analysis (1).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "47d5aa4c-2318-4e77-b997-66d0be545636",
   "metadata": {},
   "source": [
    "#### Data Analysis of Gainesville Traffic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec6b6d9-71b8-4107-80cd-98039c59ae72",
   "metadata": {},
   "source": [
    "find if there exists a correlation between streets with the most crashes and what the traffic count is on those streets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "e91294d7-c332-4d9f-92c5-917f564627f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "87f4f8ee-f282-42bd-8f1b-5a2352bac9cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = 'TrafficData/'\n",
    "crash_data = pd.read_csv(path + 'Traffic_Crashes.csv')\n",
    "traffic_data = pd.read_csv(path + 'TrafficData20140522_20240829.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "fc61b786-84bc-4d0b-a8b3-b8ba18c88c5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>the_geom</th>\n",
       "      <th>Count_Type</th>\n",
       "      <th>Station</th>\n",
       "      <th>STREET</th>\n",
       "      <th>BLOCK</th>\n",
       "      <th>ADT_2016</th>\n",
       "      <th>ADT_2015</th>\n",
       "      <th>ADT_2014</th>\n",
       "      <th>ADT_2013</th>\n",
       "      <th>ADT_2012</th>\n",
       "      <th>...</th>\n",
       "      <th>ADT_1112</th>\n",
       "      <th>DlyD1_1112</th>\n",
       "      <th>DlyD2_1112</th>\n",
       "      <th>Heavy_1112</th>\n",
       "      <th>PkAM_1112</th>\n",
       "      <th>AMD1_1112</th>\n",
       "      <th>AMD2_1112</th>\n",
       "      <th>PkPM_1112</th>\n",
       "      <th>PMD1_1112</th>\n",
       "      <th>PMD2_1112</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-82.32454871717412 29.65991213468399)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,000</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16070</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14,727</td>\n",
       "      <td>0.496299</td>\n",
       "      <td>0.503701</td>\n",
       "      <td>6%</td>\n",
       "      <td>938</td>\n",
       "      <td>0.417910</td>\n",
       "      <td>0.582090</td>\n",
       "      <td>1,206</td>\n",
       "      <td>0.535655</td>\n",
       "      <td>0.464345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-82.32458341521964 29.66294157385959)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,001</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>1,200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15881</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17,779</td>\n",
       "      <td>0.445919</td>\n",
       "      <td>0.554081</td>\n",
       "      <td>6%</td>\n",
       "      <td>1,076</td>\n",
       "      <td>0.394052</td>\n",
       "      <td>0.605948</td>\n",
       "      <td>1,516</td>\n",
       "      <td>0.447230</td>\n",
       "      <td>0.552770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-82.32389786657433 29.66964073503187)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,002</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>1,900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15418</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12,028</td>\n",
       "      <td>0.424426</td>\n",
       "      <td>0.575574</td>\n",
       "      <td>51%</td>\n",
       "      <td>793</td>\n",
       "      <td>0.344262</td>\n",
       "      <td>0.655738</td>\n",
       "      <td>940</td>\n",
       "      <td>0.425532</td>\n",
       "      <td>0.574468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-82.31936445525942 29.68557613152471)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,003</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>3,700</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13880</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13,953</td>\n",
       "      <td>0.502759</td>\n",
       "      <td>0.497241</td>\n",
       "      <td>12%</td>\n",
       "      <td>1,201</td>\n",
       "      <td>0.344713</td>\n",
       "      <td>0.655287</td>\n",
       "      <td>1,248</td>\n",
       "      <td>0.610577</td>\n",
       "      <td>0.389423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (-82.31937859840505 29.690140797111162)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,006</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>4,000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6325</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5,785</td>\n",
       "      <td>0.522385</td>\n",
       "      <td>0.477615</td>\n",
       "      <td>16%</td>\n",
       "      <td>637</td>\n",
       "      <td>0.318681</td>\n",
       "      <td>0.681319</td>\n",
       "      <td>629</td>\n",
       "      <td>0.620032</td>\n",
       "      <td>0.379968</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        the_geom Count_Type Station  \\\n",
       "0   POINT (-82.32454871717412 29.65991213468399)         CI   1,000   \n",
       "1   POINT (-82.32458341521964 29.66294157385959)         CI   1,001   \n",
       "2   POINT (-82.32389786657433 29.66964073503187)         CI   1,002   \n",
       "3   POINT (-82.31936445525942 29.68557613152471)         CI   1,003   \n",
       "4  POINT (-82.31937859840505 29.690140797111162)         CI   1,006   \n",
       "\n",
       "      STREET  BLOCK  ADT_2016  ADT_2015  ADT_2014 ADT_2013 ADT_2012  ...  \\\n",
       "0  N MAIN ST    900         0         0     16070        0        0  ...   \n",
       "1  N MAIN ST  1,200         0         0     15881        0        0  ...   \n",
       "2  N MAIN ST  1,900         0         0     15418        0        0  ...   \n",
       "3  N MAIN ST  3,700         0         0     13880        0        0  ...   \n",
       "4  N MAIN ST  4,000         0         0      6325        0        0  ...   \n",
       "\n",
       "  ADT_1112 DlyD1_1112 DlyD2_1112 Heavy_1112 PkAM_1112 AMD1_1112 AMD2_1112  \\\n",
       "0   14,727   0.496299   0.503701         6%       938  0.417910  0.582090   \n",
       "1   17,779   0.445919   0.554081         6%     1,076  0.394052  0.605948   \n",
       "2   12,028   0.424426   0.575574        51%       793  0.344262  0.655738   \n",
       "3   13,953   0.502759   0.497241        12%     1,201  0.344713  0.655287   \n",
       "4    5,785   0.522385   0.477615        16%       637  0.318681  0.681319   \n",
       "\n",
       "  PkPM_1112 PMD1_1112 PMD2_1112  \n",
       "0     1,206  0.535655  0.464345  \n",
       "1     1,516  0.447230  0.552770  \n",
       "2       940  0.425532  0.574468  \n",
       "3     1,248  0.610577  0.389423  \n",
       "4       629  0.620032  0.379968  \n",
       "\n",
       "[5 rows x 46 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "traffic_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62be0bd6-76b3-4c2e-a4e2-c347451b6251",
   "metadata": {},
   "source": [
    "#### Filtering out all Crashes not on 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "ef831dc0-12b1-4241-8307-a3550889c557",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Case Number</th>\n",
       "      <th>DHSMV Number</th>\n",
       "      <th>Crash Date</th>\n",
       "      <th>Crash Hour of Day</th>\n",
       "      <th>Crash minutes</th>\n",
       "      <th>Crash Day of Week</th>\n",
       "      <th>Address</th>\n",
       "      <th>Street Address number</th>\n",
       "      <th>Intersect Type</th>\n",
       "      <th>Distance</th>\n",
       "      <th>...</th>\n",
       "      <th>Total Motorcycles</th>\n",
       "      <th>Total Buses</th>\n",
       "      <th>Total Fatalities</th>\n",
       "      <th>Geox</th>\n",
       "      <th>Geoy</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Location</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
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       "      <th>6408</th>\n",
       "      <td>216009925</td>\n",
       "      <td>86285208</td>\n",
       "      <td>05/28/2016</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>2011 NW 13TH ST</td>\n",
       "      <td>2011</td>\n",
       "      <td>NOT AT INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>265477375</td>\n",
       "      <td>25033227</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25141</th>\n",
       "      <td>216017751</td>\n",
       "      <td>86593057</td>\n",
       "      <td>09/24/2016</td>\n",
       "      <td>10</td>\n",
       "      <td>41</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>3616 SW 34TH ST</td>\n",
       "      <td>3616</td>\n",
       "      <td>T-INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>264436650</td>\n",
       "      <td>23182755</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27485</th>\n",
       "      <td>216017590</td>\n",
       "      <td>86593082</td>\n",
       "      <td>09/22/2016</td>\n",
       "      <td>15</td>\n",
       "      <td>26</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>3801</td>\n",
       "      <td>NOT AT INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>266094150</td>\n",
       "      <td>25665897</td>\n",
       "      <td>-82.31939</td>\n",
       "      <td>29.68794</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27490</th>\n",
       "      <td>216021258</td>\n",
       "      <td>86594087</td>\n",
       "      <td>11/12/2016</td>\n",
       "      <td>19</td>\n",
       "      <td>11</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>W UNIVERSITY AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOT AT INTERSECTION</td>\n",
       "      <td>300   FEET</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>265308200</td>\n",
       "      <td>24356009</td>\n",
       "      <td>-82.32272</td>\n",
       "      <td>29.65198</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27492</th>\n",
       "      <td>216019607</td>\n",
       "      <td>86593590</td>\n",
       "      <td>10/20/2016</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>W UNIVERSITY AVE</td>\n",
       "      <td>1412</td>\n",
       "      <td>NOT AT INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>265438125</td>\n",
       "      <td>24368330</td>\n",
       "      <td>-82.30676</td>\n",
       "      <td>29.65195</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Case Number  DHSMV Number  Crash Date  Crash Hour of Day  \\\n",
       "6408     216009925      86285208  05/28/2016                 11   \n",
       "25141    216017751      86593057  09/24/2016                 10   \n",
       "27485    216017590      86593082  09/22/2016                 15   \n",
       "27490    216021258      86594087  11/12/2016                 19   \n",
       "27492    216019607      86593590  10/20/2016                  9   \n",
       "\n",
       "       Crash minutes Crash Day of Week           Address  \\\n",
       "6408               7          Saturday   2011 NW 13TH ST   \n",
       "25141             41          Saturday   3616 SW 34TH ST   \n",
       "27485             26          Thursday         N MAIN ST   \n",
       "27490             11          Saturday  W UNIVERSITY AVE   \n",
       "27492              5          Thursday  W UNIVERSITY AVE   \n",
       "\n",
       "      Street Address number       Intersect Type    Distance  ...  \\\n",
       "6408                   2011  NOT AT INTERSECTION         NaN  ...   \n",
       "25141                  3616       T-INTERSECTION         NaN  ...   \n",
       "27485                  3801  NOT AT INTERSECTION         NaN  ...   \n",
       "27490                   NaN  NOT AT INTERSECTION  300   FEET  ...   \n",
       "27492                  1412  NOT AT INTERSECTION         NaN  ...   \n",
       "\n",
       "      Total Motorcycles Total Buses   Total Fatalities       Geox      Geoy  \\\n",
       "6408                  0            0                 0  265477375  25033227   \n",
       "25141                 0            0                 0  264436650  23182755   \n",
       "27485                 0            0                 0  266094150  25665897   \n",
       "27490                 0            1                 0  265308200  24356009   \n",
       "27492                 0            0                 0  265438125  24368330   \n",
       "\n",
       "       Longitude  Latitude                    Location         City    State  \n",
       "6408         NaN       NaN  POINT (-82.32272 29.65198)  Gainesville  Florida  \n",
       "25141        NaN       NaN  POINT (-82.32272 29.65198)  Gainesville  Florida  \n",
       "27485  -82.31939  29.68794  POINT (-82.32272 29.65198)  Gainesville  Florida  \n",
       "27490  -82.32272  29.65198  POINT (-82.32272 29.65198)  Gainesville  Florida  \n",
       "27492  -82.30676  29.65195  POINT (-82.32272 29.65198)  Gainesville  Florida  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_data = crash_data[crash_data['Crash Date'].str[6:10]=='2016']\n",
    "filtered_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "cd1024db-e6fe-4811-84f9-67d39ea30bbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Case Number</th>\n",
       "      <th>DHSMV Number</th>\n",
       "      <th>Crash Date</th>\n",
       "      <th>Crash Hour of Day</th>\n",
       "      <th>Crash minutes</th>\n",
       "      <th>Crash Day of Week</th>\n",
       "      <th>Address</th>\n",
       "      <th>Street Address number</th>\n",
       "      <th>Intersect Type</th>\n",
       "      <th>Distance</th>\n",
       "      <th>...</th>\n",
       "      <th>Total Buses</th>\n",
       "      <th>Total Fatalities</th>\n",
       "      <th>Geox</th>\n",
       "      <th>Geoy</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Location</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>street_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>223008681</td>\n",
       "      <td>25598760</td>\n",
       "      <td>05/31/2023</td>\n",
       "      <td>18</td>\n",
       "      <td>27</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>CR 172 (NE 16TH AVE)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FOUR-WAY INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>266534175</td>\n",
       "      <td>24904878</td>\n",
       "      <td>-82.32272</td>\n",
       "      <td>29.65198</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "      <td>NE 16TH AVE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223008367</td>\n",
       "      <td>25598688</td>\n",
       "      <td>05/25/2023</td>\n",
       "      <td>11</td>\n",
       "      <td>52</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>SR 20 (NW 6TH ST)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FOUR-WAY INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>265727650</td>\n",
       "      <td>25696197</td>\n",
       "      <td>-82.32272</td>\n",
       "      <td>29.65198</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "      <td>NW 6TH ST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>223000500</td>\n",
       "      <td>25597022</td>\n",
       "      <td>01/11/2023</td>\n",
       "      <td>10</td>\n",
       "      <td>23</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>SR 121 (SW 34TH ST)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOT AT INTERSECTION</td>\n",
       "      <td>30    FEET</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>264441775</td>\n",
       "      <td>23820608</td>\n",
       "      <td>-82.32272</td>\n",
       "      <td>29.65198</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "      <td>SW 34TH ST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>223000480</td>\n",
       "      <td>25596992</td>\n",
       "      <td>01/10/2023</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>SR-121 (SW WILLISTON RD)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T-INTERSECTION</td>\n",
       "      <td>10    FEET</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>264467950</td>\n",
       "      <td>22561378</td>\n",
       "      <td>-82.32272</td>\n",
       "      <td>29.65198</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "      <td>SW WILLISTON RD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>223000495</td>\n",
       "      <td>25597103</td>\n",
       "      <td>01/11/2023</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>SR 26 (W NEWBERRY RD)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T-INTERSECTION</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>263265825</td>\n",
       "      <td>24592113</td>\n",
       "      <td>-82.32272</td>\n",
       "      <td>29.65198</td>\n",
       "      <td>POINT (-82.32272 29.65198)</td>\n",
       "      <td>Gainesville</td>\n",
       "      <td>Florida</td>\n",
       "      <td>W NEWBERRY RD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Case Number  DHSMV Number  Crash Date  Crash Hour of Day  Crash minutes  \\\n",
       "0    223008681      25598760  05/31/2023                 18             27   \n",
       "1    223008367      25598688  05/25/2023                 11             52   \n",
       "2    223000500      25597022  01/11/2023                 10             23   \n",
       "3    223000480      25596992  01/10/2023                 19             25   \n",
       "5    223000495      25597103  01/11/2023                  8              7   \n",
       "\n",
       "  Crash Day of Week                   Address Street Address number  \\\n",
       "0         Wednesday      CR 172 (NE 16TH AVE)                   NaN   \n",
       "1          Thursday         SR 20 (NW 6TH ST)                   NaN   \n",
       "2         Wednesday       SR 121 (SW 34TH ST)                   NaN   \n",
       "3           Tuesday  SR-121 (SW WILLISTON RD)                   NaN   \n",
       "5         Wednesday     SR 26 (W NEWBERRY RD)                   NaN   \n",
       "\n",
       "          Intersect Type    Distance  ... Total Buses  Total Fatalities  \\\n",
       "0  FOUR-WAY INTERSECTION         NaN  ...            0                0   \n",
       "1  FOUR-WAY INTERSECTION         NaN  ...            0                0   \n",
       "2    NOT AT INTERSECTION  30    FEET  ...            0                0   \n",
       "3         T-INTERSECTION  10    FEET  ...            0                0   \n",
       "5         T-INTERSECTION         NaN  ...            0                0   \n",
       "\n",
       "        Geox      Geoy  Longitude  Latitude                    Location  \\\n",
       "0  266534175  24904878  -82.32272  29.65198  POINT (-82.32272 29.65198)   \n",
       "1  265727650  25696197  -82.32272  29.65198  POINT (-82.32272 29.65198)   \n",
       "2  264441775  23820608  -82.32272  29.65198  POINT (-82.32272 29.65198)   \n",
       "3  264467950  22561378  -82.32272  29.65198  POINT (-82.32272 29.65198)   \n",
       "5  263265825  24592113  -82.32272  29.65198  POINT (-82.32272 29.65198)   \n",
       "\n",
       "          City    State      street_name  \n",
       "0  Gainesville  Florida      NE 16TH AVE  \n",
       "1  Gainesville  Florida        NW 6TH ST  \n",
       "2  Gainesville  Florida       SW 34TH ST  \n",
       "3  Gainesville  Florida  SW WILLISTON RD  \n",
       "5  Gainesville  Florida    W NEWBERRY RD  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract street name from the full address and remove all rows with NaN\n",
    "crash_data['street_name'] = crash_data['Address'].str.extract(r'\\((.*?)\\)')\n",
    "crash_data = crash_data.dropna(subset=['street_name'])\n",
    "crash_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "963e3ed4-889d-4d78-8867-f2dd931749e8",
   "metadata": {},
   "source": [
    "#### Creating graph with amount of crashes on every street in gainesville"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "61d23542-7642-4ff4-9061-7cf35d5604f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Counts number of crashes and filters out streets with less than 100 crashes\n",
    "crash_counts = crash_data['street_name'].value_counts()\n",
    "crash_counts = crash_counts[crash_counts >= 100]\n",
    "\n",
    "# Bar Graph\n",
    "plt.figure(figsize=(10, 6))\n",
    "crash_counts.plot(kind='bar', color='skyblue')\n",
    "plt.title('Number of Crashes on Each Street')\n",
    "plt.xlabel('Street Name')\n",
    "plt.ylabel('Number of Crashes')\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "470fb17b-a5c6-49f4-aa7e-811bc2d8f871",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "street_name\n",
       "SW ARCHER RD        3909\n",
       "SW 34TH ST          2998\n",
       "NW 13TH ST          2760\n",
       "W NEWBERRY RD       2630\n",
       "W UNIVERSITY AVE    2310\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crash_counts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "826edc21-9d9f-460e-9cb0-0fc1fedfcf9a",
   "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>the_geom</th>\n",
       "      <th>Count_Type</th>\n",
       "      <th>Station</th>\n",
       "      <th>STREET</th>\n",
       "      <th>BLOCK</th>\n",
       "      <th>ADT_2016</th>\n",
       "      <th>ADT_2015</th>\n",
       "      <th>ADT_2014</th>\n",
       "      <th>ADT_2013</th>\n",
       "      <th>ADT_2012</th>\n",
       "      <th>...</th>\n",
       "      <th>ADT_1112</th>\n",
       "      <th>DlyD1_1112</th>\n",
       "      <th>DlyD2_1112</th>\n",
       "      <th>Heavy_1112</th>\n",
       "      <th>PkAM_1112</th>\n",
       "      <th>AMD1_1112</th>\n",
       "      <th>AMD2_1112</th>\n",
       "      <th>PkPM_1112</th>\n",
       "      <th>PMD1_1112</th>\n",
       "      <th>PMD2_1112</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-82.32454871717412 29.65991213468399)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,000</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16070</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14,727</td>\n",
       "      <td>0.496299</td>\n",
       "      <td>0.503701</td>\n",
       "      <td>6%</td>\n",
       "      <td>938</td>\n",
       "      <td>0.417910</td>\n",
       "      <td>0.582090</td>\n",
       "      <td>1,206</td>\n",
       "      <td>0.535655</td>\n",
       "      <td>0.464345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-82.32458341521964 29.66294157385959)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,001</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>1,200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15881</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17,779</td>\n",
       "      <td>0.445919</td>\n",
       "      <td>0.554081</td>\n",
       "      <td>6%</td>\n",
       "      <td>1,076</td>\n",
       "      <td>0.394052</td>\n",
       "      <td>0.605948</td>\n",
       "      <td>1,516</td>\n",
       "      <td>0.447230</td>\n",
       "      <td>0.552770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-82.32389786657433 29.66964073503187)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,002</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>1,900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15418</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12,028</td>\n",
       "      <td>0.424426</td>\n",
       "      <td>0.575574</td>\n",
       "      <td>51%</td>\n",
       "      <td>793</td>\n",
       "      <td>0.344262</td>\n",
       "      <td>0.655738</td>\n",
       "      <td>940</td>\n",
       "      <td>0.425532</td>\n",
       "      <td>0.574468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-82.31936445525942 29.68557613152471)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,003</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>3,700</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13880</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13,953</td>\n",
       "      <td>0.502759</td>\n",
       "      <td>0.497241</td>\n",
       "      <td>12%</td>\n",
       "      <td>1,201</td>\n",
       "      <td>0.344713</td>\n",
       "      <td>0.655287</td>\n",
       "      <td>1,248</td>\n",
       "      <td>0.610577</td>\n",
       "      <td>0.389423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (-82.31937859840505 29.690140797111162)</td>\n",
       "      <td>CI</td>\n",
       "      <td>1,006</td>\n",
       "      <td>N MAIN ST</td>\n",
       "      <td>4,000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6325</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5,785</td>\n",
       "      <td>0.522385</td>\n",
       "      <td>0.477615</td>\n",
       "      <td>16%</td>\n",
       "      <td>637</td>\n",
       "      <td>0.318681</td>\n",
       "      <td>0.681319</td>\n",
       "      <td>629</td>\n",
       "      <td>0.620032</td>\n",
       "      <td>0.379968</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        the_geom Count_Type Station  \\\n",
       "0   POINT (-82.32454871717412 29.65991213468399)         CI   1,000   \n",
       "1   POINT (-82.32458341521964 29.66294157385959)         CI   1,001   \n",
       "2   POINT (-82.32389786657433 29.66964073503187)         CI   1,002   \n",
       "3   POINT (-82.31936445525942 29.68557613152471)         CI   1,003   \n",
       "4  POINT (-82.31937859840505 29.690140797111162)         CI   1,006   \n",
       "\n",
       "      STREET  BLOCK  ADT_2016  ADT_2015  ADT_2014 ADT_2013 ADT_2012  ...  \\\n",
       "0  N MAIN ST    900         0         0     16070        0        0  ...   \n",
       "1  N MAIN ST  1,200         0         0     15881        0        0  ...   \n",
       "2  N MAIN ST  1,900         0         0     15418        0        0  ...   \n",
       "3  N MAIN ST  3,700         0         0     13880        0        0  ...   \n",
       "4  N MAIN ST  4,000         0         0      6325        0        0  ...   \n",
       "\n",
       "  ADT_1112 DlyD1_1112 DlyD2_1112 Heavy_1112 PkAM_1112 AMD1_1112 AMD2_1112  \\\n",
       "0   14,727   0.496299   0.503701         6%       938  0.417910  0.582090   \n",
       "1   17,779   0.445919   0.554081         6%     1,076  0.394052  0.605948   \n",
       "2   12,028   0.424426   0.575574        51%       793  0.344262  0.655738   \n",
       "3   13,953   0.502759   0.497241        12%     1,201  0.344713  0.655287   \n",
       "4    5,785   0.522385   0.477615        16%       637  0.318681  0.681319   \n",
       "\n",
       "  PkPM_1112 PMD1_1112 PMD2_1112  \n",
       "0     1,206  0.535655  0.464345  \n",
       "1     1,516  0.447230  0.552770  \n",
       "2       940  0.425532  0.574468  \n",
       "3     1,248  0.610577  0.389423  \n",
       "4       629  0.620032  0.379968  \n",
       "\n",
       "[5 rows x 46 columns]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "traffic_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ebe2ee6-9af3-4dd3-a66a-51074faa6afc",
   "metadata": {},
   "source": [
    "For all values in ADT_2012 removes commas and converts to int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "3c3d7741-7820-4cff-96d3-44e3494d036d",
   "metadata": {},
   "outputs": [],
   "source": [
    "traffic_data['ADT_2012'] = traffic_data['ADT_2012'].str.replace(',', '').astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "5d9c4aef-847c-458b-bf28-a6f8bc85bde5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>the_geom</th>\n",
       "      <th>Count_Type</th>\n",
       "      <th>Station</th>\n",
       "      <th>STREET</th>\n",
       "      <th>BLOCK</th>\n",
       "      <th>ADT_2016</th>\n",
       "      <th>ADT_2015</th>\n",
       "      <th>ADT_2014</th>\n",
       "      <th>ADT_2013</th>\n",
       "      <th>ADT_2012</th>\n",
       "      <th>...</th>\n",
       "      <th>ADT_1112</th>\n",
       "      <th>DlyD1_1112</th>\n",
       "      <th>DlyD2_1112</th>\n",
       "      <th>Heavy_1112</th>\n",
       "      <th>PkAM_1112</th>\n",
       "      <th>AMD1_1112</th>\n",
       "      <th>AMD2_1112</th>\n",
       "      <th>PkPM_1112</th>\n",
       "      <th>PMD1_1112</th>\n",
       "      <th>PMD2_1112</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>POINT (-82.34742422259016 29.685662909569636)</td>\n",
       "      <td>CI</td>\n",
       "      <td>2,010</td>\n",
       "      <td>NW 19TH ST</td>\n",
       "      <td>3,600</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2454</td>\n",
       "      <td>0</td>\n",
       "      <td>2405</td>\n",
       "      <td>...</td>\n",
       "      <td>2,405</td>\n",
       "      <td>0.520166</td>\n",
       "      <td>0.479834</td>\n",
       "      <td>7%</td>\n",
       "      <td>225</td>\n",
       "      <td>0.462222</td>\n",
       "      <td>0.537778</td>\n",
       "      <td>245</td>\n",
       "      <td>0.591837</td>\n",
       "      <td>0.408163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>POINT (-82.32657964832495 29.664773630620704)</td>\n",
       "      <td>CI</td>\n",
       "      <td>2,014</td>\n",
       "      <td>NW 2ND ST</td>\n",
       "      <td>1,400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2870</td>\n",
       "      <td>...</td>\n",
       "      <td>2,870</td>\n",
       "      <td>0.520209</td>\n",
       "      <td>0.479791</td>\n",
       "      <td>2%</td>\n",
       "      <td>144</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>289</td>\n",
       "      <td>0.553633</td>\n",
       "      <td>0.446367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>POINT (-82.32874824486974 29.65389358969202)</td>\n",
       "      <td>CI</td>\n",
       "      <td>2,013</td>\n",
       "      <td>NW 3RD AV</td>\n",
       "      <td>400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>628</td>\n",
       "      <td>...</td>\n",
       "      <td>628</td>\n",
       "      <td>0.953822</td>\n",
       "      <td>0.046178</td>\n",
       "      <td>5%</td>\n",
       "      <td>31</td>\n",
       "      <td>0.967742</td>\n",
       "      <td>0.032258</td>\n",
       "      <td>72</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.055556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>POINT (-82.32790969497944 29.655631330502466)</td>\n",
       "      <td>CI</td>\n",
       "      <td>2,016</td>\n",
       "      <td>NW 3RD ST</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>559</td>\n",
       "      <td>...</td>\n",
       "      <td>559</td>\n",
       "      <td>0.946333</td>\n",
       "      <td>0.053667</td>\n",
       "      <td>5%</td>\n",
       "      <td>33</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>40</td>\n",
       "      <td>0.925000</td>\n",
       "      <td>0.075000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>POINT (-82.33509472419685 29.660471502051294)</td>\n",
       "      <td>CI</td>\n",
       "      <td>2,021</td>\n",
       "      <td>NW 10TH ST</td>\n",
       "      <td>900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1002</td>\n",
       "      <td>...</td>\n",
       "      <td>1,002</td>\n",
       "      <td>0.576846</td>\n",
       "      <td>0.423154</td>\n",
       "      <td>12%</td>\n",
       "      <td>77</td>\n",
       "      <td>0.155844</td>\n",
       "      <td>0.844156</td>\n",
       "      <td>120</td>\n",
       "      <td>0.816667</td>\n",
       "      <td>0.183333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         the_geom Count_Type Station  \\\n",
       "6   POINT (-82.34742422259016 29.685662909569636)         CI   2,010   \n",
       "8   POINT (-82.32657964832495 29.664773630620704)         CI   2,014   \n",
       "9    POINT (-82.32874824486974 29.65389358969202)         CI   2,013   \n",
       "11  POINT (-82.32790969497944 29.655631330502466)         CI   2,016   \n",
       "15  POINT (-82.33509472419685 29.660471502051294)         CI   2,021   \n",
       "\n",
       "        STREET  BLOCK  ADT_2016  ADT_2015  ADT_2014 ADT_2013  ADT_2012  ...  \\\n",
       "6   NW 19TH ST  3,600         0         0      2454        0      2405  ...   \n",
       "8    NW 2ND ST  1,400         0         0         0        0      2870  ...   \n",
       "9    NW 3RD AV    400         0         0         0        0       628  ...   \n",
       "11   NW 3RD ST    500         0         0         0        0       559  ...   \n",
       "15  NW 10TH ST    900         0         0         0        0      1002  ...   \n",
       "\n",
       "   ADT_1112 DlyD1_1112 DlyD2_1112 Heavy_1112 PkAM_1112 AMD1_1112 AMD2_1112  \\\n",
       "6     2,405   0.520166   0.479834         7%       225  0.462222  0.537778   \n",
       "8     2,870   0.520209   0.479791         2%       144  0.444444  0.555556   \n",
       "9       628   0.953822   0.046178         5%        31  0.967742  0.032258   \n",
       "11      559   0.946333   0.053667         5%        33  1.000000  0.000000   \n",
       "15    1,002   0.576846   0.423154        12%        77  0.155844  0.844156   \n",
       "\n",
       "   PkPM_1112 PMD1_1112 PMD2_1112  \n",
       "6        245  0.591837  0.408163  \n",
       "8        289  0.553633  0.446367  \n",
       "9         72  0.944444  0.055556  \n",
       "11        40  0.925000  0.075000  \n",
       "15       120  0.816667  0.183333  \n",
       "\n",
       "[5 rows x 46 columns]"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filters out elements == 0\n",
    "filtered_traffic = traffic_data[traffic_data['ADT_2012']!=0]\n",
    "filtered_traffic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "0e842a2d-289d-410e-8c16-b09a3e00d843",
   "metadata": {},
   "outputs": [],
   "source": [
    "#avg_traffic[filtered_traffic['STREET']] = filtered_traffic['ADT_2012'].value_counts()\n",
    "\n",
    "#avg_traffic.head()"
   ]
  }
 ],
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