07_Accidents By Road Class and Road Type.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4872e34c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies\n",
    "#import gmaps\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt\n",
    "from scipy.stats import pearsonr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c91ef20",
   "metadata": {},
   "source": [
    "Import dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "74892b93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Unnamed: 0', 'Accident_Index', '1st_Road_Class', 'Accident_Severity',\n",
      "       'Year', 'Date', 'Day_of_Week', 'Latitude', 'Light_Conditions',\n",
      "       'Local_Authority_(District)', 'Longitude', 'Number_of_Casualties',\n",
      "       'Number_of_Vehicles', 'Road_Surface_Conditions', 'Road_Type',\n",
      "       'Special_Conditions_at_Site', 'Speed_limit', 'Time',\n",
      "       'Urban_or_Rural_Area', 'Weather_Conditions', 'Age_Band_of_Driver',\n",
      "       'Age_of_Vehicle', 'Engine_Capacity_.CC.', 'Journey_Purpose_of_Driver',\n",
      "       'Junction_Location', 'make', 'model', 'Propulsion_Code',\n",
      "       'Sex_of_Driver', 'Towing_and_Articulation', 'Vehicle_Manoeuvre',\n",
      "       'Vehicle_Type', 'Was_Vehicle_Left_Hand_Drive'],\n",
      "      dtype='object')\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>Unnamed: 0</th>\n",
       "      <th>Accident_Index</th>\n",
       "      <th>1st_Road_Class</th>\n",
       "      <th>Accident_Severity</th>\n",
       "      <th>Year</th>\n",
       "      <th>Date</th>\n",
       "      <th>Day_of_Week</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Light_Conditions</th>\n",
       "      <th>Local_Authority_(District)</th>\n",
       "      <th>...</th>\n",
       "      <th>Journey_Purpose_of_Driver</th>\n",
       "      <th>Junction_Location</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>Propulsion_Code</th>\n",
       "      <th>Sex_of_Driver</th>\n",
       "      <th>Towing_and_Articulation</th>\n",
       "      <th>Vehicle_Manoeuvre</th>\n",
       "      <th>Vehicle_Type</th>\n",
       "      <th>Was_Vehicle_Left_Hand_Drive</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>478587</td>\n",
       "      <td>201001BS70003</td>\n",
       "      <td>B</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2010</td>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>Monday</td>\n",
       "      <td>51.484087</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>Kensington and Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>Commuting to/from work</td>\n",
       "      <td>Mid Junction - on roundabout or on main road</td>\n",
       "      <td>CITROEN</td>\n",
       "      <td>BERLINGO FIRST 600</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Female</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Turning right</td>\n",
       "      <td>Van / Goods 3.5 tonnes mgw or under</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>478588</td>\n",
       "      <td>201001BS70004</td>\n",
       "      <td>A</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2010</td>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>Monday</td>\n",
       "      <td>51.509212</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Kensington and Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>Journey as part of work</td>\n",
       "      <td>Mid Junction - on roundabout or on main road</td>\n",
       "      <td>RENAULT</td>\n",
       "      <td>SCENIC DYN DCI 130</td>\n",
       "      <td>Heavy oil</td>\n",
       "      <td>Male</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead other</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>478589</td>\n",
       "      <td>201001BS70007</td>\n",
       "      <td>Unclassified</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2010</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>51.513314</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Kensington and Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>Other/Not known (2005-10)</td>\n",
       "      <td>Mid Junction - on roundabout or on main road</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>PRIMERA SVE CVT</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Female</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead right-hand bend</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>478590</td>\n",
       "      <td>201001BS70007</td>\n",
       "      <td>Unclassified</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2010</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>51.513314</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Kensington and Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>Other/Not known (2005-10)</td>\n",
       "      <td>Mid Junction - on roundabout or on main road</td>\n",
       "      <td>MERCEDES</td>\n",
       "      <td>A140 ELEGANCE</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Female</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead other</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>478591</td>\n",
       "      <td>201001BS70008</td>\n",
       "      <td>A</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2010</td>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>Monday</td>\n",
       "      <td>51.484361</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Kensington and Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>Journey as part of work</td>\n",
       "      <td>Mid Junction - on roundabout or on main road</td>\n",
       "      <td>VAUXHALL</td>\n",
       "      <td>ZAFIRA ELEGANCE DTI</td>\n",
       "      <td>Heavy oil</td>\n",
       "      <td>Male</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Turning right</td>\n",
       "      <td>Taxi/Private hire car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1077648</th>\n",
       "      <td>1556235</td>\n",
       "      <td>2016984130916</td>\n",
       "      <td>B</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-10-28</td>\n",
       "      <td>Friday</td>\n",
       "      <td>55.058998</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Dumfries and Galloway</td>\n",
       "      <td>...</td>\n",
       "      <td>Commuting to/from work</td>\n",
       "      <td>Cleared junction or waiting/parked at junction...</td>\n",
       "      <td>SEAT</td>\n",
       "      <td>IBIZA ECOMOTIVE TDI</td>\n",
       "      <td>Heavy oil</td>\n",
       "      <td>Female</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead other</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1077649</th>\n",
       "      <td>1556236</td>\n",
       "      <td>2016984130916</td>\n",
       "      <td>B</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-10-28</td>\n",
       "      <td>Friday</td>\n",
       "      <td>55.058998</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Dumfries and Galloway</td>\n",
       "      <td>...</td>\n",
       "      <td>Data missing or out of range</td>\n",
       "      <td>Cleared junction or waiting/parked at junction...</td>\n",
       "      <td>RENAULT</td>\n",
       "      <td>MEGANE DYNAMIQUE 16V</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Not known</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Parked</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1077650</th>\n",
       "      <td>1556237</td>\n",
       "      <td>2016984131116</td>\n",
       "      <td>B</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-11-01</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>55.005033</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>Dumfries and Galloway</td>\n",
       "      <td>...</td>\n",
       "      <td>Not known</td>\n",
       "      <td>Mid Junction - on roundabout or on main road</td>\n",
       "      <td>MINI</td>\n",
       "      <td>MINI COOPER</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Female</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead other</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1077651</th>\n",
       "      <td>1556238</td>\n",
       "      <td>2016984131316</td>\n",
       "      <td>B</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-10-29</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>54.989597</td>\n",
       "      <td>Darkness - lights lit</td>\n",
       "      <td>Dumfries and Galloway</td>\n",
       "      <td>...</td>\n",
       "      <td>Not known</td>\n",
       "      <td>Not at or within 20 metres of junction</td>\n",
       "      <td>VAUXHALL</td>\n",
       "      <td>VECTRA SXI 16V</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Male</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead other</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1077652</th>\n",
       "      <td>1556239</td>\n",
       "      <td>2016984133416</td>\n",
       "      <td>A(M)</td>\n",
       "      <td>Slight</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-12-25</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>55.310151</td>\n",
       "      <td>Daylight</td>\n",
       "      <td>Dumfries and Galloway</td>\n",
       "      <td>...</td>\n",
       "      <td>Not known</td>\n",
       "      <td>Not at or within 20 metres of junction</td>\n",
       "      <td>MAZDA</td>\n",
       "      <td>CX-7 SPORT TECH D</td>\n",
       "      <td>Heavy oil</td>\n",
       "      <td>Male</td>\n",
       "      <td>No tow/articulation</td>\n",
       "      <td>Going ahead other</td>\n",
       "      <td>Car</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1077653 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0 Accident_Index 1st_Road_Class Accident_Severity  Year  \\\n",
       "0            478587  201001BS70003              B            Slight  2010   \n",
       "1            478588  201001BS70004              A            Slight  2010   \n",
       "2            478589  201001BS70007   Unclassified            Slight  2010   \n",
       "3            478590  201001BS70007   Unclassified            Slight  2010   \n",
       "4            478591  201001BS70008              A            Slight  2010   \n",
       "...             ...            ...            ...               ...   ...   \n",
       "1077648     1556235  2016984130916              B            Slight  2016   \n",
       "1077649     1556236  2016984130916              B            Slight  2016   \n",
       "1077650     1556237  2016984131116              B            Slight  2016   \n",
       "1077651     1556238  2016984131316              B            Slight  2016   \n",
       "1077652     1556239  2016984133416           A(M)            Slight  2016   \n",
       "\n",
       "               Date Day_of_Week   Latitude       Light_Conditions  \\\n",
       "0        2010-01-11      Monday  51.484087               Daylight   \n",
       "1        2010-01-11      Monday  51.509212  Darkness - lights lit   \n",
       "2        2010-01-02    Saturday  51.513314  Darkness - lights lit   \n",
       "3        2010-01-02    Saturday  51.513314  Darkness - lights lit   \n",
       "4        2010-01-04      Monday  51.484361  Darkness - lights lit   \n",
       "...             ...         ...        ...                    ...   \n",
       "1077648  2016-10-28      Friday  55.058998  Darkness - lights lit   \n",
       "1077649  2016-10-28      Friday  55.058998  Darkness - lights lit   \n",
       "1077650  2016-11-01     Tuesday  55.005033               Daylight   \n",
       "1077651  2016-10-29    Saturday  54.989597  Darkness - lights lit   \n",
       "1077652  2016-12-25      Sunday  55.310151               Daylight   \n",
       "\n",
       "        Local_Authority_(District)  ...     Journey_Purpose_of_Driver  \\\n",
       "0           Kensington and Chelsea  ...        Commuting to/from work   \n",
       "1           Kensington and Chelsea  ...       Journey as part of work   \n",
       "2           Kensington and Chelsea  ...     Other/Not known (2005-10)   \n",
       "3           Kensington and Chelsea  ...     Other/Not known (2005-10)   \n",
       "4           Kensington and Chelsea  ...       Journey as part of work   \n",
       "...                            ...  ...                           ...   \n",
       "1077648      Dumfries and Galloway  ...        Commuting to/from work   \n",
       "1077649      Dumfries and Galloway  ...  Data missing or out of range   \n",
       "1077650      Dumfries and Galloway  ...                     Not known   \n",
       "1077651      Dumfries and Galloway  ...                     Not known   \n",
       "1077652      Dumfries and Galloway  ...                     Not known   \n",
       "\n",
       "                                         Junction_Location      make  \\\n",
       "0             Mid Junction - on roundabout or on main road   CITROEN   \n",
       "1             Mid Junction - on roundabout or on main road   RENAULT   \n",
       "2             Mid Junction - on roundabout or on main road    NISSAN   \n",
       "3             Mid Junction - on roundabout or on main road  MERCEDES   \n",
       "4             Mid Junction - on roundabout or on main road  VAUXHALL   \n",
       "...                                                    ...       ...   \n",
       "1077648  Cleared junction or waiting/parked at junction...      SEAT   \n",
       "1077649  Cleared junction or waiting/parked at junction...   RENAULT   \n",
       "1077650       Mid Junction - on roundabout or on main road      MINI   \n",
       "1077651             Not at or within 20 metres of junction  VAUXHALL   \n",
       "1077652             Not at or within 20 metres of junction     MAZDA   \n",
       "\n",
       "                        model Propulsion_Code Sex_of_Driver  \\\n",
       "0          BERLINGO FIRST 600          Petrol        Female   \n",
       "1          SCENIC DYN DCI 130       Heavy oil          Male   \n",
       "2             PRIMERA SVE CVT          Petrol        Female   \n",
       "3               A140 ELEGANCE          Petrol        Female   \n",
       "4         ZAFIRA ELEGANCE DTI       Heavy oil          Male   \n",
       "...                       ...             ...           ...   \n",
       "1077648   IBIZA ECOMOTIVE TDI       Heavy oil        Female   \n",
       "1077649  MEGANE DYNAMIQUE 16V          Petrol     Not known   \n",
       "1077650           MINI COOPER          Petrol        Female   \n",
       "1077651        VECTRA SXI 16V          Petrol          Male   \n",
       "1077652     CX-7 SPORT TECH D       Heavy oil          Male   \n",
       "\n",
       "         Towing_and_Articulation            Vehicle_Manoeuvre  \\\n",
       "0            No tow/articulation                Turning right   \n",
       "1            No tow/articulation            Going ahead other   \n",
       "2            No tow/articulation  Going ahead right-hand bend   \n",
       "3            No tow/articulation            Going ahead other   \n",
       "4            No tow/articulation                Turning right   \n",
       "...                          ...                          ...   \n",
       "1077648      No tow/articulation            Going ahead other   \n",
       "1077649      No tow/articulation                       Parked   \n",
       "1077650      No tow/articulation            Going ahead other   \n",
       "1077651      No tow/articulation            Going ahead other   \n",
       "1077652      No tow/articulation            Going ahead other   \n",
       "\n",
       "                                Vehicle_Type Was_Vehicle_Left_Hand_Drive  \n",
       "0        Van / Goods 3.5 tonnes mgw or under                          No  \n",
       "1                                        Car                          No  \n",
       "2                                        Car                          No  \n",
       "3                                        Car                          No  \n",
       "4                      Taxi/Private hire car                          No  \n",
       "...                                      ...                         ...  \n",
       "1077648                                  Car                          No  \n",
       "1077649                                  Car                          No  \n",
       "1077650                                  Car                          No  \n",
       "1077651                                  Car                          No  \n",
       "1077652                                  Car                          No  \n",
       "\n",
       "[1077653 rows x 33 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read main CSV data file\n",
    "accidents_df = pd.read_csv(\"Resources/all.csv\", low_memory=False)\n",
    "\n",
    "# Print the columns list to see available columns\n",
    "print(accidents_df.columns)\n",
    "\n",
    "# Get an overview of the DataFrame\n",
    "accidents_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36d4b35c",
   "metadata": {},
   "source": [
    "I have imported the cleaned data from the CSV file where it was stored and got a list of the columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "28b1dffd",
   "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": [
    "class_group = accidents_df.groupby([\"1st_Road_Class\",\"Accident_Severity\"])\n",
    "\n",
    "class_group_count = class_group[\"Accident_Severity\"].count().unstack()\n",
    "\n",
    "class_group_count = class_group_count.sort_values(by=[\"Fatal\",\"Serious\",\"Slight\"], ascending=False)\n",
    "\n",
    "class_group_count = class_group_count[[\"Slight\",\"Serious\",\"Fatal\"]]\n",
    "\n",
    "class_group_count.plot.bar(stacked=True, color={\"Fatal\": \"red\", \"Serious\": \"orange\", \"Slight\":\"green\"})\n",
    "\n",
    "plt.title(\"Number of Accidents for Road Class by Accident Severity\")\n",
    "plt.ylabel(\"Number of Accidents\")\n",
    "plt.xlabel(\"Road Class\")\n",
    "plt.savefig(\"Images/No_Accidents_for_Road_Class.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cd7ad20",
   "metadata": {},
   "source": [
    "Plot appears to indicate the overwhelming majority of accidents take place on A Roads and have a severity rating of slight. The A road also have the most number Fatal accidents. This appears to be an indication that travelling on A roads puts you at the greatest chance of being involved in accident.\n",
    "\n",
    "HOWEVER, we collectively decided that we had no way to understand which roads in the UK are \"A Road\", \"B Road\", or \"C Road\" and therefore unable to understand this. It could be that the overwhelming majority of Road in the UK are A roads.\n",
    "\n",
    "As we were unable to understand this in the context we desired, we discard this plot from the report."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "89abc146",
   "metadata": {},
   "outputs": [
    {
     "data": {
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Fqvk9tiUOHGhmKyQtIgybvi1xpNcs+3xULX2fuE9N53DO1UOzZs2iadOmtGnTBq2avsKViJkxb948Zs2aRdu2bdd4/2JWnTUnlEbaEkYU3Zg6NsyEpIGSKiVVzp07N+1wnHM1+Prrr2nRooVnMimRRIsWLda6RFnMzgA/JEwUNDcOCf4wYZ77zbRq1rlWrJpIajZxgqS4flPCMPJV6dX2qSl9Xo5zrMbMhphZFzPr0rJlzm7gzrmUeSaTrnV5/YuZ0fwP6Cbpe7GtpSdhLoXngGPjNgMIc1VAmL0vMy3rscCzcXa/McAJsVdaW8IcGROA14F2sYfZhoQOA2PiPjWdwznnXIkVLaOJE/GMJkyL/FY81xDgV8AvYqN+C+CuuMtdQIuY/gvgsnicKYSZ76YSJoM618xWxjaYnxMmiXqHMG91ZgrWms5ReFJpH865Kv/617+QxLvvvrvG+1ZWVnL++ednXdemTRs+//zzrOvyiWnq1Kk5t3n11VfZZ599qKioYLfdduOqq65aq3Pl6+OPP+bYY8Nv70mTJvH4448X9XzfYWb+MKNz5862VqC0D+fWQ1OnTs2afvzxx1v37t3tyiuvLOj5tt9+e5s7d+5a7TtgwAB78MEHc26z884726RJk8zMbMWKFTZlypS1Olc+li9fvtry3Xffbeeee+5aHSvb+wBUWi3frz4ygHOuXlqyZAkvvvgid911Fw888AAAK1eu5JJLLmGPPfagQ4cO3HLLLQC8/vrr/OAHP6Bjx4507dqVxYsXM27cOI488kgA5s2bR69evWjfvj1nnnkmlpg+5R//+Addu3aloqKCn/70p6xcuRKATTbZhN/85jd07NiRbt268emnn/Lyyy8zZswYLr30UioqKnj//fezxv7ZZ5+x9dZhJuYGDRqw++7hFsClS5dy+umn07VrV/baay8eeSTU+nfr1o0pU6ZU7d+jRw8qKytr3P6ee+6hT58+HHzwwfTs2ZMZM2awxx57sGzZMq688kpGjhxJRUUFI0eOpF27dmQ6Q3377bfstNNOFLpzlI91tq5GpB2Ac+unRx55hN69e7PzzjvTokULJk6cyIQJE5gxYwaTJk2iYcOGzJ8/n2XLltGvXz9GjhzJ3nvvzRdffEGTJk1WO9bgwYPp3r07V155Jf/+97+5665Q2/7OO+8wcuRIXnrpJRo1asQ555zDiBEj6N+/P0uXLqVbt25cd911/PKXv+Rvf/sbv/3tb+nTpw9HHnlkVVVVNhdddBG77LILPXr0oHfv3gwYMIDGjRtz3XXXcfDBBzN06FAWLlxI165d+eEPf0i/fv0YNWoUgwcPZs6cOcyZM4cuXbpw+eWXZ90e4I033mDy5MlsvvnmzJgxA4ANN9yQq6++msrKSm699VYA3n33XUaMGMGFF17IM888Q8eOHSl05ygv0Tjn6qX777+fE044AYATTjiB+++/n2eeeYaf/vSnNGwYfkNvvvnmvPfee2y99dbsvffeADRr1qxqfcYLL7zAKaecAsARRxxB8+bNARg7diwTJ05k7733pqKigrFjx/LBBx8A4Us7UyLq3Llz1Zd5Pq688koqKyvp1asX9913H717hzs/nnrqKW644QYqKiro0aMHX3/9Nf/73/84/vjjGT16NACjRo2qysRq2h7gkEMOYfPNN681ltNPP53hw4cDMHToUE477bS8ryNfXqJxztU78+fP59lnn+Wtt95CEitXrkRSVWZSKGbGgAEDuP7667+zrlGjRlVdfhs0aMCKFSu+s00uO+64Iz/72c8466yzaNmyJfPmzcPMeOihh9hll12+s32LFi2YPHkyI0eO5I477qiKL9v2r732GhtvvHFecWy33XZsueWWPPvss0yYMIERIwpfTeMlGudcvTN69GhOPfVUZs6cyYwZM/joo49o27YtHTt25M4776z60p8/fz677LILc+bM4fXXXwdg8eLF38kUDjjgAO677z4AnnjiCRYsWABAz549GT16NJ999lnV8WbOzD0qftOmTVm8eHHObf79739XtQNNmzaNBg0asNlmm3HooYdyyy23VK178803q/bp168fv//971m0aBEdOnQAyLn9msR35plncsopp3DcccfRoEGDWo+xpjyjcc7VO/fffz9HHXXUamnHHHMMc+bMoXXr1nTo0IGOHTty3333seGGGzJy5EjOO+88OnbsyCGHHPKdO9wHDRrECy+8QPv27Xn44Ydp3bo1ALvvvjvXXnstvXr1okOHDhxyyCHMmTMnZ2wnnHACf/jDH9hrr71q7Axw7733sssuu1BRUcGpp57KiBEjaNCgAVdccQXLly+nQ4cOtG/fniuuuKJqn2OPPZYHHniA448/viot1/Y1Oeigg5g6dWpVZwCAPn36sGTJkqJUmwEo2btifdalSxdbq4nP7ivxvS0n+fvl1j/vvPMOu+22W9phlK3Kykouuugixo8fn3O7bO+DpIlm1iXXft5G45xz67EbbriB22+/vShtMxledeacc0Vy7rnnUlFRsdrj7rvvTjus1Vx22WXMnDmT7t27F+0cXqJxzrki+etf/5p2CHWCl2icc84VlWc0zjnnisozGuecc0XlGY1zzhXJddddR/v27enQoQMVFRW89tprVQNiAhx++OEsXLgw5zGS2yelMtz/WvLOAM65sqfBhb3fzQbVfj/bK6+8wmOPPcYbb7zBRhttxOeff86yZctW22ZdMopJkyZRWVnJ4YcfvtbHKBUv0TjnXBHMmTOHLbbYgo022giALbbYgm222Wa1bZITrF1zzTXssssudO/enRNPPJE//vGPVds9+OCDdO3alZ133pnx48dnHe6/LvOMxjnniqBXr1589NFH7Lzzzpxzzjk8//zzNW77+uuv89BDD/Hf//6XJ5544jtVZStWrGDChAn85S9/YfDgwVXD/ffr149JkybRr1+/Yl/OOvGMxjnnimCTTTZh4sSJDBkyhJYtW9KvXz/uueeerNu+9NJL9O3bl8aNG9O0aVN+9KMfrbb+6KOPBtZ8OoK6omgZjaRdJE1KPL6QdKGkzSU9LWla/Ns8bi9JN0uaLmmypE6JYw2I20+TNCCR3lnSW3GfmxXH7K7pHM45V0oNGjSgR48eDB48mFtvvZWHHnporY6TqX5bm+kI6oKiZTRm9p6ZVZhZBdAZ+BL4J3AZMNbM2gFj4zLAYUC7+BgI3A4h0wAGAfsAXYFBiYzjduCsxH69Y3pN53DOuZJ47733mDZtWtXypEmT2H777bNuu99++/Hoo4/y9ddfs2TJEh577LFaj5/PdAR1RamqznoC75vZTKAvMCymDwN+HJ/3BYZb8CqwmaStgUOBp81svpktAJ4Gesd1zczsVQtDUA+vdqxs53DOuZJYsmQJAwYMYPfdd6dDhw5MnTqVq666Kuu2e++9N3369KFDhw4cdthh7Lnnnmy66aY5j59tuP+6qlTdm08A7o/PtzSzzIQOnwBbxufbAh8l9pkV03Klz8qSnuscq5E0kFB6qpp/wjlXfvLpjlxonTt35uWXX/5O+rhx46qeJ9tbLrnkEq666iq+/PJLDjjgADp37vyd7bfYYouqfTbffPOqydzquqKXaCRtCPQBHqy+LpZEivoJyHUOMxtiZl3MrEvLli2LGYZzzuU0cOBAKioq6NSpE8cccwydOnWqfad6ohQlmsOAN8zs07j8qaStzWxOrP76LKbPBrZL7Ncqps0GelRLHxfTW2XZPtc5nHOuTspMJV2OStFGcyKrqs0AxgCZnmMDgEcS6f1j77NuwKJY/fUk0EtS89gJoBfwZFz3haRusbdZ/2rHynYO55xzJVbUEo2kjYFDgJ8mkm8ARkk6A5gJZCbAfhw4HJhO6KF2GoCZzZd0DZCpjLzazObH5+cA9wBNgCfiI9c5nHPOlVhRMxozWwq0qJY2j9ALrfq2Bpxbw3GGAkOzpFcCe2RJz3oO55xzpecjAzjnnCsqz2icc65Isk0TkK877riD4cOHFzG60vFpAtaRptW+TSGV/m4A58rAfYWdJoCTCjNNQE1WrFjB2Wefva5R1hleonHOuSKoaZqAiRMncuCBB9K5c2cOPfRQ5swJ95b36NGDCy+8kC5dunDTTTdx1VVXVU0VMGnSJLp160aHDh046qijWLBgQdU+mZGeP//8c9q0aQPAlClT6Nq1KxUVFXTo0GG1oXDS4BmNc84VQbZpApYvX855553H6NGjmThxIqeffjq/+c1vqvZZtmwZlZWVXHzxxasdq3///vzud79j8uTJ7LnnngwePDjnue+44w4uuOCCqsnRWrVqlXP7YvOqM+ecK4LMNAHjx4/nueeeo1+/fvz2t7/l7bff5pBDDgFg5cqVbL311lX7ZJtXZtGiRSxcuJADDzwQgAEDBnDcccflPPe+++7Lddddx6xZszj66KNp165dAa9szXlG45xzRZKZJqBHjx7sueee/PWvf6V9+/a88sorWbffeOON1+j4DRs25NtvvwXg66+/rko/6aST2Gefffj3v//N4Ycfzp133snBBx+89heyjrzqzDnniiDbNAG77bYbc+fOrcpoli9fzpQpU3IeZ9NNN6V58+aMHz8egHvvvbeqdNOmTRsmTpwIwOjRo6v2+eCDD9hhhx04//zz6du3L5MnTy7ota0pL9E451wRLFmyhPPOO4+FCxfSsGFDdtppJ4YMGcLAgQM5//zzWbRoEStWrODCCy+kffv2OY81bNgwzj77bL788kt22GEH7r77biCM+Hz88cczZMgQjjjiiKrtR40axb333kujRo3YaqutuPzyy4t6rbVRuCHfdenSxarP050PDS5wt8lapDHcuXNpe+edd9htt93SDmO9l+19kDTRzLrk2s+rzpxzzhWVZzTOOeeKyjMa55xzReUZjXPOuaLyjMY551xReUbjnHOuqDyjcc65ImjQoAEVFRVVjxkzZmTdbuHChdx22215HXOTTTYpYISlU9SMRtJmkkZLelfSO5L2lbS5pKclTYt/m8dtJelmSdMlTZbUKXGcAXH7aZIGJNI7S3or7nOzJMX0rOdwzq2npMI+8tCkSRMmTZpU9ciMrFzdmmQ09VWxSzQ3Af8xs12BjsA7wGXAWDNrB4yNywCHAe3iYyBwO4RMAxgE7AN0BQYlMo7bgbMS+/WO6TWdwznnUrFkyRJ69uxJp06d2HPPPXnkkUcAuOyyy3j//fepqKjg0ksvrXG7+qzWIWgk/R64FvgK+A/QAbjIzP5Ry36bAgcAPwEws2XAMkl9gR5xs2HAOOBXQF9guIWhCl6NpaGt47ZPm9n8eNyngd6SxgHNzOzVmD4c+DHwRDxWtnM451xJfPXVV1RUVADQtm1bHnzwQf75z3/SrFkzPv/8c7p160afPn244YYbePvtt5k0aRIQJj3Ltp3yLEnVRfmMddbLzH4p6ShgBnA08AKQM6MB2gJzgbsldQQmAhcAW5rZnLjNJ8CW8fm2wEeJ/WfFtFzps7Kkk+MczjlXEpmqs4zly5dz+eWX88ILL7DBBhswe/ZsPv300+/sZ2ZZt9tqq61KGH1h5ZPRNIp/jwAeNLNFeeasDYFOwHlm9pqkm6hWhWVmJqmog3flOoekgYRqOlq3bl3MMJxz67kRI0Ywd+5cJk6cSKNGjWjTps1qQ/uv6Xb1ST5tNI9KehfoDIyV1BLI56pnAbPM7LW4PJqQ8Xwaq8SIfz+L62cD2yX2bxXTcqW3ypJOjnOsxsyGmFkXM+vSsmXLPC7JOefWzqJFi/j+979Po0aNeO6555g5cyYATZs2ZfHixbVuV5/lk9EMAn4AdDGz5cCXQJ/adjKzT4CPJO0Sk3oCU4ExQKbn2AAg09I1Bugfe591AxbF6q8ngV6SmsdOAL2AJ+O6LyR1i73N+lc7VrZzOOdcKk4++WQqKyvZc889GT58OLvuuisALVq0YL/99mOPPfbg0ksvrXG7+iyfqrNXzKyqq7GZLZU0nlA6qc15wAhJGwIfAKcRMrdRks4AZgLHx20fBw4HphMys9Pi+eZLugZ4PW53daZjAHAOcA/QhNAJ4ImYfkMN53DOrY9SmA5lyZIlqy1vscUWNc6sed999622XNN21Y9ZX9SY0UjaitC43kTSXkCmYaYZ8L18Dm5mk4Bs8xT0zLKtAefWcJyhwNAs6ZXAHlnS52U7h3POudLLVaI5lNA1uRXw50T6YiDd6dqcc87VGzVmNGY2DBgm6Rgze6iEMTnnnCsj+bTRPCbpJKBNcnszu7pYQTnnXHVmVq9vWqzvbB3aufLpdfYI4U77FcDSxMM550qicePGzJs3b52+7NzaMzPmzZtH48aN12r/fEo0rcysd+2bOedccbRq1YpZs2Yxd+7ctENZbzVu3JhWrVrVvmEW+WQ0L0va08zeWqszOOfcOmrUqBFt27ZNOwy3lvLJaLoDP5H0IfANoZuzmVmHokbmnHOuLOST0RxW9Cicc86VrVo7A5jZTMJYYwfH51/ms59zzjkHeWQYkgYR5nL5dUxqRO1TBDjnnHNAfiWTowiDaC4FMLOPgabFDMo551z5yCejWRbHITMASRsXNyTnnHPlJJ+MZpSkO4HNJJ0FPAP8rbhhOeecKxe19jozsz9KOgT4AtgFuNLMni56ZM4558pCPt2biRmLZy7OOefWWK75aBYT22WyMbNmRYnIOedcWck1TUBTgDi75RzgXsKoACcDW5ckOuecc/VePp0B+pjZbWa22My+MLPbCaM510rSDElvSZokqTKmbS7paUnT4t/mMV2SbpY0XdJkSZ0SxxkQt58maUAivXM8/vS4r3KdwznnXOnlk9EslXSypAaSNpB0Mms2TcBBZlZhZpkpnS8DxppZO2BsXIYw1E27+BgI3A4h0wAGAfsAXYFBiYzjduCsxH69azmHc865EssnozkJOB74ND6Oi2lrqy8wLD4fBvw4kT7cglcJ3am3Jkwp/bSZzTezBYROCb3jumZm9mq8z2d4tWNlO4dzzrkSy6d78wzyrCrLtjvwlCQD7jSzIcCWZjYnrv8E2DI+3xb4KLHvrJiWK31WlnRynMM551yJ5ep19ksz+72kW8jS+8zMzs/j+N3NbLak7wNPS3q32jEsZkJFk+sckgYSqulo3bp1McNwzrn1Vq4SzTvxb+XaHtzMZse/n0n6J6GN5VNJW5vZnFj99VncfDZhlOiMVjFtNtCjWvq4mN4qy/bkOEf1+IYAQwC6dOnic8Q651wR1NhGY2aPxr/Dsj1qO7CkjSVlukhvDPQC3gbGAJmeYwOAR+LzMUD/2PusG7AoVn89CfSS1Dx2AugFPBnXfSGpW+xt1r/asbKdwznnXInV2kYj6WngODNbGJebAw+Y2aG17Lol8M/Y47ghcJ+Z/UfS64Tx084AZhI6GgA8DhwOTCfMeXMagJnNj/fyvB63u9rM5sfn5wD3AE2AJ+ID4IYazuGcc67E8hmCpmUmkwEwswWxzSUnM/sA6JglfR7QM0u6AefWcKyhwNAs6ZXAHvmewznnXOnl0715paSqlnJJ25NjaBrnnHMuKZ8SzW+AFyU9TxiCZn9iTy3nnHOuNvncR/OfOBxMt5h0oZl9XtywnHPOlYtaq84kHQUsN7PHzOwxYIWkHxc9Muecc2UhnzaaQWa2KLMQOwYMKlpEzjnnyko+GU22bfKaMM0555zLJ6OplPRnSTvGx43AxGIH5pxzrjzkk9GcBywDRsbHV4QbJZ1zzrla5dPrbCmJ+VziPTXnAn8oYlzOOefKRD4lGiS1lHSOpPHAc/iw+8455/KUa5qApsDRhEnOdgYeBtqaWaua9nHOOeeqy1V19hkwAfgt8GKc1+Wo0oTlnHOuXOSqOvs1sBFwG/BrSTuWJiTnnHPlJNd8NH8xs26smsb5X8A2kn4laedSBOecc67+q7UzgJl9YGb/Z2Z7Al2AZoS5Y5xzzrla5dXrLMPM3jaz35jZTsUKyDnnXHlZo4zGOeecW1Oe0TjnnCuqGjMaSWPj39+tywkkNZD0pqTH4nJbSa9Jmi5ppKQNY/pGcXl6XN8mcYxfx/T3JB2aSO8d06ZLSo5ekPUczjnnSi9XiWZrST8A+kjaS1Kn5GMNznEB8E5i+XfAjbGdZwFwRkw/A1gQ02+M2yFpd+AEoD3QG7gtZl4NgL8ChwG7AyfGbXOdwznnXInlymiuBK4AWgF/Bv6UePwxn4NLagUcAfw9Lgs4GBgdNxkG/Dg+7xuXiet7xu37Ag+Y2Tdm9iEwHegaH9Njr7hlwANA31rO4ZxzrsRqHBnAzEYDoyVdYWbXrOXx/wL8Emgal1sAC81sRVyeBWwbn28LfBTPvULSorj9tsCriWMm9/moWvo+tZxjNZIGAgMBWrduveZX55xzrlb53EdzjaQ+kv4YH0fmc+C43WdmVmfnrjGzIWbWxcy6tGzZMu1wnHOuLNU6TYCk6wnVVCNi0gWSfmBml9ey636E9p3DgcaEGz1vAjaT1DCWOFoBs+P2s4HtgFmSGgKbAvMS6RnJfbKlz8txDueccyWWT/fmI4BDzGyomQ0lNMjXWqoxs1+bWSsza0NozH/WzE4mTDNwbNxsAPBIfD4mLhPXP2tmFtNPiL3S2gLtCIN9vg60iz3MNoznGBP3qekczjnnSizf+2g2SzzfdB3P+SvgF5KmE9pT7orpdwEtYvoviJOtmdkUYBQwFfgPcK6ZrYyllZ8DTxJ6tY2K2+Y6h3POuRKrteoMuB54U9JzgIADSMy4mQ8zGweMi88/IFTFVd/ma+C4Gva/DrguS/rjZBl3raZzOOecK718pnK+X9I4YO+Y9Csz+6SoUTnnnCsb+ZRoMLM5hLYS55xzbo34WGfOOeeKyjMa55xzRZUzo4ljir1bqmCcc86Vn5wZjZmtBN6T5OOzOOecWyv5dAZoDkyRNAFYmkk0sz5Fi8o551zZyCejuaLoUTjnnCtb+dxH87yk7YF2ZvaMpO8BDYofmnPOuXJQa68zSWcR5na5MyZtC/yriDE555wrI/l0bz6XMBLzFwBmNg34fjGDcs45Vz7yyWi+iTNYAhCH8LfiheScc66c5JPRPC/pcqCJpEOAB4FHixuWc865cpFPRnMZMBd4C/gpYbTk3xYzKOecc+Ujn15n30oaBrxGqDJ7L04u5pxzztUqn6mcjwDuAN4nzEfTVtJPzeyJYgfnnHOu/svnhs0/AQeZ2XQASTsC/wY8o3HOOVerfNpoFmcymegDYHFtO0lqLGmCpP9KmiJpcExvK+k1SdMljZS0YUzfKC5Pj+vbJI7165j+nqRDE+m9Y9p0SZcl0rOewznnXOnVmNFIOlrS0UClpMcl/UTSAEKPs9fzOPY3wMFm1hGoAHpL6gb8DrjRzHYCFgBnxO3PABbE9BvjdkjaHTgBaA/0Bm6Lo0o3AP4KHAbsDpwYtyXHOZxzzpVYrhLNj+KjMfApcCDQg9ADrUltB7ZgSVxsFB8GHEwYaQBgGPDj+LxvXCau7ylJMf0BM/vGzD4EpgNd42O6mX0Q7/N5AOgb96npHM4550qsxjYaMzttXQ8eSx0TgZ0IpY/3gYVmtiJuMoswpA3x70fx3CskLQJaxPRXE4dN7vNRtfR94j41ncM551yJ5dPrrC1wHtAmuX0+0wTE+WwqJG0G/BPYdW0DLQZJA4GBAK1b+5Q7zjlXDPn0OvsXcBehbebbtTmJmS2U9BywL7CZpIaxxNEKmB03mw1sB8yKw9xsCsxLpGck98mWPi/HOarHNQQYAtClSxe/N8g554ogn15nX5vZzWb2nJk9n3nUtpOklrEkg6QmwCHAO8BzwLFxswHAI/H5mLhMXP9svDF0DHBC7JXWFmgHTCB0SGgXe5htSOgwMCbuU9M5nHPOlVg+JZqbJA0CniL0JAPAzN6oZb+tgWGxnWYDYJSZPSZpKvCApGuBNwmlJeLfeyVNB+YTMg7MbIqkUcBUYAVwbqySQ9LPgScJ8+MMNbMp8Vi/quEczjnnSky1jSYj6XrgVEJDfqbqzMzs4CLHVlJdunSxysrKNd5Pg1WEaGpmg7yGzzlXd0iaaGZdcm2TT4nmOGCH5FQBzjnnXL7yaaN5G9isyHE455wrU/mUaDYD3pX0Oqu30dTavdk555zLJ6MZVPQonHPOla185qOptSuzc845V5N8RgZYTBijDGBDwphlS82sWTEDc845Vx7yKdE0zTxPDHLZrZhBOeecKx/59DqrEkdk/hdwaG3bOuecc5Bf1dnRicUNgC7A10WLyDnnXFnJp9fZjxLPVwAzCNVnzjnnXK3yaaNZ53lpnHPOrb9qzGgkXZljPzOza4oQj3POuTKTq0SzNEvaxsAZhFksPaNxzjlXq1xTOf8p81xSU+AC4DTgAeBPNe3nnHPOJeVso5G0OfAL4GRgGNDJzBaUIjDnnHPlIVcbzR+AowlTHe9pZktKFpVzzrmykeuGzYuBbYDfAh9L+iI+Fkv6ojThOeecq+9qzGjMbAMza2JmTc2sWeLRNJ9xziRtJ+k5SVMlTZF0QUzfXNLTkqbFv81juiTdLGm6pMmSOiWONSBuP03SgER6Z0lvxX1ujkPk1HgO55xzpbdGQ9CsoRXAxWa2O2FstHMl7Q5cBow1s3bA2LgMcBjQLj4GArdDVTvRIGAfoCswKJFx3A6cldivd0yv6RzOOedKrGgZjZnNMbM34vPFwDvAtoRRBYbFzYYBP47P+wLD43hqrwKbSdqaMK7a02Y2P3ZEeBroHdc1M7NXzcyA4dWOle0czjnnSqyYJZoqktoAewGvAVua2Zy46hNgy/h8W+CjxG6zYlqu9FlZ0slxDueccyVW9IxG0ibAQ8CFZrZaJ4JYErGsOxZIrnNIGiipUlLl3LlzixmGc86tt4qa0UhqRMhkRpjZwzH501jtRfz7WUyfDWyX2L1VTMuV3ipLeq5zrMbMhphZFzPr0rJly7W7SOecczkVLaOJPcDuAt4xsz8nVo0BMj3HBgCPJNL7x95n3YBFsfrrSaCXpOaxE0Av4Mm47gtJ3eK5+lc7VrZzOOecK7F8pglYW/sBpwJvSZoU0y4HbgBGSToDmAkcH9c9DhwOTAe+JAx3g5nNl3QN8Hrc7mozmx+fnwPcAzQBnogPcpzDOedciRUtozGzFwHVsLpnlu0NOLeGYw0FhmZJrwT2yJI+L9s5nHPOlV4xSzSuHKim3wpFYEXtF+KcS4lnNC63EWkH4Jyr70pyH41zzrn1l2c0zjnnisozGuecc0XlGY1zzrmi8s4ALidNK925vM+Zc+XJSzTOOeeKyjMa55xzReUZjXPOuaLyjMY551xReUbjnHOuqDyjcc45V1Se0TjnnCsqz2icc84VlWc0zjnnisozGuecc0VVtIxG0lBJn0l6O5G2uaSnJU2Lf5vHdEm6WdJ0SZMldUrsMyBuP03SgER6Z0lvxX1ulsIMXTWdwznnXDqKWaK5B+hdLe0yYKyZtQPGxmWAw4B28TEQuB1CpgEMAvYBugKDEhnH7cBZif1613IO55xzKShaRmNmLwDzqyX3BYbF58OAHyfSh1vwKrCZpK2BQ4GnzWy+mS0AngZ6x3XNzOxVMzNgeLVjZTuHc865FJS6jWZLM5sTn38CbBmfbwt8lNhuVkzLlT4rS3quczjnnEtBap0BYkmkqCPD13YOSQMlVUqqnDt3bjFDcc659VapM5pPY7UX8e9nMX02sF1iu1YxLVd6qyzpuc7xHWY2xMy6mFmXli1brvVFOeecq1mpM5oxQKbn2ADgkUR6/9j7rBuwKFZ/PQn0ktQ8dgLoBTwZ130hqVvsbda/2rGyncM551wKijbDpqT7gR7AFpJmEXqP3QCMknQGMBM4Pm7+OHA4MB34EjgNwMzmS7oGeD1ud7WZZToYnEPo2dYEeCI+yHEO55xzKShaRmNmJ9awqmeWbQ04t4bjDAWGZkmvBPbIkj4v2zmcc86lw0cGcM45V1Se0TjnnCuqolWdOVfn3afSnu+kovbmd67O8hKNc865ovISjVtvaVppz+flGbe+8hKNc865ovKMxjnnXFF5RuOcc66oPKNxzjlXVJ7ROOecKyrPaJxzzhWVZzTOOeeKyjMa55xzReUZjXPOuaLyjMY551xReUbjnHOuqDyjcc45V1Q+qKZzZUqDSzsNgg3yYUNddmWb0UjqDdwENAD+bmY3pBySc66APCOtP8qy6kxSA+CvwGHA7sCJknZPNyrnnFs/lWuJpisw3cw+AJD0ANAXmJpqVM45l6dyKrHJrPyKg5KOBXqb2Zlx+VRgHzP7ebXtBgID4+IuwHslDHML4PMSnq/Uyvn6yvnawK+vviv19W1vZi1zbVCuJZq8mNkQYEga55ZUaWZd0jh3KZTz9ZXztYFfX31XF6+vLNtogNnAdonlVjHNOedciZVrRvM60E5SW0kbAicAY1KOyTnn1ktlWXVmZisk/Rx4ktC9eaiZTUk5rOpSqbIroXK+vnK+NvDrq+/q3PWVZWcA55xzdUe5Vp0555yrIzyjcc45V1Se0ZRIHK2gbEnaM+0Y3NqRdEE+ac6tLW+jKRFJHwAPAXebWdmNUCBpPLARcA8wwswWpRuRy5ekN8ysU7W0N81sr7RiKgRJbwE1fsGZWYcShrNeK8teZ3VUR0I3679L2gAYCjxgZl+kG1ZhmNn+ktoBpwMTJU0gZKpPpxxaQUgaa2Y9a0urTySdCJwEtJWU7P7fFJifTlQFdWT8e278e2/8e3IKsRSVpI2AY4A2JL7XzezqtGJK8hJNCiQdCNwHbAaMBq4xs+mpBlUgsYrwx8DNwBeAgMvN7OE041pbkhoD3wOeA3oQrgegGfAfM9s1pdDWmaTtgbbA9cBliVWLgclmtiKVwAosW+ksWymuPpP0H2ARMBFYmUk3sz+lFlSCl2hKJH4BHwGcRvjV8SdgBLA/8Diwc2rBFYCkDoRrOwJ4GviRmb0haRvgFaBeZjTAT4ELgW2ANxLpXwC3phFQoZjZTGAmsG/MdNqZ2TOSmgBNCBlOOZCk/czspbjwA8qvfbqVmfVOO4iaeImmRGIbzXPAXWb2crV1N5vZ+elEVhiSngf+Dow2s6+qrTvVzO7Nvmf9IOk8M7sl7TiKQdJZhMFlNzezHWMV6B31uVowSVJnQlX1poQS6QLgdDN7I+eO9YikIcAtZvZW2rFk4xlNiUjaxMyWpB2HWzuS+mdLN7PhpY6l0CRNIkyt8VqmiknSW2ZWVj0JJW0KUI4dVSRNBXYCPgS+IWSoVlc6PHjVWemskHQu0B5onEk0s9PTC6lw4q/g6wkTzSWvb4fUgiqsvRPPGwM9CVVp9T6jAb4xs2VSaH6S1JAcvbXqI0lHEP/3MtdZVxrKC+SwtAPIxTOa0rkXeBc4FLia0PPlnVQjKqy7gUHAjcBBhPaasqkHN7PzksuSNgMeSCeagnte0uVAE0mHAOcAj6YcU8FIuoPQoeMgQvXuscCEVIMqvDOBF4CXzWxp2sFU51VnJZLp+SJpspl1kNQIGG9m3dKOrRAkTTSzzskql0xa2rEVQ3z/3jazXdKOZV3F7vZnAL0IVS5PAn+3MvlySPzPZf5uAjxhZvunHVuhSDqN0LFoX0InjvHAC2b2SKqBRV6iKZ3l8e9CSXsAnwDfTzGeQvsmfmFNiyNnzwY2STmmgpH0KKuqkxoAuwGj0ouocMzsW0n/IHwxlXKW2VLJdE75MvaCnAdsnWI8BWdmdwN3S9oKOB64hNDBo2mqgUWe0ZTOEEnNgSsIc+NsEp+XiwsI1RPnA9cQqikGpBpRYf0x8XwFMNPMZqUVTCFJ6gP8AdiQcPNmBXC1mfVJNbDCeSxWdf6B0K5mwN9SjajAJP2d0D76KaE0cyyrd8dPlVeduYKQtKOZvZ92HMUkaUtWdQqYYGafpRlPoUiaCBwMjCvnXmdQdQd943LreSbpn4R7vaYCzxNKpx+kG9UqXqIpEUnvA68Sfm2Mr4MTsa2roZJaEWY3zdQP18k+/WtD0vGEX8TjCO0Yt0i61MxGpxpYYSw3s0WZ3lhR2fwCje1pPwMOiEnjJN1pZstz7FavmNlRAJJ2I3Q4ek5SAzNrlW5kgWc0pbM7sA+hwe4PknYhDPNxVLphFYaZHRinzd6bMFTLv+O9Q5unG1nB/AbYO1OKkdQSeIYwhFB9N0XSSUCD2E39fODlWvapT24HGgG3xeVTY9qZqUVUYJKOJHy3HEAY2upZwg++OsEzmtJZSegQsBL4FvgsPsqCpO6ED/r+hA/6Y9ShD3oBbFCtqmwe5dN9+zxCRvoNYQy+J4FrU42osPY2s46J5Wcl/Te1aIqjN+H/7SYz+zjtYKrzNpoSkfQl8BbwZ+AZM5uXckgFJWkFYUC/64HHzWxZyiEVlKQ/AB2A+2NSP0KJ9FfpRbXu4hh8z5jZQWnHUiyS3gCOy7QhStqBMFRS2QyqCXW7DdEzmhKR1BfoThjqYxmhauIFMxubamAFEnv17Ecouu9NKLW9YmZl07NO0tGE9xBCO9s/04ynUCSNBY4utwbyDEkHE+ZJ+oDQvrY9cJqZPZdmXIUk6ThCz8hxhGvcH6gzbYhedVYi8capRyTtShgu4kLgl4RRcus9M1sYBw7dDmgF/IBQL15OXmZV1efrKcdSSEuAtyQ9DVTdVV7fB3qFqhJbR6AdkLm59j0z+ya9qIrit9ThNkQv0ZSIpIcIH/j3CUNFvEgYxPDrVAMrkJjJvEu4rhcIRfeyqT6TdCZwJaGRVcCBhHtNhqYaWAFIyna/k5XDgKEAkiaYWde04yim6t3R483T/60rXdS9RFM61wNvmtnKWresn3Yys2/TDqKILgX2yrStSWpBKOHU+4wG2MzMbkomSLogrWCK4CVJtwIjWb3EVmduaCyA/0h6ktXbEB9PMZ7VeImmRCR9D/gF0NrMBsZupLuY2WMph1YQknYmdBnd0sz2iBOh9TGzsui9JOlloEemlBa7co8zsx+kG9m6yzbbZLZZKesrSdnaYszMDi55MEUk6RhCOynUsTZEz2hKRNJIQq+s/vGL+HuEkVYr0o2sMOLEZ5cCdybuLn/bzPZIN7J1I+kX8WkFsCfwCOFmxr6EXmc/SSeydSfpROAkQgeHZFf0ZsDKcpn4zKXPq85KZ0cz6xf/uTGzL1XtVux67ntmNqHaJZXDnPOZQQnfj4+MOjEq7jp6GZgDbEGYWjxjMTA5lYjcWok9In9HGKhXrJr4rFmqgUWe0ZTOMoW52A3C2GCEG+TKxefxmjLXdyzhS6xeM7PBacdQLGY2E5gp6YfAV3EU552BXQn3fLn64/fAj8ysTs5x5VVnJRInlPotYSiapwh1qT8xs3FpxlUo8Sa4IYRuzQsIU8qeYmYz0oyrUGJ30V/y3RlS6309fxxUc3+gOfASoev2MjM7OdXAXN4kvWRm+9W+ZTo8oymh2FOpG6FY+6qZfZ5ySAUnaWPCcC2L046lkCQ9Rei1dAlwNmEKhLn1fWQAWNUZQNJ5QBMz+72kSWXUftiYMGtod0KJ+0Xg9nK5tQBA0k3AVsC/SNSUmNnDacWU5FVnJSIp06snU53UWtKmhHlN6n1bRqLRPLMMsAiYaGaT0oipwFqY2V2SLjCz5wnTH5fLTZuStC9hevEzYlqDFOMptOGEdqdb4vJJhKnVj0stosJrBnxJmCU1wwDPaNYztwGdCI2sAvYApgCbSvqZmT2VZnAF0CU+MnPNH0m41rMlPWhmv08tssLIDCk/R9IRwMdAuYxMfQHwa+CfZjYlVoOWzfAswB5mtnti+TlJU1OLpjguNrP5yQRJbdMKprpyGX22PviYcMNfFzPrDOxFGHvpEEJDXn3XCuhkZheb2cVAZ0IPmAOAn6QZWIFcG0ugFxOqz/4OXJRuSIVhZi+YWR8z+11c/qAchp9JeENSt8yCpH2AyhTjKYZHJVX1MIvz0jyaY/uS8hJN6eycnOzMzKZK2tXMPiiTXs7fZ/VedMsJN29+Jane965L3Fi7iDBNtas/OgMvS/pfXG4NvCfpLUIX4A7phVYw/0fIbI4gjOk2nFAVWid4RlM6UyTdDjwQl/sBU+PUsuUw098I4DVJmftLfgTcFzsH1NtqCkm3kGO2yTL75V+ueqcdQLGZ2b/jTKJPEe79OsrM/l/KYVXxXmclEu+hyfR8gdCN9Dbga8LNjkvSiq1QJO1N6N4M8JKZ1fvqicSAk/sRuqaPjMvHAVPN7OxUAisgSS3KbX4kAEnNzOwLSVnb0qq3adRHWX4I9STcWDwD6s4PIc9oXEFJ+j6r32fyvxyb1xuSXgW6Z3oIxl+P482sW+496z5J04BJwN3AE1YmXwqSHjOzIyV9SPgyTtZRm5ntkFJoBVPDyNtVzGxYqWLJxTOaEomDaF5P+FWc/CKu9x92AEl9CMOYbEOYoro18K6ZtU81sAKR9B6wb+ZXsKTmhHuhdsm9Z90Xh0L6IXA6YdK6UcA9danqxdVv3kZTOncDg4AbCY3Jp1Fevf6uIdyM+oyZ7SXpIOCUlGMqpBuAN+NIwCL0prsq1YgKJJZgngaeju/bP4BzJP0XuMzMXkk1wLWUuHctq3KaJkDSfoTP4/aE7/XMWGd14oesl2hKRNJEM+ucnKAok5Z2bIUgqdLMusQvp73iuFn/NbOOacdWKJK2AvaJi6+Z2SdpxlMoccSKU4BTgU+Bu4AxhBGrHzSzOnM/xpqoYXqAjLKaJkDSu4Tu9hMJs8ACUFfa3rxEUzrfxFnvpkn6OTAb2CTlmAppoaRNCLNrjpD0GYlJpspEA2Au4f9mZ0k7m9kLKcdUCK8Q7pT/sZnNSqRXSrojpZjWmZmtT93QF5nZE2kHURMv0ZRI7JH1DrAZoZppU+D3ZvZqmnEVSuzG/DWhyH4y4fpG1JVfVOtK0u8IXdKnAJmZRM3M+qQXVWFIUrl0AEiK/3MfZUqekvoDxwAzgavKoddZhqQbCD+EHmb1sc7qRPWgZzTO5SF2BuhgZvX+5tPqynVkaklvAD80s/mSDiDcw3YeoUpwNzM7Ns34CilRTZj5Qs+00dSJ99CrzopM0l/M7EJJj5Llxr/6/otY0otm1l3SYla/vjo18VIBfAA0orzmEMoYQbg/6EgSI1OnGlFhNEiUWvoBQ8zsIeAhSZPSC6twEoPZZkauMMJ796KZfZhOVN/lGU3x3Rv//jHVKIrEzLrHv01r27ae+xKYJGksq1dN1Ikb4tZRuY5M3UBSw3jvU09gYGJduXz3Zfu/2x74jaSrzOyBLOtLrlxe7DrLzCZKagAMLNeJpOL1TTGzXdOOpYjGxEc5KteRqe8nZJqfA18B4wEk7UQYs67esxpmgI2jITzDqiGvUuUZTQmY2UpJ20va0MyWpR1PocXre09S63IZCaC6unKHdZEkR6a+hTC3Sb0fmdrMrosl0K2BpxIdHjYgtNWUrdguVWdG6/WMpnQ+AF6SNIZEt18z+3N6IRVUc8LAoRNY/frqdRtURmIYk9XUlRvi1tEzcbbJshuZOluvzvVhxIN44+2CtOPI8IymdN6Pjw3IXq9a312RdgBF1iXxvDFhUM1yqF4CeFvSp4SqpfGEhuSyqFoqd5mpDqolb06o/uxf+oiy8+7NJRDbMIZ7G015KbORHVoD+xNGqT4cWGhmFakG5WolaftqSQbMM7M6dbO0l2hKwNto6r9q42ZtQCjhlMX/j6RWhAxmf6Aj4abUF1MNyuXFzGamHUM+yuIfpZ7wNpr67U+J5ysI830cn04oBfc/4HXg/8phfh1X93jVWYlIGpQtvabuifWNpAOzpcf7MlwdJqkjYUK+AwjTO0wDnjezu1INzJUNz2icy0Ps/juI8GUM8Dxwdbk0mscBUbsTqs9OATCz6vX/zq0Vz2hKpFzHk8qQ1I1wD8ZuwIaEAf6WlssQNJIeAt4GMvfTnAp0NLOj04uqMCRVAhsBLxN7ntWXun9XP3gbTemU63hSGbcCJwAPEhrK+wM7pxpRYe1oZscklgeXy3hZwGFmVk6fRVfHlNMMj3Vdi1jnvdzMnjez04GyKM1kmNl0wkCGK83sbqB32jEV0FeSumcW4oyGX6UYT8F4JuOKzUs0pVOu40llfClpQ8LAk78H5lBeP2R+BgyLbTUC5hNKpc65WngbTYlIOpJQ/70dq8aTGmxmZTFQY7xx7FNC+8xFhInPboulnLIhKdPmtBQ4wcxGpBmPc/WBZzSuIOIMm1+Z2bdxuQGwkZl9mW5k6yZmLOcC2wKPEEbEPZcwAOVkM+ubYngFIel7hOtpbWZnSWoH7GJmj9Wyq3N5KaeqjTpN0jBJmyWWm0sammJIhTYW+F5iuQnhS7m+uxfYBXgLOAt4jjDO2VHlkMlEdxPm2Nk3Ls8Grk0vHFduvI2mdDqY2cLMgpktkLRXivEUWmMzW5JZMLMl8ZdyfbeDme0JIOnvhLan1nG043Kxo5n1k3QigJl9WZeGmHf1n5doSmcDSc0zC3FionLK6JcmxwOT1Jny6JWV6cSBma0EZpVZJgOwTFIT4ijAknakPKesdikppy+6uu5PwCuSHozLxwHXpRhPoV0IPCjpY0KvrK0I87TXdx0lfRGfC2gSlwVYmdyQOgj4D7CdpBGEATZ/kmpErqx4Z4ASkrQ7q+6dedbMpqYZT6FJakRozwB4z8yW59re1R2SWgDdCBnoq2b2ecohuTLiGY1zDknbAtuTqOUwsxfSi8iVE686c249J+l3hGrOKcC3MdkAz2hcQXiJxrn1nKT3CL0ivQOAKwov0ZRQvHu+nZk9E3v5NDSzxWnHtS6qzTz5HWb2RqlicWvtA6AR3tPMFYlnNCUi6SxgIGF8sx2BVsAdQM804yqAP+VYZ5TZwKFl6kvCGHVjSWQ2ZnZ+eiG5cuIZTemcC3QFXgMws2mSvp9uSOvOzA5KOwa3zsbEh3NF4RlN6XxjZssyN1xLaki8Qa5cSNoD2J3VJ3Ybnl5ELk8jgZ3i8+lleEOqS5lnNKXzvKTLCTf8HQKcAzyackwFI2kQ0IOQ0TwOHAa8CHhGU0fFHzv/B5wOzCTcQ7OdpLuB3/h9UK5QvNdZiUjaADgD6EX4h34S+LuVyRsg6S2gI/CmmXWUtCXwDzM7JOXQXA0k3Qg0BS7KdEqJo1X/kTAS9wVpxufKh2c0riAkTTCzrpImAgcBi4F3zGzXlENzNZA0Ddi5+o+dOMXDu2bWLp3IXLnxqrMii7/0a8zNzaxDCcMppso4DcLfgInAEuCVVCNytbFsJWozWynJf4G6gvESTZHFe2dqZGYzSxVLqUhqAzQzs8lpx+JqJulfwMPVO2xIOgU43sz6pBKYKzue0biCkHRAtnQfL6vuiuObPUyYzmFiTO5CmLTuKDObnVZsrrx4RlMikhbz3Sq0RUAlcLGZfVD6qApHUrIHXWPCPUMTzcxv2KzjJB0MtI+LU81sbJrxuPLjGU2JSLoGmAXcR+h1dgJhhIA3gJ+ZWY/0ois8SdsBfzGzY9KOxTmXLs9oSkTSf82sY7W0SWZWkW1dfRenAp5iZrunHYtzLl3e66x0vpR0PDA6Lh8LZO7Arve5vaRbWHUdGwAVhNKac2495yWaEpG0A3ATsC/hC/lV4CJgNtDZzF5MMbx1JmlAYnEFMMPMXkorHudc3eEZjSsYSS0BzGxu2rE45+oOz2hKJH4JnwW0YfXpck9PK6ZCiG0xg4CfE6rMRCjR3GJmV6cZm3OubvA2mtJ5BBgPPAOsTDmWQroI2A/Y28w+hKpqwtslXWRmN6YanXMudV6iKZFMD7O04yg0SW8Ch5jZ59XSWwJPmdle6UTmnKsrNkg7gPXIY5IOTzuIImhUPZOBqnaaRinE45yrYzyjKZ0LCJnNV5K+kLRY0hdpB1UAy9ZynXNuPeFVZ26dSFoJLM22CmhsZl6qcW495xlNkUna1czeldQp23oz85sanXNlzTOaIpM0xMwGSnouy2rzQSedc+XOMxrnnHNF5Z0BikzS3pK2Siz3l/SIpJslbZ5mbM45Vwqe0RTfncTeV3FysBuA4YS5aIakGJdzzpWEjwxQfA3MbH583g8YYmYPAQ9JmpReWM45Vxpeoim+BpIyGXpP4NnEOs/onXNlz7/oiu9+4HlJnxPmZh8PIGknQvWZc86VNe91VgKSugFbE8b+WhrTdgY28ftonHPlzjMa55xzReVtNM4554rKMxrnnHNF5Z0BnFtHcWDRtwj/Tx8Cp5rZwgIcd4mZbZJYbgGMjYtbESbQy0yb3dXMfLRsVyd5G41z6yiZIUgaBvw/M7uukMfNsu4qYImZ/XFdz+NcsXnVmXOF9QqwLYCkCkmvSpos6Z+Smsf0syS9Lum/kh6S9L2Y3lbSK5LeknRtPieT1FTSh5IaxeVmmWVJ4yTdJGmSpLcldY3bbCxpqKQJkt6U1Lcor4RzkWc0zhWIpAaEm3LHxKThwK/MrAOham1QTH/YzPY2s47AO8AZMf0m4HYz2xOYk885zWwxMA44IiadEI+/PC5/L04hfg4wNKb9BnjWzLoCBwF/kLTxGl6uc3nzjMa5ddckDif0CbAl8LSkTYHNzOz5uM0w4ID4fA9J4yW9BZwMtI/p+xFu8AW4dw3O/3fgtPj8NODuxLr7AczsBaCZpM2AXsBlMeZxQGOg9Rqcz7k14hmNc+vuq1hq2J4ws+i5tWx/D/DzWHIZTPiiz1jjRlMzewloI6kHYWy9t3Mcz2KMx5hZRXy0NrN31vS8zuXLMxrnCsTMvgTOBy4mTG+9QNL+cfWpQKZ00xSYE9tVTk4c4iVC1RfV0vMxHLiP1UszEAZyRVJ3YJGZLQKeBM6TpLhurzU8l3NrxDMa5wrIzN4EJgMnAgMI7R+TgQrg6rjZFcBrhIzl3cTuFwDnxiq1bdfw1COA5qyqesv4WtKbwB2sagu6BmgETJY0JS47VzTevdm5MiDpWKCvmZ2aSBsHXGJmlakF5hx+w6Zz9Z6kW4DDgMPTjsW5bLxE45xzrqi8jcY551xReUbjnHOuqDyjcc45V1Se0TjnnCsqz2icc84VlWc0zjnniur/A+q5+B8rR2TJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "road_group = accidents_df.groupby([\"Road_Type\",\"Accident_Severity\"])\n",
    "\n",
    "road_group_count = road_group[\"Accident_Severity\"].count().unstack()\n",
    "\n",
    "road_group_count = road_group_count.sort_values(by=[\"Fatal\",\"Serious\",\"Slight\"], ascending=False)\n",
    "\n",
    "road_group_count = road_group_count[[\"Slight\",\"Serious\",\"Fatal\"]]\n",
    "\n",
    "road_group_count.plot.bar(stacked=True, color={\"Fatal\": \"red\", \"Serious\": \"orange\", \"Slight\":\"green\"})\n",
    "\n",
    "plt.title(\"Number of Accidents for Road Type by Accident Severity\")\n",
    "plt.ylabel(\"Number of Accidents\")\n",
    "plt.xlabel(\"Road Type\")\n",
    "plt.savefig(\"Images/No_Accidents_for_Road_Type.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c877f15b",
   "metadata": {},
   "source": [
    "This plot indicates that an overwhelming majority of accidents of all severity ratings happen on Single Carriageways. This is followed by Dual Carriageways.\n",
    "\n",
    "Again, we faced the issue of not being able to give a number to how many sincle carriageways and dual carriaways there are in the UK. The definition for Single Carriagway is somewhat broad and therefore includes many different road types.\n",
    "\n",
    "We were unable to establish how many single carriageways there are in the UK, so we found this data to be not useful.\n",
    "\n",
    "As we were unable to understand this in the context we desired, we discard this plot from the report."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7a71764",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}