NoSQL_setup.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1debd745",
   "metadata": {},
   "source": [
    "# Cyclonic Cartography: Visualizing Tornado Trends"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "064ef857",
   "metadata": {},
   "source": [
    "## Part 1: Database and Jupyter Notebook Set Up"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "664e3c1f",
   "metadata": {},
   "source": [
    "Import the storm data retrieved from the online source from your Terminal. The database will be named `storm_data` and the collection `tornadoes`.\n",
    "\n",
    "Imported the dataset with: \n",
    "mongoimport --type csv -d storm_data -c tornadoes --headerline --drop all_storms.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3ecdd008",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import dependencies\n",
    "from pymongo import MongoClient\n",
    "from pprint import pprint\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "59390c4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an instance of MongoClient\n",
    "mongo = MongoClient(port=27017)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7f9ececa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['admin', 'class_db', 'config', 'epa', 'fruits_db', 'garden_db', 'local', 'met', 'petsitly_marketing', 'storm_data', 'uk_food']\n"
     ]
    }
   ],
   "source": [
    "# confirm that our new database was created\n",
    "# the list of databases should include the newly imported databased named storm_data\n",
    "print(mongo.list_database_names())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "71e373c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# assign the uk_food database to a variable name\n",
    "db = mongo['storm_data']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef1b89ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['tornadoes']\n"
     ]
    }
   ],
   "source": [
    "# review the collections in our new database\n",
    "print(db.list_collection_names())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6a0d92df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'BEGIN_AZIMUTH': 'SE',\n",
      " 'BEGIN_DATE': '1/25/2021',\n",
      " 'BEGIN_LAT': 33.5965,\n",
      " 'BEGIN_LOCATION': 'WALKER CHAPEL',\n",
      " 'BEGIN_LON': -86.8256,\n",
      " 'BEGIN_RANGE': 0,\n",
      " 'BEGIN_TIME': 2240,\n",
      " 'CZ_NAME_STR': 'JEFFERSON CO.',\n",
      " 'CZ_TIMEZONE': 'CST',\n",
      " 'DAMAGE_CROPS_NUM': 0,\n",
      " 'DAMAGE_PROPERTY_NUM': 0,\n",
      " 'DEATHS_DIRECT': 1,\n",
      " 'END_AZIMUTH': 'WNW',\n",
      " 'END_DATE': '1/25/2021',\n",
      " 'END_LAT': 33.6598,\n",
      " 'END_LOCATION': 'CHALKVILLE',\n",
      " 'END_LON': -86.6678,\n",
      " 'END_RANGE': 1,\n",
      " 'END_TIME': 2255,\n",
      " 'EPISODE_ID': 155525,\n",
      " 'EVENT_ID': 938002,\n",
      " 'EVENT_TYPE': 'Tornado',\n",
      " 'INJURIES_DIRECT': 30,\n",
      " 'STATE_ABBR': 'AL',\n",
      " 'TOR_F_SCALE': 'EF3',\n",
      " 'TOR_LENGTH': 10.4,\n",
      " 'TOR_WIDTH': 900,\n",
      " '_id': ObjectId('65dd5d4943dde26c5545321c')}\n"
     ]
    }
   ],
   "source": [
    "# review a document in the establishments collection\n",
    "pprint(db.tornadoes.find_one())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "11c9f11b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# assign the collection to a variable\n",
    "tornadoes = db['tornadoes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fc2f0b57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.UpdateResult at 0x200c3c85900>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find and replace all F3 values with EF3 and F4 values with EF4\n",
    "\n",
    "tornadoes.update_many({'TOR_F_SCALE': 'F3'}, {'$set': {'TOR_F_SCALE': 'EF3'}})\n",
    "tornadoes.update_many({'TOR_F_SCALE': 'F4'}, {'$set': {'TOR_F_SCALE': 'EF4'}})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "34b31036",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pymongo.results.UpdateResult at 0x200c3e134c0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find and replace time zones with digits so they are all matching: CST, EST, MST\n",
    "tornadoes.update_many({'CZ_TIMEZONE': 'CST-6'}, {'$set': {'CZ_TIMEZONE': 'CST'}})\n",
    "tornadoes.update_many({'CZ_TIMEZONE': 'EST-5'}, {'$set': {'CZ_TIMEZONE': 'EST'}})\n",
    "tornadoes.update_many({'CZ_TIMEZONE': 'MST-7'}, {'$set': {'CZ_TIMEZONE': 'MST'}})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbc02254",
   "metadata": {},
   "source": [
    "## Part 2: Create DataFrames for Charting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dec30ca0",
   "metadata": {},
   "source": [
    "### Create a table showing the deaths and injuries grouped by EF indicator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b11edc65",
   "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>_id</th>\n",
       "      <th>EVENT_ID</th>\n",
       "      <th>CZ_NAME_STR</th>\n",
       "      <th>BEGIN_LOCATION</th>\n",
       "      <th>BEGIN_DATE</th>\n",
       "      <th>BEGIN_TIME</th>\n",
       "      <th>EVENT_TYPE</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th>DEATHS_DIRECT</th>\n",
       "      <th>INJURIES_DIRECT</th>\n",
       "      <th>...</th>\n",
       "      <th>BEGIN_AZIMUTH</th>\n",
       "      <th>END_RANGE</th>\n",
       "      <th>END_AZIMUTH</th>\n",
       "      <th>END_LOCATION</th>\n",
       "      <th>END_DATE</th>\n",
       "      <th>END_TIME</th>\n",
       "      <th>BEGIN_LAT</th>\n",
       "      <th>BEGIN_LON</th>\n",
       "      <th>END_LAT</th>\n",
       "      <th>END_LON</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>65dd5d4943dde26c5545321c</td>\n",
       "      <td>938002</td>\n",
       "      <td>JEFFERSON CO.</td>\n",
       "      <td>WALKER CHAPEL</td>\n",
       "      <td>1/25/2021</td>\n",
       "      <td>2240</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>SE</td>\n",
       "      <td>1</td>\n",
       "      <td>WNW</td>\n",
       "      <td>CHALKVILLE</td>\n",
       "      <td>1/25/2021</td>\n",
       "      <td>2255</td>\n",
       "      <td>33.5965</td>\n",
       "      <td>-86.8256</td>\n",
       "      <td>33.6598</td>\n",
       "      <td>-86.6678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>65dd5d4943dde26c5545321d</td>\n",
       "      <td>948201</td>\n",
       "      <td>HALE CO.</td>\n",
       "      <td>GREENSBORO MUNI ARPT</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1526</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>W</td>\n",
       "      <td>2</td>\n",
       "      <td>S</td>\n",
       "      <td>HOGGLESVILLE</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1547</td>\n",
       "      <td>32.6892</td>\n",
       "      <td>-87.7387</td>\n",
       "      <td>32.814</td>\n",
       "      <td>-87.473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>65dd5d4943dde26c5545321e</td>\n",
       "      <td>946864</td>\n",
       "      <td>HALE CO.</td>\n",
       "      <td>HAVANA</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1116</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>NE</td>\n",
       "      <td>6</td>\n",
       "      <td>NE</td>\n",
       "      <td>PHIPPS</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1129</td>\n",
       "      <td>32.9386</td>\n",
       "      <td>-87.5753</td>\n",
       "      <td>33.004</td>\n",
       "      <td>-87.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>65dd5d4943dde26c5545321f</td>\n",
       "      <td>948202</td>\n",
       "      <td>PERRY CO.</td>\n",
       "      <td>MORGAN SPGS</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1547</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>NW</td>\n",
       "      <td>5</td>\n",
       "      <td>NW</td>\n",
       "      <td>ELLARDS</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1557</td>\n",
       "      <td>32.814</td>\n",
       "      <td>-87.473</td>\n",
       "      <td>32.864</td>\n",
       "      <td>-87.319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>65dd5d4943dde26c55453220</td>\n",
       "      <td>946870</td>\n",
       "      <td>CALHOUN CO.</td>\n",
       "      <td>BOILING SPGS</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1331</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>WSW</td>\n",
       "      <td>2</td>\n",
       "      <td>WSW</td>\n",
       "      <td>LADIGA</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1418</td>\n",
       "      <td>33.7026</td>\n",
       "      <td>-86.1053</td>\n",
       "      <td>33.962</td>\n",
       "      <td>-85.634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>65dd5d4943dde26c55453221</td>\n",
       "      <td>948219</td>\n",
       "      <td>BIBB CO.</td>\n",
       "      <td>PONDVILLE</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1557</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>S</td>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>BRIERFIELD</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1631</td>\n",
       "      <td>32.864</td>\n",
       "      <td>-87.319</td>\n",
       "      <td>33.027</td>\n",
       "      <td>-86.877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>65dd5d4943dde26c55453222</td>\n",
       "      <td>945569</td>\n",
       "      <td>BRUNSWICK CO.</td>\n",
       "      <td>GRISSETTOWN</td>\n",
       "      <td>2/15/2021</td>\n",
       "      <td>2334</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>SSW</td>\n",
       "      <td>3</td>\n",
       "      <td>E</td>\n",
       "      <td>CAMP BRANCH</td>\n",
       "      <td>2/16/2021</td>\n",
       "      <td>2</td>\n",
       "      <td>33.9118</td>\n",
       "      <td>-78.5096</td>\n",
       "      <td>34.1774</td>\n",
       "      <td>-78.3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>65dd5d4943dde26c55453223</td>\n",
       "      <td>954213</td>\n",
       "      <td>KNOX CO.</td>\n",
       "      <td>TRUSCOTT</td>\n",
       "      <td>4/27/2021</td>\n",
       "      <td>1449</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>W</td>\n",
       "      <td>3</td>\n",
       "      <td>NNE</td>\n",
       "      <td>TRUSCOTT</td>\n",
       "      <td>4/27/2021</td>\n",
       "      <td>1505</td>\n",
       "      <td>33.751</td>\n",
       "      <td>-99.921</td>\n",
       "      <td>33.791</td>\n",
       "      <td>-99.788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>65dd5d4943dde26c55453224</td>\n",
       "      <td>954642</td>\n",
       "      <td>ST. LANDRY PAR.</td>\n",
       "      <td>WAXIA</td>\n",
       "      <td>4/10/2021</td>\n",
       "      <td>106</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>WSW</td>\n",
       "      <td>2</td>\n",
       "      <td>NNE</td>\n",
       "      <td>DANKS</td>\n",
       "      <td>4/10/2021</td>\n",
       "      <td>118</td>\n",
       "      <td>30.666</td>\n",
       "      <td>-91.9586</td>\n",
       "      <td>30.7499</td>\n",
       "      <td>-91.8492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>65dd5d4943dde26c55453225</td>\n",
       "      <td>960282</td>\n",
       "      <td>COOK CO.</td>\n",
       "      <td>BURR RIDGE</td>\n",
       "      <td>6/20/2021</td>\n",
       "      <td>2221</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>SSW</td>\n",
       "      <td>0</td>\n",
       "      <td>SSW</td>\n",
       "      <td>WILLOW SPRINGS</td>\n",
       "      <td>6/20/2021</td>\n",
       "      <td>2225</td>\n",
       "      <td>41.7374</td>\n",
       "      <td>-87.9151</td>\n",
       "      <td>41.7368</td>\n",
       "      <td>-87.8612</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        _id  EVENT_ID      CZ_NAME_STR        BEGIN_LOCATION  \\\n",
       "0  65dd5d4943dde26c5545321c    938002    JEFFERSON CO.         WALKER CHAPEL   \n",
       "1  65dd5d4943dde26c5545321d    948201         HALE CO.  GREENSBORO MUNI ARPT   \n",
       "2  65dd5d4943dde26c5545321e    946864         HALE CO.                HAVANA   \n",
       "3  65dd5d4943dde26c5545321f    948202        PERRY CO.           MORGAN SPGS   \n",
       "4  65dd5d4943dde26c55453220    946870      CALHOUN CO.          BOILING SPGS   \n",
       "5  65dd5d4943dde26c55453221    948219         BIBB CO.             PONDVILLE   \n",
       "6  65dd5d4943dde26c55453222    945569    BRUNSWICK CO.           GRISSETTOWN   \n",
       "7  65dd5d4943dde26c55453223    954213         KNOX CO.              TRUSCOTT   \n",
       "8  65dd5d4943dde26c55453224    954642  ST. LANDRY PAR.                 WAXIA   \n",
       "9  65dd5d4943dde26c55453225    960282         COOK CO.            BURR RIDGE   \n",
       "\n",
       "  BEGIN_DATE  BEGIN_TIME EVENT_TYPE TOR_F_SCALE  DEATHS_DIRECT  \\\n",
       "0  1/25/2021        2240    Tornado         EF3              1   \n",
       "1  3/25/2021        1526    Tornado         EF3              0   \n",
       "2  3/25/2021        1116    Tornado         EF3              0   \n",
       "3  3/25/2021        1547    Tornado         EF3              0   \n",
       "4  3/25/2021        1331    Tornado         EF3              6   \n",
       "5  3/25/2021        1557    Tornado         EF3              0   \n",
       "6  2/15/2021        2334    Tornado         EF3              3   \n",
       "7  4/27/2021        1449    Tornado         EF3              0   \n",
       "8  4/10/2021         106    Tornado         EF3              1   \n",
       "9  6/20/2021        2221    Tornado         EF3              0   \n",
       "\n",
       "   INJURIES_DIRECT  ...  BEGIN_AZIMUTH  END_RANGE END_AZIMUTH    END_LOCATION  \\\n",
       "0               30  ...             SE          1         WNW      CHALKVILLE   \n",
       "1                6  ...              W          2           S    HOGGLESVILLE   \n",
       "2                0  ...             NE          6          NE          PHIPPS   \n",
       "3                0  ...             NW          5          NW         ELLARDS   \n",
       "4               10  ...            WSW          2         WSW          LADIGA   \n",
       "5                5  ...              S          3           E      BRIERFIELD   \n",
       "6               10  ...            SSW          3           E     CAMP BRANCH   \n",
       "7                0  ...              W          3         NNE        TRUSCOTT   \n",
       "8                7  ...            WSW          2         NNE           DANKS   \n",
       "9                0  ...            SSW          0         SSW  WILLOW SPRINGS   \n",
       "\n",
       "    END_DATE  END_TIME  BEGIN_LAT BEGIN_LON  END_LAT  END_LON  \n",
       "0  1/25/2021      2255    33.5965  -86.8256  33.6598 -86.6678  \n",
       "1  3/25/2021      1547    32.6892  -87.7387   32.814  -87.473  \n",
       "2  3/25/2021      1129    32.9386  -87.5753   33.004  -87.421  \n",
       "3  3/25/2021      1557     32.814   -87.473   32.864  -87.319  \n",
       "4  3/25/2021      1418    33.7026  -86.1053   33.962  -85.634  \n",
       "5  3/25/2021      1631     32.864   -87.319   33.027  -86.877  \n",
       "6  2/16/2021         2    33.9118  -78.5096  34.1774 -78.3008  \n",
       "7  4/27/2021      1505     33.751   -99.921   33.791  -99.788  \n",
       "8  4/10/2021       118     30.666  -91.9586  30.7499 -91.8492  \n",
       "9  6/20/2021      2225    41.7374  -87.9151  41.7368 -87.8612  \n",
       "\n",
       "[10 rows x 28 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a dataframe of the full data set\n",
    "query = {'EVENT_TYPE': 'Tornado'}\n",
    "\n",
    "results = list(tornadoes.find(query))\n",
    "\n",
    "tornado_df = pd.json_normalize(results)\n",
    "\n",
    "# print first 10 rows to check\n",
    "tornado_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e6836815",
   "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>TOR_F_SCALE</th>\n",
       "      <th>DEATHS_DIRECT</th>\n",
       "      <th>INJURIES_DIRECT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EF3</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EF3</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  TOR_F_SCALE  DEATHS_DIRECT  INJURIES_DIRECT\n",
       "0         EF3              1               30\n",
       "1         EF3              0                6\n",
       "2         EF3              0                0\n",
       "3         EF3              0                0\n",
       "4         EF3              6               10"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a dataframe showing only EF indicator and total number of direct deaths and direct injuries\n",
    "\n",
    "deathInj_df = tornado_df[['TOR_F_SCALE', 'DEATHS_DIRECT', 'INJURIES_DIRECT']]\n",
    "\n",
    "#print 5 rows to check\n",
    "deathInj_df.head()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "baac0541",
   "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>Deaths</th>\n",
       "      <th>Injuries</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>EF3</th>\n",
       "      <td>603</td>\n",
       "      <td>7600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF4</th>\n",
       "      <td>495</td>\n",
       "      <td>6226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF5</th>\n",
       "      <td>312</td>\n",
       "      <td>1725</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Deaths  Injuries\n",
       "TOR_F_SCALE                  \n",
       "EF3             603      7600\n",
       "EF4             495      6226\n",
       "EF5             312      1725"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group by EF scale\n",
    "deathInj_grouped = deathInj_df.groupby(['TOR_F_SCALE'])\n",
    "\n",
    "# find sums for deaths and injuries\n",
    "deaths = deathInj_grouped['DEATHS_DIRECT'].sum()\n",
    "injuries = deathInj_grouped['INJURIES_DIRECT'].sum()\n",
    "\n",
    "# create new dataframe using sums\n",
    "deathInj_counts_df = pd.DataFrame({'Deaths': deaths, 'Injuries': injuries})\n",
    "\n",
    "deathInj_counts_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebaf74f1",
   "metadata": {},
   "source": [
    "### Create a table showing count of tornadoes by time zone (by EF indicator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d350e003",
   "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>CZ_TIMEZONE</th>\n",
       "      <th>STATE_ABBR</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th>EVENT_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CST</td>\n",
       "      <td>AL</td>\n",
       "      <td>EF3</td>\n",
       "      <td>938002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CST</td>\n",
       "      <td>AL</td>\n",
       "      <td>EF3</td>\n",
       "      <td>948201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CST</td>\n",
       "      <td>AL</td>\n",
       "      <td>EF3</td>\n",
       "      <td>946864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CST</td>\n",
       "      <td>AL</td>\n",
       "      <td>EF3</td>\n",
       "      <td>948202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CST</td>\n",
       "      <td>AL</td>\n",
       "      <td>EF3</td>\n",
       "      <td>946870</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CZ_TIMEZONE STATE_ABBR TOR_F_SCALE  EVENT_ID\n",
       "0         CST         AL         EF3    938002\n",
       "1         CST         AL         EF3    948201\n",
       "2         CST         AL         EF3    946864\n",
       "3         CST         AL         EF3    948202\n",
       "4         CST         AL         EF3    946870"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new df from tornado df with only columns we want\n",
    "timezone_df = tornado_df[['CZ_TIMEZONE', 'STATE_ABBR', 'TOR_F_SCALE', 'EVENT_ID']]\n",
    "\n",
    "timezone_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5ad6af1c",
   "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></th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZ_TIMEZONE</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">CST</th>\n",
       "      <th>EF3</th>\n",
       "      <td>635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF4</th>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF5</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">EST</th>\n",
       "      <th>EF3</th>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF4</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <th>EF3</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Count\n",
       "CZ_TIMEZONE TOR_F_SCALE       \n",
       "CST         EF3            635\n",
       "            EF4            152\n",
       "            EF5             14\n",
       "EST         EF3            185\n",
       "            EF4             21\n",
       "MST         EF3             18"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group by timezone\n",
    "time_grouped = timezone_df.groupby(['CZ_TIMEZONE', 'TOR_F_SCALE'])\n",
    "\n",
    "# find counts of each EF indicator\n",
    "event_count = time_grouped['EVENT_ID'].count()\n",
    "\n",
    "# new dataframe showing counts for timezone/EF\n",
    "zone_df = pd.DataFrame({'Count': event_count})\n",
    "\n",
    "zone_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb3b08ee",
   "metadata": {},
   "source": [
    "### Create a table showing count of tornadoes by state (by EF indicator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ccb7658f",
   "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></th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATE_ABBR</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">AL</th>\n",
       "      <th>EF3</th>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF4</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF5</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">AR</th>\n",
       "      <th>EF3</th>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF4</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">VA</th>\n",
       "      <th>EF3</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EF4</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WI</th>\n",
       "      <th>EF3</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WV</th>\n",
       "      <th>EF3</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WY</th>\n",
       "      <th>EF3</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>64 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Count\n",
       "STATE_ABBR TOR_F_SCALE       \n",
       "AL         EF3             69\n",
       "           EF4             24\n",
       "           EF5              4\n",
       "AR         EF3             44\n",
       "           EF4              4\n",
       "...                       ...\n",
       "VA         EF3             13\n",
       "           EF4              1\n",
       "WI         EF3             15\n",
       "WV         EF3              2\n",
       "WY         EF3              3\n",
       "\n",
       "[64 rows x 1 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new grouped by from timezone showing the state\n",
    "state_grouped = timezone_df.groupby(['STATE_ABBR', 'TOR_F_SCALE'])\n",
    "\n",
    "# find counts\n",
    "ef_counts = state_grouped['EVENT_ID'].count()\n",
    "\n",
    "#new dataframe showing counts for the state/EF\n",
    "state_df = pd.DataFrame({'Count': ef_counts})\n",
    "\n",
    "state_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d64dd437",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\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>STATE_ABBR</th>\n",
       "      <th>EVENT_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AL</td>\n",
       "      <td>938002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL</td>\n",
       "      <td>948201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL</td>\n",
       "      <td>946864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL</td>\n",
       "      <td>948202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL</td>\n",
       "      <td>946870</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  STATE_ABBR  EVENT_ID\n",
       "0         AL    938002\n",
       "1         AL    948201\n",
       "2         AL    946864\n",
       "3         AL    948202\n",
       "4         AL    946870"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create dataframe showing count of events by state\n",
    "states_only_df = tornado_df[['STATE_ABBR', 'EVENT_ID']]\n",
    "\n",
    "states_only_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a319f847",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STATE_ABBR</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IA</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL</th>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IN</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KS</th>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KY</th>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LA</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MN</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MO</th>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS</th>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ND</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NE</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NJ</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NY</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OK</th>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PA</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SC</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SD</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TN</th>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VA</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WI</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WV</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WY</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Count\n",
       "STATE_ABBR       \n",
       "AL             97\n",
       "AR             48\n",
       "AZ              2\n",
       "CO              8\n",
       "DE              1\n",
       "FL              8\n",
       "GA             58\n",
       "IA             29\n",
       "IL             41\n",
       "IN             36\n",
       "KS             77\n",
       "KY             54\n",
       "LA             25\n",
       "MA              2\n",
       "MD              3\n",
       "MI              3\n",
       "MN             25\n",
       "MO             68\n",
       "MS             99\n",
       "MT              3\n",
       "NC             14\n",
       "ND             16\n",
       "NE             29\n",
       "NJ              1\n",
       "NY              2\n",
       "OH             17\n",
       "OK             60\n",
       "PA              4\n",
       "SC             16\n",
       "SD             12\n",
       "TN             64\n",
       "TX             69\n",
       "VA             14\n",
       "WI             15\n",
       "WV              2\n",
       "WY              3"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group by state and complete a count, then display as a new dataframe\n",
    "\n",
    "state_group = states_only_df.groupby(['STATE_ABBR'])\n",
    "\n",
    "storm_count = state_group['EVENT_ID'].count()\n",
    "\n",
    "state_counts_df = pd.DataFrame({'Count': storm_count})\n",
    "\n",
    "state_counts_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8d00a82",
   "metadata": {},
   "source": [
    "### Create a table showing count of tornadoes by month for each state (include time zone and EF indicator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "33dc0247",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1025 entries, 0 to 1024\n",
      "Data columns (total 28 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   _id                  1025 non-null   object \n",
      " 1   EVENT_ID             1025 non-null   int64  \n",
      " 2   CZ_NAME_STR          1025 non-null   object \n",
      " 3   BEGIN_LOCATION       1025 non-null   object \n",
      " 4   BEGIN_DATE           1025 non-null   object \n",
      " 5   BEGIN_TIME           1025 non-null   int64  \n",
      " 6   EVENT_TYPE           1025 non-null   object \n",
      " 7   TOR_F_SCALE          1025 non-null   object \n",
      " 8   DEATHS_DIRECT        1025 non-null   int64  \n",
      " 9   INJURIES_DIRECT      1025 non-null   int64  \n",
      " 10  DAMAGE_PROPERTY_NUM  1025 non-null   int64  \n",
      " 11  DAMAGE_CROPS_NUM     1025 non-null   int64  \n",
      " 12  STATE_ABBR           1025 non-null   object \n",
      " 13  CZ_TIMEZONE          1025 non-null   object \n",
      " 14  EPISODE_ID           1025 non-null   int64  \n",
      " 15  TOR_LENGTH           1025 non-null   float64\n",
      " 16  TOR_WIDTH            1025 non-null   float64\n",
      " 17  BEGIN_RANGE          1025 non-null   object \n",
      " 18  BEGIN_AZIMUTH        1025 non-null   object \n",
      " 19  END_RANGE            1025 non-null   object \n",
      " 20  END_AZIMUTH          1025 non-null   object \n",
      " 21  END_LOCATION         1025 non-null   object \n",
      " 22  END_DATE             1025 non-null   object \n",
      " 23  END_TIME             1025 non-null   int64  \n",
      " 24  BEGIN_LAT            1025 non-null   object \n",
      " 25  BEGIN_LON            1025 non-null   object \n",
      " 26  END_LAT              1025 non-null   object \n",
      " 27  END_LON              1025 non-null   object \n",
      "dtypes: float64(2), int64(8), object(18)\n",
      "memory usage: 224.3+ KB\n"
     ]
    }
   ],
   "source": [
    "# check tornado_df info\n",
    "\n",
    "tornado_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1f789e32",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1025 entries, 0 to 1024\n",
      "Data columns (total 28 columns):\n",
      " #   Column               Non-Null Count  Dtype         \n",
      "---  ------               --------------  -----         \n",
      " 0   _id                  1025 non-null   object        \n",
      " 1   EVENT_ID             1025 non-null   int64         \n",
      " 2   CZ_NAME_STR          1025 non-null   object        \n",
      " 3   BEGIN_LOCATION       1025 non-null   object        \n",
      " 4   BEGIN_DATE           1025 non-null   datetime64[ns]\n",
      " 5   BEGIN_TIME           1025 non-null   int64         \n",
      " 6   EVENT_TYPE           1025 non-null   object        \n",
      " 7   TOR_F_SCALE          1025 non-null   object        \n",
      " 8   DEATHS_DIRECT        1025 non-null   int64         \n",
      " 9   INJURIES_DIRECT      1025 non-null   int64         \n",
      " 10  DAMAGE_PROPERTY_NUM  1025 non-null   int64         \n",
      " 11  DAMAGE_CROPS_NUM     1025 non-null   int64         \n",
      " 12  STATE_ABBR           1025 non-null   object        \n",
      " 13  CZ_TIMEZONE          1025 non-null   object        \n",
      " 14  EPISODE_ID           1025 non-null   int64         \n",
      " 15  TOR_LENGTH           1025 non-null   float64       \n",
      " 16  TOR_WIDTH            1025 non-null   float64       \n",
      " 17  BEGIN_RANGE          1025 non-null   object        \n",
      " 18  BEGIN_AZIMUTH        1025 non-null   object        \n",
      " 19  END_RANGE            1025 non-null   object        \n",
      " 20  END_AZIMUTH          1025 non-null   object        \n",
      " 21  END_LOCATION         1025 non-null   object        \n",
      " 22  END_DATE             1025 non-null   object        \n",
      " 23  END_TIME             1025 non-null   int64         \n",
      " 24  BEGIN_LAT            1025 non-null   object        \n",
      " 25  BEGIN_LON            1025 non-null   object        \n",
      " 26  END_LAT              1025 non-null   object        \n",
      " 27  END_LON              1025 non-null   object        \n",
      "dtypes: datetime64[ns](1), float64(2), int64(8), object(17)\n",
      "memory usage: 224.3+ KB\n"
     ]
    }
   ],
   "source": [
    "# begin_date is an object; change to date/time\n",
    "tornado_df['BEGIN_DATE'] = pd.to_datetime(tornado_df['BEGIN_DATE'])\n",
    "\n",
    "#check it\n",
    "tornado_df.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "900c90ab",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_id</th>\n",
       "      <th>EVENT_ID</th>\n",
       "      <th>CZ_NAME_STR</th>\n",
       "      <th>BEGIN_LOCATION</th>\n",
       "      <th>BEGIN_DATE</th>\n",
       "      <th>BEGIN_TIME</th>\n",
       "      <th>EVENT_TYPE</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th>DEATHS_DIRECT</th>\n",
       "      <th>INJURIES_DIRECT</th>\n",
       "      <th>...</th>\n",
       "      <th>END_RANGE</th>\n",
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       "      <th>END_DATE</th>\n",
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       "      <th>BEGIN_LAT</th>\n",
       "      <th>BEGIN_LON</th>\n",
       "      <th>END_LAT</th>\n",
       "      <th>END_LON</th>\n",
       "      <th>MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>65dd5d4943dde26c5545321c</td>\n",
       "      <td>938002</td>\n",
       "      <td>JEFFERSON CO.</td>\n",
       "      <td>WALKER CHAPEL</td>\n",
       "      <td>2021-01-25</td>\n",
       "      <td>2240</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>WNW</td>\n",
       "      <td>CHALKVILLE</td>\n",
       "      <td>1/25/2021</td>\n",
       "      <td>2255</td>\n",
       "      <td>33.5965</td>\n",
       "      <td>-86.8256</td>\n",
       "      <td>33.6598</td>\n",
       "      <td>-86.6678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>65dd5d4943dde26c5545321d</td>\n",
       "      <td>948201</td>\n",
       "      <td>HALE CO.</td>\n",
       "      <td>GREENSBORO MUNI ARPT</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>1526</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>S</td>\n",
       "      <td>HOGGLESVILLE</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1547</td>\n",
       "      <td>32.6892</td>\n",
       "      <td>-87.7387</td>\n",
       "      <td>32.814</td>\n",
       "      <td>-87.473</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>65dd5d4943dde26c5545321e</td>\n",
       "      <td>946864</td>\n",
       "      <td>HALE CO.</td>\n",
       "      <td>HAVANA</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>1116</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>NE</td>\n",
       "      <td>PHIPPS</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1129</td>\n",
       "      <td>32.9386</td>\n",
       "      <td>-87.5753</td>\n",
       "      <td>33.004</td>\n",
       "      <td>-87.421</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>65dd5d4943dde26c5545321f</td>\n",
       "      <td>948202</td>\n",
       "      <td>PERRY CO.</td>\n",
       "      <td>MORGAN SPGS</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>1547</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>NW</td>\n",
       "      <td>ELLARDS</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1557</td>\n",
       "      <td>32.814</td>\n",
       "      <td>-87.473</td>\n",
       "      <td>32.864</td>\n",
       "      <td>-87.319</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>65dd5d4943dde26c55453220</td>\n",
       "      <td>946870</td>\n",
       "      <td>CALHOUN CO.</td>\n",
       "      <td>BOILING SPGS</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>1331</td>\n",
       "      <td>Tornado</td>\n",
       "      <td>EF3</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>WSW</td>\n",
       "      <td>LADIGA</td>\n",
       "      <td>3/25/2021</td>\n",
       "      <td>1418</td>\n",
       "      <td>33.7026</td>\n",
       "      <td>-86.1053</td>\n",
       "      <td>33.962</td>\n",
       "      <td>-85.634</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        _id  EVENT_ID    CZ_NAME_STR        BEGIN_LOCATION  \\\n",
       "0  65dd5d4943dde26c5545321c    938002  JEFFERSON CO.         WALKER CHAPEL   \n",
       "1  65dd5d4943dde26c5545321d    948201       HALE CO.  GREENSBORO MUNI ARPT   \n",
       "2  65dd5d4943dde26c5545321e    946864       HALE CO.                HAVANA   \n",
       "3  65dd5d4943dde26c5545321f    948202      PERRY CO.           MORGAN SPGS   \n",
       "4  65dd5d4943dde26c55453220    946870    CALHOUN CO.          BOILING SPGS   \n",
       "\n",
       "  BEGIN_DATE  BEGIN_TIME EVENT_TYPE TOR_F_SCALE  DEATHS_DIRECT  \\\n",
       "0 2021-01-25        2240    Tornado         EF3              1   \n",
       "1 2021-03-25        1526    Tornado         EF3              0   \n",
       "2 2021-03-25        1116    Tornado         EF3              0   \n",
       "3 2021-03-25        1547    Tornado         EF3              0   \n",
       "4 2021-03-25        1331    Tornado         EF3              6   \n",
       "\n",
       "   INJURIES_DIRECT  ...  END_RANGE  END_AZIMUTH  END_LOCATION   END_DATE  \\\n",
       "0               30  ...          1          WNW    CHALKVILLE  1/25/2021   \n",
       "1                6  ...          2            S  HOGGLESVILLE  3/25/2021   \n",
       "2                0  ...          6           NE        PHIPPS  3/25/2021   \n",
       "3                0  ...          5           NW       ELLARDS  3/25/2021   \n",
       "4               10  ...          2          WSW        LADIGA  3/25/2021   \n",
       "\n",
       "   END_TIME  BEGIN_LAT  BEGIN_LON  END_LAT  END_LON MONTH  \n",
       "0      2255    33.5965   -86.8256  33.6598 -86.6678     1  \n",
       "1      1547    32.6892   -87.7387   32.814  -87.473     3  \n",
       "2      1129    32.9386   -87.5753   33.004  -87.421     3  \n",
       "3      1557     32.814    -87.473   32.864  -87.319     3  \n",
       "4      1418    33.7026   -86.1053   33.962  -85.634     3  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# extract the month from the date/time into a new column\n",
    "tornado_df['MONTH'] = tornado_df['BEGIN_DATE'].dt.month\n",
    "\n",
    "tornado_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1c81c499",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MONTH</th>\n",
       "      <th>CZ_TIMEZONE</th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th>EVENT_ID</th>\n",
       "    </tr>\n",
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       "      <td>948201</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>3</td>\n",
       "      <td>CST</td>\n",
       "      <td>EF3</td>\n",
       "      <td>948202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>CST</td>\n",
       "      <td>EF3</td>\n",
       "      <td>946870</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MONTH CZ_TIMEZONE TOR_F_SCALE  EVENT_ID\n",
       "0      1         CST         EF3    938002\n",
       "1      3         CST         EF3    948201\n",
       "2      3         CST         EF3    946864\n",
       "3      3         CST         EF3    948202\n",
       "4      3         CST         EF3    946870"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df grouped by timezone showing counts by month by ef\n",
    "month_df = tornado_df[['MONTH', 'CZ_TIMEZONE', 'TOR_F_SCALE', 'EVENT_ID']]\n",
    "\n",
    "month_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7782808e",
   "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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>TOR_F_SCALE</th>\n",
       "      <th>EVENT_ID</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONTH</th>\n",
       "      <th>CZ_TIMEZONE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>CST</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
       "      <th>CST</th>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">3</th>\n",
       "      <th>CST</th>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">4</th>\n",
       "      <th>CST</th>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">5</th>\n",
       "      <th>CST</th>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">6</th>\n",
       "      <th>CST</th>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">7</th>\n",
       "      <th>CST</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">8</th>\n",
       "      <th>CST</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">9</th>\n",
       "      <th>CST</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">10</th>\n",
       "      <th>CST</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MST</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">11</th>\n",
       "      <th>CST</th>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">12</th>\n",
       "      <th>CST</th>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EST</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   TOR_F_SCALE  EVENT_ID\n",
       "MONTH CZ_TIMEZONE                       \n",
       "1     CST                   29        29\n",
       "      EST                   12        12\n",
       "2     CST                   50        50\n",
       "      EST                   16        16\n",
       "3     CST                   73        73\n",
       "      EST                   48        48\n",
       "      MST                    1         1\n",
       "4     CST                  205       205\n",
       "      EST                   55        55\n",
       "5     CST                  200       200\n",
       "      EST                   23        23\n",
       "      MST                    2         2\n",
       "6     CST                   68        68\n",
       "      EST                    6         6\n",
       "      MST                    8         8\n",
       "7     CST                   15        15\n",
       "      EST                    8         8\n",
       "      MST                    4         4\n",
       "8     CST                   21        21\n",
       "      EST                    5         5\n",
       "      MST                    1         1\n",
       "9     CST                    6         6\n",
       "      EST                   11        11\n",
       "10    CST                   16        16\n",
       "      EST                    4         4\n",
       "      MST                    2         2\n",
       "11    CST                   62        62\n",
       "      EST                   14        14\n",
       "12    CST                   56        56\n",
       "      EST                    4         4"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "month_grouped = month_df.groupby(['MONTH', 'CZ_TIMEZONE'])\n",
    "\n",
    "\n",
    "month_grouped.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9047c1c0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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