Coursera Capstone - Final.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook will be primarily used for Coursera's IBM Data Science Capstone Project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pylab as pl\n",
    "import numpy as np\n",
    "import scipy.optimize as opt\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import NullFormatter\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split\n",
    "#from sklearn import svm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello Capstone Project Course!\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello Capstone Project Course!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SEVERITYCODE        int64\n",
      "X                 float64\n",
      "Y                 float64\n",
      "OBJECTID            int64\n",
      "INCKEY              int64\n",
      "COLDETKEY           int64\n",
      "REPORTNO           object\n",
      "STATUS             object\n",
      "ADDRTYPE           object\n",
      "INTKEY            float64\n",
      "LOCATION           object\n",
      "EXCEPTRSNCODE      object\n",
      "EXCEPTRSNDESC      object\n",
      "SEVERITYCODE.1      int64\n",
      "SEVERITYDESC       object\n",
      "COLLISIONTYPE      object\n",
      "PERSONCOUNT         int64\n",
      "PEDCOUNT            int64\n",
      "PEDCYLCOUNT         int64\n",
      "VEHCOUNT            int64\n",
      "INCDATE            object\n",
      "INCDTTM            object\n",
      "JUNCTIONTYPE       object\n",
      "SDOT_COLCODE        int64\n",
      "SDOT_COLDESC       object\n",
      "INATTENTIONIND     object\n",
      "UNDERINFL          object\n",
      "WEATHER            object\n",
      "ROADCOND           object\n",
      "LIGHTCOND          object\n",
      "PEDROWNOTGRNT      object\n",
      "SDOTCOLNUM        float64\n",
      "SPEEDING           object\n",
      "ST_COLCODE         object\n",
      "ST_COLDESC         object\n",
      "SEGLANEKEY          int64\n",
      "CROSSWALKKEY        int64\n",
      "HITPARKEDCAR       object\n",
      "dtype: object\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3058: DtypeWarning: Columns (33) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SEVERITYCODE</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>INCKEY</th>\n",
       "      <th>COLDETKEY</th>\n",
       "      <th>REPORTNO</th>\n",
       "      <th>STATUS</th>\n",
       "      <th>ADDRTYPE</th>\n",
       "      <th>INTKEY</th>\n",
       "      <th>...</th>\n",
       "      <th>ROADCOND</th>\n",
       "      <th>LIGHTCOND</th>\n",
       "      <th>PEDROWNOTGRNT</th>\n",
       "      <th>SDOTCOLNUM</th>\n",
       "      <th>SPEEDING</th>\n",
       "      <th>ST_COLCODE</th>\n",
       "      <th>ST_COLDESC</th>\n",
       "      <th>SEGLANEKEY</th>\n",
       "      <th>CROSSWALKKEY</th>\n",
       "      <th>HITPARKEDCAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>0</td>\n",
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       "      <td>-122.323148</td>\n",
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       "      <td>37475.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Wet</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>Entering at angle</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-122.347294</td>\n",
       "      <td>47.647172</td>\n",
       "      <td>2</td>\n",
       "      <td>52200</td>\n",
       "      <td>52200</td>\n",
       "      <td>2607959</td>\n",
       "      <td>Matched</td>\n",
       "      <td>Block</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6354039.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>From same direction - both going straight - bo...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>-122.334540</td>\n",
       "      <td>47.607871</td>\n",
       "      <td>3</td>\n",
       "      <td>26700</td>\n",
       "      <td>26700</td>\n",
       "      <td>1482393</td>\n",
       "      <td>Matched</td>\n",
       "      <td>Block</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4323031.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>One parked--one moving</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>-122.334803</td>\n",
       "      <td>47.604803</td>\n",
       "      <td>4</td>\n",
       "      <td>1144</td>\n",
       "      <td>1144</td>\n",
       "      <td>3503937</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>From same direction - all others</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>-122.306426</td>\n",
       "      <td>47.545739</td>\n",
       "      <td>5</td>\n",
       "      <td>17700</td>\n",
       "      <td>17700</td>\n",
       "      <td>1807429</td>\n",
       "      <td>Matched</td>\n",
       "      <td>Intersection</td>\n",
       "      <td>34387.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4028032.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>Entering at angle</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SEVERITYCODE           X          Y  OBJECTID  INCKEY  COLDETKEY REPORTNO  \\\n",
       "0             2 -122.323148  47.703140         1    1307       1307  3502005   \n",
       "1             1 -122.347294  47.647172         2   52200      52200  2607959   \n",
       "2             1 -122.334540  47.607871         3   26700      26700  1482393   \n",
       "3             1 -122.334803  47.604803         4    1144       1144  3503937   \n",
       "4             2 -122.306426  47.545739         5   17700      17700  1807429   \n",
       "\n",
       "    STATUS      ADDRTYPE   INTKEY  ... ROADCOND                LIGHTCOND  \\\n",
       "0  Matched  Intersection  37475.0  ...      Wet                 Daylight   \n",
       "1  Matched         Block      NaN  ...      Wet  Dark - Street Lights On   \n",
       "2  Matched         Block      NaN  ...      Dry                 Daylight   \n",
       "3  Matched         Block      NaN  ...      Dry                 Daylight   \n",
       "4  Matched  Intersection  34387.0  ...      Wet                 Daylight   \n",
       "\n",
       "  PEDROWNOTGRNT  SDOTCOLNUM SPEEDING ST_COLCODE  \\\n",
       "0           NaN         NaN      NaN         10   \n",
       "1           NaN   6354039.0      NaN         11   \n",
       "2           NaN   4323031.0      NaN         32   \n",
       "3           NaN         NaN      NaN         23   \n",
       "4           NaN   4028032.0      NaN         10   \n",
       "\n",
       "                                          ST_COLDESC  SEGLANEKEY  \\\n",
       "0                                  Entering at angle           0   \n",
       "1  From same direction - both going straight - bo...           0   \n",
       "2                             One parked--one moving           0   \n",
       "3                   From same direction - all others           0   \n",
       "4                                  Entering at angle           0   \n",
       "\n",
       "   CROSSWALKKEY  HITPARKEDCAR  \n",
       "0             0             N  \n",
       "1             0             N  \n",
       "2             0             N  \n",
       "3             0             N  \n",
       "4             0             N  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read dataset and prepare it\n",
    "df = pd.read_csv('Data-Collisions.csv')\n",
    "print(df.dtypes)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 1], dtype=int64)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#What are the different values of SEVERITYCODE?\n",
    "df.SEVERITYCODE.unique()\n",
    "#only 2 values, strange."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:4102: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  errors=errors,\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SEVERITYCODE</th>\n",
       "      <th>JUNCTIONTYPE</th>\n",
       "      <th>INATTENTIONIND</th>\n",
       "      <th>WEATHER</th>\n",
       "      <th>ROADCOND</th>\n",
       "      <th>LIGHTCOND</th>\n",
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       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - No Street Lights</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (but intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>Y</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>Y</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (but not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>Y</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>2</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SEVERITYCODE                                       JUNCTIONTYPE  \\\n",
       "0              2             At Intersection (intersection related)   \n",
       "1              1            Mid-Block (not related to intersection)   \n",
       "2              1            Mid-Block (not related to intersection)   \n",
       "3              1            Mid-Block (not related to intersection)   \n",
       "4              2             At Intersection (intersection related)   \n",
       "5              1             At Intersection (intersection related)   \n",
       "6              1             At Intersection (intersection related)   \n",
       "7              2             At Intersection (intersection related)   \n",
       "8              1            Mid-Block (not related to intersection)   \n",
       "9              2             At Intersection (intersection related)   \n",
       "10             1                                  Driveway Junction   \n",
       "11             1             At Intersection (intersection related)   \n",
       "12             1            Mid-Block (not related to intersection)   \n",
       "13             1            Mid-Block (not related to intersection)   \n",
       "14             2            Mid-Block (not related to intersection)   \n",
       "15             1                                  Driveway Junction   \n",
       "16             2             At Intersection (intersection related)   \n",
       "17             1               Mid-Block (but intersection related)   \n",
       "18             2            Mid-Block (not related to intersection)   \n",
       "19             1            Mid-Block (not related to intersection)   \n",
       "20             2            Mid-Block (not related to intersection)   \n",
       "21             2             At Intersection (intersection related)   \n",
       "22             1            Mid-Block (not related to intersection)   \n",
       "23             1            Mid-Block (not related to intersection)   \n",
       "24             2             At Intersection (intersection related)   \n",
       "25             2            Mid-Block (not related to intersection)   \n",
       "26             1             At Intersection (intersection related)   \n",
       "27             1                                  Driveway Junction   \n",
       "28             1            Mid-Block (not related to intersection)   \n",
       "29             1            Mid-Block (not related to intersection)   \n",
       "30             1             At Intersection (intersection related)   \n",
       "31             1             At Intersection (intersection related)   \n",
       "32             1  At Intersection (but not related to intersection)   \n",
       "33             1            Mid-Block (not related to intersection)   \n",
       "34             1            Mid-Block (not related to intersection)   \n",
       "35             1            Mid-Block (not related to intersection)   \n",
       "36             1                                  Driveway Junction   \n",
       "37             1            Mid-Block (not related to intersection)   \n",
       "38             1             At Intersection (intersection related)   \n",
       "39             1             At Intersection (intersection related)   \n",
       "40             1             At Intersection (intersection related)   \n",
       "41             1             At Intersection (intersection related)   \n",
       "42             1             At Intersection (intersection related)   \n",
       "43             2            Mid-Block (not related to intersection)   \n",
       "44             1            Mid-Block (not related to intersection)   \n",
       "45             1            Mid-Block (not related to intersection)   \n",
       "46             1            Mid-Block (not related to intersection)   \n",
       "47             1            Mid-Block (not related to intersection)   \n",
       "48             1             At Intersection (intersection related)   \n",
       "49             2                                  Driveway Junction   \n",
       "\n",
       "   INATTENTIONIND   WEATHER ROADCOND                LIGHTCOND SPEEDING  \n",
       "0             NaN  Overcast      Wet                 Daylight      NaN  \n",
       "1             NaN   Raining      Wet  Dark - Street Lights On      NaN  \n",
       "2             NaN  Overcast      Dry                 Daylight      NaN  \n",
       "3             NaN     Clear      Dry                 Daylight      NaN  \n",
       "4             NaN   Raining      Wet                 Daylight      NaN  \n",
       "5             NaN     Clear      Dry                 Daylight      NaN  \n",
       "6             NaN   Raining      Wet                 Daylight      NaN  \n",
       "7             NaN     Clear      Dry                 Daylight      NaN  \n",
       "8             NaN     Clear      Dry                 Daylight      NaN  \n",
       "9             NaN     Clear      Dry                 Daylight      NaN  \n",
       "10            NaN  Overcast      Dry                 Daylight      NaN  \n",
       "11            NaN     Clear      Dry                 Daylight      NaN  \n",
       "12            NaN   Raining      Wet  Dark - Street Lights On      NaN  \n",
       "13            NaN   Raining      Wet  Dark - No Street Lights      NaN  \n",
       "14            NaN     Clear      Dry  Dark - Street Lights On      NaN  \n",
       "15            NaN       NaN      NaN                      NaN      NaN  \n",
       "16            NaN  Overcast      Dry                 Daylight      NaN  \n",
       "17            NaN  Overcast      Dry                 Daylight      NaN  \n",
       "18            NaN     Clear      Dry                 Daylight      NaN  \n",
       "19            NaN   Unknown      Dry                  Unknown      NaN  \n",
       "20            NaN     Clear      Dry  Dark - Street Lights On      NaN  \n",
       "21            NaN     Clear      Dry                 Daylight      NaN  \n",
       "22              Y     Clear      Dry  Dark - Street Lights On      NaN  \n",
       "23            NaN   Unknown  Unknown                  Unknown      NaN  \n",
       "24            NaN     Clear      Dry                 Daylight        Y  \n",
       "25              Y     Clear      Dry                 Daylight      NaN  \n",
       "26            NaN  Overcast      Wet                  Unknown      NaN  \n",
       "27            NaN     Clear      Dry                 Daylight      NaN  \n",
       "28            NaN     Clear      Dry                 Daylight      NaN  \n",
       "29            NaN     Clear      Dry                 Daylight      NaN  \n",
       "30            NaN   Raining      Wet  Dark - Street Lights On      NaN  \n",
       "31            NaN     Clear      Dry  Dark - Street Lights On      NaN  \n",
       "32            NaN     Clear      Dry                 Daylight      NaN  \n",
       "33            NaN     Clear      Dry  Dark - Street Lights On      NaN  \n",
       "34            NaN     Other  Unknown                 Daylight      NaN  \n",
       "35            NaN   Raining      Wet                 Daylight      NaN  \n",
       "36            NaN       NaN      NaN                      NaN      NaN  \n",
       "37            NaN     Clear      Dry                 Daylight      NaN  \n",
       "38            NaN     Clear      Dry  Dark - Street Lights On      NaN  \n",
       "39            NaN     Clear      Dry                 Daylight      NaN  \n",
       "40            NaN     Clear      Dry                 Daylight      NaN  \n",
       "41            NaN  Overcast      Dry  Dark - Street Lights On      NaN  \n",
       "42            NaN     Clear      Dry                 Daylight      NaN  \n",
       "43            NaN   Raining      Wet  Dark - Street Lights On        Y  \n",
       "44            NaN  Overcast      Wet                 Daylight      NaN  \n",
       "45            NaN     Clear      Dry                 Daylight      NaN  \n",
       "46              Y     Clear      Dry                 Daylight      NaN  \n",
       "47            NaN     Clear      Dry                 Daylight      NaN  \n",
       "48            NaN     Clear      Dry                 Daylight      NaN  \n",
       "49            NaN     Clear      Dry                 Daylight      NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df[['SEVERITYCODE', 'JUNCTIONTYPE', 'INATTENTIONIND', 'UNDERINFL', 'WEATHER', 'ROADCOND', 'LIGHTCOND', 'SPEEDING']]\n",
    "\n",
    "#UNDERINFL is not formatted well, as it contains the values N, 0, 1, and NaN, so let's drop it\n",
    "df1.drop('UNDERINFL', axis = 1, inplace=True)\n",
    "\n",
    "df1.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n",
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:3494: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self[k1] = value[k2]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SEVERITYCODE</th>\n",
       "      <th>JUNCTIONTYPE</th>\n",
       "      <th>INATTENTIONIND</th>\n",
       "      <th>WEATHER</th>\n",
       "      <th>ROADCOND</th>\n",
       "      <th>LIGHTCOND</th>\n",
       "      <th>SPEEDING</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SEVERITYCODE                             JUNCTIONTYPE INATTENTIONIND  \\\n",
       "0             2   At Intersection (intersection related)              N   \n",
       "1             1  Mid-Block (not related to intersection)              N   \n",
       "2             1  Mid-Block (not related to intersection)              N   \n",
       "3             1  Mid-Block (not related to intersection)              N   \n",
       "4             2   At Intersection (intersection related)              N   \n",
       "\n",
       "    WEATHER ROADCOND                LIGHTCOND SPEEDING  \n",
       "0  Overcast      Wet                 Daylight        N  \n",
       "1   Raining      Wet  Dark - Street Lights On        N  \n",
       "2  Overcast      Dry                 Daylight        N  \n",
       "3     Clear      Dry                 Daylight        N  \n",
       "4   Raining      Wet                 Daylight        N  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#INATTENTIONIND and SPEEDING have NaN instead of N.\n",
    "df1['INATTENTIONIND'] = df1['INATTENTIONIND'].replace(np.nan, \"N\")\n",
    "df1[['SPEEDING']] = df1[['SPEEDING']].replace(np.nan, \"N\")\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "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>SEVERITYCODE</th>\n",
       "      <th>JUNCTIONTYPE</th>\n",
       "      <th>INATTENTIONIND</th>\n",
       "      <th>WEATHER</th>\n",
       "      <th>ROADCOND</th>\n",
       "      <th>LIGHTCOND</th>\n",
       "      <th>SPEEDING</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - No Street Lights</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (but intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>Y</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>Y</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (but not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>Y</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>1</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>2</td>\n",
       "      <td>Driveway Junction</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54</td>\n",
       "      <td>2</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (but intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>56</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dusk</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>57</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (but intersection related)</td>\n",
       "      <td>N</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SEVERITYCODE                                       JUNCTIONTYPE  \\\n",
       "0              2             At Intersection (intersection related)   \n",
       "1              1            Mid-Block (not related to intersection)   \n",
       "2              1            Mid-Block (not related to intersection)   \n",
       "3              1            Mid-Block (not related to intersection)   \n",
       "4              2             At Intersection (intersection related)   \n",
       "5              1             At Intersection (intersection related)   \n",
       "6              1             At Intersection (intersection related)   \n",
       "7              2             At Intersection (intersection related)   \n",
       "8              1            Mid-Block (not related to intersection)   \n",
       "9              2             At Intersection (intersection related)   \n",
       "10             1                                  Driveway Junction   \n",
       "11             1             At Intersection (intersection related)   \n",
       "12             1            Mid-Block (not related to intersection)   \n",
       "13             1            Mid-Block (not related to intersection)   \n",
       "14             2            Mid-Block (not related to intersection)   \n",
       "16             2             At Intersection (intersection related)   \n",
       "17             1               Mid-Block (but intersection related)   \n",
       "18             2            Mid-Block (not related to intersection)   \n",
       "20             2            Mid-Block (not related to intersection)   \n",
       "21             2             At Intersection (intersection related)   \n",
       "22             1            Mid-Block (not related to intersection)   \n",
       "24             2             At Intersection (intersection related)   \n",
       "25             2            Mid-Block (not related to intersection)   \n",
       "27             1                                  Driveway Junction   \n",
       "28             1            Mid-Block (not related to intersection)   \n",
       "29             1            Mid-Block (not related to intersection)   \n",
       "30             1             At Intersection (intersection related)   \n",
       "31             1             At Intersection (intersection related)   \n",
       "32             1  At Intersection (but not related to intersection)   \n",
       "33             1            Mid-Block (not related to intersection)   \n",
       "35             1            Mid-Block (not related to intersection)   \n",
       "37             1            Mid-Block (not related to intersection)   \n",
       "38             1             At Intersection (intersection related)   \n",
       "39             1             At Intersection (intersection related)   \n",
       "40             1             At Intersection (intersection related)   \n",
       "41             1             At Intersection (intersection related)   \n",
       "42             1             At Intersection (intersection related)   \n",
       "43             2            Mid-Block (not related to intersection)   \n",
       "44             1            Mid-Block (not related to intersection)   \n",
       "45             1            Mid-Block (not related to intersection)   \n",
       "46             1            Mid-Block (not related to intersection)   \n",
       "47             1            Mid-Block (not related to intersection)   \n",
       "48             1             At Intersection (intersection related)   \n",
       "49             2                                  Driveway Junction   \n",
       "50             1            Mid-Block (not related to intersection)   \n",
       "51             1            Mid-Block (not related to intersection)   \n",
       "54             2            Mid-Block (not related to intersection)   \n",
       "55             1               Mid-Block (but intersection related)   \n",
       "56             2             At Intersection (intersection related)   \n",
       "57             1               Mid-Block (but intersection related)   \n",
       "\n",
       "   INATTENTIONIND   WEATHER ROADCOND                LIGHTCOND SPEEDING  \n",
       "0               N  Overcast      Wet                 Daylight        N  \n",
       "1               N   Raining      Wet  Dark - Street Lights On        N  \n",
       "2               N  Overcast      Dry                 Daylight        N  \n",
       "3               N     Clear      Dry                 Daylight        N  \n",
       "4               N   Raining      Wet                 Daylight        N  \n",
       "5               N     Clear      Dry                 Daylight        N  \n",
       "6               N   Raining      Wet                 Daylight        N  \n",
       "7               N     Clear      Dry                 Daylight        N  \n",
       "8               N     Clear      Dry                 Daylight        N  \n",
       "9               N     Clear      Dry                 Daylight        N  \n",
       "10              N  Overcast      Dry                 Daylight        N  \n",
       "11              N     Clear      Dry                 Daylight        N  \n",
       "12              N   Raining      Wet  Dark - Street Lights On        N  \n",
       "13              N   Raining      Wet  Dark - No Street Lights        N  \n",
       "14              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "16              N  Overcast      Dry                 Daylight        N  \n",
       "17              N  Overcast      Dry                 Daylight        N  \n",
       "18              N     Clear      Dry                 Daylight        N  \n",
       "20              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "21              N     Clear      Dry                 Daylight        N  \n",
       "22              Y     Clear      Dry  Dark - Street Lights On        N  \n",
       "24              N     Clear      Dry                 Daylight        Y  \n",
       "25              Y     Clear      Dry                 Daylight        N  \n",
       "27              N     Clear      Dry                 Daylight        N  \n",
       "28              N     Clear      Dry                 Daylight        N  \n",
       "29              N     Clear      Dry                 Daylight        N  \n",
       "30              N   Raining      Wet  Dark - Street Lights On        N  \n",
       "31              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "32              N     Clear      Dry                 Daylight        N  \n",
       "33              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "35              N   Raining      Wet                 Daylight        N  \n",
       "37              N     Clear      Dry                 Daylight        N  \n",
       "38              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "39              N     Clear      Dry                 Daylight        N  \n",
       "40              N     Clear      Dry                 Daylight        N  \n",
       "41              N  Overcast      Dry  Dark - Street Lights On        N  \n",
       "42              N     Clear      Dry                 Daylight        N  \n",
       "43              N   Raining      Wet  Dark - Street Lights On        Y  \n",
       "44              N  Overcast      Wet                 Daylight        N  \n",
       "45              N     Clear      Dry                 Daylight        N  \n",
       "46              Y     Clear      Dry                 Daylight        N  \n",
       "47              N     Clear      Dry                 Daylight        N  \n",
       "48              N     Clear      Dry                 Daylight        N  \n",
       "49              N     Clear      Dry                 Daylight        N  \n",
       "50              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "51              N     Clear      Dry  Dark - Street Lights On        N  \n",
       "54              N     Clear      Dry                 Daylight        N  \n",
       "55              N   Raining      Wet  Dark - Street Lights On        N  \n",
       "56              N     Clear      Dry                     Dusk        N  \n",
       "57              N     Clear      Dry  Dark - Street Lights On        N  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#continue to clean the data\n",
    "dfClean = df1.replace('Unknown', np.nan) #replace unknown with NaN as that's the same thing\n",
    "dfClean.dropna(inplace = True) #some rows still have NaN values, so lets drop them\n",
    "dfClean.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#function for finding mean of columns\n",
    "def average(column, condition):\n",
    "    return dfClean.loc[dfClean[column] == condition].SEVERITYCODE.mean()\n",
    "    \n",
    "#function for finding count of columns\n",
    "def count(column, condition):\n",
    "    return dfClean.loc[dfClean[column] == condition].SEVERITYCODE.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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 a weather count bar chart\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "bars = [\"Clear\", \"Overcast\", \"Raining\"]\n",
    "counts = [count(\"WEATHER\", \"Clear\"), count(\"WEATHER\", \"Overcast\"), count(\"WEATHER\", \"Raining\")]\n",
    "ax.bar(bars, counts)\n",
    "\n",
    "plt.xlabel('WEATHER', fontsize=16)\n",
    "plt.ylabel('Number of Accidents', fontsize=16)\n",
    "\n",
    "plt.show()\n",
    "#more accidents occur when the skys are clear, but this could easily be because of an unbalanced dataset. Lets not use count."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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 a weather mean bar chart\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "bars = [\"Clear\", \"Overcast\", \"Raining\"]\n",
    "counts = [average(\"WEATHER\", \"Clear\"), average(\"WEATHER\", \"Overcast\"), average(\"WEATHER\", \"Raining\")]\n",
    "ax.bar(bars, counts)\n",
    "\n",
    "plt.xlabel('WEATHER', fontsize=16)\n",
    "plt.ylabel('Average SEVERITYCODE', fontsize=16)\n",
    "\n",
    "plt.show()\n",
    "#there is slightly more accidents when it's raining"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kwAGPLUnSBqNfQN+fJkCB2y9PPw74etv7XeP7wDYDnm+6sbynvqK1CbADsC9wKPDRJFve5UDJ4iTLkyxftWrWq+uSJK1X+gX0VcCDetZ3A+4BfG9Ku1uBmxjMSmDbnvVtgCunafO5qrq5qn5Oc5l9h6kHqqolVbWoqhbNmzdvwNNLkrR+6BfQy2hGDVvzINlLaXq7Z01ptwt3Ddl+x9whyfZJNqO5h710Spszgf0AkmxFc8n70gGPL0nSBqHfSGJvo+ktX57kOmAn4LNV9ZMp7V4InDfIyarqliSvBM4GNgZOrqoLkxwLLK+qpe2+JyW5iKZ3/tqqunZOP5UkSeu5fiOJ/TjJ44HDgfvRPHF9fG+bJPNpLoUP/K5yVZ3FlF54VR3T87mAI9tFkqSJ1Hcs7qpaBryoz/5fAk8bdlGSJE06h/qUJKmDDGhJkjrIgJYkqYMMaEmSOsiAliSpg+YU0Ek2SrJLkn2S/MGoipIkadINHNBJXgH8GvhP4Bzg4e32M5O8ajTlSZI0mQYK6CR/CbyPZhjOP+fOk158G3j28EuTJGlyDdqDPhL4x6paDHx2yr6f0PamJUnScAwa0NvTjJE9nRuBu0wHKUmS1t6gAX0NsHCGfQ8HfjmUaiRJEjB4QH8eOCbJQ3q2VTsd5BE096YlSdKQDBrQRwO/By4AvkozL/T7gYtppoQ8diTVSZI0oQYK6HY+5kXAO4BNgZ/RzIT1AWCvqrp+ZBVKkjSB+k432auqbgDe2i6SJGmEHOpTkqQOGqgHneScPrtvA64HfgCcVFVXDaMwSZIm2aCXuAPsCDwY+DlwFfBAmvejf9WuHwQckWSfqrpoBLVKkjQxBr3E/U/A74A/rqqHVtXeVfVQYPd2+1uAHYBVwHEjqVSSpAkyaEC/DXhzVf2od2NV/YAmnN9WVSuB44HHD7dESZImz6ABvSPNaGLTWQU8rP38M8BpKCVJupsGDejLgMNm2Le43Q+wFXDt3StJkiQN+pDYscAnkpwPnAFcDWxNM83kLsDz2nYHAP8x7CIlSZo0AwV0VX0qyTU095vfSDOa2M3AcuBJVfXVtumRNEN/SpKku2EuI4l9BfhKko1oLmVfU1W3TWnzuyHXJ0nSRBo4oNdoQ/nqEdQiSZJaAwd0ks2Ap9DM/7zFlN1VVY7RLUnSkAw61OcfAt8BFtJMNZl2V/U0M6AlSRqSQV+zOp7mfecFNOH8WOAhNKOGrWg/S5KkIRn0Evf/AV4DXNmu31ZVlwHHJNkYeD9w8PDLkyRpMg3ag34AcGX7gNiNwP169p0D7DvkuiRJmmiDBvRKmleroBnO80k9+/agmTBjIEkOTHJJkhVJjurT7jlJKsmiQY8tSdKGYtBL3F8H9gHOBD4CnJjkMTSDlTy53Tar9nL4icATaUJ/WZKlU6enTHJv4FU4KpkkaUIN2oM+GvgQQFV9CPgb4J4080O/G/jbAY+zB7Ciqi6tqpuA05j+3vVb2+M68IkkaSINGtA3A79Ys1JVJ1TV46pqt6p64xxGEJsPXNGzvrLddrskfwRsW1VfGPCYkiRtcGYN6CSb0MxQ9aTZ2g4g02y7/V3qdhjR9zBAjzzJ4iTLkyxftWrVEEqTJKk7Zg3oqroFuIrhTIKxEti2Z30b7nh1C+DeNLNjfSPJZcCewNLpHhSrqiVVtaiqFs2bN28IpUmS1B2DXuL+BDPPBz0Xy4AdkmzfDh16CLB0zc6qur6qtqqqhVW1EDgPeHpVLR/CuSVJWm8M+hT3ZcDzkiwDPgf8ijsP80lVnTzbQarqliSvBM4GNgZOrqoLkxwLLK+qpf2PIEnSZBg0oE9s/3c+8MfT7C9g1oAGqKqzgLOmbDtmhrb7DlifJEkblEEDevuRViFJku5koICuql/M3kqSJA3LwPNBAyTZFXg8zdjcH6mqXyd5GHBVVd0wigIlSZpEg84HvTnNk9zPonmXuYDPA7+mGfHrp8CM42pLkqS5GfQ1q+OAA4AXAg/kzgOOfIlmPG5JkjQkg17iPhQ4uqo+2U540evnwMKhViVJ0oSby3zQF/c5xubDKUeSJMHgAf1zYK8Z9u0BXDKcciRJEgwe0B8HjkryfGCzdlsl2Q84ggEHKZEkSYMZNKDfDXwROBVY3W77DvBV4N+r6oQR1CZJ0sQadKCSW4FDkpxI88T21jRTUP57VX1zhPVJkjSR5jRQSVV9G/j2iGqRJEmtgS5xJ/lhklcneeCoC5IkSYPfg76K5j70FUnOSnJIki1GWJckSRNtoICuqqcA2wCvo7n//EngqiQntU9yS5KkIRq0B01VXV1V762qRcAjaeaI3h/4ahJnu5IkaYgGDuheVXUxcCzwd8CVNL1rSZI0JHMO6CRPSPLPNPelPw6sBA4fdmGSJE2yQaeb3AV4AfA8YD7wC+B9wKlV9d+jK0+SpMk06HvQ5wPXA5+mCWXfhZYkaYQGDeg/B5ZW1e9HWYwkSWoM+prVp2cK5yT7JHGyDEmShmitnuJO8rAkxyb5OfB14M+GW5YkSZNt4IBOct8ki5N8h2b+578DrgP+GvjDEdUnSdJE6nsPOslGwIHAi4CnA1vQvPd8IvAK4NVV9a1RFylJ0qSZMaCT/APwfJqhPX8HfBb4GM0c0PcBXjmOAiVJmkT9etBHAgWcBbykqq5dsyNJjbowSZImWb970CcDNwBPBS5J8oEke4ynLEmSJtuMAV1VhwEPohlB7AfAXwHfS3Ix8Hqa3rUkSRqBvk9xV9XvquqTVfVkYFvgjcCtwFFAgHcmeYFzQ0uSNFxzmW7yV1X1rqraBXgs8EFgB5oJM341ovokSZpIazvd5LKqeiXN+8/PAb451KokSZpwaxXQa1TVzVX1b1X1jEG/k+TAJJckWZHkqGn2H5nkoiTnJ/laku3uTo2SJK2P7lZAz1WSjWkGOXkKsDNwaJKdpzT7EbCoqnYFPgO8e5w1SpLUBWMNaGAPYEVVXVpVNwGnAQf3Nqiqr1fVb9vV84BtxlyjJEnr3LgDej5wRc/6ynbbTF4GfGmkFUmS1EGDzgc9LJlm27TvUyd5AbAI2GeG/YuBxQALFiwYVn2SJHXCuHvQK2nep15jG5rJN+4kyQE0s2U9faZ5qKtqSVUtqqpF8+bNG0mxkiStK+MO6GXADkm2T7IZcAiwtLdBkj8CPkITzlePuT5JkjphrAFdVbfQzIJ1NnAxcHpVXZjk2CRPb5sdD9wL+HSSHydZOsPhJEnaYI37HjRVdRbNDFm9247p+XzAuGuSJKlrxn2JW5IkDcCAliSpgwxoSZI6yICWJKmDDGhJkjrIgJYkqYMMaEmSOsiAliSpgwxoSZI6yICWJKmDDGhJkjrIgJYkqYMMaEmSOsiAliSpgwxoSZI6yICWJKmDDGhJkjrIgJYkqYMMaEmSOsiAliSpgwxoSZI6yICWJKmDDGhJkjrIgJYkqYMMaEmSOsiAliSpgwxoSZI6yICWJKmDDGhJkjrIgJYkqYMMaEmSOsiAliSpg8Ye0EkOTHJJkhVJjppm/+ZJ/rXd/x9JFo67RkmS1rWxBnSSjYETgacAOwOHJtl5SrOXAddV1cOA9wDvGmeNkiR1wbh70HsAK6rq0qq6CTgNOHhKm4OBj7WfPwPsnyRjrFGSpHVu3AE9H7iiZ31lu23aNlV1C3A98ICxVCdJUkdsMubzTdcTrrVoQ5LFwOJ29TdJLrmbtWk8tgKuWddFbIjizSDdwd+zERry79p2M+0Yd0CvBLbtWd8GuHKGNiuTbALcF1g99UBVtQRYMqI6NSJJllfVonVdh7Qh8/dswzDuS9zLgB2SbJ9kM+AQYOmUNkuBF7efnwOcU1V36UFLkrQhG2sPuqpuSfJK4GxgY+DkqrowybHA8qpaCpwEnJpkBU3P+ZBx1ihJUhfEzqnGKcni9vaEpBHx92zDYEBLktRBDvUpSVIHGdAaqiS3JvlxkguT/GeSI5P4/zNpSJK8J8mre9bPTvLRnvV/THLkDN/dMsnLx1Gn7j7/4tSw/W9VPaaqHgk8ETgIeNPURu0rdJLm7rvA3gDtP363Ah7Zs39v4NwZvrslYECvJwxojUxVXU0zmMwr03hJkk8n+Tzw5SSnJrl9qNck/5Lk6eusYGn9cC5tQNME8wXADUnul2RzYCfgR0lem2RZkvOTvKVt/07goe1VruPHX7rmwl6MRqqqLm3/lb91u2kvYNeqWp1kH+AI4HNJ7kvzl86LZziUJKCqrkxyS5IFNL8z36MZInkvmqGRzwf2BXagmf8gwNIkjweOAnapqsesi9o1N/agNQ69w7d+papWA1TVN4GHJdkaOBQ4ox1/XVJ/a3rRawL6ez3r3wWe1C4/An4IPIImsLUesQetkUryEOBW4Op2041TmpwKPJ9mQJqXjrE0aX225j70o2gucV8B/C3wP8DJND3od1TVR3q/lGThOIvU3WMPWiOTZB7wYeADfYZrPQV4NUBVXTim0qT13bnAnwKrq+rW9qrUljSXub9HM1rjS5PcCyDJ/PZK1Q3AvddRzZoje9Aatnsk+TGwKXALTQ/5n2ZqXFVXJbkYOHNM9Ukbgv+ieXr7k1O23auqrqF5CHMn4HtJAH4DvKCqfpbk3CQXAF+qqteOu3ANzpHEtE4luSfNXyy7VdX167oeSeoKL3FrnUlyAPAT4ATDWZLuzB60JEkdZA9akqQOMqAlSeogA1qSpA4yoKUxaccir57lpiQ/S/L2JFtM0373JGckuSrJ75NcluSDSeb3Occ9klzfHv/RM7T5Rk8Ntya5rh2b+YQkj5zuO+339kpyepIr29qvTfKVJC9OsvHa1t5Tz8en2XdYu29hz7ZTeuq/rf15L0pyUpK9ZqpfWt8Y0NL4PZdmQImn0gwo8QbgThMXJHkhzYATDwD+hmZmsHcAT6aZCGHXGY79LOA+7ecX9anh/LaGPwH+HPg4sB/w4+mmI2ynNzwXuD/weuAAmpHffgp8iGbQjLtb+/OT7Nyn5l6r2vr3pvmZP0AzScR3k7xjwGNI3VZVLi4uY1iAlwAFPGzK9q8AvwU2atcfDvwO+MyabT1tHwCsoAnGTac5x5eBa4HzgF8DG0/T5hvAd6bZvml7zluB3Xu2Px64DXj/DD/XQ2kmQFmr2tt6fgRcRTMee+93Dmv/zBb2bDsFWDlNHQHe27Z/9rr+7+3icncXe9DSuvdD4B40I0NBM/TpxsDhVXVbb8OquhZ4I83EB8/q3ddePt4fOA34KPBAml7rQKrqZpq5gm8BXtWz6yhgNfC6Gb73s6o6/+7UTjNG+9uBZyVZNGjNU45fbY1XtXVI6zUDWlr3FtJME3htu74/sLyqfjVD+y/S9GifMGX7C2l+pz8OnE7Tk53T9J3VzOG9nObSN+295X2BL1fV7wY4xNrWDs247ZcDb5tLzb2q6ibga8AeSRzKWOs1A1oav42TbJLkfkleCjwbOLqqbm33bwtcNtOXq+pGmnuw207Z9SLgkqr6j6r6H5rxzQ9OsuUc67sceHD7eSua3v0vBvzu2tZOVf0eOBZ4cjt38dq6HNiM5pK6tN4yoKXx+wlwM81l45OAj1TVB+Z4jNxpJdmD5iGpU3s2fwzYHPiztTj2KIcYTJ99p9Dcoz5uCMd3mESt1wxoafyeCewOHAR8FXh5kt4nrlfSXPaeVpI/oOnZXtGzec2l7M8n2bLtNS+j6a3O6TI3Te92zSXqa4H/BbYb8LtrU/vt2qsIxwCPS/KUAc851bbATTT/AJLWWwa0NH4XVNXyqvoSzetJPwWOb8MLmnuoi5I8eIbvP5Xmd/ccgCSbAYe0+/4TuK5drgHmAXsnedgghbVzBi8CvgNQVbfQPGX9xCSbD3CIOdU+g9OBH9Pci+7X276L9s/iAOC8tnZpvWVAS+tQe9/1tcDWNE9QA7yP5kGqE5Lc6Xc0yf1pnnZeAfxbu/lpNO8nv4XmXebeZU1w93snes2xNwU+SDNP/Pt7dr2T5n7u8TN8b/ued5vnWvtdtE9jHw3sRnN/fiBpJj5+N82f5XsG/Z7UVT7lKK1jVbU0yTLgNUk+UFUXJ/m/NK9KfS3Jh2kuOT+C5jWiLYEntq9FQXMJ+zfAP1TVb6YeP8kRwIuSvKkNP4B7J/p5nokAAAEDSURBVNlzzWfgUcBf0LzH/PKq+kFPfd9KciTwT0l2orlPfDlwP5qntg8Dngecvxa1z/Rn8sUk5zLza2Kb9dR/z7buF9AMXvK2qjqz3/Gl9cK6fhHbxWVSFmYYqKTd96R23xE92/YEPktzH/kmmiepPwxs29NmHs0DZyf1Oe9ftsfet13/RrteNL3d62kuKZ8APLLPcfYGPk0TuGsecvsyTTBOHZRk1tp72n6D6QdO2aenzoU920+ZUv8NwMU0D9ztua7/O7u4DGtxPmhJkjrIe9CSJHWQAS1JUgcZ0JIkdZABLUlSBxnQkiR1kAEtSVIHGdCSJHWQAS1JUgcZ0JIkddD/B/FltAceedKUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create a road condition mean bar chart\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "bars = [\"Dry\", \"Wet\"]\n",
    "counts = [average(\"ROADCOND\", \"Dry\"), average(\"ROADCOND\", \"Wet\")]\n",
    "ax.bar(bars, counts)\n",
    "\n",
    "plt.xlabel('ROADCOND', fontsize=16)\n",
    "plt.ylabel('Average SEVERITYCODE', fontsize=16)\n",
    "\n",
    "plt.show()\n",
    "#road road condition doesn't seem to have much significance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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 a speeding mean bar chart\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "bars = [\"Y\", \"N\"]\n",
    "counts = [average(\"SPEEDING\", \"Y\"), average(\"SPEEDING\", \"N\")]\n",
    "ax.bar(bars, counts)\n",
    "\n",
    "plt.xlabel('SPEEDING', fontsize=16)\n",
    "plt.ylabel('Average SEVERITYCODE', fontsize=16)\n",
    "\n",
    "plt.show()\n",
    "#Aha! Speeding increases the severity of the accident by a noticable amount."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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 a inattention mean bar chart\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "bars = [\"Y\", \"N\"]\n",
    "counts = [average(\"INATTENTIONIND\", \"Y\"), average(\"INATTENTIONIND\", \"N\")]\n",
    "ax.bar(bars, counts)\n",
    "\n",
    "plt.xlabel('INATTENTIONIND', fontsize=16)\n",
    "plt.ylabel('Average SEVERITYCODE', fontsize=16)\n",
    "\n",
    "plt.show()\n",
    "#Inattention also increases the severity of the accident by a noticable (but smaller) amount.\n",
    "\n",
    "#next steps, only include columns that have a significance of the rating in the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>SEVERITYCODE</th>\n",
       "      <th>JUNCTIONTYPE</th>\n",
       "      <th>INATTENTIONIND</th>\n",
       "      <th>WEATHER</th>\n",
       "      <th>ROADCOND</th>\n",
       "      <th>LIGHTCOND</th>\n",
       "      <th>SPEEDING</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>0</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>0</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Dark - Street Lights On</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>0</td>\n",
       "      <td>Overcast</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Mid-Block (not related to intersection)</td>\n",
       "      <td>0</td>\n",
       "      <td>Clear</td>\n",
       "      <td>Dry</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>At Intersection (intersection related)</td>\n",
       "      <td>0</td>\n",
       "      <td>Raining</td>\n",
       "      <td>Wet</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SEVERITYCODE                             JUNCTIONTYPE  INATTENTIONIND  \\\n",
       "0             2   At Intersection (intersection related)               0   \n",
       "1             1  Mid-Block (not related to intersection)               0   \n",
       "2             1  Mid-Block (not related to intersection)               0   \n",
       "3             1  Mid-Block (not related to intersection)               0   \n",
       "4             2   At Intersection (intersection related)               0   \n",
       "\n",
       "    WEATHER ROADCOND                LIGHTCOND  SPEEDING  \n",
       "0  Overcast      Wet                 Daylight         0  \n",
       "1   Raining      Wet  Dark - Street Lights On         0  \n",
       "2  Overcast      Dry                 Daylight         0  \n",
       "3     Clear      Dry                 Daylight         0  \n",
       "4   Raining      Wet                 Daylight         0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dfClean['SEVERITYCODE'].value_counts()\n",
    "#df['SEVERITYCODE'].value_counts()\n",
    "#there seems to be only two values in here for the severity code rather than the 5 in the documentation\n",
    "\n",
    "#prepare the data more\n",
    "dfClean[[\"INATTENTIONIND\"]] = dfClean[[\"INATTENTIONIND\"]].replace(['Y', 'N'], [1, 0])\n",
    "#dfClean[\"ROADCOND\"] = dfClean[\"ROADCOND\"].replace(['Wet', 'Dry'], [1, 0])\n",
    "dfClean[\"SPEEDING\"] = dfClean[\"SPEEDING\"].replace(['Y', 'N'], [1, 0])\n",
    "dfClean.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>SEVERITYCODE</th>\n",
       "      <th>INATTENTIONIND</th>\n",
       "      <th>SPEEDING</th>\n",
       "      <th>LIGHTCOND_Dark - No Street Lights</th>\n",
       "      <th>LIGHTCOND_Dark - Street Lights Off</th>\n",
       "      <th>LIGHTCOND_Dark - Street Lights On</th>\n",
       "      <th>LIGHTCOND_Dark - Unknown Lighting</th>\n",
       "      <th>LIGHTCOND_Dawn</th>\n",
       "      <th>LIGHTCOND_Daylight</th>\n",
       "      <th>LIGHTCOND_Dusk</th>\n",
       "      <th>LIGHTCOND_Other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SEVERITYCODE  INATTENTIONIND  SPEEDING  LIGHTCOND_Dark - No Street Lights  \\\n",
       "0             2               0         0                                  0   \n",
       "1             1               0         0                                  0   \n",
       "2             1               0         0                                  0   \n",
       "3             1               0         0                                  0   \n",
       "4             2               0         0                                  0   \n",
       "\n",
       "   LIGHTCOND_Dark - Street Lights Off  LIGHTCOND_Dark - Street Lights On  \\\n",
       "0                                   0                                  0   \n",
       "1                                   0                                  1   \n",
       "2                                   0                                  0   \n",
       "3                                   0                                  0   \n",
       "4                                   0                                  0   \n",
       "\n",
       "   LIGHTCOND_Dark - Unknown Lighting  LIGHTCOND_Dawn  LIGHTCOND_Daylight  \\\n",
       "0                                  0               0                   1   \n",
       "1                                  0               0                   0   \n",
       "2                                  0               0                   1   \n",
       "3                                  0               0                   1   \n",
       "4                                  0               0                   1   \n",
       "\n",
       "   LIGHTCOND_Dusk  LIGHTCOND_Other  \n",
       "0               0                0  \n",
       "1               0                0  \n",
       "2               0                0  \n",
       "3               0                0  \n",
       "4               0                0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#preprocess the data for classification. we want to turn these values into numbers, so use one hot encoding on all values\n",
    "#function to hot encode\n",
    "def encode_and_concat(df, feature):\n",
    "    dummies = pd.get_dummies(df[[feature]])\n",
    "    new = pd.concat([df, dummies], axis = 1)\n",
    "    return new\n",
    "#encode these features\n",
    "dfEncode = encode_and_concat(dfClean, 'JUNCTIONTYPE')\n",
    "dfEncode = encode_and_concat(dfClean, 'WEATHER')\n",
    "dfEncode = encode_and_concat(dfClean, 'ROADCOND')\n",
    "dfEncode = encode_and_concat(dfClean, 'LIGHTCOND')\n",
    "\n",
    "#drop old old columns\n",
    "dfEncode.drop('JUNCTIONTYPE', axis = 1, inplace=True)\n",
    "dfEncode.drop('WEATHER', axis = 1, inplace=True)\n",
    "dfEncode.drop('ROADCOND', axis = 1, inplace=True)\n",
    "dfEncode.drop('LIGHTCOND', axis = 1, inplace=True)\n",
    "\n",
    "dfEncode.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.45044411, -0.23850372, -0.09027377, -0.08081202, -0.61538371,\n",
       "        -0.00731951, -0.11995366,  0.71418362, -0.18526783, -0.03320277],\n",
       "       [-0.45044411, -0.23850372, -0.09027377, -0.08081202,  1.6250024 ,\n",
       "        -0.00731951, -0.11995366, -1.40020013, -0.18526783, -0.03320277],\n",
       "       [-0.45044411, -0.23850372, -0.09027377, -0.08081202, -0.61538371,\n",
       "        -0.00731951, -0.11995366,  0.71418362, -0.18526783, -0.03320277],\n",
       "       [-0.45044411, -0.23850372, -0.09027377, -0.08081202, -0.61538371,\n",
       "        -0.00731951, -0.11995366,  0.71418362, -0.18526783, -0.03320277],\n",
       "       [-0.45044411, -0.23850372, -0.09027377, -0.08081202, -0.61538371,\n",
       "        -0.00731951, -0.11995366,  0.71418362, -0.18526783, -0.03320277]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_df = dfEncode[['INATTENTIONIND', 'SPEEDING', \n",
    "                       'LIGHTCOND_Dark - No Street Lights',\n",
    "                       'LIGHTCOND_Dark - Street Lights Off',\n",
    "                       'LIGHTCOND_Dark - Street Lights On',\n",
    "                       'LIGHTCOND_Dark - Unknown Lighting', \n",
    "                       'LIGHTCOND_Dawn', 'LIGHTCOND_Daylight', \n",
    "                       'LIGHTCOND_Dusk', 'LIGHTCOND_Other']]\n",
    "#X = np.asarray(feature_df)\n",
    "X= preprocessing.StandardScaler().fit(feature_df).transform(feature_df)\n",
    "X[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = dfEncode['SEVERITYCODE'].values\n",
    "#y = np.asarray(dfEncode['SEVERITYCODE'])\n",
    "#y [0:5]\n",
    "#dfEncode.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train set: (134397, 10) (134397,)\n",
      "Test set: (33600, 10) (33600,)\n"
     ]
    }
   ],
   "source": [
    "#test and train split\n",
    "X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.2, random_state=4)\n",
    "print ('Train set:', X_train.shape,  y_train.shape)\n",
    "print ('Test set:', X_test.shape,  y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.43247024, 0.45002976, 0.43779762, 0.60794643, 0.60744048,\n",
       "       0.64306548, 0.52255952, 0.56708333, 0.53604167])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#KNN\n",
    "Ks = 10\n",
    "mean_acc = np.zeros((Ks-1))\n",
    "std_acc = np.zeros((Ks-1))\n",
    "ConfustionMx = [];\n",
    "for n in range(1,Ks):\n",
    "    \n",
    "    #Train Model and Predict  \n",
    "    neigh = KNeighborsClassifier(n_neighbors = n).fit(X_train,y_train)\n",
    "    yhat=neigh.predict(X_test)\n",
    "    mean_acc[n-1] = metrics.accuracy_score(y_test, yhat)\n",
    "\n",
    "    \n",
    "    std_acc[n-1]=np.std(yhat==y_test)/np.sqrt(yhat.shape[0])\n",
    "\n",
    "mean_acc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The best accuracy was with 0.6430654761904762 with k= 6\n"
     ]
    }
   ],
   "source": [
    "plt.plot(range(1,Ks),mean_acc,'g')\n",
    "plt.fill_between(range(1,Ks),mean_acc - 1 * std_acc,mean_acc + 1 * std_acc, alpha=0.10)\n",
    "plt.legend(('Accuracy ', '+/- 3xstd'))\n",
    "plt.ylabel('Accuracy ')\n",
    "plt.xlabel('Number of Nabors (K)')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print( \"The best accuracy was with\", mean_acc.max(), \"with k=\", mean_acc.argmax()+1) \n",
    "#k = 6 is best fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "neigh = KNeighborsClassifier(n_neighbors = 6).fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KNN's Jaccard: 0.6430654761904762\n",
      "KNN's F1 Score: 0.5535452215572196\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:635: DeprecationWarning: jaccard_similarity_score has been deprecated and replaced with jaccard_score. It will be removed in version 0.23. This implementation has surprising behavior for binary and multiclass classification tasks.\n",
      "  'and multiclass classification tasks.', DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "#Evaluation\n",
    "from sklearn.metrics import f1_score\n",
    "#f1_score(y_test, yhat, average='weighted') \n",
    "\n",
    "from sklearn.metrics import jaccard_similarity_score\n",
    "#jaccard_similarity_score(y_test, yhat)\n",
    "\n",
    "knn_result = neigh.predict(X_test)\n",
    "print(\"KNN's Jaccard:\", jaccard_similarity_score(y_test, knn_result))\n",
    "print(\"KNN's F1 Score:\", f1_score(y_test, knn_result, average='weighted'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Decision Tree\n",
    "carTree = DecisionTreeClassifier(criterion=\"entropy\", max_depth = 4)\n",
    "carTree.fit(X_train, y_train)\n",
    "predTree = carTree.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTrees's Jaccard: 0.6658035714285714\n",
      "DecisionTrees's F1 Score: 0.5322288934065346\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:635: DeprecationWarning: jaccard_similarity_score has been deprecated and replaced with jaccard_score. It will be removed in version 0.23. This implementation has surprising behavior for binary and multiclass classification tasks.\n",
      "  'and multiclass classification tasks.', DeprecationWarning)\n",
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1437: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    }
   ],
   "source": [
    "print(\"DecisionTrees's Jaccard:\", jaccard_similarity_score(y_test, predTree))\n",
    "print(\"DecisionTrees's F1 Score:\", f1_score(y_test, predTree, average='weighted'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import log_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Logistic Regression\n",
    "LR = LogisticRegression(C=0.01, solver='liblinear').fit(X_train,y_train)\n",
    "yhat = LR.predict(X_test)\n",
    "yhat_prob = LR.predict_proba(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic Regression's Jaccard: 0.6658035714285714\n",
      "Logistic Regression's F1 Score: 0.5322288934065346\n",
      "Logistic Regression's Log Loss: 0.6352971133324362\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:635: DeprecationWarning: jaccard_similarity_score has been deprecated and replaced with jaccard_score. It will be removed in version 0.23. This implementation has surprising behavior for binary and multiclass classification tasks.\n",
      "  'and multiclass classification tasks.', DeprecationWarning)\n",
      "C:\\Users\\cpche\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1437: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    }
   ],
   "source": [
    "print(\"Logistic Regression's Jaccard:\", jaccard_similarity_score(y_test, yhat))\n",
    "print(\"Logistic Regression's F1 Score:\", f1_score(y_test, yhat, average='weighted'))\n",
    "print(\"Logistic Regression's Log Loss:\", log_loss(y_test, yhat_prob))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
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