analysis/fars-exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploration of the 2014 FARS Auto Fatalities Dataset\n",
    "**Author:** Alex Nisnevich\n",
    "\n",
    "This is a brief exploration of the data in `data/fatalities-2014-allfields.tsv`, which was obtained from the [Fatality Analysis Reporting System](http://www-fars.nhtsa.dot.gov//QueryTool/QuerySection/SelectYear.aspx) (I used _\"Option 3 (Crash / Vehicle / Driver / Precrash / Occupant)\"_ as the combination of tables).\n",
    "\n",
    "You can use the FARS web UI to query for other years, to limit the number of columns (I chose to export all columns here, but many of them will probably not be useful for you), and to do some basic query operations (e.g. limit individual fields to specific values or ranges)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0. Prerequisites"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First run in the terminal:\n",
    "```\n",
    "pip install -r requirements.txt\n",
    "```\n",
    "\n",
    "(It may be helpful to do this inside a virtualenv).\n",
    "\n",
    "Now we can import `pandas`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Load the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Python/2.7/site-packages/IPython/core/interactiveshell.py:2723: DtypeWarning: Columns (4,5,6,8,9,23,24,25,27,29,30,31,34,35,36,39,40,41,42,43,52,53,55,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,89,90,91,92,94,96,97,99,101,104,108,110,112,113,114,115,116,117,118,120,121,125,127,129,134,135,136,137,138,139,152,153,154,155,173,174,179,180,181,183,184,185,186,188,189,192) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "fatalities_df = pd.read_csv(\"../data/fatalities-2014-allfields.tsv\", sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(66971, 193)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fatalities_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see what some of the records look like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>statenum</th>\n",
       "      <th>casenum</th>\n",
       "      <th>vnumber</th>\n",
       "      <th>pnumber</th>\n",
       "      <th>arrhr</th>\n",
       "      <th>arrmin</th>\n",
       "      <th>arrtime</th>\n",
       "      <th>atmcond</th>\n",
       "      <th>atmcond2</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>preimpstab</th>\n",
       "      <th>vehmanvr</th>\n",
       "      <th>roadalgn</th>\n",
       "      <th>roadprof</th>\n",
       "      <th>surfcond</th>\n",
       "      <th>surftype</th>\n",
       "      <th>spdlim</th>\n",
       "      <th>traflane</th>\n",
       "      <th>contdev</th>\n",
       "      <th>trafflow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>135</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>135</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>50</td>\n",
       "      <td>1350</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>310</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3050</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>310</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3050</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 193 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   statenum  casenum  vnumber  pnumber arrhr arrmin arrtime  atmcond atmcond2  \\\n",
       "0         1        1        1        1     1     35     135        1        0   \n",
       "1         1        1        1        2     1     35     135        1        0   \n",
       "2         1        2        1        1    13     50    1350        1        0   \n",
       "3         1        3        1        1     3     10     310        1        0   \n",
       "4         1        3        1        2     3     10     310        1        0   \n",
       "\n",
       "   city    ...     preimpstab  vehmanvr  roadalgn  roadprof  surfcond  \\\n",
       "0     0    ...              1        14         2         1         1   \n",
       "1     0    ...              1        14         2         1         1   \n",
       "2     0    ...              1         1         1         1         1   \n",
       "3  3050    ...              1         1         1         1         1   \n",
       "4  3050    ...              1         1         1         1         1   \n",
       "\n",
       "   surftype  spdlim  traflane  contdev  trafflow  \n",
       "0         2      45         2        0         1  \n",
       "1         2      45         2        0         1  \n",
       "2         2      40         2        0         1  \n",
       "3         2      45         5        3         2  \n",
       "4         2      45         5        3         2  \n",
       "\n",
       "[5 rows x 193 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fatalities_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hmm, these column names aren't very useful. I've prepared a field mapping by scraping the full field names from the FARS web UI. Here's how to use it to get more descriptive column names:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "field_mapping = pd.read_csv(\"../data/fatalities-fieldnames.tsv\", sep=\"\\t\")\n",
    "fatalities_df.columns = field_mapping.fieldname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>fieldname</th>\n",
       "      <th>State Number</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>Vehicle Number</th>\n",
       "      <th>Person Number</th>\n",
       "      <th>Crash Arrival Hour EMS</th>\n",
       "      <th>Crash Arrival Minute EMS</th>\n",
       "      <th>Crash Arrival Time EMS</th>\n",
       "      <th>Crash Atmospheric Condition (1)</th>\n",
       "      <th>Crash Atmospheric Condition (2)</th>\n",
       "      <th>Crash City</th>\n",
       "      <th>...</th>\n",
       "      <th>Precrash Pre - Impact Stability</th>\n",
       "      <th>Precrash Pre-Event Movement(Prior To Recognition Of Critical Event)</th>\n",
       "      <th>Precrash Roadway Alignment</th>\n",
       "      <th>Precrash Roadway Grade</th>\n",
       "      <th>Precrash Roadway Surface Condition</th>\n",
       "      <th>Precrash Roadway Surface Type</th>\n",
       "      <th>Precrash Speed Limit</th>\n",
       "      <th>Precrash Total Lanes in Roadway</th>\n",
       "      <th>Precrash Traffic Control Device</th>\n",
       "      <th>Precrash Trafficway Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>135</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>135</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>50</td>\n",
       "      <td>1350</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>310</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3050</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>310</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3050</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 193 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "fieldname  State Number  Case Number  Vehicle Number  Person Number  \\\n",
       "0                     1            1               1              1   \n",
       "1                     1            1               1              2   \n",
       "2                     1            2               1              1   \n",
       "3                     1            3               1              1   \n",
       "4                     1            3               1              2   \n",
       "\n",
       "fieldname Crash Arrival Hour EMS Crash Arrival Minute EMS  \\\n",
       "0                              1                       35   \n",
       "1                              1                       35   \n",
       "2                             13                       50   \n",
       "3                              3                       10   \n",
       "4                              3                       10   \n",
       "\n",
       "fieldname Crash Arrival Time EMS  Crash Atmospheric Condition (1)  \\\n",
       "0                            135                                1   \n",
       "1                            135                                1   \n",
       "2                           1350                                1   \n",
       "3                            310                                1   \n",
       "4                            310                                1   \n",
       "\n",
       "fieldname Crash Atmospheric Condition (2) Crash City  \\\n",
       "0                                       0          0   \n",
       "1                                       0          0   \n",
       "2                                       0          0   \n",
       "3                                       0       3050   \n",
       "4                                       0       3050   \n",
       "\n",
       "fieldname               ...                 Precrash Pre - Impact Stability  \\\n",
       "0                       ...                                               1   \n",
       "1                       ...                                               1   \n",
       "2                       ...                                               1   \n",
       "3                       ...                                               1   \n",
       "4                       ...                                               1   \n",
       "\n",
       "fieldname  Precrash Pre-Event Movement(Prior To Recognition Of Critical Event)  \\\n",
       "0                                                         14                     \n",
       "1                                                         14                     \n",
       "2                                                          1                     \n",
       "3                                                          1                     \n",
       "4                                                          1                     \n",
       "\n",
       "fieldname  Precrash Roadway Alignment  Precrash Roadway Grade  \\\n",
       "0                                   2                       1   \n",
       "1                                   2                       1   \n",
       "2                                   1                       1   \n",
       "3                                   1                       1   \n",
       "4                                   1                       1   \n",
       "\n",
       "fieldname  Precrash Roadway Surface Condition  Precrash Roadway Surface Type  \\\n",
       "0                                           1                              2   \n",
       "1                                           1                              2   \n",
       "2                                           1                              2   \n",
       "3                                           1                              2   \n",
       "4                                           1                              2   \n",
       "\n",
       "fieldname  Precrash Speed Limit  Precrash Total Lanes in Roadway  \\\n",
       "0                            45                                2   \n",
       "1                            45                                2   \n",
       "2                            40                                2   \n",
       "3                            45                                5   \n",
       "4                            45                                5   \n",
       "\n",
       "fieldname  Precrash Traffic Control Device  Precrash Trafficway Description  \n",
       "0                                        0                                1  \n",
       "1                                        0                                1  \n",
       "2                                        0                                1  \n",
       "3                                        3                                2  \n",
       "4                                        3                                2  \n",
       "\n",
       "[5 rows x 193 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fatalities_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ah, that's better."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look a one individual record:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fieldname\n",
       "State Number                                                                 1\n",
       "Case Number                                                                  1\n",
       "Vehicle Number                                                               1\n",
       "Person Number                                                                1\n",
       "Crash Arrival Hour EMS                                                       1\n",
       "Crash Arrival Minute EMS                                                    35\n",
       "Crash Arrival Time EMS                                                     135\n",
       "Crash Atmospheric Condition (1)                                              1\n",
       "Crash Atmospheric Condition (2)                                              0\n",
       "Crash City                                                                   0\n",
       "Crash County                                                                71\n",
       "Crash Date (mmddyyyy)                                                  1012014\n",
       "Crash Day                                                                    1\n",
       "Crash Hour                                                                   1\n",
       "Crash Minute                                                                15\n",
       "Crash Month                                                                  1\n",
       "Crash Related Factor (1)                                                     0\n",
       "Crash Related Factor (2)                                                     0\n",
       "Crash Related Factor (3)                                                     0\n",
       "Crash Time                                                                 115\n",
       "Crash Year                                                                2014\n",
       "Crash Day Of Week                                                            4\n",
       "Crash Drowsy Driver                                                          0\n",
       "Crash EMS Hour At Hospital                                                  99\n",
       "Crash EMS Minute At Hospital                                                99\n",
       "Crash EMS Time At Hospital                                                9999\n",
       "Crash First Harmful Event                                                   17\n",
       "Crash Holiday Related                                                        0\n",
       "Crash Large Truck Related                                                    0\n",
       "Crash Latitude (Decimal)                                               34.6237\n",
       "                                                                        ...   \n",
       "Driver Non-CDL License Type                                                  1\n",
       "Driver Previous DWI Convictions                                              2\n",
       "Driver Previous Other Harmful Mv Convictions                                 1\n",
       "Driver Previous Recorded Crashes                                             0\n",
       "Driver Previous Recorded Speeding Convictions                                1\n",
       "Driver Previous Recorded Suspensions And Revocations                         6\n",
       "Driver Speeding Related                                                      3\n",
       "Driver Violations Charged                                                   00\n",
       "Driver Year of First Crash - Suspension                                   2011\n",
       "Driver Year of Last Crash - Suspension                                    2013\n",
       "Precrash Attempted Avoidance Maneuver                                        1\n",
       "Precrash Contributing Circumstances - Motor Vehicle                          0\n",
       "Precrash Crash Type                                                          6\n",
       "Precrash Critical Event - PreCrash (Category)                                2\n",
       "Precrash Critical Event - PreCrash (Event)                                  12\n",
       "Precrash Device Functioning                                                  0\n",
       "Precrash Driver Distracted By                                                0\n",
       "Precrash Driver Maneuvered to Avoid                                          0\n",
       "Precrash Driver(s) Vision Obscured By                                       00\n",
       "Precrash Pre - Impact Location                                               4\n",
       "Precrash Pre - Impact Stability                                              1\n",
       "Precrash Pre-Event Movement(Prior To Recognition Of Critical Event)         14\n",
       "Precrash Roadway Alignment                                                   2\n",
       "Precrash Roadway Grade                                                       1\n",
       "Precrash Roadway Surface Condition                                           1\n",
       "Precrash Roadway Surface Type                                                2\n",
       "Precrash Speed Limit                                                        45\n",
       "Precrash Total Lanes in Roadway                                              2\n",
       "Precrash Traffic Control Device                                              0\n",
       "Precrash Trafficway Description                                              1\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fatalities_df.ix[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Let's explore some fields!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What are the most represented states?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABHcAAAGUCAYAAAC/R86QAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112042290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = fatalities_df[\"State Number\"].value_counts().plot.pie(figsize=(20, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Judging from the [ANSI state code list](https://www.census.gov/geo/reference/ansi_statetables.html), looks like it's Texas, California, and Florida, in that order."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What's the distribution of # of occupants per vehicle?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAD9CAYAAABwfjqFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1118669d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = fatalities_df[\"Vehicle Number of Occupants\"].plot.hist(bins=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How about # of fatalities per vehicle?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAAD9CAYAAACbSYGGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nciwJpRMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11027e5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = fatalities_df[\"Vehicle Number Of Fatalities In Vehicle\"].plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. About those categorical fields ..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many of the fields are integers but represent categorical data, and so you need to know the coding scheme before you can interpret them.\n",
    "\n",
    "You can see what the codes for each field mean using the [FARS web UI](http://www-fars.nhtsa.dot.gov/QueryTool/QuerySection/SelectYear.aspx) or you can make use of a text file I made from a quick scrape of the web UI: [`fatalities-codes.txt`](https://github.com/bayesimpact/bayeshack-transportation-ems/blob/master/data/fatalities-codes.txt)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Armed with these codes, we can now explore all sorts of things. Like, what are the most common types of crashes (that lead to fatalities)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "98    9043\n",
       "13    7059\n",
       "1     5959\n",
       "6     4448\n",
       "51    3205\n",
       "2     3187\n",
       "7     2920\n",
       "50    2817\n",
       "68    2207\n",
       "69    1848\n",
       "Name: Precrash Crash Type, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fatalities_df[\"Precrash Crash Type\"].value_counts()[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the [Crash Type codes](https://github.com/bayesimpact/bayeshack-transportation-ems/blob/master/data/fatalities-codes.txt#L7307), the most common crash types are `(98)Other Crash Type`, `(13)Pedestrian/ Animal`, and `(1)Drive Off Road`, in that order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}