{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>YEAR OF STOP</th>\n",
       "      <th>DATE OF STOP</th>\n",
       "      <th>RACE OF DRIVER</th>\n",
       "      <th>GENDER OF DRIVER</th>\n",
       "      <th>DRIVER SEARCHED?</th>\n",
       "      <th>VEHICLE SEARCHED?</th>\n",
       "      <th>CITATION ISSUED?</th>\n",
       "      <th>AGE OF DRIVER</th>\n",
       "      <th>REASON FOR STOP</th>\n",
       "      <th>POLICE GRID NUMBER</th>\n",
       "      <th>LOCATION OF STOP BY POLICE GRID</th>\n",
       "      <th>COUNT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>01/01/2001 12:11:00 AM</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No Data</td>\n",
       "      <td>55.0</td>\n",
       "      <td>(44.97391713, -93.06089457)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>01/01/2001 12:14:00 AM</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No Data</td>\n",
       "      <td>106.0</td>\n",
       "      <td>(44.95211807, -93.15173337)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YEAR OF STOP            DATE OF STOP RACE OF DRIVER GENDER OF DRIVER  \\\n",
       "0          2001  01/01/2001 12:11:00 AM          White           Female   \n",
       "1          2001  01/01/2001 12:14:00 AM          White             Male   \n",
       "\n",
       "  DRIVER SEARCHED? VEHICLE SEARCHED? CITATION ISSUED?  AGE OF DRIVER  \\\n",
       "0               No                No               No            NaN   \n",
       "1               No                No               No            NaN   \n",
       "\n",
       "  REASON FOR STOP  POLICE GRID NUMBER LOCATION OF STOP BY POLICE GRID  COUNT  \n",
       "0         No Data                55.0     (44.97391713, -93.06089457)      1  \n",
       "1         No Data               106.0     (44.95211807, -93.15173337)      1  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "import warnings\n",
    "%matplotlib inline \n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "warnings.filterwarnings('ignore')\n",
    "import plotly\n",
    "from IPython.display import HTML\n",
    "from IPython.display import display\n",
    "import json # library to handle JSON files\n",
    "from geopy.geocoders import Nominatim # convert an address into latitude and longitude values\n",
    "import requests # library to handle requests\n",
    "from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe\n",
    "from sodapy import Socrata\n",
    "\n",
    "#Data Load\n",
    "df = pd.read_csv('Data/Traffic_Stop_Dataset.csv')\n",
    "\n",
    "cols= ['Year','Date','Race','Gender','Driver_search','Vehicle_search','Citation','Age','Reason','Grid','GridLocation', 'Count']\n",
    "df.columns= cols\n",
    "\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols= ['Year','Date','Race','Gender','Driver_search','Vehicle_search','Citation','Age','Reason','Grid','GridLocation', 'Count']\n",
    "df.columns= cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}