shootings.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "import numpy as np\n",
    "from config import gkey\n",
    "import scipy.stats as stats\n",
    "import gmaps\n",
    "gmaps.configure(api_key=gkey)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        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>CaseID</th>\n",
       "      <th>Title</th>\n",
       "      <th>Location</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Number of Civilian Fatalities</th>\n",
       "      <th>Number of Civilian Injured</th>\n",
       "      <th>Number of Enforcement Fatalities</th>\n",
       "      <th>...</th>\n",
       "      <th>Data Source 3</th>\n",
       "      <th>Data Source 4</th>\n",
       "      <th>Data Source 5</th>\n",
       "      <th>Data Source 6</th>\n",
       "      <th>Data Source 7</th>\n",
       "      <th>Military Experience</th>\n",
       "      <th>Class</th>\n",
       "      <th>Depreciation</th>\n",
       "      <th>Notes</th>\n",
       "      <th>Edit Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>Austin, Texas</td>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>30.198887</td>\n",
       "      <td>-97.844159</td>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>http://news.google.com/newspapers?id=lkk0AAAAI...</td>\n",
       "      <td>http://news.google.com/newspapers?id=PPUjAAAAI...</td>\n",
       "      <td>http://books.google.com/books?id=ClYEAAAAMBAJ&amp;...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>SPK</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/8/2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Rose-Mar College of Beauty</td>\n",
       "      <td>Mesa, Arizona</td>\n",
       "      <td>Mesa</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>33.422687</td>\n",
       "      <td>-111.816320</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>http://www.nydailynews.com/news/crime/beauty-s...</td>\n",
       "      <td>http://books.google.com/books?id=Cre7qsswRiwC&amp;...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>MS</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/8/2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>New Orleans Police Shootings</td>\n",
       "      <td>New Orleans, Louisiana</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>30.068724</td>\n",
       "      <td>-89.931474</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>http://www.trutv.com/library/crime/notorious_m...</td>\n",
       "      <td>http://books.google.com/books?id=TfEDmROcZwEC&amp;...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>SPK</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/22/2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Clara Barton Elementary School</td>\n",
       "      <td>Chicago, Illinois</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>41.839280</td>\n",
       "      <td>-87.688181</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>http://www.leagle.com/xmlResult.aspx?page=1&amp;xm...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>MS</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/21/2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Olean High School</td>\n",
       "      <td>Olean, New York</td>\n",
       "      <td>Olean</td>\n",
       "      <td>New York</td>\n",
       "      <td>42.081854</td>\n",
       "      <td>-78.432139</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>http://www.newswithviews.com/Erica/Carle10.htm</td>\n",
       "      <td>http://books.google.com/books?id=ZuKoSskEWyIC&amp;...</td>\n",
       "      <td>\"Olean High School Shooting\". Larrie Benton Za...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>MS</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6/21/2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   CaseID                           Title                Location  \\\n",
       "0       1   University of Texas at Austin           Austin, Texas   \n",
       "1       2      Rose-Mar College of Beauty           Mesa, Arizona   \n",
       "2       3    New Orleans Police Shootings  New Orleans, Louisiana   \n",
       "3       4  Clara Barton Elementary School       Chicago, Illinois   \n",
       "4       5               Olean High School         Olean, New York   \n",
       "\n",
       "          City      State   Latitude   Longitude  \\\n",
       "0       Austin      Texas  30.198887  -97.844159   \n",
       "1         Mesa    Arizona  33.422687 -111.816320   \n",
       "2  New Orleans  Louisiana  30.068724  -89.931474   \n",
       "3      Chicago   Illinois  41.839280  -87.688181   \n",
       "4        Olean   New York  42.081854  -78.432139   \n",
       "\n",
       "   Number of Civilian Fatalities  Number of Civilian Injured  \\\n",
       "0                             15                          32   \n",
       "1                              5                           1   \n",
       "2                              4                           8   \n",
       "3                              1                           3   \n",
       "4                              3                           7   \n",
       "\n",
       "   Number of Enforcement Fatalities    ...      \\\n",
       "0                                 1    ...       \n",
       "1                                 0    ...       \n",
       "2                                 5    ...       \n",
       "3                                 0    ...       \n",
       "4                                 0    ...       \n",
       "\n",
       "                                       Data Source 3  \\\n",
       "0  http://news.google.com/newspapers?id=lkk0AAAAI...   \n",
       "1  http://www.nydailynews.com/news/crime/beauty-s...   \n",
       "2  http://www.trutv.com/library/crime/notorious_m...   \n",
       "3  http://www.leagle.com/xmlResult.aspx?page=1&xm...   \n",
       "4     http://www.newswithviews.com/Erica/Carle10.htm   \n",
       "\n",
       "                                       Data Source 4  \\\n",
       "0  http://news.google.com/newspapers?id=PPUjAAAAI...   \n",
       "1  http://books.google.com/books?id=Cre7qsswRiwC&...   \n",
       "2  http://books.google.com/books?id=TfEDmROcZwEC&...   \n",
       "3                                                NaN   \n",
       "4  http://books.google.com/books?id=ZuKoSskEWyIC&...   \n",
       "\n",
       "                                       Data Source 5 Data Source 6  \\\n",
       "0  http://books.google.com/books?id=ClYEAAAAMBAJ&...           NaN   \n",
       "1                                                NaN           NaN   \n",
       "2                                                NaN           NaN   \n",
       "3                                                NaN           NaN   \n",
       "4  \"Olean High School Shooting\". Larrie Benton Za...           NaN   \n",
       "\n",
       "  Data Source 7 Military Experience Class Depreciation Notes  Edit Date  \n",
       "0           NaN                 Yes   SPK            1   NaN   6/8/2016  \n",
       "1           NaN             Unknown    MS            1   NaN   6/8/2016  \n",
       "2           NaN             Unknown   SPK            1   NaN  6/22/2016  \n",
       "3           NaN             Unknown    MS            1   NaN  6/21/2016  \n",
       "4           NaN             Unknown    MS            1   NaN  6/21/2016  \n",
       "\n",
       "[5 rows x 55 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read in csv file\n",
    "shootings_df = pd.read_csv(\"Stanford_MSA_Shooting.csv\",encoding=\"utf-8-sig\")\n",
    "shootings_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Filter out needed columns from original dataframe\n",
    "shootings_df = shootings_df[[\"Title\", \"City\", \"State\", \"Latitude\", \"Longitude\", \"Number of Civilian Fatalities\",\n",
    "                    \"Number of Civilian Injured\", \"Number of Enforcement Fatalities\", \n",
    "                    \"Number of Enforcement Injured\",\"Total Number of Victims\",\n",
    "                    \"Date\", \"Type of Gun - General\",\n",
    "                    \"Total Number of Guns\", \"Relationship to Incident Location\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "loc = []\n",
    "for index, row in shootings_df.iterrows():\n",
    "    coordinates = (row[\"Latitude\"],row[\"Longitude\"]) \n",
    "    loc.append(coordinates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "figure_layout = {\n",
    "    'width': '800px',\n",
    "    'height': '500px',\n",
    "    'border': '1px solid black',\n",
    "    'padding': '1px',\n",
    "    'margin': '0 auto 0 auto'\n",
    "}\n",
    "fig = gmaps.figure(layout=figure_layout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "13e25d29238242bea9645b4f15d7ebfd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(border='1px solid black', height='500px', margin='0 auto 0 auto', padding='1px', wi…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Assign the marker layer to a variable\n",
    "markers = gmaps.marker_layer(loc)\n",
    "#Add the layer to the map\n",
    "fig.add_layer(markers)\n",
    "plt.savefig('Images/map.png')\n",
    "fig\n",
    "\n",
    "#if map does not display go to command prompt and issue the command below:\n",
    "#  jupyter nbextension enable --py gmaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Data cleaning\n",
    "shootings_df[\"Relationship to Incident Location\"] = shootings_df[\"Relationship to Incident Location\"].replace(\n",
    "    {\"Place of Residency\": \"Place of residency\", \"Place of Recreation\": \"Place of recreation\",\n",
    "    \"Place of Business/employment\": \"Place of business/employment\", \"Residential home/Neighborhood\": \"Place of residency\" })\n",
    "\n",
    "shootings_df[\"Type of Gun - General\"] = shootings_df[\"Type of Gun - General\"].replace({\"handgun\": \"Handgun\", \"Multiple Guns\": \"Multiple guns\",\n",
    "                                                                                      \"Multiple guns\\r\\n\": \"Multiple guns\", \"\\r\\nMultiple guns\": \"Multiple guns\",\n",
    "                                                                                      \"Semi-Automatic Rifle\": \"Rifle\", \"9-mm\": \"Handgun\"})\n",
    "\n",
    "#Fill empty rows with unknown\n",
    "shootings_df[\"Relationship to Incident Location\"] = shootings_df[\"Relationship to Incident Location\"].fillna(\"Unknown\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Location</th>\n",
       "      <th>Number of Civilian Fatalities</th>\n",
       "      <th>Number of Civilian Injured</th>\n",
       "      <th>Number of Enforcement Fatalities</th>\n",
       "      <th>Number of Enforcement Injured</th>\n",
       "      <th>Total Number of Victim Fatalities</th>\n",
       "      <th>Total Number of Victims</th>\n",
       "      <th>Date</th>\n",
       "      <th>Type of Gun - General</th>\n",
       "      <th>Total Number of Guns</th>\n",
       "      <th>Relationship to Incident Location</th>\n",
       "      <th>Death Percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>30.198887300000003,-97.84415949</td>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>48</td>\n",
       "      <td>8/1/1966</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>7</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>33.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rose-Mar College of Beauty</td>\n",
       "      <td>Mesa</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>33.42268696,-111.8163202</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>11/12/1966</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>83.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>New Orleans Police Shootings</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>30.0687242,-89.93147412</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>22</td>\n",
       "      <td>12/31/1972</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Local government</td>\n",
       "      <td>40.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clara Barton Elementary School</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>41.83928045,-87.68818145</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1/17/1974</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Olean High School</td>\n",
       "      <td>Olean</td>\n",
       "      <td>New York</td>\n",
       "      <td>42.08185369,-78.43213922</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>12/30/1974</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>30.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Los Angeles Computer Learning Center</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>34.17622092,-118.53995420000001</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2/19/1976</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Cal State Fullerton</td>\n",
       "      <td>Fullerton</td>\n",
       "      <td>California</td>\n",
       "      <td>33.88404244,-117.92785</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>7/12/1976</td>\n",
       "      <td>Rifle</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>77.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Grover Cleveland Elementary School</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>32.86357277,-117.1281628</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>1/29/1979</td>\n",
       "      <td>Rifle</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>18.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>University of South Carolina</td>\n",
       "      <td>Columbia</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>34.05098834,-80.82077527</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>10/6/1979</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>28.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Valley High School</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>36.18931923,-115.3264875</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3/19/1982</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>33.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Welding shop in Miami</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>25.79653943,-80.20840397</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>8/20/1982</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>72.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Wah Mee Club in Seattle</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>47.62199575,-122.323646</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>2/18/1983</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of recreation</td>\n",
       "      <td>92.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Johnston Post Office</td>\n",
       "      <td>Johnston</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>33.83272887,-81.8051584</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>8/19/1983</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>49th Street Elementary School</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>34.17622092,-118.53995420000001</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>2/24/1984</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>3</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>14.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Ianni's Club in Dallas</td>\n",
       "      <td>Dallas</td>\n",
       "      <td>Texas</td>\n",
       "      <td>32.79480596,-96.76631094</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>6/29/1984</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of recreation</td>\n",
       "      <td>85.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>McDonald's restaurant in San Ysidro</td>\n",
       "      <td>San Ysidro</td>\n",
       "      <td>California</td>\n",
       "      <td>32.555556,-117.047656</td>\n",
       "      <td>21</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>40</td>\n",
       "      <td>7/18/1984</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>3</td>\n",
       "      <td>Place of recreation</td>\n",
       "      <td>52.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Goddard Junior High School</td>\n",
       "      <td>Goddard</td>\n",
       "      <td>Kansas</td>\n",
       "      <td>37.67129418,-97.55070476</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1/21/1985</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Atlanta Post Office</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>33.7629969,-84.4231328</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3/6/1985</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>66.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>New York Technical College</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.679276,-73.939513</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8/12/1986</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>20.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Post office in Edmond, Oklahoma</td>\n",
       "      <td>Edmond</td>\n",
       "      <td>Oklahoma</td>\n",
       "      <td>35.66889223,-97.41438792</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>8/20/1986</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>3</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>70.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Fergus County High School</td>\n",
       "      <td>Lewistown</td>\n",
       "      <td>Montana</td>\n",
       "      <td>47.03740653,-109.4844918</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>12/4/1986</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Palm Bay Shopping Centers</td>\n",
       "      <td>Palm Bay</td>\n",
       "      <td>Florida</td>\n",
       "      <td>27.98388983,-80.66662713</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>4/23/1987</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>3</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>30.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Pinellas Park High School</td>\n",
       "      <td>Pinellas Park</td>\n",
       "      <td>Florida</td>\n",
       "      <td>27.84887061,-82.71058000000001</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2/11/1988</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>33.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Electromagnetic Systems Laboratory (ESL)</td>\n",
       "      <td>Sunnyvale</td>\n",
       "      <td>California</td>\n",
       "      <td>37.38344257,-122.02561850000001</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>2/16/1988</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>7</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>63.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Hubbard Woods Elementary School</td>\n",
       "      <td>Winnetka</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>42.10648807,-87.74211141</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>5/20/1988</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>12.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Comet Auto Parts and Montefiore School</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>41.83928045,-87.68818145</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>9/22/1988</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>66.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Oakland Elementary School</td>\n",
       "      <td>Greenwood</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>34.1928952,-82.15355508</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>9/26/1988</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>18.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>New Orleans Downtown Post Office</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>30.0687242,-89.93147412</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>12/14/1988</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Cleveland Elementary School</td>\n",
       "      <td>Stockton</td>\n",
       "      <td>California</td>\n",
       "      <td>37.96631812,-121.30187749999999</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>35</td>\n",
       "      <td>1/17/1989</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>14.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Orange Glenn Post Office</td>\n",
       "      <td>Escondido</td>\n",
       "      <td>California</td>\n",
       "      <td>33.13439925,-117.07225279999999</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>8/10/1989</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>75.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>Forestville, Maryland Drive-by</td>\n",
       "      <td>Forestville</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>38.845113,-76.874972</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4/26/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>20.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>Ferguson, MO Drive by</td>\n",
       "      <td>Ferguson</td>\n",
       "      <td>Missouri</td>\n",
       "      <td>38.744217,-90.305391</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4/29/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>Appling, GA family murder</td>\n",
       "      <td>Appling</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>33.54609,-82.316315</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4/22/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>Auburn, AL club shootout</td>\n",
       "      <td>Auburn</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>32.609857,-85.48078199999999</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4/23/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>75.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>Nashville Music City Central shooting</td>\n",
       "      <td>Nashville</td>\n",
       "      <td>Tennessee</td>\n",
       "      <td>36.162664,-86.781602</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4/25/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>Murfreesboro, TN party shooting</td>\n",
       "      <td>Murfreesboro</td>\n",
       "      <td>Tennessee</td>\n",
       "      <td>35.845621,-86.39027</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5/1/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>Florida Ex-wife, ex-girlfriend murder</td>\n",
       "      <td>Green Cove Springs</td>\n",
       "      <td>Florida</td>\n",
       "      <td>29.991909000000003,-81.678147</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5/3/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>Katy, Texas work retaliation murder</td>\n",
       "      <td>Katy</td>\n",
       "      <td>Texas</td>\n",
       "      <td>29.785784999999997,-95.824396</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5/4/2016</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of business/employment</td>\n",
       "      <td>33.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>Card game ambush in Shreveport, Louisiana</td>\n",
       "      <td>Shreveport</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>32.525152,-93.750179</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>5/5/2016</td>\n",
       "      <td>Rifle</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>Allapattah, Florida street shooting</td>\n",
       "      <td>Allapattah</td>\n",
       "      <td>Florida</td>\n",
       "      <td>25.800314999999998,-80.226555</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5/5/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>Federal Security Officer has day shooting ramp...</td>\n",
       "      <td>Bethesda</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>38.984652000000004,-77.094709</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>5/6/2016</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>50.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>Montgomery, Alabama street shooting</td>\n",
       "      <td>Montgomery</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>32.366805,-86.29996899999999</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5/6/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>Detroit street shooting</td>\n",
       "      <td>Detroit</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>42.331427000000005,-83.045754</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5/6/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>20.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>Austin Taco truck murder</td>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>30.267153000000004,-97.743061</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5/8/2016</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319</th>\n",
       "      <td>Birmingham Domestic Dispute Murder</td>\n",
       "      <td>Birmingham</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>33.520661,-86.80249</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5/11/2016</td>\n",
       "      <td>Rifle</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>20.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>Chicago bus stop ambush</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>41.878114000000004,-87.629798</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5/11/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>321</th>\n",
       "      <td>Chicago Family Murder Suicide</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>41.878114000000004,-87.629798</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5/12/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322</th>\n",
       "      <td>Phoenix girlfriend murder and cop shootout</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>33.448377,-112.074037</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5/14/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>33.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>323</th>\n",
       "      <td>Friend murder and fire coverup in Moultrie, GA</td>\n",
       "      <td>Moultrie</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>31.179940999999996,-83.788839</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5/15/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324</th>\n",
       "      <td>Trailer park triple homocide in South Carolina</td>\n",
       "      <td>Ravenel</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>32.763232,-80.250099</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5/17/2016</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>75.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>Graduation party drive by</td>\n",
       "      <td>Jackson</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>33.294565000000006,-83.966021</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5/18/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Place of residency</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>Stockton, CA murder</td>\n",
       "      <td>Stockton</td>\n",
       "      <td>California</td>\n",
       "      <td>37.957702000000005,-121.29078</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5/21/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>327</th>\n",
       "      <td>NYC Concert shooting</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.712784,-74.005941</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5/25/2016</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>33.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>Las Vegas sidewalk shooting</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>36.169940999999994,-115.13983</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5/29/2016</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>Army vet shooting in Houston</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>29.760427000000004,-95.369803</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>5/29/2016</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "      <td>14.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>Fort Warne drive by</td>\n",
       "      <td>Fort Wayne</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>41.079273,-85.139351</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5/31/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>Cape Coral Shooting Spree</td>\n",
       "      <td>Cape Coral</td>\n",
       "      <td>Florida</td>\n",
       "      <td>26.562853999999998,-81.949533</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>6/7/2016</td>\n",
       "      <td>Shotgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>40.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>332</th>\n",
       "      <td>Webster, MN party shooting</td>\n",
       "      <td>Webster</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>44.529686,-93.352723</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>6/11/2016</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>333</th>\n",
       "      <td>Orlando Nightclub Massacre</td>\n",
       "      <td>Orlando</td>\n",
       "      <td>Florida</td>\n",
       "      <td>28.538334999999996,-81.37923599999999</td>\n",
       "      <td>49</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>49</td>\n",
       "      <td>102</td>\n",
       "      <td>6/12/2016</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of recreation</td>\n",
       "      <td>48.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334</th>\n",
       "      <td>Nightclub Disput</td>\n",
       "      <td>Lyman</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>34.948174,-82.12733100000001</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>6/26/2016</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>335 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 Title                City  \\\n",
       "0                        University of Texas at Austin              Austin   \n",
       "1                           Rose-Mar College of Beauty                Mesa   \n",
       "2                         New Orleans Police Shootings         New Orleans   \n",
       "3                       Clara Barton Elementary School             Chicago   \n",
       "4                                    Olean High School               Olean   \n",
       "5                 Los Angeles Computer Learning Center         Los Angeles   \n",
       "6                                  Cal State Fullerton           Fullerton   \n",
       "7                   Grover Cleveland Elementary School           San Diego   \n",
       "8                         University of South Carolina            Columbia   \n",
       "9                                   Valley High School           Las Vegas   \n",
       "10                               Welding shop in Miami               Miami   \n",
       "11                             Wah Mee Club in Seattle             Seattle   \n",
       "12                                Johnston Post Office            Johnston   \n",
       "13                       49th Street Elementary School         Los Angeles   \n",
       "14                              Ianni's Club in Dallas              Dallas   \n",
       "15                 McDonald's restaurant in San Ysidro          San Ysidro   \n",
       "16                          Goddard Junior High School             Goddard   \n",
       "17                                 Atlanta Post Office             Atlanta   \n",
       "18                          New York Technical College            Brooklyn   \n",
       "19                     Post office in Edmond, Oklahoma              Edmond   \n",
       "20                           Fergus County High School           Lewistown   \n",
       "21                           Palm Bay Shopping Centers            Palm Bay   \n",
       "22                           Pinellas Park High School       Pinellas Park   \n",
       "23            Electromagnetic Systems Laboratory (ESL)           Sunnyvale   \n",
       "24                     Hubbard Woods Elementary School            Winnetka   \n",
       "25              Comet Auto Parts and Montefiore School             Chicago   \n",
       "26                           Oakland Elementary School           Greenwood   \n",
       "27                    New Orleans Downtown Post Office         New Orleans   \n",
       "28                         Cleveland Elementary School            Stockton   \n",
       "29                            Orange Glenn Post Office           Escondido   \n",
       "..                                                 ...                 ...   \n",
       "305                     Forestville, Maryland Drive-by         Forestville   \n",
       "306                              Ferguson, MO Drive by            Ferguson   \n",
       "307                          Appling, GA family murder             Appling   \n",
       "308                           Auburn, AL club shootout              Auburn   \n",
       "309              Nashville Music City Central shooting           Nashville   \n",
       "310                    Murfreesboro, TN party shooting        Murfreesboro   \n",
       "311              Florida Ex-wife, ex-girlfriend murder  Green Cove Springs   \n",
       "312                Katy, Texas work retaliation murder                Katy   \n",
       "313          Card game ambush in Shreveport, Louisiana          Shreveport   \n",
       "314                Allapattah, Florida street shooting          Allapattah   \n",
       "315  Federal Security Officer has day shooting ramp...            Bethesda   \n",
       "316                Montgomery, Alabama street shooting          Montgomery   \n",
       "317                            Detroit street shooting             Detroit   \n",
       "318                           Austin Taco truck murder              Austin   \n",
       "319                 Birmingham Domestic Dispute Murder          Birmingham   \n",
       "320                            Chicago bus stop ambush             Chicago   \n",
       "321                      Chicago Family Murder Suicide             Chicago   \n",
       "322         Phoenix girlfriend murder and cop shootout             Phoenix   \n",
       "323     Friend murder and fire coverup in Moultrie, GA            Moultrie   \n",
       "324     Trailer park triple homocide in South Carolina             Ravenel   \n",
       "325                          Graduation party drive by             Jackson   \n",
       "326                                Stockton, CA murder            Stockton   \n",
       "327                               NYC Concert shooting       New York City   \n",
       "328                        Las Vegas sidewalk shooting           Las Vegas   \n",
       "329                       Army vet shooting in Houston             Houston   \n",
       "330                                Fort Warne drive by          Fort Wayne   \n",
       "331                          Cape Coral Shooting Spree          Cape Coral   \n",
       "332                         Webster, MN party shooting             Webster   \n",
       "333                         Orlando Nightclub Massacre             Orlando   \n",
       "334                                   Nightclub Disput               Lyman   \n",
       "\n",
       "              State                               Location  \\\n",
       "0             Texas        30.198887300000003,-97.84415949   \n",
       "1           Arizona               33.42268696,-111.8163202   \n",
       "2         Louisiana                30.0687242,-89.93147412   \n",
       "3          Illinois               41.83928045,-87.68818145   \n",
       "4          New York               42.08185369,-78.43213922   \n",
       "5        California        34.17622092,-118.53995420000001   \n",
       "6        California                 33.88404244,-117.92785   \n",
       "7        California               32.86357277,-117.1281628   \n",
       "8    South Carolina               34.05098834,-80.82077527   \n",
       "9            Nevada               36.18931923,-115.3264875   \n",
       "10          Florida               25.79653943,-80.20840397   \n",
       "11       Washington                47.62199575,-122.323646   \n",
       "12   South Carolina                33.83272887,-81.8051584   \n",
       "13       California        34.17622092,-118.53995420000001   \n",
       "14            Texas               32.79480596,-96.76631094   \n",
       "15       California                  32.555556,-117.047656   \n",
       "16           Kansas               37.67129418,-97.55070476   \n",
       "17          Georgia                 33.7629969,-84.4231328   \n",
       "18         New York                   40.679276,-73.939513   \n",
       "19         Oklahoma               35.66889223,-97.41438792   \n",
       "20          Montana               47.03740653,-109.4844918   \n",
       "21          Florida               27.98388983,-80.66662713   \n",
       "22          Florida         27.84887061,-82.71058000000001   \n",
       "23       California        37.38344257,-122.02561850000001   \n",
       "24         Illinois               42.10648807,-87.74211141   \n",
       "25         Illinois               41.83928045,-87.68818145   \n",
       "26   South Carolina                34.1928952,-82.15355508   \n",
       "27        Louisiana                30.0687242,-89.93147412   \n",
       "28       California        37.96631812,-121.30187749999999   \n",
       "29       California        33.13439925,-117.07225279999999   \n",
       "..              ...                                    ...   \n",
       "305        Maryland                   38.845113,-76.874972   \n",
       "306        Missouri                   38.744217,-90.305391   \n",
       "307         Georgia                    33.54609,-82.316315   \n",
       "308         Alabama           32.609857,-85.48078199999999   \n",
       "309       Tennessee                   36.162664,-86.781602   \n",
       "310       Tennessee                    35.845621,-86.39027   \n",
       "311         Florida          29.991909000000003,-81.678147   \n",
       "312           Texas          29.785784999999997,-95.824396   \n",
       "313       Louisiana                   32.525152,-93.750179   \n",
       "314         Florida          25.800314999999998,-80.226555   \n",
       "315        Maryland          38.984652000000004,-77.094709   \n",
       "316         Alabama           32.366805,-86.29996899999999   \n",
       "317        Michigan          42.331427000000005,-83.045754   \n",
       "318           Texas          30.267153000000004,-97.743061   \n",
       "319         Alabama                    33.520661,-86.80249   \n",
       "320        Illinois          41.878114000000004,-87.629798   \n",
       "321        Illinois          41.878114000000004,-87.629798   \n",
       "322         Arizona                  33.448377,-112.074037   \n",
       "323         Georgia          31.179940999999996,-83.788839   \n",
       "324  South Carolina                   32.763232,-80.250099   \n",
       "325         Georgia          33.294565000000006,-83.966021   \n",
       "326      California          37.957702000000005,-121.29078   \n",
       "327        New York                   40.712784,-74.005941   \n",
       "328          Nevada          36.169940999999994,-115.13983   \n",
       "329           Texas          29.760427000000004,-95.369803   \n",
       "330         Indiana                   41.079273,-85.139351   \n",
       "331         Florida          26.562853999999998,-81.949533   \n",
       "332       Minnesota                   44.529686,-93.352723   \n",
       "333         Florida  28.538334999999996,-81.37923599999999   \n",
       "334  South Carolina           34.948174,-82.12733100000001   \n",
       "\n",
       "     Number of Civilian Fatalities  Number of Civilian Injured  \\\n",
       "0                               15                          32   \n",
       "1                                5                           1   \n",
       "2                                4                           8   \n",
       "3                                1                           3   \n",
       "4                                3                           7   \n",
       "5                                1                           6   \n",
       "6                                7                           2   \n",
       "7                                2                           8   \n",
       "8                                2                           5   \n",
       "9                                1                           2   \n",
       "10                               8                           3   \n",
       "11                              13                           1   \n",
       "12                               1                           3   \n",
       "13                               2                          12   \n",
       "14                               6                           1   \n",
       "15                              21                          19   \n",
       "16                               1                           3   \n",
       "17                               2                           1   \n",
       "18                               1                           4   \n",
       "19                              14                           6   \n",
       "20                               1                           3   \n",
       "21                               4                          14   \n",
       "22                               1                           2   \n",
       "23                               7                           4   \n",
       "24                               1                           7   \n",
       "25                               3                           1   \n",
       "26                               2                           9   \n",
       "27                               0                           3   \n",
       "28                               5                          30   \n",
       "29                               3                           1   \n",
       "..                             ...                         ...   \n",
       "305                              1                           4   \n",
       "306                              0                           4   \n",
       "307                              5                           0   \n",
       "308                              3                           1   \n",
       "309                              0                           4   \n",
       "310                              5                           0   \n",
       "311                              3                           0   \n",
       "312                              1                           2   \n",
       "313                              2                           6   \n",
       "314                              1                           3   \n",
       "315                              3                           3   \n",
       "316                              1                           3   \n",
       "317                              1                           4   \n",
       "318                              1                           3   \n",
       "319                              1                           4   \n",
       "320                              0                           5   \n",
       "321                              3                           0   \n",
       "322                              1                           0   \n",
       "323                              5                           0   \n",
       "324                              3                           1   \n",
       "325                              1                           3   \n",
       "326                              1                           3   \n",
       "327                              1                           2   \n",
       "328                              0                           4   \n",
       "329                              1                           4   \n",
       "330                              0                           4   \n",
       "331                              2                           3   \n",
       "332                              0                           4   \n",
       "333                             49                          52   \n",
       "334                              0                           3   \n",
       "\n",
       "     Number of Enforcement Fatalities  Number of Enforcement Injured  \\\n",
       "0                                   1                              0   \n",
       "1                                   0                              0   \n",
       "2                                   5                              5   \n",
       "3                                   0                              0   \n",
       "4                                   0                              0   \n",
       "5                                   1                              0   \n",
       "6                                   0                              0   \n",
       "7                                   0                              1   \n",
       "8                                   0                              0   \n",
       "9                                   0                              0   \n",
       "10                                  0                              0   \n",
       "11                                  0                              0   \n",
       "12                                  0                              0   \n",
       "13                                  0                              0   \n",
       "14                                  0                              0   \n",
       "15                                  0                              0   \n",
       "16                                  0                              0   \n",
       "17                                  0                              0   \n",
       "18                                  0                              0   \n",
       "19                                  0                              0   \n",
       "20                                  0                              0   \n",
       "21                                  2                              0   \n",
       "22                                  0                              0   \n",
       "23                                  0                              0   \n",
       "24                                  0                              0   \n",
       "25                                  1                              1   \n",
       "26                                  0                              0   \n",
       "27                                  0                              1   \n",
       "28                                  0                              0   \n",
       "29                                  0                              0   \n",
       "..                                ...                            ...   \n",
       "305                                 0                              0   \n",
       "306                                 0                              0   \n",
       "307                                 0                              0   \n",
       "308                                 0                              0   \n",
       "309                                 0                              0   \n",
       "310                                 0                              0   \n",
       "311                                 0                              0   \n",
       "312                                 0                              0   \n",
       "313                                 0                              0   \n",
       "314                                 0                              0   \n",
       "315                                 0                              0   \n",
       "316                                 0                              0   \n",
       "317                                 0                              0   \n",
       "318                                 0                              0   \n",
       "319                                 0                              0   \n",
       "320                                 0                              0   \n",
       "321                                 0                              0   \n",
       "322                                 0                              2   \n",
       "323                                 0                              0   \n",
       "324                                 0                              0   \n",
       "325                                 0                              0   \n",
       "326                                 0                              0   \n",
       "327                                 0                              0   \n",
       "328                                 0                              0   \n",
       "329                                 0                              2   \n",
       "330                                 0                              0   \n",
       "331                                 0                              0   \n",
       "332                                 0                              0   \n",
       "333                                 0                              1   \n",
       "334                                 0                              0   \n",
       "\n",
       "     Total Number of Victim Fatalities  Total Number of Victims        Date  \\\n",
       "0                                   16                       48    8/1/1966   \n",
       "1                                    5                        6  11/12/1966   \n",
       "2                                    9                       22  12/31/1972   \n",
       "3                                    1                        4   1/17/1974   \n",
       "4                                    3                       10  12/30/1974   \n",
       "5                                    2                        8   2/19/1976   \n",
       "6                                    7                        9   7/12/1976   \n",
       "7                                    2                       11   1/29/1979   \n",
       "8                                    2                        7   10/6/1979   \n",
       "9                                    1                        3   3/19/1982   \n",
       "10                                   8                       11   8/20/1982   \n",
       "11                                  13                       14   2/18/1983   \n",
       "12                                   1                        4   8/19/1983   \n",
       "13                                   2                       14   2/24/1984   \n",
       "14                                   6                        7   6/29/1984   \n",
       "15                                  21                       40   7/18/1984   \n",
       "16                                   1                        4   1/21/1985   \n",
       "17                                   2                        3    3/6/1985   \n",
       "18                                   1                        5   8/12/1986   \n",
       "19                                  14                       20   8/20/1986   \n",
       "20                                   1                        4   12/4/1986   \n",
       "21                                   6                       20   4/23/1987   \n",
       "22                                   1                        3   2/11/1988   \n",
       "23                                   7                       11   2/16/1988   \n",
       "24                                   1                        8   5/20/1988   \n",
       "25                                   4                        6   9/22/1988   \n",
       "26                                   2                       11   9/26/1988   \n",
       "27                                   0                        4  12/14/1988   \n",
       "28                                   5                       35   1/17/1989   \n",
       "29                                   3                        4   8/10/1989   \n",
       "..                                 ...                      ...         ...   \n",
       "305                                  1                        5   4/26/2016   \n",
       "306                                  0                        4   4/29/2016   \n",
       "307                                  5                        5   4/22/2016   \n",
       "308                                  3                        4   4/23/2016   \n",
       "309                                  0                        4   4/25/2016   \n",
       "310                                  5                        5    5/1/2016   \n",
       "311                                  3                        3    5/3/2016   \n",
       "312                                  1                        3    5/4/2016   \n",
       "313                                  2                        8    5/5/2016   \n",
       "314                                  1                        4    5/5/2016   \n",
       "315                                  3                        6    5/6/2016   \n",
       "316                                  1                        4    5/6/2016   \n",
       "317                                  1                        5    5/6/2016   \n",
       "318                                  1                        4    5/8/2016   \n",
       "319                                  1                        5   5/11/2016   \n",
       "320                                  0                        5   5/11/2016   \n",
       "321                                  3                        3   5/12/2016   \n",
       "322                                  1                        3   5/14/2016   \n",
       "323                                  5                        5   5/15/2016   \n",
       "324                                  3                        4   5/17/2016   \n",
       "325                                  1                        4   5/18/2016   \n",
       "326                                  1                        4   5/21/2016   \n",
       "327                                  1                        3   5/25/2016   \n",
       "328                                  0                        4   5/29/2016   \n",
       "329                                  1                        7   5/29/2016   \n",
       "330                                  0                        4   5/31/2016   \n",
       "331                                  2                        5    6/7/2016   \n",
       "332                                  0                        4   6/11/2016   \n",
       "333                                 49                      102   6/12/2016   \n",
       "334                                  0                        3   6/26/2016   \n",
       "\n",
       "    Type of Gun - General Total Number of Guns  \\\n",
       "0           Multiple guns                    7   \n",
       "1                 Handgun                    1   \n",
       "2           Multiple guns                    2   \n",
       "3                 Handgun                    2   \n",
       "4           Multiple guns                    2   \n",
       "5                 Shotgun                    1   \n",
       "6                   Rifle                    1   \n",
       "7                   Rifle                    1   \n",
       "8                 Handgun                    1   \n",
       "9                 Handgun                    1   \n",
       "10                Shotgun                    1   \n",
       "11                Handgun                    2   \n",
       "12                Shotgun                    1   \n",
       "13          Multiple guns                    3   \n",
       "14                Handgun                    1   \n",
       "15          Multiple guns                    3   \n",
       "16          Multiple guns                    2   \n",
       "17                Handgun                    1   \n",
       "18                Handgun                    2   \n",
       "19                Handgun                    3   \n",
       "20                Handgun                    1   \n",
       "21          Multiple guns                    3   \n",
       "22          Multiple guns                    2   \n",
       "23          Multiple guns                    7   \n",
       "24          Multiple guns                    2   \n",
       "25                Handgun                    1   \n",
       "26                Handgun                    1   \n",
       "27                Shotgun                    1   \n",
       "28          Multiple guns                    2   \n",
       "29                Handgun                    1   \n",
       "..                    ...                  ...   \n",
       "305               Unknown              Unknown   \n",
       "306               Unknown              Unknown   \n",
       "307               Unknown              Unknown   \n",
       "308               Unknown              Unknown   \n",
       "309               Unknown              Unknown   \n",
       "310               Unknown              Unknown   \n",
       "311               Unknown              Unknown   \n",
       "312               Shotgun                    1   \n",
       "313                 Rifle              Unknown   \n",
       "314               Unknown              Unknown   \n",
       "315               Handgun                    1   \n",
       "316               Unknown              Unknown   \n",
       "317               Unknown              Unknown   \n",
       "318               Shotgun                    1   \n",
       "319                 Rifle                    1   \n",
       "320               Unknown              Unknown   \n",
       "321               Unknown              Unknown   \n",
       "322               Unknown              Unknown   \n",
       "323               Unknown              Unknown   \n",
       "324               Handgun                    1   \n",
       "325               Unknown              Unknown   \n",
       "326               Unknown              Unknown   \n",
       "327               Handgun                    1   \n",
       "328               Handgun                    1   \n",
       "329         Multiple guns                    2   \n",
       "330               Unknown              Unknown   \n",
       "331               Shotgun                    1   \n",
       "332               Unknown              Unknown   \n",
       "333         Multiple guns                    2   \n",
       "334               Handgun                    1   \n",
       "\n",
       "    Relationship to Incident Location  Death Percent  \n",
       "0                  Place of schooling          33.33  \n",
       "1                                None          83.33  \n",
       "2                    Local government          40.91  \n",
       "3                  Place of schooling          25.00  \n",
       "4                  Place of schooling          30.00  \n",
       "5                  Place of schooling          25.00  \n",
       "6        Place of business/employment          77.78  \n",
       "7                  Place of residency          18.18  \n",
       "8                  Place of schooling          28.57  \n",
       "9                  Place of schooling          33.33  \n",
       "10       Place of business/employment          72.73  \n",
       "11                Place of recreation          92.86  \n",
       "12       Place of business/employment          25.00  \n",
       "13                 Place of residency          14.29  \n",
       "14                Place of recreation          85.71  \n",
       "15                Place of recreation          52.50  \n",
       "16                 Place of schooling          25.00  \n",
       "17       Place of business/employment          66.67  \n",
       "18                 Place of schooling          20.00  \n",
       "19       Place of business/employment          70.00  \n",
       "20                 Place of schooling          25.00  \n",
       "21                 Place of residency          30.00  \n",
       "22                 Place of schooling          33.33  \n",
       "23       Place of business/employment          63.64  \n",
       "24                 Place of residency          12.50  \n",
       "25                 Place of residency          66.67  \n",
       "26                 Place of schooling          18.18  \n",
       "27       Place of business/employment           0.00  \n",
       "28                 Place of schooling          14.29  \n",
       "29       Place of business/employment          75.00  \n",
       "..                                ...            ...  \n",
       "305                           Unknown          20.00  \n",
       "306                           Unknown           0.00  \n",
       "307                Place of residency         100.00  \n",
       "308                           Unknown          75.00  \n",
       "309                           Unknown           0.00  \n",
       "310                           Unknown         100.00  \n",
       "311      Place of business/employment         100.00  \n",
       "312      Place of business/employment          33.33  \n",
       "313                           Unknown          25.00  \n",
       "314                           Unknown          25.00  \n",
       "315                           Unknown          50.00  \n",
       "316                           Unknown          25.00  \n",
       "317                           Unknown          20.00  \n",
       "318                           Unknown          25.00  \n",
       "319                Place of residency          20.00  \n",
       "320                           Unknown           0.00  \n",
       "321                Place of residency         100.00  \n",
       "322                Place of residency          33.33  \n",
       "323                Place of residency         100.00  \n",
       "324                Place of residency          75.00  \n",
       "325                Place of residency          25.00  \n",
       "326                           Unknown          25.00  \n",
       "327                           Unknown          33.33  \n",
       "328                              None           0.00  \n",
       "329                              None          14.29  \n",
       "330                           Unknown           0.00  \n",
       "331                           Unknown          40.00  \n",
       "332                           Unknown           0.00  \n",
       "333               Place of recreation          48.04  \n",
       "334                           Unknown           0.00  \n",
       "\n",
       "[335 rows x 15 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Combine the lat. and long. into one column\n",
    "shootings_df[\"Location\"] = (shootings_df[\"Latitude\"]).astype(str)+','+ shootings_df[\"Longitude\"].astype(str)\n",
    "\n",
    "#Create new column with total number of victim fatalitites\n",
    "shootings_df[\"Total Number of Victim Fatalities\"] = shootings_df[\"Number of Civilian Fatalities\"] + shootings_df[\"Number of Enforcement Fatalities\"]\n",
    "\n",
    "#Rearrange column order\n",
    "shootings_df = shootings_df[[\"Title\", \"City\", \"State\", \"Location\", \"Number of Civilian Fatalities\",\n",
    "                    \"Number of Civilian Injured\", \"Number of Enforcement Fatalities\", \n",
    "                    \"Number of Enforcement Injured\", \"Total Number of Victim Fatalities\", \"Total Number of Victims\",\n",
    "                    \"Date\", \"Type of Gun - General\",\n",
    "                    \"Total Number of Guns\", \"Relationship to Incident Location\"]]\n",
    "shootings_df[\"Death Percent\"] = round((((shootings_df[\"Number of Civilian Fatalities\"] + shootings_df[\"Number of Enforcement Fatalities\"]) / shootings_df[\"Total Number of Victims\"])) * 100, 2)\n",
    "shootings_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Type of Gun - General\n",
       "Handgun          140\n",
       "Multiple guns     64\n",
       "Rifle             32\n",
       "Shotgun           17\n",
       "Unknown           82\n",
       "Name: Type of Gun - General, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Group by gun type\n",
    "weapons_group = shootings_df.groupby([\"Type of Gun - General\"])\n",
    "gun_count = weapons_group[\"Type of Gun - General\"].count()\n",
    "gun_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Build Pie Chart\n",
    "labels = [\"Handgun\", \"Multiple guns\", \"Rifle\", \"Shotgun\", \"Unknown\"]\n",
    "colors = [\"steelblue\", \"darkorange\", \"forestgreen\", \"crimson\", \"mediumpurple\"]\n",
    "explode = (0.15, 0, 0, 0, 0)\n",
    "plt.pie(gun_count, explode=explode, labels=labels, colors=colors,\n",
    "        autopct=\"%1.1f%%\", shadow=True, startangle=150)\n",
    "plt.title(\"% of Shootings, by Gun Type\")\n",
    "plt.savefig(\"Images/pctshootings.png\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>avg victims</th>\n",
       "      <th>avg deaths</th>\n",
       "      <th>avg death percent (from total victims)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type of Gun - General</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Handgun</th>\n",
       "      <td>7.32</td>\n",
       "      <td>3.81</td>\n",
       "      <td>54.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Multiple guns</th>\n",
       "      <td>14.47</td>\n",
       "      <td>6.22</td>\n",
       "      <td>48.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rifle</th>\n",
       "      <td>7.00</td>\n",
       "      <td>2.78</td>\n",
       "      <td>44.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shotgun</th>\n",
       "      <td>4.94</td>\n",
       "      <td>2.18</td>\n",
       "      <td>41.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown</th>\n",
       "      <td>4.35</td>\n",
       "      <td>1.70</td>\n",
       "      <td>42.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       avg victims  avg deaths  \\\n",
       "Type of Gun - General                            \n",
       "Handgun                       7.32        3.81   \n",
       "Multiple guns                14.47        6.22   \n",
       "Rifle                         7.00        2.78   \n",
       "Shotgun                       4.94        2.18   \n",
       "Unknown                       4.35        1.70   \n",
       "\n",
       "                       avg death percent (from total victims)  \n",
       "Type of Gun - General                                          \n",
       "Handgun                                                 54.40  \n",
       "Multiple guns                                           48.13  \n",
       "Rifle                                                   44.09  \n",
       "Shotgun                                                 41.43  \n",
       "Unknown                                                 42.41  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Group by gun type to get average victim count\n",
    "avg = round(weapons_group[\"Total Number of Victims\"].mean(), 2)\n",
    "#Average number of deaths\n",
    "death_cnt = round(weapons_group[\"Number of Civilian Fatalities\"].mean() + weapons_group[\"Number of Enforcement Fatalities\"].mean(), 2)\n",
    "# Average death percent from total victims\n",
    "death_pct = round(weapons_group[\"Death Percent\"].mean(), 2)\n",
    "# Create dataframe\n",
    "deaths_df = pd.DataFrame({\"avg victims\": avg, \"avg deaths\": death_cnt, \"avg death percent (from total victims)\": death_pct})\n",
    "deaths_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "index = ['Handgun', 'Multiple guns', 'Rifle', 'Shotgun', 'Unknown']\n",
    "df = pd.DataFrame({\"avg victims\": avg, \"avg deaths\": death_cnt}, index=index)\n",
    "ax = df.plot.bar(rot=0, title=\"Average # of Victims and Deaths in Shootings, by Gun Type\")\n",
    "ax.set_xlabel(\"Gun Type\")\n",
    "\n",
    "plt.savefig(\"Images/avgvictimsanddeaths.png\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_guns = pd.DataFrame({\"avg death percent\": death_pct})\n",
    "new_guns = new_guns.sort_values(['avg death percent'], ascending=[False])\n",
    "ax = new_guns.plot(kind='bar', title=\"Average % of Fatalities from Total Victims, by Gun Type\") \n",
    "\n",
    "for p in ax.patches:\n",
    "    ax.annotate(str(p.get_height()), (p.get_x() * 1.005, p.get_height() * 1.009))\n",
    "\n",
    "plt.savefig(\"Images/fatalities.png\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#count number of mass shooting per state\n",
    "s = shootings_df[\"State\"].value_counts()\n",
    "s_df = pd.DataFrame(s)\n",
    "\n",
    "#reset index\n",
    "s_df.reset_index(inplace=True)\n",
    "\n",
    "#rename column header\n",
    "s_df.rename(columns ={\"index\":\"State\",\"State\":\"Number of Mass Shootings\"},inplace=True)\n",
    "\n",
    "#plot bar graph to show number of mass shootings per state\n",
    "x =s_df[\"State\"]\n",
    "y =s_df[\"Number of Mass Shootings\"]\n",
    "\n",
    "plt.figure(figsize=(11,6))\n",
    "plt.bar(x,y,color =\"b\",width=0.8, align=\"center\")\n",
    "\n",
    "#add x labels, y labels, title\n",
    "plt.xlabel(\"State\")\n",
    "plt.ylabel(\"Number of Mass Shootings\")\n",
    "plt.title(\"Number of Mass Shootings per State (1966-2016)\")\n",
    "\n",
    "#rotate x-axis to display name of states vertically\n",
    "plt.xticks(rotation=90) \n",
    "plt.tight_layout()\n",
    "#save image\n",
    "plt.savefig(\"Images/shootingsperstate.png\", bbox_inches=\"tight\")\n",
    "#show fig\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#count number of mass shooting at each location type\n",
    "loc = shootings_df[\"Relationship to Incident Location\"].value_counts()\n",
    "loc_df = pd. DataFrame(loc)\n",
    "\n",
    "#drop unknown and none location type \n",
    "loc_df.drop([\"Unknown\",\"None\"],inplace=True)\n",
    "\n",
    "#reset index\n",
    "loc_df.reset_index(inplace=True)\n",
    "\n",
    "#rename column header\n",
    "loc_df.rename(columns ={\"index\":\"Location Type\",\"Relationship to Incident Location\":\"Number of Mass Shootings\"},inplace=True)\n",
    "loc_df\n",
    "\n",
    "#plot bar graph to show number of mass shootings occured at different location type\n",
    "x =loc_df[\"Location Type\"]\n",
    "y =loc_df[\"Number of Mass Shootings\"]\n",
    "\n",
    "plt.figure(figsize=(12,4))\n",
    "plt.bar(x,y,color =\"b\",width=0.8, align=\"center\")\n",
    "\n",
    "#add x labels, y labels, title\n",
    "plt.xlabel(\"Location Type\")\n",
    "plt.ylabel(\"Number of Mass Shootings\")\n",
    "plt.title(\"Number of Mass Shootings vs. Location Type (1966-2016)\")\n",
    "\n",
    "#rotate x-axis to display name of location type vertically\n",
    "plt.xticks(rotation=45) \n",
    "\n",
    "#save image\n",
    "plt.savefig(\"Images/locationtype.png\", bbox_inches=\"tight\")\n",
    "\n",
    "#show fig\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>Title</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Location</th>\n",
       "      <th>Number of Civilian Fatalities</th>\n",
       "      <th>Number of Civilian Injured</th>\n",
       "      <th>Number of Enforcement Fatalities</th>\n",
       "      <th>Number of Enforcement Injured</th>\n",
       "      <th>Total Number of Victim Fatalities</th>\n",
       "      <th>Total Number of Victims</th>\n",
       "      <th>Date</th>\n",
       "      <th>Type of Gun - General</th>\n",
       "      <th>Total Number of Guns</th>\n",
       "      <th>Relationship to Incident Location</th>\n",
       "      <th>Death Percent</th>\n",
       "      <th>Nearest Police Department</th>\n",
       "      <th>Nearest Police Department Proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>Austin</td>\n",
       "      <td>Texas</td>\n",
       "      <td>30.198887300000003,-97.84415949</td>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>48</td>\n",
       "      <td>8/1/1966</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>7</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>33.33</td>\n",
       "      <td>Sunset Valley Police</td>\n",
       "      <td>3.5 mi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rose-Mar College of Beauty</td>\n",
       "      <td>Mesa</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>33.42268696,-111.8163202</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>11/12/1966</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>83.33</td>\n",
       "      <td>Mesa Police Department</td>\n",
       "      <td>1.5 mi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>New Orleans Police Shootings</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>30.0687242,-89.93147412</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>22</td>\n",
       "      <td>12/31/1972</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Local government</td>\n",
       "      <td>40.91</td>\n",
       "      <td>New Orleans Police Department</td>\n",
       "      <td>4.4 mi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clara Barton Elementary School</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>41.83928045,-87.68818145</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1/17/1974</td>\n",
       "      <td>Handgun</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>25.00</td>\n",
       "      <td>Cook County Sheriff-Criminal</td>\n",
       "      <td>1.0 mi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Olean High School</td>\n",
       "      <td>Olean</td>\n",
       "      <td>New York</td>\n",
       "      <td>42.08185369,-78.43213922</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>12/30/1974</td>\n",
       "      <td>Multiple guns</td>\n",
       "      <td>2</td>\n",
       "      <td>Place of schooling</td>\n",
       "      <td>30.00</td>\n",
       "      <td>Olean Police Department</td>\n",
       "      <td>0.5 mi</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Title         City      State  \\\n",
       "0   University of Texas at Austin       Austin      Texas   \n",
       "1      Rose-Mar College of Beauty         Mesa    Arizona   \n",
       "2    New Orleans Police Shootings  New Orleans  Louisiana   \n",
       "3  Clara Barton Elementary School      Chicago   Illinois   \n",
       "4               Olean High School        Olean   New York   \n",
       "\n",
       "                          Location  Number of Civilian Fatalities  \\\n",
       "0  30.198887300000003,-97.84415949                             15   \n",
       "1         33.42268696,-111.8163202                              5   \n",
       "2          30.0687242,-89.93147412                              4   \n",
       "3         41.83928045,-87.68818145                              1   \n",
       "4         42.08185369,-78.43213922                              3   \n",
       "\n",
       "   Number of Civilian Injured  Number of Enforcement Fatalities  \\\n",
       "0                          32                                 1   \n",
       "1                           1                                 0   \n",
       "2                           8                                 5   \n",
       "3                           3                                 0   \n",
       "4                           7                                 0   \n",
       "\n",
       "   Number of Enforcement Injured  Total Number of Victim Fatalities  \\\n",
       "0                              0                                 16   \n",
       "1                              0                                  5   \n",
       "2                              5                                  9   \n",
       "3                              0                                  1   \n",
       "4                              0                                  3   \n",
       "\n",
       "   Total Number of Victims        Date Type of Gun - General  \\\n",
       "0                       48    8/1/1966         Multiple guns   \n",
       "1                        6  11/12/1966               Handgun   \n",
       "2                       22  12/31/1972         Multiple guns   \n",
       "3                        4   1/17/1974               Handgun   \n",
       "4                       10  12/30/1974         Multiple guns   \n",
       "\n",
       "  Total Number of Guns Relationship to Incident Location  Death Percent  \\\n",
       "0                    7                Place of schooling          33.33   \n",
       "1                    1                              None          83.33   \n",
       "2                    2                  Local government          40.91   \n",
       "3                    2                Place of schooling          25.00   \n",
       "4                    2                Place of schooling          30.00   \n",
       "\n",
       "       Nearest Police Department Nearest Police Department Proximity  \n",
       "0           Sunset Valley Police                              3.5 mi  \n",
       "1         Mesa Police Department                              1.5 mi  \n",
       "2  New Orleans Police Department                              4.4 mi  \n",
       "3   Cook County Sheriff-Criminal                              1.0 mi  \n",
       "4        Olean Police Department                              0.5 mi  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create 2 new columns\n",
    "shootings_df[\"Nearest Police Department\"] = \"\"\n",
    "shootings_df[\"Nearest Police Department Proximity\"] = \"\"\n",
    "\n",
    "#Parameters for google api nearby search \n",
    "params = {\"location\": \"\",\n",
    "          \"rankby\": \"distance\", \n",
    "          \"type\": \"police\",\n",
    "          \"keyword\": \"department\",\n",
    "          \"name\": \"police department\",\n",
    "          \"key\": gkey,}\n",
    "\n",
    "#Loop through rows in the dataframe\n",
    "for index, row in shootings_df.iterrows():\n",
    "    \n",
    "    location = row[\"Location\"]\n",
    "    \n",
    "    params[\"location\"] = location\n",
    "    \n",
    "    base_url = \"https://maps.googleapis.com/maps/api/place/nearbysearch/json\"\n",
    "    \n",
    "    response = requests.get(base_url, params=params).json()\n",
    "    \n",
    "    #Add name of the nearest police department to column\n",
    "    shootings_df.loc[index, \"Nearest Police Department\"] = response[\"results\"][0][\"name\"]\n",
    "    \n",
    "    #Obtain latitude of nearest police department\n",
    "    pd_lat = response[\"results\"][0][\"geometry\"][\"location\"][\"lat\"]\n",
    "    \n",
    "    #Obtain longitude of nearest police department\n",
    "    pd_lon = response[\"results\"][0][\"geometry\"][\"location\"][\"lng\"]\n",
    "    \n",
    "    #Combine the latitude and longitude into a string\n",
    "    pd_location = f\"{pd_lat},{pd_lon}\"\n",
    "    \n",
    "    #Find distance from shooting site to the nearest police department\n",
    "    dist_url = ('https://maps.googleapis.com/maps/api/distancematrix/json?units=imperial&origins={0}&destinations={1}&key={2}').format(location, pd_location, gkey)\n",
    "    \n",
    "    data = requests.get(dist_url).json()\n",
    "    \n",
    "    proximity = str(data[\"rows\"][0][\"elements\"][0][\"distance\"][\"text\"])\n",
    "    \n",
    "    #If the unit is in ft...\n",
    "    #Drop the last 3 characters\n",
    "    #Convert units to miles\n",
    "    #Add proximity to column \n",
    "    if \" ft\" in proximity:        \n",
    "        proximity = proximity[:-3]\n",
    "        proximity = float(proximity) / 5280\n",
    "        shootings_df.loc[index, \"Nearest Police Department Proximity\"] = str(proximity)\n",
    "      \n",
    "    #Else add the proximity to column\n",
    "    else:\n",
    "        shootings_df.loc[index, \"Nearest Police Department Proximity\"] = proximity\n",
    "\n",
    "#Preview updated data frame\n",
    "shootings_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop the last 3 characters in the column\n",
    "shootings_df['Nearest Police Department Proximity'] = shootings_df['Nearest Police Department Proximity'].apply(lambda x: x.replace(\" mi\", \"\"))\n",
    "\n",
    "#Convert values in column to floats\n",
    "shootings_df[\"Nearest Police Department Proximity\"] = pd.to_numeric(shootings_df[\"Nearest Police Department Proximity\"])\n",
    "\n",
    "#Round two decimal places\n",
    "decimals = 2\n",
    "shootings_df[\"Nearest Police Department Proximity\"] = shootings_df[\"Nearest Police Department Proximity\"].apply(lambda x: round(x, decimals))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Create scatter plot\n",
    "#Correlation between nearest police department proximity and total number of victims\n",
    "plt.scatter(shootings_df[\"Nearest Police Department Proximity\"], shootings_df[\"Total Number of Victims\"], marker=\"o\", facecolors=\"gold\", edgecolors=\"black\", alpha=0.65)\n",
    "plt.ylabel(\"Total Number of Victims\")\n",
    "plt.xlabel(\"Nearest Police Department Proximity (mi)\")\n",
    "plt.title(\"Total Number of Victims vs. Nearest Police Department Proximity\")\n",
    "plt.savefig(\"Images/victimsvspdproximity.png\", bbox_inches=\"tight\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Based on the p-value of 0.7697786009594472, there is no significant difference between the amount of victims based on\n",
      "the proximity to the nearest police department.\n"
     ]
    }
   ],
   "source": [
    "#Number of victims from shootings that occured within 0-5 mi of nearest police dept\n",
    "g1 = shootings_df[\"Total Number of Victims\"].loc[shootings_df[\"Nearest Police Department Proximity\"] <= 5]\n",
    "\n",
    "#Number of victims from shootings that occurred within 5-10 mi of nearest police dept\n",
    "g2 = shootings_df[\"Total Number of Victims\"].loc[(shootings_df[\"Nearest Police Department Proximity\"] > 5) & (shootings_df[\"Nearest Police Department Proximity\"] <= 10)]\n",
    "\n",
    "#Number of victims from shootings that occurred within 10-15 mi of nearest police dept\n",
    "g3 = shootings_df[\"Total Number of Victims\"].loc[(shootings_df[\"Nearest Police Department Proximity\"] > 10) & (shootings_df[\"Nearest Police Department Proximity\"] <= 15)]\n",
    "\n",
    "#Number of victims from shootings that occured within 15-25 mi of nearest police dept\n",
    "g4 = shootings_df[\"Total Number of Victims\"].loc[(shootings_df[\"Nearest Police Department Proximity\"] > 15) & (shootings_df[\"Nearest Police Department Proximity\"] <= 25)]\n",
    "#ANOVA test\n",
    "statistic, pvalue = stats.f_oneway(g1, g2, g3, g4)\n",
    "\n",
    "if pvalue < 0.05:\n",
    "   print(f\"Based on the p-value of {pvalue}, there is a significant difference between the amount of victims based on\\nthe proximity to the nearest police department.\")\n",
    "\n",
    "elif pvalue > 0.05:\n",
    "  print(f\"Based on the p-value of {pvalue}, there is no significant difference between the amount of victims based on\\nthe proximity to the nearest police department.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = shootings_df\n",
    "\n",
    "#Rename the column to remove spaces\n",
    "new_df = new_df.rename(columns={\"Total Number of Guns\": \"tot_num_guns\"})\n",
    "\n",
    "#Drop all rows that contain the unknown value\n",
    "new_df = new_df[~new_df.tot_num_guns.str.contains(\"Unknown\")]\n",
    "\n",
    "#Convert all values in column to floats\n",
    "new_df[\"tot_num_guns\"] = pd.to_numeric(new_df[\"tot_num_guns\"])\n",
    "\n",
    "#Plot correlation between total number of guns and total number of victims\n",
    "plt.scatter(new_df[\"tot_num_guns\"], new_df[\"Total Number of Victims\"], edgecolors=\"black\", alpha=0.65)\n",
    "plt.ylabel(\"Total Number of Victims\")\n",
    "plt.xlabel(\"Total Number of Guns Used\")\n",
    "plt.title(\"Total Number of Victims vs. Total Number of Guns Used\") \n",
    "plt.savefig(\"Images/victimsvsnumofguns.png\", bbox_inches=\"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Based on the p-value of 2.0050631731909367e-06 there is a significant difference in the amount of mass shootings victims between the use of one weapon versus multiple weapons.\n"
     ]
    }
   ],
   "source": [
    "#Gather values of total number of victims from shooters that used one weapon\n",
    "one_weapon = new_df[\"Total Number of Victims\"].loc[new_df[\"tot_num_guns\"] == 1]\n",
    "\n",
    "#Gather values of total number of victims from shooters that used multiple weapons \n",
    "multiple_weapons = new_df[\"Total Number of Victims\"].loc[new_df[\"tot_num_guns\"] >= 2]\n",
    "\n",
    "#T-test\n",
    "statistic, pvalue = stats.ttest_ind(one_weapon, multiple_weapons, equal_var=False)\n",
    "\n",
    "if pvalue > 0.05:\n",
    "    print(f\"Based on the p-value of {pvalue} there is no significant difference in the amount of mass shooting victims between the use of one weapon versus multiple weapons.\")\n",
    "\n",
    "elif pvalue < 0.05:\n",
    "    print(f\"Based on the p-value of {pvalue} there is a significant difference in the amount of mass shootings victims between the use of one weapon versus multiple weapons.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}