ADS-Exploratory-Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import pylab\n",
    "import scipy.stats as stats\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\yusef\\appdata\\local\\programs\\python\\python36-32\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2728: DtypeWarning: Columns (2,4,8,9,10,11,14,15,16,17,18,20,21,22,23,24,25,26,29,32,33,34,35) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               EVENT_TYPE CZ_TYPE CZ_FIPS     CZ_NAME  WFO  \\\n",
      "0                 Tornado       C     149     WASHITA  NaN   \n",
      "1                 Tornado       C      93    COMANCHE  NaN   \n",
      "2                 Tornado       C      77      LEHIGH  NaN   \n",
      "3                 Tornado       C      43     DAUPHIN  NaN   \n",
      "4                 Tornado       C      39    CRAWFORD  NaN   \n",
      "5                 Tornado       C      17       BUCKS  NaN   \n",
      "6                 Tornado       C      71   LANCASTER  NaN   \n",
      "7                 Tornado       C      11       BERKS  NaN   \n",
      "8                 Tornado       C      63      HUGHES  NaN   \n",
      "9                 Tornado       C     121   PITTSBURG  NaN   \n",
      "10                Tornado       C      25    CIMARRON  NaN   \n",
      "11                Tornado       C     129    NUCKOLLS  NaN   \n",
      "12                Tornado       C     109    OKLAHOMA  NaN   \n",
      "13                Tornado       C     121   PITTSBURG  NaN   \n",
      "14                Tornado       C      81     LINCOLN  NaN   \n",
      "15                Tornado       C     143       TULSA  NaN   \n",
      "16                Tornado       C      75       KIOWA  NaN   \n",
      "17                Tornado       C      75       KIOWA  NaN   \n",
      "18                Tornado       C      63      HUGHES  NaN   \n",
      "19                Tornado       C      29        COAL  NaN   \n",
      "20                Tornado       C      39      CUSTER  NaN   \n",
      "21                Tornado       C       9     BECKHAM  NaN   \n",
      "22                Tornado       C     153    WOODWARD  NaN   \n",
      "23                Tornado       C      45       ELLIS  NaN   \n",
      "24                Tornado       C     119       PAYNE  NaN   \n",
      "25                Tornado       C      73  KINGFISHER  NaN   \n",
      "26                Tornado       C     121      RANKIN  NaN   \n",
      "27                Tornado       C     121      RANKIN  NaN   \n",
      "28                Tornado       C      25        CLAY  NaN   \n",
      "29                Tornado       C     141  TISHOMINGO  NaN   \n",
      "...                   ...     ...     ...         ...  ...   \n",
      "973086              Flood       C      69     FLEMING  JKL   \n",
      "973087        Flash Flood       C      23  SANTA CRUZ  TWC   \n",
      "973088  Thunderstorm Wind       C      77     GREELEY  GID   \n",
      "973089               Hail       C      77     GREELEY  GID   \n",
      "973090  Thunderstorm Wind       C      35     FORREST  JAN   \n",
      "973091  Thunderstorm Wind       C      53   HUMPHREYS  JAN   \n",
      "973092        Flash Flood       C      35     FORREST  JAN   \n",
      "973093  Thunderstorm Wind       C      29      COPIAH  JAN   \n",
      "973094  Thunderstorm Wind       C      85     LINCOLN  JAN   \n",
      "973095        Flash Flood       C      43    HERKIMER  ALY   \n",
      "973096        Flash Flood       C      43    HERKIMER  ALY   \n",
      "973097  Thunderstorm Wind       C     211    HEMPHILL  AMA   \n",
      "973098               Hail       C      65      CARSON  AMA   \n",
      "973099               Hail       C     179        GRAY  AMA   \n",
      "973100              Flood       C      17   MIDDLESEX  BOX   \n",
      "973101               Hail       C     175      VALLEY  GID   \n",
      "973102        Flash Flood       C      43    HERKIMER  ALY   \n",
      "973103  Thunderstorm Wind       C      59     JACKSON  LIX   \n",
      "973104        Flash Flood       C      85     LINCOLN  JAN   \n",
      "973105  Thunderstorm Wind       C      19        PIMA  TWC   \n",
      "973106  Thunderstorm Wind       C     141      PENDER  ILM   \n",
      "973107               Hail       C      31      CORSON  ABR   \n",
      "973108               Hail       C      45     EDMUNDS  ABR   \n",
      "973109               Hail       C      13       BROWN  ABR   \n",
      "973110               Hail       C      41        CLAY  FSD   \n",
      "973111               Hail       C     119        LYON  FSD   \n",
      "973112               Hail       C     143     OSCEOLA  FSD   \n",
      "973113  Thunderstorm Wind       C      73   SAN DIEGO  SGX   \n",
      "973114        Flash Flood       C      73   SAN DIEGO  SGX   \n",
      "973115        Flash Flood       C      73   SAN DIEGO  SGX   \n",
      "\n",
      "           BEGIN_DATE_TIME CZ_TIMEZONE       END_DATE_TIME INJURIES_DIRECT  \\\n",
      "0       28-APR-50 14:45:00         CST  28-APR-50 14:45:00               0   \n",
      "1       29-APR-50 15:30:00         CST  29-APR-50 15:30:00               0   \n",
      "2       05-JUL-50 18:00:00         CST  05-JUL-50 18:00:00               2   \n",
      "3       05-JUL-50 18:30:00         CST  05-JUL-50 18:30:00               0   \n",
      "4       24-JUL-50 14:40:00         CST  24-JUL-50 14:40:00               0   \n",
      "5       29-AUG-50 16:00:00         CST  29-AUG-50 16:00:00               0   \n",
      "6       04-NOV-50 17:00:00         CST  04-NOV-50 17:00:00               1   \n",
      "7       04-NOV-50 17:30:00         CST  04-NOV-50 17:30:00               0   \n",
      "8       15-SEP-50 17:45:00         CST  15-SEP-50 17:45:00               6   \n",
      "9       16-SEP-50 01:30:00         CST  16-SEP-50 01:30:00               0   \n",
      "10      01-OCT-50 21:00:00         CST  01-OCT-50 21:00:00               0   \n",
      "11      22-JUN-50 21:00:00         CST  22-JUN-50 21:00:00               0   \n",
      "12      27-FEB-50 10:20:00         CST  27-FEB-50 10:20:00               0   \n",
      "13      27-MAR-50 03:00:00         CST  27-MAR-50 03:00:00               0   \n",
      "14      02-APR-50 18:00:00         CST  02-APR-50 18:00:00               0   \n",
      "15      03-APR-50 16:15:00         CST  03-APR-50 16:15:00               0   \n",
      "16      28-APR-50 14:17:00         CST  28-APR-50 14:17:00               1   \n",
      "17      28-APR-50 14:35:00         CST  28-APR-50 14:35:00               0   \n",
      "18      28-APR-50 19:05:00         CST  28-APR-50 19:05:00              32   \n",
      "19      28-APR-50 19:30:00         CST  28-APR-50 19:30:00               0   \n",
      "20      04-MAY-50 21:30:00         CST  04-MAY-50 21:30:00               0   \n",
      "21      04-MAY-50 21:30:00         CST  04-MAY-50 21:30:00               0   \n",
      "22      04-MAY-50 21:45:00         CST  04-MAY-50 21:45:00               0   \n",
      "23      07-MAY-50 18:30:00         CST  07-MAY-50 18:30:00               0   \n",
      "24      07-MAY-50 23:00:00         CST  07-MAY-50 23:00:00               0   \n",
      "25      07-MAY-50 23:00:00         CST  07-MAY-50 23:00:00               3   \n",
      "26      27-MAR-50 08:00:00         CST  27-MAR-50 08:00:00               0   \n",
      "27      27-MAR-50 08:05:00         CST  27-MAR-50 08:05:00               0   \n",
      "28      27-MAR-50 08:45:00         CST  27-MAR-50 08:45:00               0   \n",
      "29      27-MAR-50 11:00:00         CST  27-MAR-50 11:00:00               2   \n",
      "...                    ...         ...                 ...             ...   \n",
      "973086  23-JUL-17 02:40:00       EST-5  23-JUL-17 04:30:00               0   \n",
      "973087  17-JUL-17 05:30:00       MST-7  17-JUL-17 06:05:00               0   \n",
      "973088  08-JUL-17 17:11:00       CST-6  08-JUL-17 17:11:00               0   \n",
      "973089  08-JUL-17 17:40:00       CST-6  08-JUL-17 17:40:00               0   \n",
      "973090  07-JUL-17 16:10:00       CST-6  07-JUL-17 16:10:00               0   \n",
      "973091  08-JUL-17 08:28:00       CST-6  08-JUL-17 08:28:00               0   \n",
      "973092  24-JUL-17 07:02:00       CST-6  24-JUL-17 09:15:00               0   \n",
      "973093  24-JUL-17 09:40:00       CST-6  24-JUL-17 09:47:00               0   \n",
      "973094  24-JUL-17 10:18:00       CST-6  24-JUL-17 10:18:00               0   \n",
      "973095  01-JUL-17 12:00:00       EST-5  01-JUL-17 15:30:00               0   \n",
      "973096  01-JUL-17 15:00:00       EST-5  01-JUL-17 15:30:00               0   \n",
      "973097  03-JUL-17 18:24:00       CST-6  03-JUL-17 18:24:00               0   \n",
      "973098  03-JUL-17 19:05:00       CST-6  03-JUL-17 19:05:00               0   \n",
      "973099  03-JUL-17 19:43:00       CST-6  03-JUL-17 19:43:00               0   \n",
      "973100  12-JUL-17 17:00:00       EST-5  12-JUL-17 22:00:00               0   \n",
      "973101  02-JUL-17 15:20:00       CST-6  02-JUL-17 15:20:00               0   \n",
      "973102  01-JUL-17 15:10:00       EST-5  01-JUL-17 15:30:00               0   \n",
      "973103  25-JUL-17 12:00:00       CST-6  25-JUL-17 12:00:00               0   \n",
      "973104  25-JUL-17 07:27:00       CST-6  25-JUL-17 09:15:00               0   \n",
      "973105  13-JUL-17 19:25:00       MST-7  13-JUL-17 19:35:00               0   \n",
      "973106  06-JUL-17 13:30:00       EST-5  06-JUL-17 13:31:00               0   \n",
      "973107  05-JUL-17 16:20:00       MST-7  05-JUL-17 16:20:00               0   \n",
      "973108  05-JUL-17 17:26:00       CST-6  05-JUL-17 17:26:00               0   \n",
      "973109  05-JUL-17 17:48:00       CST-6  05-JUL-17 17:48:00               0   \n",
      "973110  21-AUG-17 01:05:00       CST-6  21-AUG-17 01:05:00               0   \n",
      "973111  21-AUG-17 10:48:00       CST-6  21-AUG-17 10:48:00               0   \n",
      "973112  21-AUG-17 10:57:00       CST-6  21-AUG-17 10:57:00               0   \n",
      "973113  12-AUG-17 16:25:00       PST-8  12-AUG-17 16:35:00               0   \n",
      "973114  12-AUG-17 16:30:00       PST-8  12-AUG-17 17:30:00               0   \n",
      "973115  12-AUG-17 16:10:00       PST-8  12-AUG-17 18:00:00               0   \n",
      "\n",
      "       INJURIES_INDIRECT   ...    BEGIN_RANGE BEGIN_AZIMUTH  \\\n",
      "0                      0   ...              0           NaN   \n",
      "1                      0   ...              0           NaN   \n",
      "2                      0   ...              0           NaN   \n",
      "3                      0   ...              0           NaN   \n",
      "4                      0   ...              0           NaN   \n",
      "5                      0   ...              0           NaN   \n",
      "6                      0   ...              0           NaN   \n",
      "7                      0   ...              0           NaN   \n",
      "8                      0   ...              0           NaN   \n",
      "9                      0   ...              0           NaN   \n",
      "10                     0   ...              0           NaN   \n",
      "11                     0   ...              0           NaN   \n",
      "12                     0   ...              0           NaN   \n",
      "13                     0   ...              0           NaN   \n",
      "14                     0   ...              0           NaN   \n",
      "15                     0   ...              0           NaN   \n",
      "16                     0   ...              0           NaN   \n",
      "17                     0   ...              0           NaN   \n",
      "18                     0   ...              0           NaN   \n",
      "19                     0   ...              0           NaN   \n",
      "20                     0   ...              0           NaN   \n",
      "21                     0   ...              0           NaN   \n",
      "22                     0   ...              0           NaN   \n",
      "23                     0   ...              0           NaN   \n",
      "24                     0   ...              0           NaN   \n",
      "25                     0   ...              0           NaN   \n",
      "26                     0   ...              0           NaN   \n",
      "27                     0   ...              0           NaN   \n",
      "28                     0   ...              0           NaN   \n",
      "29                     0   ...              0           NaN   \n",
      "...                  ...   ...            ...           ...   \n",
      "973086                 0   ...              1           WSW   \n",
      "973087                 0   ...              1           WSW   \n",
      "973088                 0   ...              0             N   \n",
      "973089                 0   ...              1             E   \n",
      "973090                 0   ...              1            SE   \n",
      "973091                 0   ...              1             S   \n",
      "973092                 0   ...              4           SSW   \n",
      "973093                 0   ...              2           SSW   \n",
      "973094                 0   ...              4           WSW   \n",
      "973095                 0   ...              1            SE   \n",
      "973096                 0   ...              3            NW   \n",
      "973097                 0   ...              6           ENE   \n",
      "973098                 0   ...              1             E   \n",
      "973099                 0   ...              1           NNE   \n",
      "973100                 0   ...              1            SW   \n",
      "973101                 0   ...              5           ENE   \n",
      "973102                 0   ...              1           NNW   \n",
      "973103                 0   ...              1           SSW   \n",
      "973104                 0   ...              2           WNW   \n",
      "973105                 0   ...              2            SW   \n",
      "973106                 0   ...              1            NW   \n",
      "973107                 0   ...              5           ESE   \n",
      "973108                 0   ...              3           NNE   \n",
      "973109                 0   ...              0             E   \n",
      "973110                 0   ...              3           ENE   \n",
      "973111                 0   ...              1             E   \n",
      "973112                 0   ...              2             E   \n",
      "973113                 0   ...              4            SE   \n",
      "973114                 0   ...              3            SE   \n",
      "973115                 0   ...              8             S   \n",
      "\n",
      "              BEGIN_LOCATION END_RANGE END_AZIMUTH          END_LOCATION  \\\n",
      "0                        NaN         0         NaN                   NaN   \n",
      "1                        NaN         0         NaN                   NaN   \n",
      "2                        NaN         0         NaN                   NaN   \n",
      "3                        NaN         0         NaN                   NaN   \n",
      "4                        NaN         0         NaN                   NaN   \n",
      "5                        NaN         0         NaN                   NaN   \n",
      "6                        NaN         0         NaN                   NaN   \n",
      "7                        NaN         0         NaN                   NaN   \n",
      "8                        NaN         0         NaN                   NaN   \n",
      "9                        NaN         0         NaN                   NaN   \n",
      "10                       NaN         0         NaN                   NaN   \n",
      "11                       NaN         0         NaN                   NaN   \n",
      "12                       NaN         0         NaN                   NaN   \n",
      "13                       NaN         0         NaN                   NaN   \n",
      "14                       NaN         0         NaN                   NaN   \n",
      "15                       NaN         0         NaN                   NaN   \n",
      "16                       NaN         0         NaN                   NaN   \n",
      "17                       NaN         0         NaN                   NaN   \n",
      "18                       NaN         0         NaN                   NaN   \n",
      "19                       NaN         0         NaN                   NaN   \n",
      "20                       NaN         0         NaN                   NaN   \n",
      "21                       NaN         0         NaN                   NaN   \n",
      "22                       NaN         0         NaN                   NaN   \n",
      "23                       NaN         0         NaN                   NaN   \n",
      "24                       NaN         0         NaN                   NaN   \n",
      "25                       NaN         0         NaN                   NaN   \n",
      "26                       NaN         0         NaN                   NaN   \n",
      "27                       NaN         0         NaN                   NaN   \n",
      "28                       NaN         0         NaN                   NaN   \n",
      "29                       NaN         0         NaN                   NaN   \n",
      "...                      ...       ...         ...                   ...   \n",
      "973086     FLEMINGSBURG ARPT         0          SW     FLEMINGSBURG ARPT   \n",
      "973087               NOGALES         1         WSW               NOGALES   \n",
      "973088               WOLBACH         0           N               WOLBACH   \n",
      "973089                SCOTIA         1           E                SCOTIA   \n",
      "973090                 MAXIE         1          SE                 MAXIE   \n",
      "973091               BELZONI         1           S               BELZONI   \n",
      "973092                CARNES         4         SSW                CARNES   \n",
      "973093            HAZLEHURST         1           N            HAZLEHURST   \n",
      "973094             NEW SIGHT         4         WSW             NEW SIGHT   \n",
      "973095               NEWPORT         1         SSE               NEWPORT   \n",
      "973096            EATONVILLE         3           S           MIDDLEFIELD   \n",
      "973097              CANADIAN         6         ENE              CANADIAN   \n",
      "973098            SKELLYTOWN         1           E            SKELLYTOWN   \n",
      "973099                 PAMPA         1         NNE                 PAMPA   \n",
      "973100  (BED)HANSCOM FLD BED         1          SW  (BED)HANSCOM FLD BED   \n",
      "973101                   ORD         5         ENE                   ORD   \n",
      "973102         WEST SCHUYLER         2           W                HARBOR   \n",
      "973103       OCEAN SPGS ARPT         1         SSW       OCEAN SPGS ARPT   \n",
      "973104  BROOKHAVEN MUNI ARPT         1         WSW  BROOKHAVEN MUNI ARPT   \n",
      "973105             GREEN VLY         1           N           CONTINENTAL   \n",
      "973106              WOODSIDE         1          NW              WOODSIDE   \n",
      "973107               WAKPALA         5         ESE               WAKPALA   \n",
      "973108                  MINA         3         NNE                  MINA   \n",
      "973109                  BATH         0           E                  BATH   \n",
      "973110               DICKENS         3         ENE               DICKENS   \n",
      "973111           ROCK RAPIDS         1           E           ROCK RAPIDS   \n",
      "973112                SIBLEY         2           E                SIBLEY   \n",
      "973113    AGUA CALIENTE SPGS         5          SE    AGUA CALIENTE SPGS   \n",
      "973114    AGUA CALIENTE SPGS         5          SE    AGUA CALIENTE SPGS   \n",
      "973115        OCOTILLO WELLS         5          NE    AGUA CALIENTE SPGS   \n",
      "\n",
      "       BEGIN_LAT BEGIN_LON  END_LAT  END_LON  \n",
      "0          35.12    -99.20    35.17   -99.20  \n",
      "1          31.90    -98.60    31.73   -98.60  \n",
      "2          40.58    -75.70    40.65   -75.47  \n",
      "3          40.60    -76.75      NaN      NaN  \n",
      "4          41.63    -79.68      NaN      NaN  \n",
      "5          40.22    -75.00      NaN      NaN  \n",
      "6          40.20    -76.12    40.27   -76.07  \n",
      "7          40.27    -76.07    40.40   -75.93  \n",
      "8          35.00    -96.25    35.07   -96.17  \n",
      "9          34.83    -95.85      NaN      NaN  \n",
      "10         36.73   -102.52    36.88  -102.30  \n",
      "11         40.18    -98.03    40.20   -97.98  \n",
      "12         35.55    -97.60      NaN      NaN  \n",
      "13         34.85    -95.75      NaN      NaN  \n",
      "14         35.82    -97.02      NaN      NaN  \n",
      "15         36.13    -95.83      NaN      NaN  \n",
      "16         34.88    -99.28    35.00   -99.20  \n",
      "17         35.00    -99.20    35.12   -99.20  \n",
      "18         35.08    -96.40    35.13   -96.35  \n",
      "19         34.55    -96.20      NaN      NaN  \n",
      "20         35.58    -99.17      NaN      NaN  \n",
      "21         35.25    -99.55    35.32   -99.50  \n",
      "22         36.57    -99.57      NaN      NaN  \n",
      "23         36.30    -99.80      NaN      NaN  \n",
      "24         36.00    -97.00      NaN      NaN  \n",
      "25         36.12    -97.83    36.17   -97.78  \n",
      "26         32.30    -90.12    32.98   -89.82  \n",
      "27         32.30    -90.17    32.48   -89.78  \n",
      "28         33.67    -88.78    33.72   -88.73  \n",
      "29         34.73    -88.27      NaN      NaN  \n",
      "...          ...       ...      ...      ...  \n",
      "973086   38.4269   -83.742  38.4271 -83.7347  \n",
      "973087   31.3416  -110.951  31.3415 -110.951  \n",
      "973088      41.4     -98.4     41.4    -98.4  \n",
      "973089     41.47  -98.7007    41.47 -98.7007  \n",
      "973090     30.96    -89.19    30.96   -89.19  \n",
      "973091     33.17     -90.5    33.17    -90.5  \n",
      "973092     30.92    -89.29  30.9237 -89.3015  \n",
      "973093     31.84    -90.41    31.89    -90.4  \n",
      "973094   31.6173  -90.5096  31.6173 -90.5096  \n",
      "973095   43.1644  -75.0016  43.1645 -75.0068  \n",
      "973096     43.11    -74.98  43.1115 -74.9886  \n",
      "973097     35.92   -100.28    35.92  -100.28  \n",
      "973098     35.57   -101.17    35.57  -101.17  \n",
      "973099     35.55   -100.96    35.55  -100.96  \n",
      "973100   42.4637  -71.2925  42.4636 -71.2904  \n",
      "973101   41.6277  -98.8406  41.6277 -98.8406  \n",
      "973102   43.1083  -75.1561   43.083 -75.1884  \n",
      "973103    30.371  -88.7567   30.371 -88.7567  \n",
      "973104   31.6087  -90.4256  31.5932 -90.4168  \n",
      "973105   31.8849  -110.995  31.8611 -110.978  \n",
      "973106   34.4283  -77.6802  34.4286 -77.6803  \n",
      "973107     45.65   -100.44    45.65  -100.44  \n",
      "973108     45.47    -98.75    45.47   -98.75  \n",
      "973109     45.47    -98.32    45.47   -98.32  \n",
      "973110     43.14    -94.97    43.14   -94.97  \n",
      "973111     43.43    -96.17    43.43   -96.17  \n",
      "973112      43.4    -95.73     43.4   -95.73  \n",
      "973113   32.9156  -116.244  32.9008 -116.239  \n",
      "973114   32.9181  -116.254  32.8959 -116.253  \n",
      "973115   33.0425  -116.105  32.9962 -116.231  \n",
      "\n",
      "[973116 rows x 36 columns]\n"
     ]
    }
   ],
   "source": [
    "folderPath = r\"C:\\Users\\Yusef\\AdvancedDataScience\\BW_Analysis\\Storm_allyears.csv\"\n",
    "df = pd.read_csv(folderPath) \n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['EVENT_TYPE', 'CZ_TYPE', 'CZ_FIPS', 'CZ_NAME', 'WFO', 'BEGIN_DATE_TIME',\n",
      "       'CZ_TIMEZONE', 'END_DATE_TIME', 'INJURIES_DIRECT', 'INJURIES_INDIRECT',\n",
      "       'DEATHS_DIRECT', 'DEATHS_INDIRECT', 'DAMAGE_PROPERTY', 'DAMAGE_CROPS',\n",
      "       'SOURCE', 'MAGNITUDE', 'MAGNITUDE_TYPE', 'FLOOD_CAUSE', 'CATEGORY',\n",
      "       'TOR_F_SCALE', 'TOR_LENGTH', 'TOR_WIDTH', 'TOR_OTHER_WFO',\n",
      "       'TOR_OTHER_CZ_STATE', 'TOR_OTHER_CZ_FIPS', 'TOR_OTHER_CZ_NAME',\n",
      "       'BEGIN_RANGE', 'BEGIN_AZIMUTH', 'BEGIN_LOCATION', 'END_RANGE',\n",
      "       'END_AZIMUTH', 'END_LOCATION', 'BEGIN_LAT', 'BEGIN_LON', 'END_LAT',\n",
      "       'END_LON'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['EVENT_TYPE', 'CZ_NAME', 'BEGIN_DATE_TIME', 'INJURIES_DIRECT',\n",
      "       'INJURIES_INDIRECT', 'DEATHS_DIRECT', 'DEATHS_INDIRECT',\n",
      "       'DAMAGE_PROPERTY', 'DAMAGE_CROPS', 'BEGIN_LAT', 'BEGIN_LON'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Delete unused columns\n",
    "del df['CZ_FIPS']\n",
    "del df['CZ_TYPE']\n",
    "del df['WFO']\n",
    "del df['END_DATE_TIME']\n",
    "del df['CZ_TIMEZONE']\n",
    "del df['SOURCE']\n",
    "del df['MAGNITUDE']\n",
    "del df['MAGNITUDE_TYPE']\n",
    "del df['FLOOD_CAUSE']\n",
    "del df['CATEGORY']\n",
    "del df['TOR_F_SCALE']\n",
    "del df['TOR_LENGTH']\n",
    "del df['TOR_WIDTH']\n",
    "del df['TOR_OTHER_WFO']\n",
    "del df['TOR_OTHER_CZ_STATE']\n",
    "del df['TOR_OTHER_CZ_FIPS']\n",
    "del df['TOR_OTHER_CZ_NAME']\n",
    "del df['BEGIN_RANGE']\n",
    "del df['BEGIN_AZIMUTH']\n",
    "del df['BEGIN_LOCATION']\n",
    "del df['END_RANGE']\n",
    "del df['END_AZIMUTH']\n",
    "del df['END_LOCATION']\n",
    "del df['END_LAT']\n",
    "del df['END_LON']\n",
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove any rows that match the header row\n",
    "df = df[df.EVENT_TYPE != 'EVENT_TYPE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EVENT_TYPE\n",
      "CZ_NAME\n",
      "BEGIN_DATE_TIME\n",
      "INJURIES_DIRECT\n",
      "INJURIES_INDIRECT\n",
      "DEATHS_DIRECT\n",
      "DEATHS_INDIRECT\n",
      "DAMAGE_PROPERTY\n",
      "DAMAGE_CROPS\n",
      "BEGIN_LAT\n",
      "BEGIN_LON\n"
     ]
    }
   ],
   "source": [
    "# Check to see whether any rows still match the title columns\n",
    "# Don't run this, takes a long ass time\n",
    "for col in df.columns:\n",
    "    print(col)\n",
    "    for row in df.iterrows():\n",
    "        if row[1][col] == col:\n",
    "            print(row)\n",
    "            break\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tornado\n",
      "Hail\n",
      "Thunderstorm Wind\n",
      "TORNADOES, TSTM WIND, HAIL\n",
      "THUNDERSTORM WINDS/FLOODING\n",
      "HAIL/ICY ROADS\n",
      "HAIL FLOODING\n",
      "THUNDERSTORM WINDS/FLASH FLOOD\n",
      "THUNDERSTORM WINDS LIGHTNING\n",
      "THUNDERSTORM WIND/ TREES\n",
      "THUNDERSTORM WIND/ TREE\n",
      "THUNDERSTORM WINDS FUNNEL CLOU\n",
      "TORNADO/WATERSPOUT\n",
      "THUNDERSTORM WINDS/HEAVY RAIN\n",
      "THUNDERSTORM WINDS HEAVY RAIN\n",
      "THUNDERSTORM WINDS/ FLOOD\n",
      "Winter Storm\n",
      "Cold/Wind Chill\n",
      "Heavy Snow\n",
      "Flood\n",
      "High Wind\n",
      "Flash Flood\n",
      "Blizzard\n",
      "Ice Storm\n",
      "Lightning\n",
      "Frost/Freeze\n",
      "Heavy Rain\n",
      "Strong Wind\n",
      "Coastal Flood\n",
      "Wildfire\n",
      "High Surf\n",
      "Funnel Cloud\n",
      "Winter Weather\n",
      "Waterspout\n",
      "Drought\n",
      "Avalanche\n",
      "Debris Flow\n",
      "Heat\n",
      "Tropical Storm\n",
      "Dust Devil\n",
      "Dense Fog\n",
      "Hurricane (Typhoon)\n",
      "Storm Surge/Tide\n",
      "Marine High Wind\n",
      "Dust Storm\n",
      "Lake-Effect Snow\n",
      "Rip Current\n",
      "Seiche\n",
      "Extreme Cold/Wind Chill\n",
      "Excessive Heat\n",
      "Volcanic Ash\n",
      "Marine Thunderstorm Wind\n",
      "Marine Hail\n",
      "Tsunami\n",
      "Landslide\n",
      "Sleet\n",
      "Marine Strong Wind\n",
      "Freezing Fog\n",
      "Lakeshore Flood\n",
      "Astronomical Low Tide\n",
      "Tropical Depression\n",
      "Hurricane\n",
      "Dense Smoke\n",
      "Volcanic Ashfall\n",
      "Sneakerwave\n",
      "Marine Tropical Storm\n",
      "Marine Dense Fog\n",
      "Marine Hurricane/Typhoon\n",
      "Marine Lightning\n",
      "Marine Tropical Depression\n"
     ]
    }
   ],
   "source": [
    "# Find unique/distinct weather events\n",
    "for storm_event in df.EVENT_TYPE.unique():\n",
    "    print(storm_event)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EVENT_TYPE           object\n",
      "CZ_NAME              object\n",
      "BEGIN_DATE_TIME      object\n",
      "INJURIES_DIRECT      object\n",
      "INJURIES_INDIRECT    object\n",
      "DEATHS_DIRECT        object\n",
      "DEATHS_INDIRECT      object\n",
      "DAMAGE_PROPERTY      object\n",
      "DAMAGE_CROPS         object\n",
      "BEGIN_LAT            object\n",
      "BEGIN_LON            object\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EVENT_TYPE            object\n",
      "CZ_NAME               object\n",
      "BEGIN_DATE_TIME       object\n",
      "INJURIES_DIRECT        int64\n",
      "INJURIES_INDIRECT      int64\n",
      "DEATHS_DIRECT          int64\n",
      "DEATHS_INDIRECT        int64\n",
      "DAMAGE_PROPERTY       object\n",
      "DAMAGE_CROPS          object\n",
      "BEGIN_LAT            float64\n",
      "BEGIN_LON            float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "df[['EVENT_TYPE', 'CZ_NAME']] = df[['EVENT_TYPE', 'CZ_NAME']].astype('str')\n",
    "df[['INJURIES_DIRECT', 'INJURIES_INDIRECT', 'DEATHS_DIRECT', 'DEATHS_INDIRECT']] = df[['INJURIES_DIRECT', 'INJURIES_INDIRECT', 'DEATHS_DIRECT', 'DEATHS_INDIRECT']].astype('int64')\n",
    "df[['BEGIN_LAT','BEGIN_LON']] = df[['BEGIN_LAT','BEGIN_LON']].astype('float')\n",
    "#df[['BEGIN_DATE_TIME']] = df[['BEGIN_DATE_TIME']].to_datetime()\n",
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This code block makes me wish I had 64 GB of ram......\n",
    "for col in ['DAMAGE_PROPERTY', 'DAMAGE_CROPS']:\n",
    "    for index, value in enumerate(df[col]):\n",
    "        if 'K' in str(value):\n",
    "            df.loc[index,col] = value.replace('K','')\n",
    "df[['DAMAGE_PROPERTY', 'DAMAGE_CROPS']] = df[['DAMAGE_PROPERTY', 'DAMAGE_CROPS']].astype('int64')\n",
    "#for col in ['DAMAGE_PROPERTY', 'DAMAGE_CROPS']:\n",
    "#    for index, value in enumerate(df[col]):\n",
    "#       df[col][index] = value*1000\n",
    "print(df.types)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[df.EVENT_TYPE == 'Hurricane'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Deaths\n",
      "Tornado: 0.09704016557572902\n",
      "Hail: 4.8021744245794496e-05\n",
      "Thunderstorm Wind: 0.002352137088953268\n",
      "TORNADOES, TSTM WIND, HAIL: 25.0\n",
      "THUNDERSTORM WINDS/FLOODING: 0.0\n",
      "HAIL/ICY ROADS: 0.0\n",
      "HAIL FLOODING: 0.0\n",
      "THUNDERSTORM WINDS/FLASH FLOOD: 0.0\n",
      "THUNDERSTORM WINDS LIGHTNING: 0.0\n",
      "THUNDERSTORM WIND/ TREES: 0.0\n",
      "THUNDERSTORM WIND/ TREE: 0.0\n",
      "THUNDERSTORM WINDS FUNNEL CLOU: 0.0\n",
      "TORNADO/WATERSPOUT: 0.0\n",
      "THUNDERSTORM WINDS/HEAVY RAIN: 0.0\n",
      "THUNDERSTORM WINDS HEAVY RAIN: 0.0\n",
      "THUNDERSTORM WINDS/ FLOOD: 0.0\n",
      "Winter Storm: 0.002635725540753474\n",
      "Cold/Wind Chill: 0.06032786885245902\n",
      "Heavy Snow: 0.0015867019267094824\n",
      "Flood: 0.013510060683487703\n",
      "High Wind: 0.005210930487683255\n",
      "Flash Flood: 0.021038471885929513\n",
      "Blizzard: 0.009123013537374927\n",
      "Ice Storm: 0.00937950937950938\n",
      "Lightning: 0.032092530748554206\n",
      "Frost/Freeze: 0.00013039509714434736\n",
      "Heavy Rain: 0.005339730691843368\n",
      "Strong Wind: 0.009648887697668185\n",
      "Coastal Flood: 0.03015075376884422\n",
      "Wildfire: 0.033257171871033255\n",
      "High Surf: 0.025961157352358304\n",
      "Funnel Cloud: 0.0\n",
      "Winter Weather: 0.002501488981536629\n",
      "Waterspout: 0.0008613264427217916\n",
      "Drought: 0.0\n",
      "Avalanche: 0.55470737913486\n",
      "Debris Flow: 0.13286713286713286\n",
      "Heat: 0.08804737416238118\n",
      "Tropical Storm: 0.04115523465703971\n",
      "Dust Devil: 0.006172839506172839\n",
      "Dense Fog: 0.005596465390279823\n",
      "Hurricane (Typhoon): 1.209750566893424\n",
      "Storm Surge/Tide: 0.029288702928870293\n",
      "Marine High Wind: 0.02064896755162242\n",
      "Dust Storm: 0.016058394160583942\n",
      "Lake-Effect Snow: 0.0011098779134295228\n",
      "Rip Current: 0.7413554633471646\n",
      "Seiche: 0.0\n",
      "Extreme Cold/Wind Chill: 0.01630083925112976\n",
      "Excessive Heat: 0.10147671336614919\n",
      "Volcanic Ash: 0.0\n",
      "Marine Thunderstorm Wind: 0.0011296882060551287\n",
      "Marine Hail: 0.0\n",
      "Tsunami: 1.1\n",
      "Landslide: 0.0111731843575419\n",
      "Sleet: 0.0\n",
      "Marine Strong Wind: 0.3611111111111111\n",
      "Freezing Fog: 0.016736401673640166\n",
      "Lakeshore Flood: 0.038461538461538464\n",
      "Astronomical Low Tide: 0.0020920502092050207\n",
      "Tropical Depression: 0.006042296072507553\n",
      "Hurricane: 0.04225352112676056\n",
      "Dense Smoke: 0.0\n",
      "Volcanic Ashfall: 0.0\n",
      "Sneakerwave: 1.1538461538461537\n",
      "Marine Tropical Storm: 0.0\n",
      "Marine Dense Fog: 0.0\n",
      "Marine Hurricane/Typhoon: 0.0\n",
      "Marine Lightning: 0.0\n",
      "Marine Tropical Depression: 0.0\n"
     ]
    }
   ],
   "source": [
    "print('Average Deaths')\n",
    "for event in df.EVENT_TYPE.unique():\n",
    "    print(event+': '+str(df[df['EVENT_TYPE'] == event]['DEATHS_DIRECT'].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for event in df.EVENT_TYPE.unique():\n",
    "    df[df['EVENT_TYPE'] == event].boxplot(by = 'EVENT_TYPE', column = 'DEATHS_DIRECT')\n",
    "    \n",
    "plt.show()\n",
    "#flashflood, tornado, heat, hurricane, excessive heat have the highest number of deaths consistently"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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