{
 "cells": [
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_entries=pd.read_csv('test_set.csv')"
   ]
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  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "if 'Yes' in filtered_entries['Pedestrian_Involved'][3]: print('Available')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "yes_count=0\n",
    "no_count=0\n",
    "not_available_count=0\n",
    "for i in range(len(filtered_entries)):\n",
    "    if ('Yes' in filtered_entries['Pedestrian_Involved'][i] or 'yes' in filtered_entries['Pedestrian_Involved'][i]): yes_count+=1\n",
    "    if ('No' in filtered_entries['Pedestrian_Involved'][i] or 'no' in filtered_entries['Pedestrian_Involved'][i]): no_count+=1\n",
    "    if ('Not Available' in filtered_entries['Pedestrian_Involved'][i]): not_available_count+=1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "Pedestrian_Involved_list = ['Yes', 'No', 'Not Available']\n",
    "Count_list = [yes_count, no_count, not_available_count]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yes_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dictionary of lists \n",
    "dict = {'Pedestrian Involved': Pedestrian_Involved_list, 'Count':Count_list} \n",
    "pedestrian_involvement = pd.DataFrame(dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "    .dataframe thead th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pedestrian Involved</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>8</td>\n",
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       "      <td>18</td>\n",
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       "      <td>12</td>\n",
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       "  Pedestrian Involved  Count\n",
       "0                 Yes      8\n",
       "1                  No     18\n",
       "2       Not Available     12"
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     },
     "execution_count": 11,
     "metadata": {},
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  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pie chart showing the percentage of accidents involving pedestrians vs. those that don't\n",
    "# pedestrian_involvement = df['Pedestrian_Involved'].value_counts().reset_index()\n",
    "# pedestrian_involvement.columns = ['Pedestrian Involved', 'Count']\n",
    "\n",
    "fig4 = px.pie(pedestrian_involvement, \n",
    "                names='Pedestrian Involved', \n",
    "                values='Count', \n",
    "                title=\"Accidents Involving Pedestrians\",\n",
    "                labels={'Pedestrian Involved': 'Pedestrian Involved'})\n"
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    "yes_count=0\n",
    "no_count=0\n",
    "not_available_count=0\n",
    "for i in range(len(filtered_entries)):\n",
    "    if ('Yes' in filtered_entries['Pedestrian_Involved'][i] or 'yes' in filtered_entries['Pedestrian_Involved'][i]): yes_count+=1\n",
    "    if ('No' in filtered_entries['Pedestrian_Involved'][i] or 'no' in filtered_entries['Pedestrian_Involved'][i]): no_count+=1\n",
    "    if ('Not Available' in filtered_entries['Pedestrian_Involved'][i]): not_available_count+=1\n",
    "Pedestrian_Involved_list = ['Yes', 'No', 'Not Available']\n",
    "Count_list = [yes_count, no_count, not_available_count]\n",
    "# dictionary of lists \n",
    "dict = {'Pedestrian Involved': Pedestrian_Involved_list, 'Count':Count_list} \n",
    "pedestrian_involvement = pd.DataFrame(dict)\n",
    "# Pie chart showing the percentage of accidents involving pedestrians vs. those that don't\n",
    "# pedestrian_involvement = filtered_entries['Pedestrian_Involved'].value_counts().reset_index()\n",
    "# pedestrian_involvement.columns = ['Pedestrian Involved', 'Count']\n",
    "\n",
    "fig4 = px.pie(pedestrian_involvement, \n",
    "                names='Pedestrian Involved', \n",
    "                values='Count', \n",
    "                title=\"Accidents Involving Pedestrians\",\n",
    "                labels={'Pedestrian Involved': 'Pedestrian Involved'})"
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