00\n",
      "Flight ID 16355 included in the schedule with penalty 0.00\n",
      "Flight ID 16356 included in the schedule with penalty 0.00\n",
      "Flight ID 16357 included in the schedule with penalty 0.00\n",
      "Flight ID 16358 included in the schedule with penalty 1850.00\n",
      "Flight ID 16359 included in the schedule with penalty 1740.00\n",
      "Flight ID 16609 included in the schedule with penalty 5100.00\n",
      "Flight ID 16610 included in the schedule with penalty 2050.00\n",
      "Flight ID 16612 included in the schedule with penalty 0.00\n",
      "Flight ID 16614 included in the schedule with penalty 0.00\n",
      "Flight ID 16616 included in the schedule with penalty 0.00\n",
      "Flight ID 16618 included in the schedule with penalty 0.00\n",
      "Flight ID 16619 included in the schedule with penalty 0.00\n",
      "Flight ID 16622 included in the schedule with penalty 0.00\n",
      "Flight ID 16623 included in the schedule with penalty 0.00\n",
      "Flight ID 16625 included in the schedule with penalty 0.00\n",
      "Flight ID 16675 included in the schedule with penalty 0.00\n",
      "Flight ID 16676 included in the schedule with penalty 0.00\n",
      "Flight ID 16684 included in the schedule with penalty 0.00\n",
      "Flight ID 16695 included in the schedule with penalty 0.00\n",
      "Flight ID 16702 included in the schedule with penalty 0.00\n",
      "Flight ID 16710 included in the schedule with penalty 0.00\n",
      "Flight ID 16712 included in the schedule with penalty 2700.00\n",
      "Flight ID 16713 included in the schedule with penalty 0.00\n",
      "Flight ID 16714 included in the schedule with penalty 6400.00\n",
      "Flight ID 16715 included in the schedule with penalty 0.00\n",
      "Flight ID 16717 included in the schedule with penalty 0.00\n",
      "Flight ID 16718 included in the schedule with penalty 0.00\n",
      "Flight ID 16729 included in the schedule with penalty 0.00\n",
      "Flight ID 16768 included in the schedule with penalty 0.00\n",
      "Flight ID 16774 included in the schedule with penalty 0.00\n",
      "Flight ID 16776 included in the schedule with penalty 0.00\n",
      "Flight ID 16781 included in the schedule with penalty 0.00\n",
      "Flight ID 16784 included in the schedule with penalty 0.00\n",
      "Flight ID 16788 included in the schedule with penalty 0.00\n",
      "Flight ID 16790 included in the schedule with penalty 0.00\n",
      "Flight ID 16797 included in the schedule with penalty 0.00\n",
      "Flight ID 16799 included in the schedule with penalty 2550.00\n",
      "Flight ID 16802 included in the schedule with penalty 0.00\n",
      "Flight ID 16809 included in the schedule with penalty 0.00\n",
      "Flight ID 16811 included in the schedule with penalty 0.00\n",
      "Flight ID 16824 included in the schedule with penalty 0.00\n",
      "Flight ID 16825 included in the schedule with penalty 0.00\n",
      "Flight ID 16826 included in the schedule with penalty 0.00\n",
      "Flight ID 16829 included in the schedule with penalty 0.00\n",
      "Flight ID 16830 included in the schedule with penalty 0.00\n",
      "Flight ID 16831 included in the schedule with penalty 0.00\n",
      "Flight ID 16832 included in the schedule with penalty 800.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-27 ---\n",
      "Flight ID 16838 included in the schedule with penalty 3380.00\n",
      "Flight ID 16844 included in the schedule with penalty 0.00\n",
      "Flight ID 16846 included in the schedule with penalty 840.00\n",
      "Flight ID 16851 included in the schedule with penalty 0.00\n",
      "Flight ID 16854 included in the schedule with penalty 0.00\n",
      "Flight ID 16858 included in the schedule with penalty 2900.00\n",
      "Flight ID 16860 included in the schedule with penalty 0.00\n",
      "Flight ID 16867 included in the schedule with penalty 0.00\n",
      "Flight ID 16869 included in the schedule with penalty 4850.00\n",
      "Flight ID 16872 included in the schedule with penalty 0.00\n",
      "Flight ID 16879 included in the schedule with penalty 4150.00\n",
      "Flight ID 16881 included in the schedule with penalty 4450.00\n",
      "Flight ID 16894 included in the schedule with penalty 0.00\n",
      "Flight ID 16895 included in the schedule with penalty 0.00\n",
      "Flight ID 16896 included in the schedule with penalty 800.00\n",
      "Flight ID 16900 included in the schedule with penalty 0.00\n",
      "Flight ID 16901 included in the schedule with penalty 2500.00\n",
      "Flight ID 16902 included in the schedule with penalty 2450.00\n",
      "Flight ID 16903 included in the schedule with penalty 800.00\n",
      "Flight ID 16904 included in the schedule with penalty 5650.00\n",
      "Flight ID 16993 included in the schedule with penalty 0.00\n",
      "Flight ID 17008 included in the schedule with penalty 0.00\n",
      "Flight ID 17063 included in the schedule with penalty 0.00\n",
      "Flight ID 17064 included in the schedule with penalty 6300.00\n",
      "Flight ID 17065 included in the schedule with penalty 0.00\n",
      "Flight ID 17066 included in the schedule with penalty 6420.00\n",
      "Flight ID 17067 included in the schedule with penalty 1550.00\n",
      "Flight ID 17068 included in the schedule with penalty 0.00\n",
      "Flight ID 17069 included in the schedule with penalty 1990.00\n",
      "Flight ID 17070 included in the schedule with penalty 3400.00\n",
      "Flight ID 17071 included in the schedule with penalty 4280.00\n",
      "Flight ID 17072 included in the schedule with penalty 0.00\n",
      "Flight ID 17099 included in the schedule with penalty 7600.00\n",
      "Flight ID 17101 included in the schedule with penalty 1850.00\n",
      "Flight ID 17102 included in the schedule with penalty 0.00\n",
      "Flight ID 17103 included in the schedule with penalty 0.00\n",
      "Flight ID 17105 included in the schedule with penalty 2300.00\n",
      "Flight ID 17107 included in the schedule with penalty 1440.00\n",
      "Flight ID 17110 included in the schedule with penalty 2950.00\n",
      "Flight ID 17113 included in the schedule with penalty 2050.00\n",
      "Flight ID 17114 included in the schedule with penalty 4700.00\n",
      "Flight ID 17117 included in the schedule with penalty 0.00\n",
      "Flight ID 17165 included in the schedule with penalty 0.00\n",
      "Flight ID 17172 included in the schedule with penalty 6600.00\n",
      "Flight ID 17181 included in the schedule with penalty 1250.00\n",
      "Flight ID 17182 included in the schedule with penalty 0.00\n",
      "Flight ID 17193 included in the schedule with penalty 1800.00\n",
      "Flight ID 17205 included in the schedule with penalty 1500.00\n",
      "Flight ID 17214 included in the schedule with penalty 0.00\n",
      "Flight ID 17216 included in the schedule with penalty 3150.00\n",
      "Flight ID 17217 included in the schedule with penalty 3350.00\n",
      "Flight ID 17218 included in the schedule with penalty 2050.00\n",
      "Flight ID 17219 included in the schedule with penalty 3500.00\n",
      "Flight ID 17221 included in the schedule with penalty 0.00\n",
      "Flight ID 17222 included in the schedule with penalty 0.00\n",
      "Flight ID 17231 included in the schedule with penalty 4600.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-28 ---\n",
      "Flight ID 17533 included in the schedule with penalty 1700.00\n",
      "Flight ID 17539 included in the schedule with penalty 0.00\n",
      "Flight ID 17541 included in the schedule with penalty 0.00\n",
      "Flight ID 17546 included in the schedule with penalty 1380.00\n",
      "Flight ID 17549 included in the schedule with penalty 0.00\n",
      "Flight ID 17553 included in the schedule with penalty 2610.00\n",
      "Flight ID 17555 included in the schedule with penalty 0.00\n",
      "Flight ID 17562 included in the schedule with penalty 1050.00\n",
      "Flight ID 17564 included in the schedule with penalty 2700.00\n",
      "Flight ID 17567 included in the schedule with penalty 0.00\n",
      "Flight ID 17574 included in the schedule with penalty 3650.00\n",
      "Flight ID 17576 included in the schedule with penalty 0.00\n",
      "Flight ID 17581 included in the schedule with penalty 0.00\n",
      "Flight ID 17582 included in the schedule with penalty 1000.00\n",
      "Flight ID 17594 included in the schedule with penalty 3570.00\n",
      "Flight ID 17595 included in the schedule with penalty 0.00\n",
      "Flight ID 17596 included in the schedule with penalty 1150.00\n",
      "Flight ID 17600 included in the schedule with penalty 0.00\n",
      "Flight ID 17601 included in the schedule with penalty 0.00\n",
      "Flight ID 17602 included in the schedule with penalty 0.00\n",
      "Flight ID 17603 included in the schedule with penalty 0.00\n",
      "Flight ID 17609 included in the schedule with penalty 0.00\n",
      "Flight ID 17618 included in the schedule with penalty 900.00\n",
      "Flight ID 17619 included in the schedule with penalty 0.00\n",
      "Flight ID 17629 included in the schedule with penalty 0.00\n",
      "Flight ID 17704 included in the schedule with penalty 0.00\n",
      "Flight ID 17705 included in the schedule with penalty 0.00\n",
      "Flight ID 17706 included in the schedule with penalty 3760.00\n",
      "Flight ID 17707 included in the schedule with penalty 2100.00\n",
      "Flight ID 17708 included in the schedule with penalty 4250.00\n",
      "Flight ID 17709 included in the schedule with penalty 0.00\n",
      "Flight ID 17710 included in the schedule with penalty 6360.00\n",
      "Flight ID 17711 included in the schedule with penalty 7400.00\n",
      "Flight ID 17712 included in the schedule with penalty 0.00\n",
      "Flight ID 17713 included in the schedule with penalty 0.00\n",
      "Flight ID 18059 included in the schedule with penalty 0.00\n",
      "Flight ID 18073 included in the schedule with penalty 0.00\n",
      "Flight ID 18120 included in the schedule with penalty 5800.00\n",
      "Flight ID 18122 included in the schedule with penalty 0.00\n",
      "Flight ID 18124 included in the schedule with penalty 0.00\n",
      "Flight ID 18125 included in the schedule with penalty 0.00\n",
      "Flight ID 18127 included in the schedule with penalty 750.00\n",
      "Flight ID 18129 included in the schedule with penalty 0.00\n",
      "Flight ID 18131 included in the schedule with penalty 0.00\n",
      "Flight ID 18132 included in the schedule with penalty 0.00\n",
      "Flight ID 18134 included in the schedule with penalty 0.00\n",
      "Flight ID 18185 included in the schedule with penalty 0.00\n",
      "Flight ID 18194 included in the schedule with penalty 850.00\n",
      "Flight ID 18196 included in the schedule with penalty 0.00\n",
      "Flight ID 18197 included in the schedule with penalty 0.00\n",
      "Flight ID 18198 included in the schedule with penalty 750.00\n",
      "Flight ID 18199 included in the schedule with penalty 2650.00\n",
      "Flight ID 18201 included in the schedule with penalty 0.00\n",
      "Flight ID 18202 included in the schedule with penalty 0.00\n",
      "Flight ID 18210 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-29 ---\n",
      "Flight ID 18307 included in the schedule with penalty 0.00\n",
      "Flight ID 18321 included in the schedule with penalty 0.00\n",
      "Flight ID 18328 included in the schedule with penalty 1300.00\n",
      "Flight ID 18330 included in the schedule with penalty 800.00\n",
      "Flight ID 18332 included in the schedule with penalty 0.00\n",
      "Flight ID 18333 included in the schedule with penalty 1900.00\n",
      "Flight ID 18334 included in the schedule with penalty 0.00\n",
      "Flight ID 18337 included in the schedule with penalty 0.00\n",
      "Flight ID 18338 included in the schedule with penalty 0.00\n",
      "Flight ID 18341 included in the schedule with penalty 0.00\n",
      "Flight ID 18342 included in the schedule with penalty 0.00\n",
      "Flight ID 18344 included in the schedule with penalty 0.00\n",
      "Flight ID 18422 included in the schedule with penalty 0.00\n",
      "Flight ID 18423 included in the schedule with penalty 4620.00\n",
      "Flight ID 18424 included in the schedule with penalty 0.00\n",
      "Flight ID 18425 included in the schedule with penalty 0.00\n",
      "Flight ID 18426 included in the schedule with penalty 0.00\n",
      "Flight ID 18427 included in the schedule with penalty 1260.00\n",
      "Flight ID 18428 included in the schedule with penalty 1200.00\n",
      "Flight ID 18429 included in the schedule with penalty 3120.00\n",
      "Flight ID 18430 included in the schedule with penalty 0.00\n",
      "Flight ID 18431 included in the schedule with penalty 0.00\n",
      "Flight ID 18774 included in the schedule with penalty 3870.00\n",
      "Flight ID 18780 included in the schedule with penalty 0.00\n",
      "Flight ID 18782 included in the schedule with penalty 0.00\n",
      "Flight ID 18787 included in the schedule with penalty 0.00\n",
      "Flight ID 18790 included in the schedule with penalty 0.00\n",
      "Flight ID 18794 included in the schedule with penalty 0.00\n",
      "Flight ID 18796 included in the schedule with penalty 0.00\n",
      "Flight ID 18803 included in the schedule with penalty 0.00\n",
      "Flight ID 18805 included in the schedule with penalty 0.00\n",
      "Flight ID 18808 included in the schedule with penalty 0.00\n",
      "Flight ID 18815 included in the schedule with penalty 3200.00\n",
      "Flight ID 18817 included in the schedule with penalty 0.00\n",
      "Flight ID 18830 included in the schedule with penalty 0.00\n",
      "Flight ID 18831 included in the schedule with penalty 0.00\n",
      "Flight ID 18832 included in the schedule with penalty 0.00\n",
      "Flight ID 18836 included in the schedule with penalty 0.00\n",
      "Flight ID 18837 included in the schedule with penalty 0.00\n",
      "Flight ID 18838 included in the schedule with penalty 0.00\n",
      "Flight ID 18839 included in the schedule with penalty 0.00\n",
      "Flight ID 18840 included in the schedule with penalty 0.00\n",
      "Flight ID 18842 included in the schedule with penalty 0.00\n",
      "Flight ID 18848 included in the schedule with penalty 0.00\n",
      "Flight ID 18857 included in the schedule with penalty 0.00\n",
      "Flight ID 18858 included in the schedule with penalty 2250.00\n",
      "Flight ID 18868 included in the schedule with penalty 0.00\n",
      "Flight ID 18878 included in the schedule with penalty 0.00\n",
      "Flight ID 18887 included in the schedule with penalty 0.00\n",
      "Flight ID 18889 included in the schedule with penalty 0.00\n",
      "Flight ID 18890 included in the schedule with penalty 0.00\n",
      "Flight ID 18891 included in the schedule with penalty 0.00\n",
      "Flight ID 18892 included in the schedule with penalty 0.00\n",
      "Flight ID 18894 included in the schedule with penalty 0.00\n",
      "Flight ID 18895 included in the schedule with penalty 0.00\n",
      "Flight ID 18903 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-30 ---\n",
      "Flight ID 18913 included in the schedule with penalty 1100.00\n",
      "Flight ID 18919 included in the schedule with penalty 0.00\n",
      "Flight ID 18921 included in the schedule with penalty 0.00\n",
      "Flight ID 18926 included in the schedule with penalty 0.00\n",
      "Flight ID 18929 included in the schedule with penalty 0.00\n",
      "Flight ID 18933 included in the schedule with penalty 2750.00\n",
      "Flight ID 18935 included in the schedule with penalty 0.00\n",
      "Flight ID 18942 included in the schedule with penalty 0.00\n",
      "Flight ID 18944 included in the schedule with penalty 800.00\n",
      "Flight ID 18947 included in the schedule with penalty 0.00\n",
      "Flight ID 18954 included in the schedule with penalty 0.00\n",
      "Flight ID 18956 included in the schedule with penalty 0.00\n",
      "Flight ID 18969 included in the schedule with penalty 0.00\n",
      "Flight ID 18970 included in the schedule with penalty 0.00\n",
      "Flight ID 18971 included in the schedule with penalty 0.00\n",
      "Flight ID 18975 included in the schedule with penalty 900.00\n",
      "Flight ID 18976 included in the schedule with penalty 0.00\n",
      "Flight ID 18977 included in the schedule with penalty 1000.00\n",
      "Flight ID 18978 included in the schedule with penalty 0.00\n",
      "Flight ID 18979 included in the schedule with penalty 0.00\n",
      "Flight ID 18981 included in the schedule with penalty 0.00\n",
      "Flight ID 18988 included in the schedule with penalty 3400.00\n",
      "Flight ID 18997 included in the schedule with penalty 0.00\n",
      "Flight ID 18998 included in the schedule with penalty 0.00\n",
      "Flight ID 19009 included in the schedule with penalty 0.00\n",
      "Flight ID 19021 included in the schedule with penalty 1650.00\n",
      "Flight ID 19030 included in the schedule with penalty 0.00\n",
      "Flight ID 19032 included in the schedule with penalty 3970.00\n",
      "Flight ID 19033 included in the schedule with penalty 0.00\n",
      "Flight ID 19034 included in the schedule with penalty 5380.00\n",
      "Flight ID 19035 included in the schedule with penalty 2000.00\n",
      "Flight ID 19037 included in the schedule with penalty 0.00\n",
      "Flight ID 19038 included in the schedule with penalty 0.00\n",
      "Flight ID 19047 included in the schedule with penalty 0.00\n",
      "Flight ID 19114 included in the schedule with penalty 4100.00\n",
      "Flight ID 19182 included in the schedule with penalty 0.00\n",
      "Flight ID 19197 included in the schedule with penalty 0.00\n",
      "Flight ID 19271 included in the schedule with penalty 0.00\n",
      "Flight ID 19272 included in the schedule with penalty 4940.00\n",
      "Flight ID 19273 included in the schedule with penalty 0.00\n",
      "Flight ID 19274 included in the schedule with penalty 0.00\n",
      "Flight ID 19275 included in the schedule with penalty 1800.00\n",
      "Flight ID 19276 included in the schedule with penalty 2160.00\n",
      "Flight ID 19277 included in the schedule with penalty 0.00\n",
      "Flight ID 19278 included in the schedule with penalty 2220.00\n",
      "Flight ID 19279 included in the schedule with penalty 0.00\n",
      "Flight ID 19280 included in the schedule with penalty 0.00\n",
      "Flight ID 19572 included in the schedule with penalty 1400.00\n",
      "Flight ID 19573 included in the schedule with penalty 0.00\n",
      "Flight ID 19574 included in the schedule with penalty 0.00\n",
      "Flight ID 19577 included in the schedule with penalty 0.00\n",
      "Flight ID 19579 included in the schedule with penalty 0.00\n",
      "Flight ID 19580 included in the schedule with penalty 1300.00\n",
      "Flight ID 19582 included in the schedule with penalty 5580.00\n",
      "Flight ID 19583 included in the schedule with penalty 0.00\n",
      "Flight ID 19586 included in the schedule with penalty 0.00\n",
      "\n",
      "\n",
      "--- Flights for 2018-08-31 ---\n",
      "Flight ID 19612 included in the schedule with penalty 0.00\n",
      "Flight ID 19618 included in the schedule with penalty 1200.00\n",
      "Flight ID 19620 included in the schedule with penalty 0.00\n",
      "Flight ID 19625 included in the schedule with penalty 0.00\n",
      "Flight ID 19628 included in the schedule with penalty 0.00\n",
      "Flight ID 19632 included in the schedule with penalty 2550.00\n",
      "Flight ID 19634 included in the schedule with penalty 0.00\n",
      "Flight ID 19641 included in the schedule with penalty 0.00\n",
      "Flight ID 19643 included in the schedule with penalty 0.00\n",
      "Flight ID 19646 included in the schedule with penalty 0.00\n",
      "Flight ID 19653 included in the schedule with penalty 0.00\n",
      "Flight ID 19655 included in the schedule with penalty 0.00\n",
      "Flight ID 19668 included in the schedule with penalty 0.00\n",
      "Flight ID 19669 included in the schedule with penalty 0.00\n",
      "Flight ID 19670 included in the schedule with penalty 800.00\n",
      "Flight ID 19674 included in the schedule with penalty 2350.00\n",
      "Flight ID 19675 included in the schedule with penalty 0.00\n",
      "Flight ID 19676 included in the schedule with penalty 0.00\n",
      "Flight ID 19677 included in the schedule with penalty 0.00\n",
      "Flight ID 19678 included in the schedule with penalty 0.00\n",
      "Flight ID 19682 included in the schedule with penalty 0.00\n",
      "Flight ID 19688 included in the schedule with penalty 0.00\n",
      "Flight ID 19697 included in the schedule with penalty 0.00\n",
      "Flight ID 19698 included in the schedule with penalty 0.00\n",
      "Flight ID 19708 included in the schedule with penalty 800.00\n",
      "Flight ID 19720 included in the schedule with penalty 0.00\n",
      "Flight ID 19729 included in the schedule with penalty 0.00\n",
      "Flight ID 19731 included in the schedule with penalty 0.00\n",
      "Flight ID 19732 included in the schedule with penalty 3780.00\n",
      "Flight ID 19733 included in the schedule with penalty 0.00\n",
      "Flight ID 19734 included in the schedule with penalty 0.00\n",
      "Flight ID 19736 included in the schedule with penalty 0.00\n",
      "Flight ID 19737 included in the schedule with penalty 0.00\n",
      "Flight ID 19746 included in the schedule with penalty 0.00\n",
      "Flight ID 19877 included in the schedule with penalty 0.00\n",
      "Flight ID 19892 included in the schedule with penalty 0.00\n",
      "Flight ID 19966 included in the schedule with penalty 0.00\n",
      "Flight ID 19967 included in the schedule with penalty 1100.00\n",
      "Flight ID 19968 included in the schedule with penalty 940.00\n",
      "Flight ID 19969 included in the schedule with penalty 0.00\n",
      "Flight ID 19970 included in the schedule with penalty 3210.00\n",
      "Flight ID 19971 included in the schedule with penalty 0.00\n",
      "Flight ID 19972 included in the schedule with penalty 6420.00\n",
      "Flight ID 19973 included in the schedule with penalty 0.00\n",
      "Flight ID 19974 included in the schedule with penalty 2040.00\n",
      "Flight ID 19975 included in the schedule with penalty 0.00\n",
      "Flight ID 20271 included in the schedule with penalty 5000.00\n",
      "Flight ID 20273 included in the schedule with penalty 0.00\n",
      "Flight ID 20275 included in the schedule with penalty 0.00\n",
      "Flight ID 20277 included in the schedule with penalty 0.00\n",
      "Flight ID 20279 included in the schedule with penalty 2300.00\n",
      "Flight ID 20281 included in the schedule with penalty 2350.00\n",
      "Flight ID 20284 included in the schedule with penalty 6040.00\n",
      "Flight ID 20285 included in the schedule with penalty 0.00\n",
      "Flight ID 20287 included in the schedule with penalty 0.00\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Solver Status:\", pulp.LpStatus[problem.status])\n",
    "for date in route_data['FL_DATE'].unique():\n",
    "    date_str = pd.Timestamp(date).strftime('%Y-%m-%d')\n",
    "    print(f\"--- Flights for {date_str} ---\")\n",
    "    for i in flight_vars[date]:\n",
    "        if flight_vars[date][i].value() == 1:\n",
    "            print(f\"Flight ID {i} included in the schedule with penalty {route_data.at[i, 'TOTAL_PENALTY']:.2f}\")\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f83a1dd4-1752-4f08-92e4-5d2f4d32cff6",
   "metadata": {},
   "source": [
    "#### Above is the optimized schedule that airline operators can use which reduces their delay based penalties as per below mentioned metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "25d036f6-a499-4266-a66a-4ac2d0813718",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Flights before optimization: 1652\n",
      "Total Flights after optimization: 1624\n",
      "Reduction in Flights in a month: 28.0\n",
      "Total Penalty Cost before optimization: $1838950.00\n",
      "Total Penalty Cost after optimization: $1468400.00\n",
      "Reduction in Penalty: $370550.00 (20.15%)\n"
     ]
    }
   ],
   "source": [
    "# Filter for the specific route\n",
    "route_data = data[(data['ORIGIN'] == origin_input) & (data['DEST'] == destination_input)]\n",
    "total_flights_before = len(route_data)  # Count flights before optimization\n",
    "\n",
    "# Calculate total penalty cost after optimization and count flights after optimization\n",
    "total_flights_after = sum(flight_vars[date][i].value() for date in route_data['FL_DATE'].unique() for i in flight_vars[date])\n",
    "total_penalty_cost_after = pulp.value(pulp.lpSum([flight_vars[date][i] * route_data.at[i, 'TOTAL_PENALTY'] for date in route_data['FL_DATE'].unique() for i in flight_vars[date]]))\n",
    "flights_reduction = total_flights_before - total_flights_after\n",
    "penalty_reduction = total_penalty_cost_before - total_penalty_cost_after\n",
    "percentage_change = (penalty_reduction / total_penalty_cost_before * 100) if total_penalty_cost_before > 0 else 0\n",
    "\n",
    "\n",
    "print(f\"Total Flights before optimization: {total_flights_before}\")\n",
    "print(f\"Total Flights after optimization: {int(total_flights_after)}\")\n",
    "print(f\"Reduction in Flights in a month: {flights_reduction}\")\n",
    "print(f\"Total Penalty Cost before optimization: ${total_penalty_cost_before:.2f}\")\n",
    "print(f\"Total Penalty Cost after optimization: ${total_penalty_cost_after:.2f}\")\n",
    "print(f\"Reduction in Penalty: ${penalty_reduction:.2f} ({percentage_change:.2f}%)\")"
   ]
  },
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    "## Flight Schedule Optimization Analysis\n",
    "\n",
    "### Optimization Results Summary\n",
    "\n",
    "The optimization model yielded the following results for the month of August 2018:\n",
    "\n",
    "- **Total Flights Before Optimization:** 1,652\n",
    "- **Total Flights After Optimization:** 1,624\n",
    "- **Reduction in Flights:** 28 flights\n",
    "\n",
    "This minimal reduction suggests that the optimization targeted flights contributing disproportionately to delays, rather than broadly reducing the number of flights.\n",
    "\n",
    "- **Total Penalty Cost Before Optimization:** \\$1,838,950\n",
    "- **Total Penalty Cost After Optimization:** \\$1,468,400\n",
    "- **Reduction in Penalty Costs:** \\$370,550 (20.15%)\n",
    "\n",
    "### Insights Derived from Optimization\n",
    "\n",
    "1. **Efficiency in Operation**: The slight decrease in total flights coupled with a significant reduction in penalty costs indicates a targeted approach in the optimization process. Flights that were frequently delayed by controllable factors were likely prioritized, thus maintaining service levels while enhancing operational efficiency.\n",
    "\n",
    "2. **Cost Management**: The substantial decrease in penalty costs highlights the effectiveness of the optimization. This demonstrates that airlines can significantly reduce operational costs related to delays by strategically managing and adjusting schedules.\n",
    "\n",
    "3. **Strategic Operational Benefits**: The results underscore the potential for airlines to improve profitability and operational performance by applying data-driven strategies to their scheduling practices. It also showcases the capability to maintain customer service quality while achieving cost efficiencies.\n",
    "\n",
    "### Conclusion\n",
    "\n",
    "The flight schedule optimization for August 2018 exemplifies how airlines can leverage optimization techniques to balance service quality with operational and financial improvements. This approach not only helps in reducing delay-related costs but also supports airlines in ma\n"
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