modeling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "434310e2-668b-4eca-9128-df43d7951f42",
   "metadata": {},
   "source": [
    "# Modeling "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "129a7590-3a8c-4525-a486-705d054cec4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# frst lets clean some of our data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "58ea5c13-a87f-4b9e-b10f-9b15bd8c4aae",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split, cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "48ac968d-ce18-4a4a-af8d-1786bfb7c93f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_accident = pd.read_csv('./data/accident.csv')\n",
    "df_accident.columns = df_accident.columns.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d0de48a8-c646-405e-a2ec-87eb666f22c2",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>statename</th>\n",
       "      <th>st_case</th>\n",
       "      <th>ve_total</th>\n",
       "      <th>ve_forms</th>\n",
       "      <th>pvh_invl</th>\n",
       "      <th>peds</th>\n",
       "      <th>persons</th>\n",
       "      <th>permvit</th>\n",
       "      <th>pernotmvit</th>\n",
       "      <th>...</th>\n",
       "      <th>arr_hour</th>\n",
       "      <th>arr_hourname</th>\n",
       "      <th>arr_min</th>\n",
       "      <th>arr_minname</th>\n",
       "      <th>hosp_hr</th>\n",
       "      <th>hosp_hrname</th>\n",
       "      <th>hosp_mn</th>\n",
       "      <th>hosp_mnname</th>\n",
       "      <th>fatals</th>\n",
       "      <th>drunk_dr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10001</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3:00am-3:59am</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10002</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>5:00pm-5:59pm</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10003</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>3:00pm-3:59pm</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10004</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Scene Arrival Hour</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Scene Arrival Minutes</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10005</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0:00am-0:59am</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>88</td>\n",
       "      <td>Not Applicable (Not Transported)</td>\n",
       "      <td>88</td>\n",
       "      <td>Not Applicable (Not Transported)</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   state statename  st_case  ve_total  ve_forms  pvh_invl  peds  persons  \\\n",
       "0      1   Alabama    10001         1         1         0     0        4   \n",
       "1      1   Alabama    10002         4         4         0     0        6   \n",
       "2      1   Alabama    10003         2         2         0     0        2   \n",
       "3      1   Alabama    10004         1         1         0     0        5   \n",
       "4      1   Alabama    10005         1         1         0     0        1   \n",
       "\n",
       "   permvit  pernotmvit  ...  arr_hour                    arr_hourname  \\\n",
       "0        4           0  ...         3                   3:00am-3:59am   \n",
       "1        6           0  ...        17                   5:00pm-5:59pm   \n",
       "2        2           0  ...        15                   3:00pm-3:59pm   \n",
       "3        5           0  ...        99  Unknown EMS Scene Arrival Hour   \n",
       "4        1           0  ...         0                   0:00am-0:59am   \n",
       "\n",
       "   arr_min                        arr_minname  hosp_hr  \\\n",
       "0       10                                 10       99   \n",
       "1       26                                 26       99   \n",
       "2       15                                 15       99   \n",
       "3       99  Unknown EMS Scene Arrival Minutes       99   \n",
       "4       55                                 55       88   \n",
       "\n",
       "                        hosp_hrname  hosp_mn  \\\n",
       "0                           Unknown       99   \n",
       "1                           Unknown       99   \n",
       "2                           Unknown       99   \n",
       "3                           Unknown       99   \n",
       "4  Not Applicable (Not Transported)       88   \n",
       "\n",
       "                         hosp_mnname  fatals  drunk_dr  \n",
       "0  Unknown EMS Hospital Arrival Time       3         1  \n",
       "1  Unknown EMS Hospital Arrival Time       1         0  \n",
       "2  Unknown EMS Hospital Arrival Time       1         0  \n",
       "3  Unknown EMS Hospital Arrival Time       1         0  \n",
       "4   Not Applicable (Not Transported)       1         0  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_accident.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "045d99e7-8b79-4c32-9d8d-10f115d1e90e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state          0\n",
       "statename      0\n",
       "st_case        0\n",
       "ve_total       0\n",
       "ve_forms       0\n",
       "              ..\n",
       "hosp_hrname    0\n",
       "hosp_mn        0\n",
       "hosp_mnname    0\n",
       "fatals         0\n",
       "drunk_dr       0\n",
       "Length: 81, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_accident.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "56e97f27-a0b4-4fce-b1b6-293b58c98547",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state          0\n",
       "statename      0\n",
       "st_case        0\n",
       "ve_total       0\n",
       "ve_forms       0\n",
       "              ..\n",
       "hosp_hrname    0\n",
       "hosp_mn        0\n",
       "hosp_mnname    0\n",
       "fatals         0\n",
       "drunk_dr       0\n",
       "Length: 81, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_accident.isnull().sum()"
   ]
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   "cell_type": "code",
   "execution_count": 9,
   "id": "32583f89-56f7-411c-b475-d48fc0c21b19",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 35766 entries, 0 to 35765\n",
      "Data columns (total 81 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   state         35766 non-null  int64  \n",
      " 1   statename     35766 non-null  object \n",
      " 2   st_case       35766 non-null  int64  \n",
      " 3   ve_total      35766 non-null  int64  \n",
      " 4   ve_forms      35766 non-null  int64  \n",
      " 5   pvh_invl      35766 non-null  int64  \n",
      " 6   peds          35766 non-null  int64  \n",
      " 7   persons       35766 non-null  int64  \n",
      " 8   permvit       35766 non-null  int64  \n",
      " 9   pernotmvit    35766 non-null  int64  \n",
      " 10  county        35766 non-null  int64  \n",
      " 11  countyname    35766 non-null  object \n",
      " 12  city          35766 non-null  int64  \n",
      " 13  cityname      35766 non-null  object \n",
      " 14  day           35766 non-null  int64  \n",
      " 15  dayname       35766 non-null  int64  \n",
      " 16  month         35766 non-null  int64  \n",
      " 17  monthname     35766 non-null  object \n",
      " 18  year          35766 non-null  int64  \n",
      " 19  day_week      35766 non-null  int64  \n",
      " 20  day_weekname  35766 non-null  object \n",
      " 21  hour          35766 non-null  int64  \n",
      " 22  hourname      35766 non-null  object \n",
      " 23  minute        35766 non-null  int64  \n",
      " 24  minutename    35766 non-null  object \n",
      " 25  nhs           35766 non-null  int64  \n",
      " 26  nhsname       35766 non-null  object \n",
      " 27  route         35766 non-null  int64  \n",
      " 28  routename     35766 non-null  object \n",
      " 29  tway_id       35766 non-null  object \n",
      " 30  tway_id2      8769 non-null   object \n",
      " 31  rur_urb       35766 non-null  int64  \n",
      " 32  rur_urbname   35766 non-null  object \n",
      " 33  func_sys      35766 non-null  int64  \n",
      " 34  func_sysname  35766 non-null  object \n",
      " 35  rd_owner      35766 non-null  int64  \n",
      " 36  rd_ownername  35766 non-null  object \n",
      " 37  milept        35766 non-null  int64  \n",
      " 38  mileptname    35766 non-null  object \n",
      " 39  latitude      35766 non-null  float64\n",
      " 40  latitudename  35766 non-null  object \n",
      " 41  longitud      35766 non-null  float64\n",
      " 42  longitudname  35766 non-null  object \n",
      " 43  sp_jur        35766 non-null  int64  \n",
      " 44  sp_jurname    35766 non-null  object \n",
      " 45  harm_ev       35766 non-null  int64  \n",
      " 46  harm_evname   35766 non-null  object \n",
      " 47  man_coll      35766 non-null  int64  \n",
      " 48  man_collname  35766 non-null  object \n",
      " 49  reljct1       35766 non-null  int64  \n",
      " 50  reljct1name   35766 non-null  object \n",
      " 51  reljct2       35766 non-null  int64  \n",
      " 52  reljct2name   35766 non-null  object \n",
      " 53  typ_int       35766 non-null  int64  \n",
      " 54  typ_intname   35766 non-null  object \n",
      " 55  wrk_zone      35766 non-null  int64  \n",
      " 56  wrk_zonename  35766 non-null  object \n",
      " 57  rel_road      35766 non-null  int64  \n",
      " 58  rel_roadname  35766 non-null  object \n",
      " 59  lgt_cond      35766 non-null  int64  \n",
      " 60  lgt_condname  35766 non-null  object \n",
      " 61  weather       35766 non-null  int64  \n",
      " 62  weathername   35766 non-null  object \n",
      " 63  sch_bus       35766 non-null  int64  \n",
      " 64  sch_busname   35766 non-null  object \n",
      " 65  rail          35766 non-null  object \n",
      " 66  railname      35766 non-null  object \n",
      " 67  not_hour      35766 non-null  int64  \n",
      " 68  not_hourname  35766 non-null  object \n",
      " 69  not_min       35766 non-null  int64  \n",
      " 70  not_minname   35766 non-null  object \n",
      " 71  arr_hour      35766 non-null  int64  \n",
      " 72  arr_hourname  35766 non-null  object \n",
      " 73  arr_min       35766 non-null  int64  \n",
      " 74  arr_minname   35766 non-null  object \n",
      " 75  hosp_hr       35766 non-null  int64  \n",
      " 76  hosp_hrname   35766 non-null  object \n",
      " 77  hosp_mn       35766 non-null  int64  \n",
      " 78  hosp_mnname   35766 non-null  object \n",
      " 79  fatals        35766 non-null  int64  \n",
      " 80  drunk_dr      35766 non-null  int64  \n",
      "dtypes: float64(2), int64(43), object(36)\n",
      "memory usage: 22.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df_accident.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e50e6a3c-9700-4c47-bdbf-3d0159382377",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_accident.drop(columns='tway_id2', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "30a99da2-0b09-4a07-b6c6-31449bd6d100",
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    {
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       "      <th>permvit</th>\n",
       "      <th>pernotmvit</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10001</td>\n",
       "      <td>1</td>\n",
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       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3:00am-3:59am</td>\n",
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       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
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       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10002</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>5:00pm-5:59pm</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10003</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>3:00pm-3:59pm</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10004</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Scene Arrival Hour</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Scene Arrival Minutes</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>99</td>\n",
       "      <td>Unknown EMS Hospital Arrival Time</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>10005</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0:00am-0:59am</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>88</td>\n",
       "      <td>Not Applicable (Not Transported)</td>\n",
       "      <td>88</td>\n",
       "      <td>Not Applicable (Not Transported)</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   state statename  st_case  ve_total  ve_forms  pvh_invl  peds  persons  \\\n",
       "0      1   Alabama    10001         1         1         0     0        4   \n",
       "1      1   Alabama    10002         4         4         0     0        6   \n",
       "2      1   Alabama    10003         2         2         0     0        2   \n",
       "3      1   Alabama    10004         1         1         0     0        5   \n",
       "4      1   Alabama    10005         1         1         0     0        1   \n",
       "\n",
       "   permvit  pernotmvit  ...  arr_hour                    arr_hourname  \\\n",
       "0        4           0  ...         3                   3:00am-3:59am   \n",
       "1        6           0  ...        17                   5:00pm-5:59pm   \n",
       "2        2           0  ...        15                   3:00pm-3:59pm   \n",
       "3        5           0  ...        99  Unknown EMS Scene Arrival Hour   \n",
       "4        1           0  ...         0                   0:00am-0:59am   \n",
       "\n",
       "   arr_min                        arr_minname  hosp_hr  \\\n",
       "0       10                                 10       99   \n",
       "1       26                                 26       99   \n",
       "2       15                                 15       99   \n",
       "3       99  Unknown EMS Scene Arrival Minutes       99   \n",
       "4       55                                 55       88   \n",
       "\n",
       "                        hosp_hrname  hosp_mn  \\\n",
       "0                           Unknown       99   \n",
       "1                           Unknown       99   \n",
       "2                           Unknown       99   \n",
       "3                           Unknown       99   \n",
       "4  Not Applicable (Not Transported)       88   \n",
       "\n",
       "                         hosp_mnname  fatals  drunk_dr  \n",
       "0  Unknown EMS Hospital Arrival Time       3         1  \n",
       "1  Unknown EMS Hospital Arrival Time       1         0  \n",
       "2  Unknown EMS Hospital Arrival Time       1         0  \n",
       "3  Unknown EMS Hospital Arrival Time       1         0  \n",
       "4   Not Applicable (Not Transported)       1         0  \n",
       "\n",
       "[5 rows x 80 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_accident.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "32d7932e-296c-4985-afd1-7d43288e7595",
   "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>county</th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>73</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>117</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35761</th>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35762</th>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35763</th>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35764</th>\n",
       "      <td>21</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35765</th>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35766 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       county  city\n",
       "0          51     0\n",
       "1          73   350\n",
       "2         117     0\n",
       "3          15     0\n",
       "4          37     0\n",
       "...       ...   ...\n",
       "35761      21     0\n",
       "35762      23     0\n",
       "35763      13     0\n",
       "35764      21   100\n",
       "35765      31     0\n",
       "\n",
       "[35766 rows x 2 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_accident[['county', 'city']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c6bf6195-34ba-4a13-87bf-5f269668b4b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['drunk_dr', 've_total', 'persons']\n",
    "X = df_accident[features]\n",
    "\n",
    "y = df_accident['fatals']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4163b404-bddb-41af-b59a-e9e186ddc985",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a8ce1ae3-3fcb-4e24-b782-46f6976134ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = LinearRegression()\n",
    "lr.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "604557f6-ca29-4488-9f54-dd672d6a316f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.09476415384790493"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train score\n",
    "lr.score(X_train,y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31b1daff-c62d-41e7-ac71-8a923eb2c826",
   "metadata": {},
   "source": [
    "# Now for the real data cleaning "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0ff15485-d489-4510-aaa1-7abd890be62e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_accident_new = df_accident.drop(columns = ['arr_hourname', 'arr_minname',] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c32ea39f-12de-465f-a429-6fd10c711af6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3bdcaa5c-5dc3-46bf-be6c-b04f00f2367d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "790b369b-37df-4bea-9ab3-662a95140706",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "940ebd3d-5dd5-48f0-a3e9-c4ceb203dbe1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aac5e2be-a8fa-4a57-b8c1-738eb7547dcb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "163e0c00-79d7-48f5-a7f1-c7a2561e991d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "560cce52-339c-488d-b0e8-ce9f0773492a",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n"
   ]
  }
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