jupyter/Pandas_Data_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Data Analysis\n",
    "\n",
    "### Here I analyze the dataset again using Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing the pandas and csv file readers and libraries so that I can read in a view my dataset in Python rather than as the file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This code below simply shows me my dataset so that I know it imported correctly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INCIDENT_DATE</th>\n",
       "      <th>AIRPORT_ID</th>\n",
       "      <th>AIRPORT</th>\n",
       "      <th>ATYPE</th>\n",
       "      <th>SPECIES_ID</th>\n",
       "      <th>SPECIES</th>\n",
       "      <th>DAMAGE</th>\n",
       "      <th>REMAINS_COLLECTED</th>\n",
       "      <th>REMAINS_SENT</th>\n",
       "      <th>INCIDENT_MONTH</th>\n",
       "      <th>...</th>\n",
       "      <th>DISTANCE</th>\n",
       "      <th>PHASE_OF_FLT</th>\n",
       "      <th>EFFECT</th>\n",
       "      <th>SKY</th>\n",
       "      <th>PRECIP</th>\n",
       "      <th>BIRDS_SEEN</th>\n",
       "      <th>BIRDS_STRUCK</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>WARNED</th>\n",
       "      <th>REMARKS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12/14/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>B-737-800</td>\n",
       "      <td>J2204</td>\n",
       "      <td>Canada goose</td>\n",
       "      <td>M?</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>11 to 100</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>Flock of geese at our altitude. One struck the...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11/20/2017 12:00:00 AM</td>\n",
       "      <td>KPNE</td>\n",
       "      <td>NORTHEAST PHILADELPHIA ARPT</td>\n",
       "      <td>C-210 CENTUR</td>\n",
       "      <td>UNKBM</td>\n",
       "      <td>Unknown bird - medium</td>\n",
       "      <td>N</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Climb</td>\n",
       "      <td>Precautionary Landing</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Medium</td>\n",
       "      <td>N</td>\n",
       "      <td>no damage</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11/17/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>J2204</td>\n",
       "      <td>Canada goose</td>\n",
       "      <td>M?</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>Precautionary Landing</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>11 to 100</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>DENTS FUSELAGE, FLAP TRACK BEARING.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11/10/2017 12:00:00 AM</td>\n",
       "      <td>KPIT</td>\n",
       "      <td>PITTSBURGH INTL ARPT</td>\n",
       "      <td>CRJ700</td>\n",
       "      <td>UNKBL</td>\n",
       "      <td>Unknown bird - large</td>\n",
       "      <td>M?</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>None</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>Y</td>\n",
       "      <td>CRACKED RADOME POSSIBLE BENT FRAME BEHIND IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11/10/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>UNKBL</td>\n",
       "      <td>Unknown bird - large</td>\n",
       "      <td>N</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            INCIDENT_DATE AIRPORT_ID                      AIRPORT  \\\n",
       "0  12/14/2017 12:00:00 AM       KPHL            PHILADELPHIA INTL   \n",
       "1  11/20/2017 12:00:00 AM       KPNE  NORTHEAST PHILADELPHIA ARPT   \n",
       "2  11/17/2017 12:00:00 AM       KPHL            PHILADELPHIA INTL   \n",
       "3  11/10/2017 12:00:00 AM       KPIT         PITTSBURGH INTL ARPT   \n",
       "4  11/10/2017 12:00:00 AM       KPHL            PHILADELPHIA INTL   \n",
       "\n",
       "          ATYPE SPECIES_ID                SPECIES DAMAGE  REMAINS_COLLECTED  \\\n",
       "0     B-737-800      J2204           Canada goose     M?               True   \n",
       "1  C-210 CENTUR      UNKBM  Unknown bird - medium      N               True   \n",
       "2         A-321      J2204           Canada goose     M?              False   \n",
       "3        CRJ700      UNKBL   Unknown bird - large     M?              False   \n",
       "4         A-321      UNKBL   Unknown bird - large      N              False   \n",
       "\n",
       "   REMAINS_SENT  INCIDENT_MONTH  \\\n",
       "0         False              12   \n",
       "1         False              11   \n",
       "2         False              11   \n",
       "3         False              11   \n",
       "4         False              11   \n",
       "\n",
       "                         ...                          DISTANCE PHASE_OF_FLT  \\\n",
       "0                        ...                              10.0     Approach   \n",
       "1                        ...                               0.0        Climb   \n",
       "2                        ...                               NaN        Climb   \n",
       "3                        ...                               3.0     Approach   \n",
       "4                        ...                               NaN        Climb   \n",
       "\n",
       "                  EFFECT       SKY  PRECIP  BIRDS_SEEN BIRDS_STRUCK    SIZE  \\\n",
       "0                   None  No Cloud    None   11 to 100            1   Large   \n",
       "1  Precautionary Landing  No Cloud    None           1            1  Medium   \n",
       "2  Precautionary Landing  No Cloud    None   11 to 100      2 to 10   Large   \n",
       "3                   None  Overcast    None     2 to 10            1   Large   \n",
       "4                   None  No Cloud    None         NaN      2 to 10   Large   \n",
       "\n",
       "  WARNED                                            REMARKS  \n",
       "0      N  Flock of geese at our altitude. One struck the...  \n",
       "1      N                                          no damage  \n",
       "2      N                DENTS FUSELAGE, FLAP TRACK BEARING.  \n",
       "3      Y       CRACKED RADOME POSSIBLE BENT FRAME BEHIND IT  \n",
       "4      N                                                NaN  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faa_data_pandas = pd.read_csv(\"Pennsylvania_Condensed.csv\") # Bringing in the Facebook message data\n",
    "faa_data_pandas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Besides just seeing that I could properly display the data, I needed to make sure it imported the whole spreadsheet. By displaying the shape of the data I was able to see that all 6167 lines did in fact get imported. This also shows that all 25 rows did as well. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6167, 25)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faa_data_pandas.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is how you pull out just one type. This case pulls out only the instances where the Airport_ID is true for KPHL, then displays just the first few rows. I did this just to test my ability to see just certain subsets of the data. This skill is helpful when analysing the data later in the project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2267, 25)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INCIDENT_DATE</th>\n",
       "      <th>AIRPORT_ID</th>\n",
       "      <th>AIRPORT</th>\n",
       "      <th>ATYPE</th>\n",
       "      <th>SPECIES_ID</th>\n",
       "      <th>SPECIES</th>\n",
       "      <th>DAMAGE</th>\n",
       "      <th>REMAINS_COLLECTED</th>\n",
       "      <th>REMAINS_SENT</th>\n",
       "      <th>INCIDENT_MONTH</th>\n",
       "      <th>...</th>\n",
       "      <th>DISTANCE</th>\n",
       "      <th>PHASE_OF_FLT</th>\n",
       "      <th>EFFECT</th>\n",
       "      <th>SKY</th>\n",
       "      <th>PRECIP</th>\n",
       "      <th>BIRDS_SEEN</th>\n",
       "      <th>BIRDS_STRUCK</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>WARNED</th>\n",
       "      <th>REMARKS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12/14/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>B-737-800</td>\n",
       "      <td>J2204</td>\n",
       "      <td>Canada goose</td>\n",
       "      <td>M?</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>11 to 100</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>Flock of geese at our altitude. One struck the...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11/17/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>J2204</td>\n",
       "      <td>Canada goose</td>\n",
       "      <td>M?</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>Precautionary Landing</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>11 to 100</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>DENTS FUSELAGE, FLAP TRACK BEARING.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11/10/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>UNKBL</td>\n",
       "      <td>Unknown bird - large</td>\n",
       "      <td>N</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10/28/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>B-737-700</td>\n",
       "      <td>L6001</td>\n",
       "      <td>Wild turkey</td>\n",
       "      <td>N</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>Some Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>Y</td>\n",
       "      <td>LOTS OF BIRD DEBRIS BUT APPEARS WENT THROUGH E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9/20/2017 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>UNKBS</td>\n",
       "      <td>Unknown bird - small</td>\n",
       "      <td>N</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>9</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>Small</td>\n",
       "      <td>N</td>\n",
       "      <td>None seen. Just remains.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             INCIDENT_DATE AIRPORT_ID            AIRPORT      ATYPE  \\\n",
       "0   12/14/2017 12:00:00 AM       KPHL  PHILADELPHIA INTL  B-737-800   \n",
       "2   11/17/2017 12:00:00 AM       KPHL  PHILADELPHIA INTL      A-321   \n",
       "4   11/10/2017 12:00:00 AM       KPHL  PHILADELPHIA INTL      A-321   \n",
       "7   10/28/2017 12:00:00 AM       KPHL  PHILADELPHIA INTL  B-737-700   \n",
       "11   9/20/2017 12:00:00 AM       KPHL  PHILADELPHIA INTL      A-321   \n",
       "\n",
       "   SPECIES_ID               SPECIES DAMAGE  REMAINS_COLLECTED  REMAINS_SENT  \\\n",
       "0       J2204          Canada goose     M?               True         False   \n",
       "2       J2204          Canada goose     M?              False         False   \n",
       "4       UNKBL  Unknown bird - large      N              False         False   \n",
       "7       L6001           Wild turkey      N              False         False   \n",
       "11      UNKBS  Unknown bird - small      N              False         False   \n",
       "\n",
       "    INCIDENT_MONTH                        ...                          \\\n",
       "0               12                        ...                           \n",
       "2               11                        ...                           \n",
       "4               11                        ...                           \n",
       "7               10                        ...                           \n",
       "11               9                        ...                           \n",
       "\n",
       "    DISTANCE PHASE_OF_FLT                 EFFECT         SKY  PRECIP  \\\n",
       "0       10.0     Approach                   None    No Cloud    None   \n",
       "2        NaN        Climb  Precautionary Landing    No Cloud    None   \n",
       "4        NaN        Climb                   None    No Cloud    None   \n",
       "7        NaN     Approach                   None  Some Cloud    None   \n",
       "11       4.0     Approach                   None    No Cloud    None   \n",
       "\n",
       "    BIRDS_SEEN BIRDS_STRUCK   SIZE WARNED  \\\n",
       "0    11 to 100            1  Large      N   \n",
       "2    11 to 100      2 to 10  Large      N   \n",
       "4          NaN      2 to 10  Large      N   \n",
       "7            1            1  Large      Y   \n",
       "11         NaN      2 to 10  Small      N   \n",
       "\n",
       "                                              REMARKS  \n",
       "0   Flock of geese at our altitude. One struck the...  \n",
       "2                 DENTS FUSELAGE, FLAP TRACK BEARING.  \n",
       "4                                                 NaN  \n",
       "7   LOTS OF BIRD DEBRIS BUT APPEARS WENT THROUGH E...  \n",
       "11                           None seen. Just remains.  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new dataframe for the Airport ID (It does so by testing true/false on date equaling 2018-05-31)\n",
    "faa_data_phil_pandas = faa_data_pandas[faa_data_pandas['AIRPORT_ID'] == \"KPHL\"]\n",
    "\n",
    "print(faa_data_phil_pandas.shape)\n",
    "faa_data_phil_pandas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the Pandas method for counting the instances of a categorical dataset, such as in this case airport id. This below counts the dataset and each time it finds a new value in the airport field it makes a counter for it, which goes up with each time it passes an occurance. This shows me which airport has more occurances of animal strikes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PHILADELPHIA INTL                            2267\n",
      "PITTSBURGH INTL ARPT                         1611\n",
      "HARRISBURG INTL                               892\n",
      "LEHIGH VALLEY INTL                            432\n",
      "WILKES-BARRE/SCRANTON INTL                    192\n",
      "ERIE INTL ARPT-TOM RIDGE FIELD                147\n",
      "UNIVERSITY PARK ARPT                           96\n",
      "ALLEGHENY COUNTY ARPT                          83\n",
      "READING REGNL ARPT/CARL A SPAATZ FIELD         83\n",
      "NORTHEAST PHILADELPHIA ARPT                    57\n",
      "LANCASTER ARPT (PA)                            40\n",
      "WILLIAMSPORT REGIONAL ARPT                     33\n",
      "CAPITAL CITY ARPT (PA)                         29\n",
      "CHESTER COUNTY G O CARLSON ARPT                25\n",
      "ARNOLD PALMER REGIONAL                         23\n",
      "JOHN MURTHA JOHNSTOWN-CAMBRIA COUNTY ARPT      23\n",
      "DUBOIS REGIONAL ARPT                           22\n",
      "ALTOONA-BLAIR COUNTY                           21\n",
      "VENANGO REGIONAL                               13\n",
      "BEAVER COUNTY ARPT                             11\n",
      "BRADFORD REGIONAL                              10\n",
      "WASHINGTON COUNTY                              10\n",
      "WINGS FIELD ARPT                                6\n",
      "ALLENTOWN QUEEN CITY MUNICIPAL                  5\n",
      "ROSTRAVER                                       5\n",
      "ZELIENOPLE MUNICIPAL                            3\n",
      "SCHUYKILL COUNTY (JOE ZERBEY) ARPT              2\n",
      "PENNS LANDING HELIPORT                          2\n",
      "MUIR ARMY AIRFIELD                              2\n",
      "BRANDYWINE ARPT                                 2\n",
      "DECK ARPT                                       2\n",
      "PORT MEADVILLE ARPT                             2\n",
      "NEW CASTLE MUNICIPAL ARPT                       1\n",
      "MORGANTOWN ARPT                                 1\n",
      "HERITAGE FIELD ARPT                             1\n",
      "BUTLER FARM SHOW                                1\n",
      "MARIAN HELIPORT                                 1\n",
      "VANSANT                                         1\n",
      "GREEN COUNTY                                    1\n",
      "NEW GARDEN                                      1\n",
      "ALLEGHENY GEN HOSP EMERG HELIPORT               1\n",
      "FINLEYVILLE AIRPARK                             1\n",
      "POCONO MOUNTAINS MUNI ARPT                      1\n",
      "SPRING HILL ARPT                                1\n",
      "GREENSBURG JEANETTE REGIONAL ARPT               1\n",
      "YORK ARPT                                       1\n",
      "AIR HAVEN ARPT                                  1\n",
      "DOYLESTOWN ARPT                                 1\n",
      "Name: AIRPORT, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "airport_count = faa_data_pandas['AIRPORT'].value_counts()\n",
    "print(airport_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For ease of importing to my DH project, I then exported this variable into its own spreadsheet so I could then import that into my HTML code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done Writing!\n"
     ]
    }
   ],
   "source": [
    "airport_count.to_excel('airport_count.xlsx')\n",
    "print(\"Done Writing!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As before with the airport, I repeated this process with animals. This way I could see which animal was struck more often and then split out the mammals from the birds manually since there were so few."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unknown bird - small      1223\n",
      "Unknown bird - medium      887\n",
      "European starling          405\n",
      "Gulls                      343\n",
      "Mourning dove              300\n",
      "Barn swallow               208\n",
      "Unknown bird               202\n",
      "Bank swallow               199\n",
      "Sparrows                   187\n",
      "American kestrel           174\n",
      "Killdeer                   126\n",
      "Canada goose               113\n",
      "Ring-billed gull           112\n",
      "Unknown bird - large       103\n",
      "Tree swallow                97\n",
      "Swallows                    96\n",
      "Blackbirds                  82\n",
      "Horned lark                 80\n",
      "Red-tailed hawk             76\n",
      "White-tailed deer           72\n",
      "Hawks                       71\n",
      "American robin              55\n",
      "Rock pigeon                 52\n",
      "Chimney swift               48\n",
      "Eastern meadowlark          48\n",
      "Brown-headed cowbird        38\n",
      "Red-winged blackbird        38\n",
      "Ducks                       33\n",
      "Woodchuck                   25\n",
      "Big brown bat               24\n",
      "                          ... \n",
      "Common yellowthroat          1\n",
      "Black-capped chickadee       1\n",
      "American black duck          1\n",
      "Sharp-shinned hawk           1\n",
      "Nelson's sparrow             1\n",
      "Chipping sparrow             1\n",
      "American tree sparrow        1\n",
      "Cackling goose               1\n",
      "Shorebirds                   1\n",
      "New World Vultures           1\n",
      "Indigo bunting               1\n",
      "Barred owl                   1\n",
      "Mink                         1\n",
      "American wigeon              1\n",
      "Broad-winged hawk            1\n",
      "Wood thrush                  1\n",
      "Pigeons, doves               1\n",
      "Blackburnian warbler         1\n",
      "Black-bellied plover         1\n",
      "Tundra swan                  1\n",
      "American redstart            1\n",
      "Cave swallow                 1\n",
      "Egrets                       1\n",
      "Painted turtle               1\n",
      "Sanderling                   1\n",
      "Northern pintail             1\n",
      "Ruddy duck                   1\n",
      "Chestnut-sided warbler       1\n",
      "Prairie falcon               1\n",
      "Caspian tern                 1\n",
      "Name: SPECIES, Length: 184, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "species_count = faa_data_pandas['SPECIES'].value_counts()\n",
    "print(species_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here I also exported this new variable of the count to an excel spreadsheet so that I could then import this to my html code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done Writing!\n"
     ]
    }
   ],
   "source": [
    "species_count.to_excel('species_output.xlsx')\n",
    "print(\"Done Writing!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As with the species of animal and the airport I counted each datapoint of damage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N     4094\n",
      "M      205\n",
      "S      125\n",
      "M?     119\n",
      "E        3\n",
      "C        1\n",
      "D        1\n",
      "Name: DAMAGE, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "damage_count = faa_data_pandas['DAMAGE'].value_counts()\n",
    "print(damage_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the letter code within the dataset does not really tell us much. I then took the output of the damage_count vaiable from just above and ran it through code to export the answers in a more human readable format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "damage_lookup_dictionary = {\"N\": \"None\",\n",
    "                            \"M\": \"Minor\",\n",
    "                            \"M?\": \"Unknown\",\n",
    "                            \"S\": \"Substantial\",\n",
    "                            \"D\": \"Destroyed\",\n",
    "                            \"A\": \"Over $2,000,000 (Military)\",\n",
    "                            \"B\": \"$500,000 to $2,000,000 (Military)\",\n",
    "                            \"C\": \"$50,000 - $500,000 (Military)\",\n",
    "                            \"E\": \"Less than $50,000 (Military)\",\n",
    "                            \"\": \"No Damage Reported\",}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here I then run the datase through this dictionary and display the count for each value and show it by the name of the "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None                             4094\n",
       "Minor                             205\n",
       "Substantial                       125\n",
       "Unknown                           119\n",
       "Less than $50,000 (Military)        3\n",
       "$50,000 - $500,000 (Military)       1\n",
       "Destroyed                           1\n",
       "Name: DAMAGE, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faa_data_pandas[\"DAMAGE\"].value_counts().rename(index=damage_lookup_dictionary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here I used the same methods to count the damage done at each phase of the flight. This way I could see at what point during the flight the planes make contact with the animals. Later I hope to do some more complex analysis of this portion of the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Approach        2108\n",
      "Climb            909\n",
      "Landing Roll     856\n",
      "Take-off run     742\n",
      "Descent           94\n",
      "Departure         34\n",
      "Landing           22\n",
      "Taxi              10\n",
      "Local              9\n",
      "APPROACH           6\n",
      "TAKE-OFF RUN       2\n",
      "Arrival            2\n",
      "DEPARTURE          1\n",
      "Landing roll       1\n",
      "Unknown            1\n",
      "Name: PHASE_OF_FLT, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "flight_phase = faa_data_pandas['PHASE_OF_FLT'].value_counts()\n",
    "print(flight_phase)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For ease of importing to my website, I created a spreadsheet of just this variable counted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done Writing!\n"
     ]
    }
   ],
   "source": [
    "flight_phase.to_excel('flight_phase.xlsx')\n",
    "print(\"Done Writing!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Here it counts the time of day. There is a time variable, but counting it would prve to be difficult since it is simply input as an integer. Therefore for now I just analyzed the 'time of day' field. I hope to late use the time field and give a more in depth look at the information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Day      2847\n",
      "Night    1310\n",
      "Dusk      202\n",
      "Dawn      123\n",
      "Name: TIME_OF_DAY, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "time_of_day = faa_data_pandas['TIME_OF_DAY'].value_counts()\n",
    "print(time_of_day)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While I have not done anything with this portion of the data analysis for the first draft of my project. I began analysing the data as amount of damage done to the aircraft at each airport. I hope to later normalize the data against flights at each location, then combine it with this analysis to see what airport has the most destructive animals at it. Though I lack current skills to normalize the dataset, so I just did the portion that I could for now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(205, 25)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INCIDENT_DATE</th>\n",
       "      <th>AIRPORT_ID</th>\n",
       "      <th>AIRPORT</th>\n",
       "      <th>ATYPE</th>\n",
       "      <th>SPECIES_ID</th>\n",
       "      <th>SPECIES</th>\n",
       "      <th>DAMAGE</th>\n",
       "      <th>REMAINS_COLLECTED</th>\n",
       "      <th>REMAINS_SENT</th>\n",
       "      <th>INCIDENT_MONTH</th>\n",
       "      <th>...</th>\n",
       "      <th>DISTANCE</th>\n",
       "      <th>PHASE_OF_FLT</th>\n",
       "      <th>EFFECT</th>\n",
       "      <th>SKY</th>\n",
       "      <th>PRECIP</th>\n",
       "      <th>BIRDS_SEEN</th>\n",
       "      <th>BIRDS_STRUCK</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>WARNED</th>\n",
       "      <th>REMARKS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>11/17/2016 12:00:00 AM</td>\n",
       "      <td>9D4</td>\n",
       "      <td>DECK ARPT</td>\n",
       "      <td>C-177</td>\n",
       "      <td>K5114</td>\n",
       "      <td>American kestrel</td>\n",
       "      <td>M</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Climb</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Small</td>\n",
       "      <td>Y</td>\n",
       "      <td>Slight damage to the leading edge of the left ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>11/6/2016 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>UNKBM</td>\n",
       "      <td>Unknown bird - medium</td>\n",
       "      <td>M</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>Medium</td>\n",
       "      <td>N</td>\n",
       "      <td>5 miles NNW KPHL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285</th>\n",
       "      <td>8/16/2016 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-321</td>\n",
       "      <td>UNKBL</td>\n",
       "      <td>Unknown bird - large</td>\n",
       "      <td>M</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APPROACH</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>DAMAGE TO LEFT WING WITH 4 POPPED RIVETS. MOR_...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>8/15/2016 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>CRJ700</td>\n",
       "      <td>K1002</td>\n",
       "      <td>Turkey vulture</td>\n",
       "      <td>M</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Approach</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>2 to 10</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>HAS A DENT IN THE RVSM CRITICAL AREA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>4/4/2016 12:00:00 AM</td>\n",
       "      <td>KMDT</td>\n",
       "      <td>HARRISBURG INTL</td>\n",
       "      <td>EMB-145</td>\n",
       "      <td>NE1</td>\n",
       "      <td>Gulls</td>\n",
       "      <td>M</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Landing Roll</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>Medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UNDETERMINED SPECIES OF WHITE-HEADED GULL. DNA...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              INCIDENT_DATE AIRPORT_ID            AIRPORT    ATYPE SPECIES_ID  \\\n",
       "126  11/17/2016 12:00:00 AM        9D4          DECK ARPT    C-177      K5114   \n",
       "136   11/6/2016 12:00:00 AM       KPHL  PHILADELPHIA INTL    A-321      UNKBM   \n",
       "285   8/16/2016 12:00:00 AM       KPHL  PHILADELPHIA INTL    A-321      UNKBL   \n",
       "290   8/15/2016 12:00:00 AM       KPHL  PHILADELPHIA INTL   CRJ700      K1002   \n",
       "450    4/4/2016 12:00:00 AM       KMDT    HARRISBURG INTL  EMB-145        NE1   \n",
       "\n",
       "                   SPECIES DAMAGE  REMAINS_COLLECTED  REMAINS_SENT  \\\n",
       "126       American kestrel      M              False         False   \n",
       "136  Unknown bird - medium      M              False         False   \n",
       "285   Unknown bird - large      M              False         False   \n",
       "290         Turkey vulture      M              False         False   \n",
       "450                  Gulls      M               True          True   \n",
       "\n",
       "     INCIDENT_MONTH                        ...                          \\\n",
       "126              11                        ...                           \n",
       "136              11                        ...                           \n",
       "285               8                        ...                           \n",
       "290               8                        ...                           \n",
       "450               4                        ...                           \n",
       "\n",
       "     DISTANCE  PHASE_OF_FLT  EFFECT       SKY  PRECIP  BIRDS_SEEN  \\\n",
       "126       0.0         Climb    None  No Cloud    None           1   \n",
       "136       5.0      Approach    None  No Cloud    None         NaN   \n",
       "285       NaN      APPROACH    None  No Cloud    None     2 to 10   \n",
       "290       NaN      Approach    None  No Cloud    None     2 to 10   \n",
       "450       0.0  Landing Roll     NaN  Overcast     NaN         NaN   \n",
       "\n",
       "    BIRDS_STRUCK    SIZE WARNED  \\\n",
       "126            1   Small      Y   \n",
       "136      2 to 10  Medium      N   \n",
       "285            1   Large      N   \n",
       "290            1   Large      N   \n",
       "450            1  Medium    NaN   \n",
       "\n",
       "                                               REMARKS  \n",
       "126  Slight damage to the leading edge of the left ...  \n",
       "136                                   5 miles NNW KPHL  \n",
       "285  DAMAGE TO LEFT WING WITH 4 POPPED RIVETS. MOR_...  \n",
       "290              HAS A DENT IN THE RVSM CRITICAL AREA.  \n",
       "450  UNDETERMINED SPECIES OF WHITE-HEADED GULL. DNA...  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new dataframe for the Airport ID (It does so by testing true/false on date equaling 2018-05-31)\n",
    "faa_data_minor_damage_pandas = faa_data_pandas[faa_data_pandas['DAMAGE'] == \"M\"]\n",
    "\n",
    "print(faa_data_minor_damage_pandas.shape)\n",
    "faa_data_minor_damage_pandas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PHILADELPHIA INTL                            72\n",
       "PITTSBURGH INTL ARPT                         25\n",
       "HARRISBURG INTL                              18\n",
       "LEHIGH VALLEY INTL                           10\n",
       "NORTHEAST PHILADELPHIA ARPT                   9\n",
       "READING REGNL ARPT/CARL A SPAATZ FIELD        9\n",
       "ERIE INTL ARPT-TOM RIDGE FIELD                7\n",
       "ALLEGHENY COUNTY ARPT                         6\n",
       "WILLIAMSPORT REGIONAL ARPT                    5\n",
       "ALTOONA-BLAIR COUNTY                          4\n",
       "CAPITAL CITY ARPT (PA)                        4\n",
       "WILKES-BARRE/SCRANTON INTL                    4\n",
       "WASHINGTON COUNTY                             3\n",
       "LANCASTER ARPT (PA)                           3\n",
       "ROSTRAVER                                     2\n",
       "WINGS FIELD ARPT                              2\n",
       "CHESTER COUNTY G O CARLSON ARPT               2\n",
       "ZELIENOPLE MUNICIPAL                          2\n",
       "JOHN MURTHA JOHNSTOWN-CAMBRIA COUNTY ARPT     2\n",
       "ALLENTOWN QUEEN CITY MUNICIPAL                1\n",
       "UNIVERSITY PARK ARPT                          1\n",
       "VENANGO REGIONAL                              1\n",
       "GREENSBURG JEANETTE REGIONAL ARPT             1\n",
       "BRADFORD REGIONAL                             1\n",
       "HERITAGE FIELD ARPT                           1\n",
       "MUIR ARMY AIRFIELD                            1\n",
       "BEAVER COUNTY ARPT                            1\n",
       "SCHUYKILL COUNTY (JOE ZERBEY) ARPT            1\n",
       "FINLEYVILLE AIRPARK                           1\n",
       "DECK ARPT                                     1\n",
       "ARNOLD PALMER REGIONAL                        1\n",
       "BUTLER FARM SHOW                              1\n",
       "DUBOIS REGIONAL ARPT                          1\n",
       "ALLEGHENY GEN HOSP EMERG HELIPORT             1\n",
       "NEW GARDEN                                    1\n",
       "Name: AIRPORT, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faa_data_minor_damage_pandas['AIRPORT'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(125, 25)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INCIDENT_DATE</th>\n",
       "      <th>AIRPORT_ID</th>\n",
       "      <th>AIRPORT</th>\n",
       "      <th>ATYPE</th>\n",
       "      <th>SPECIES_ID</th>\n",
       "      <th>SPECIES</th>\n",
       "      <th>DAMAGE</th>\n",
       "      <th>REMAINS_COLLECTED</th>\n",
       "      <th>REMAINS_SENT</th>\n",
       "      <th>INCIDENT_MONTH</th>\n",
       "      <th>...</th>\n",
       "      <th>DISTANCE</th>\n",
       "      <th>PHASE_OF_FLT</th>\n",
       "      <th>EFFECT</th>\n",
       "      <th>SKY</th>\n",
       "      <th>PRECIP</th>\n",
       "      <th>BIRDS_SEEN</th>\n",
       "      <th>BIRDS_STRUCK</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>WARNED</th>\n",
       "      <th>REMARKS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>4/11/2016 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>B-737-700</td>\n",
       "      <td>UNKBL</td>\n",
       "      <td>Unknown bird - large</td>\n",
       "      <td>S</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Take-off run</td>\n",
       "      <td>Precautionary Landing</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BIRD REPORTED AS \"EAGLE/LARGE BIRD OF PREY.\" N...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>12/13/2015 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>A-330</td>\n",
       "      <td>J2202</td>\n",
       "      <td>Snow goose</td>\n",
       "      <td>S</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>Precautionary Landing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASSUME ONE STRUCK. PILOT SAW A WHITE FLASH ARO...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>648</th>\n",
       "      <td>8/2/2015 12:00:00 AM</td>\n",
       "      <td>KPHL</td>\n",
       "      <td>PHILADELPHIA INTL</td>\n",
       "      <td>EMB-170</td>\n",
       "      <td>NE1</td>\n",
       "      <td>Gulls</td>\n",
       "      <td>S</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Climb</td>\n",
       "      <td>None</td>\n",
       "      <td>No Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Medium</td>\n",
       "      <td>N</td>\n",
       "      <td>LEFT FRONT SIDE OF NOSE CONE HAS A DENT. AIRCR...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>807</th>\n",
       "      <td>3/19/2015 12:00:00 AM</td>\n",
       "      <td>KMDT</td>\n",
       "      <td>HARRISBURG INTL</td>\n",
       "      <td>EMB-170</td>\n",
       "      <td>NE104</td>\n",
       "      <td>Ring-billed gull</td>\n",
       "      <td>S</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>Precautionary Landing</td>\n",
       "      <td>Some Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Medium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DURING T/O THERE WAS A LOUD SOUND AFTER BRINGI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>8/20/2014 12:00:00 AM</td>\n",
       "      <td>KMPO</td>\n",
       "      <td>POCONO MOUNTAINS MUNI ARPT</td>\n",
       "      <td>PA-31 NAVAJO</td>\n",
       "      <td>1G11</td>\n",
       "      <td>White-tailed deer</td>\n",
       "      <td>S</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Landing Roll</td>\n",
       "      <td>None</td>\n",
       "      <td>Some Cloud</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>Large</td>\n",
       "      <td>N</td>\n",
       "      <td>RT NOSE GEAR DOOR SERIOUSLY DAMAGED. 1 SMALL B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               INCIDENT_DATE AIRPORT_ID                     AIRPORT  \\\n",
       "445    4/11/2016 12:00:00 AM       KPHL           PHILADELPHIA INTL   \n",
       "482   12/13/2015 12:00:00 AM       KPHL           PHILADELPHIA INTL   \n",
       "648     8/2/2015 12:00:00 AM       KPHL           PHILADELPHIA INTL   \n",
       "807    3/19/2015 12:00:00 AM       KMDT             HARRISBURG INTL   \n",
       "1010   8/20/2014 12:00:00 AM       KMPO  POCONO MOUNTAINS MUNI ARPT   \n",
       "\n",
       "             ATYPE SPECIES_ID               SPECIES DAMAGE  REMAINS_COLLECTED  \\\n",
       "445      B-737-700      UNKBL  Unknown bird - large      S               True   \n",
       "482          A-330      J2202            Snow goose      S               True   \n",
       "648        EMB-170        NE1                 Gulls      S              False   \n",
       "807        EMB-170      NE104      Ring-billed gull      S               True   \n",
       "1010  PA-31 NAVAJO       1G11     White-tailed deer      S               True   \n",
       "\n",
       "      REMAINS_SENT  INCIDENT_MONTH  \\\n",
       "445          False               4   \n",
       "482           True              12   \n",
       "648          False               8   \n",
       "807          False               3   \n",
       "1010         False               8   \n",
       "\n",
       "                            ...                          DISTANCE  \\\n",
       "445                         ...                               0.0   \n",
       "482                         ...                               NaN   \n",
       "648                         ...                               1.0   \n",
       "807                         ...                               NaN   \n",
       "1010                        ...                               0.0   \n",
       "\n",
       "      PHASE_OF_FLT                 EFFECT         SKY  PRECIP  BIRDS_SEEN  \\\n",
       "445   Take-off run  Precautionary Landing    No Cloud    None           1   \n",
       "482          Climb  Precautionary Landing         NaN     NaN           1   \n",
       "648          Climb                   None    No Cloud    None           1   \n",
       "807          Climb  Precautionary Landing  Some Cloud    None           1   \n",
       "1010  Landing Roll                   None  Some Cloud    None         NaN   \n",
       "\n",
       "     BIRDS_STRUCK    SIZE WARNED  \\\n",
       "445             1   Large    NaN   \n",
       "482             1   Large    NaN   \n",
       "648             1  Medium      N   \n",
       "807             1  Medium    NaN   \n",
       "1010            1   Large      N   \n",
       "\n",
       "                                                REMARKS  \n",
       "445   BIRD REPORTED AS \"EAGLE/LARGE BIRD OF PREY.\" N...  \n",
       "482   ASSUME ONE STRUCK. PILOT SAW A WHITE FLASH ARO...  \n",
       "648   LEFT FRONT SIDE OF NOSE CONE HAS A DENT. AIRCR...  \n",
       "807   DURING T/O THERE WAS A LOUD SOUND AFTER BRINGI...  \n",
       "1010  RT NOSE GEAR DOOR SERIOUSLY DAMAGED. 1 SMALL B...  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new dataframe for the Airport ID (It does so by testing true/false on date equaling 2018-05-31)\n",
    "faa_data_substantial_damage_pandas = faa_data_pandas[faa_data_pandas['DAMAGE'] == \"S\"]\n",
    "\n",
    "print(faa_data_substantial_damage_pandas.shape)\n",
    "faa_data_substantial_damage_pandas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 25)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INCIDENT_DATE</th>\n",
       "      <th>AIRPORT_ID</th>\n",
       "      <th>AIRPORT</th>\n",
       "      <th>ATYPE</th>\n",
       "      <th>SPECIES_ID</th>\n",
       "      <th>SPECIES</th>\n",
       "      <th>DAMAGE</th>\n",
       "      <th>REMAINS_COLLECTED</th>\n",
       "      <th>REMAINS_SENT</th>\n",
       "      <th>INCIDENT_MONTH</th>\n",
       "      <th>...</th>\n",
       "      <th>DISTANCE</th>\n",
       "      <th>PHASE_OF_FLT</th>\n",
       "      <th>EFFECT</th>\n",
       "      <th>SKY</th>\n",
       "      <th>PRECIP</th>\n",
       "      <th>BIRDS_SEEN</th>\n",
       "      <th>BIRDS_STRUCK</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>WARNED</th>\n",
       "      <th>REMARKS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3203</th>\n",
       "      <td>3/6/2009 12:00:00 AM</td>\n",
       "      <td>KAVP</td>\n",
       "      <td>WILKES-BARRE/SCRANTON INTL</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>J2204</td>\n",
       "      <td>Canada goose</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Climb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Large</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             INCIDENT_DATE AIRPORT_ID                     AIRPORT    ATYPE  \\\n",
       "3203  3/6/2009 12:00:00 AM       KAVP  WILKES-BARRE/SCRANTON INTL  UNKNOWN   \n",
       "\n",
       "     SPECIES_ID       SPECIES DAMAGE  REMAINS_COLLECTED  REMAINS_SENT  \\\n",
       "3203      J2204  Canada goose      D              False         False   \n",
       "\n",
       "      INCIDENT_MONTH   ...    DISTANCE PHASE_OF_FLT  EFFECT  SKY  PRECIP  \\\n",
       "3203               3   ...         NaN        Climb     NaN  NaN     NaN   \n",
       "\n",
       "      BIRDS_SEEN BIRDS_STRUCK   SIZE WARNED REMARKS  \n",
       "3203         NaN          NaN  Large    NaN     NaN  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new dataframe for the (It does so by testing true/false on date equaling 2018-05-31)\n",
    "faa_data_destroyed_damage_pandas = faa_data_pandas[faa_data_pandas['DAMAGE'] == \"D\"]\n",
    "\n",
    "print(faa_data_destroyed_damage_pandas.shape)\n",
    "faa_data_destroyed_damage_pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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