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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d10c43ef",
+   "metadata": {},
+   "source": [
+    "# Mini Project: Penn Dot Bicycle Crashes\n",
+    "## Name: Melanie Duong\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f00186e",
+   "metadata": {},
+   "source": [
+    "## 1. Data Cleaning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "id": "6344a969",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import pandas\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "id": "13b9c9b2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set dataframe\n",
+    "\n",
+    "df = []\n",
+    "selected_columns = ['MUNICIPALITY', 'FATAL_COUNT', 'INJURY_COUNT', 'BICYCLE_COUNT', 'AUTOMOBILE_COUNT', 'BUS_COUNT', 'COMM_VEH_COUNT',\n",
+    " 'HEAVY_TRUCK_COUNT', 'MOTORCYCLE_COUNT', 'PED_COUNT', 'SMALL_TRUCK_COUNT', 'VAN_COUNT'\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 149,
+   "id": "5a0c721d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load CRASH files\n",
+    "\n",
+    "for year in range (2014, 2024):\n",
+    "    file_name = f\"CRASH_{year}.csv\"\n",
+    "    file_path = f\"C:/Users/maidn/OneDrive - Dickinson College/Dickinson/senior/DATA 400/mini project data/Statewide_{year}/\" + file_name\n",
+    "    crash_files = pd.read_csv(file_path, usecols = selected_columns)\n",
+    "    crash_files['Year'] = year\n",
+    "    df.append(crash_files)\n",
+    "    \n",
+    "df = pd.concat(df)\n",
+    "\n",
+    "# Load municipality list\n",
+    "\n",
+    "municipality_name = pd.read_csv(\"C:/Users/maidn/OneDrive - Dickinson College/Dickinson/senior/DATA 400/municipalities_list.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 150,
+   "id": "d94c35f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "MUNICIPALITY          int64\n",
+       "MUNICIPALITY_NAME    object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 150,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check for municipality name types\n",
+    "\n",
+    "municipality_name.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "bc6fcdde",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         AUTOMOBILE_COUNT  BICYCLE_COUNT  BUS_COUNT  COMM_VEH_COUNT  \\\n",
+      "0                       0              0          0               0   \n",
+      "1                       2              0          0               0   \n",
+      "2                       1              0          0               0   \n",
+      "3                       1              0          0               0   \n",
+      "4                       0              0          0               0   \n",
+      "...                   ...            ...        ...             ...   \n",
+      "1210636                 0              1          0               0   \n",
+      "1210637                 0              0          0               0   \n",
+      "1210638                 1              0          0               0   \n",
+      "1210639                 0              0          0               0   \n",
+      "1210640                 2              0          0               0   \n",
+      "\n",
+      "         FATAL_COUNT  HEAVY_TRUCK_COUNT  INJURY_COUNT  MOTORCYCLE_COUNT  \\\n",
+      "0                  0                  0             1                 0   \n",
+      "1                  0                  0             1                 0   \n",
+      "2                  0                  0             0                 0   \n",
+      "3                  0                  0             0                 0   \n",
+      "4                  0                  0             1                 0   \n",
+      "...              ...                ...           ...               ...   \n",
+      "1210636            0                  0             1                 0   \n",
+      "1210637            0                  0             0                 0   \n",
+      "1210638            0                  0             0                 0   \n",
+      "1210639            0                  0             0                 0   \n",
+      "1210640            0                  0             0                 0   \n",
+      "\n",
+      "         MUNICIPALITY  PED_COUNT  SMALL_TRUCK_COUNT  VAN_COUNT  Year  \\\n",
+      "0               46109          0                  1          0  2014   \n",
+      "1               39301          0                  0          0  2014   \n",
+      "2               11222          0                  1          0  2014   \n",
+      "3                2212          0                  0          0  2014   \n",
+      "4                8201          0                  1          0  2014   \n",
+      "...               ...        ...                ...        ...   ...   \n",
+      "1210636         36211          0                  1          0  2023   \n",
+      "1210637         17404          0                  0          0  2023   \n",
+      "1210638         36225          0                  0          0  2023   \n",
+      "1210639         17219          0                  0          0  2023   \n",
+      "1210640         67301          0                  0          0  2023   \n",
+      "\n",
+      "          MUNICIPALITY_NAME  \n",
+      "0          Upper Dublin Twp  \n",
+      "1            Allentown City  \n",
+      "2              Richland Twp  \n",
+      "3              Marshall Twp  \n",
+      "4                Albany Twp  \n",
+      "...                     ...  \n",
+      "1210636    East Donegal Twp  \n",
+      "1210637     Clearfield Boro  \n",
+      "1210638       Mount Joy Twp  \n",
+      "1210639          Huston Twp  \n",
+      "1210640   Philadelphia City  \n",
+      "\n",
+      "[1210641 rows x 14 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Merge crash data and municipality data\n",
+    "\n",
+    "df = pd.merge(df, municipality_name, how = 'left', on = 'MUNICIPALITY')\n",
+    "print(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "id": "24db65c4",
+   "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>AUTOMOBILE_COUNT</th>\n",
+       "      <th>BICYCLE_COUNT</th>\n",
+       "      <th>BUS_COUNT</th>\n",
+       "      <th>COMM_VEH_COUNT</th>\n",
+       "      <th>FATAL_COUNT</th>\n",
+       "      <th>HEAVY_TRUCK_COUNT</th>\n",
+       "      <th>INJURY_COUNT</th>\n",
+       "      <th>MOTORCYCLE_COUNT</th>\n",
+       "      <th>MUNICIPALITY</th>\n",
+       "      <th>PED_COUNT</th>\n",
+       "      <th>SMALL_TRUCK_COUNT</th>\n",
+       "      <th>VAN_COUNT</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>MUNICIPALITY_NAME</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>46109</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Upper Dublin Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>39301</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Allentown City</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>11222</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Richland Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2212</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Marshall Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8201</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Albany Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9219</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Plumstead Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2213</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Moon Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40228</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Salem Twp</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>39301</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Allentown City</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4203</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>Chippewa Twp</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   AUTOMOBILE_COUNT  BICYCLE_COUNT  BUS_COUNT  COMM_VEH_COUNT  FATAL_COUNT  \\\n",
+       "0                 0              0          0               0            0   \n",
+       "1                 2              0          0               0            0   \n",
+       "2                 1              0          0               0            0   \n",
+       "3                 1              0          0               0            0   \n",
+       "4                 0              0          0               0            0   \n",
+       "5                 1              0          0               0            0   \n",
+       "6                 1              0          0               0            0   \n",
+       "7                 0              0          0               0            0   \n",
+       "8                 2              0          0               0            0   \n",
+       "9                 2              0          0               0            0   \n",
+       "\n",
+       "   HEAVY_TRUCK_COUNT  INJURY_COUNT  MOTORCYCLE_COUNT  MUNICIPALITY  PED_COUNT  \\\n",
+       "0                  0             1                 0         46109          0   \n",
+       "1                  0             1                 0         39301          0   \n",
+       "2                  0             0                 0         11222          0   \n",
+       "3                  0             0                 0          2212          0   \n",
+       "4                  0             1                 0          8201          0   \n",
+       "5                  0             1                 0          9219          0   \n",
+       "6                  0             0                 0          2213          0   \n",
+       "7                  0             1                 0         40228          0   \n",
+       "8                  0             1                 0         39301          0   \n",
+       "9                  0             0                 0          4203          0   \n",
+       "\n",
+       "   SMALL_TRUCK_COUNT  VAN_COUNT  Year  MUNICIPALITY_NAME  \n",
+       "0                  1          0  2014   Upper Dublin Twp  \n",
+       "1                  0          0  2014     Allentown City  \n",
+       "2                  1          0  2014       Richland Twp  \n",
+       "3                  0          0  2014       Marshall Twp  \n",
+       "4                  1          0  2014         Albany Twp  \n",
+       "5                  0          0  2014      Plumstead Twp  \n",
+       "6                  0          1  2014           Moon Twp  \n",
+       "7                  1          0  2014          Salem Twp  \n",
+       "8                  0          0  2014     Allentown City  \n",
+       "9                  0          0  2014       Chippewa Twp  "
+      ]
+     },
+     "execution_count": 152,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# View dataframe\n",
+    "\n",
+    "df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "34deae30",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((1210641, 14),\n",
+       " Index(['AUTOMOBILE_COUNT', 'BICYCLE_COUNT', 'BUS_COUNT', 'COMM_VEH_COUNT',\n",
+       "        'FATAL_COUNT', 'HEAVY_TRUCK_COUNT', 'INJURY_COUNT', 'MOTORCYCLE_COUNT',\n",
+       "        'MUNICIPALITY', 'PED_COUNT', 'SMALL_TRUCK_COUNT', 'VAN_COUNT', 'Year',\n",
+       "        'MUNICIPALITY_NAME'],\n",
+       "       dtype='object'),\n",
+       " AUTOMOBILE_COUNT      int64\n",
+       " BICYCLE_COUNT         int64\n",
+       " BUS_COUNT             int64\n",
+       " COMM_VEH_COUNT        int64\n",
+       " FATAL_COUNT           int64\n",
+       " HEAVY_TRUCK_COUNT     int64\n",
+       " INJURY_COUNT          int64\n",
+       " MOTORCYCLE_COUNT      int64\n",
+       " MUNICIPALITY          int64\n",
+       " PED_COUNT             int64\n",
+       " SMALL_TRUCK_COUNT     int64\n",
+       " VAN_COUNT             int64\n",
+       " Year                  int64\n",
+       " MUNICIPALITY_NAME    object\n",
+       " dtype: object)"
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#View dataframe\n",
+    "\n",
+    "df.shape, df.columns, df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
+   "id": "7e85df79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Group data by municipal ID\n",
+    "\n",
+    "df = df.groupby('MUNICIPALITY').agg({\n",
+    "    'Year': 'first', # Take the first value of the 'Year' column\n",
+    "    'MUNICIPALITY_NAME' : 'first',\n",
+    "    'FATAL_COUNT': 'sum',\n",
+    "    'INJURY_COUNT': 'sum',\n",
+    "    'AUTOMOBILE_COUNT': 'sum',\n",
+    "    'BICYCLE_COUNT': 'sum',\n",
+    "    'BUS_COUNT': 'sum',\n",
+    "    'COMM_VEH_COUNT': 'sum',\n",
+    "    'HEAVY_TRUCK_COUNT': 'sum',\n",
+    "    'MOTORCYCLE_COUNT': 'sum',\n",
+    "    'PED_COUNT': 'sum',\n",
+    "    'SMALL_TRUCK_COUNT': 'sum',\n",
+    "    'VAN_COUNT': 'sum'\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "id": "d8c3dbaf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Reset index\n",
+    "\n",
+    "df.reset_index(inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "c2ffd120",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Create new variable\n",
+    "\n",
+    "df['total_killed_injured'] = df['FATAL_COUNT'] + df['INJURY_COUNT']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
+   "id": "5b77ffd5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_copy = df.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "id": "010daaed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Drop unnecessary columns\n",
+    "\n",
+    "df = df.drop(columns = ['AUTOMOBILE_COUNT', 'BICYCLE_COUNT', 'BUS_COUNT', 'COMM_VEH_COUNT', 'HEAVY_TRUCK_COUNT', 'MOTORCYCLE_COUNT', 'PED_COUNT', 'SMALL_TRUCK_COUNT', 'VAN_COUNT', 'Year'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 159,
+   "id": "a74d5386",
+   "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>index</th>\n",
+       "      <th>MUNICIPALITY</th>\n",
+       "      <th>MUNICIPALITY_NAME</th>\n",
+       "      <th>FATAL_COUNT</th>\n",
+       "      <th>INJURY_COUNT</th>\n",
+       "      <th>total_killed_injured</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1201</td>\n",
+       "      <td>Berwick Twp</td>\n",
+       "      <td>4</td>\n",
+       "      <td>201</td>\n",
+       "      <td>205</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1202</td>\n",
+       "      <td>Butler Twp</td>\n",
+       "      <td>3</td>\n",
+       "      <td>214</td>\n",
+       "      <td>217</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1203</td>\n",
+       "      <td>Conewago Twp</td>\n",
+       "      <td>6</td>\n",
+       "      <td>236</td>\n",
+       "      <td>242</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1204</td>\n",
+       "      <td>Cumberland Twp</td>\n",
+       "      <td>6</td>\n",
+       "      <td>308</td>\n",
+       "      <td>314</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1205</td>\n",
+       "      <td>Franklin Twp</td>\n",
+       "      <td>12</td>\n",
+       "      <td>383</td>\n",
+       "      <td>395</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2554</th>\n",
+       "      <td>2554</td>\n",
+       "      <td>66433</td>\n",
+       "      <td>Wrightsville Boro</td>\n",
+       "      <td>1</td>\n",
+       "      <td>52</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2555</th>\n",
+       "      <td>2555</td>\n",
+       "      <td>66434</td>\n",
+       "      <td>Yoe Boro</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2556</th>\n",
+       "      <td>2556</td>\n",
+       "      <td>66435</td>\n",
+       "      <td>Yorkana Boro</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2557</th>\n",
+       "      <td>2557</td>\n",
+       "      <td>66436</td>\n",
+       "      <td>York Haven Boro</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2558</th>\n",
+       "      <td>2558</td>\n",
+       "      <td>67301</td>\n",
+       "      <td>Philadelphia City</td>\n",
+       "      <td>1157</td>\n",
+       "      <td>102556</td>\n",
+       "      <td>103713</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2559 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      index  MUNICIPALITY   MUNICIPALITY_NAME  FATAL_COUNT  INJURY_COUNT  \\\n",
+       "0         0          1201         Berwick Twp            4           201   \n",
+       "1         1          1202          Butler Twp            3           214   \n",
+       "2         2          1203        Conewago Twp            6           236   \n",
+       "3         3          1204      Cumberland Twp            6           308   \n",
+       "4         4          1205        Franklin Twp           12           383   \n",
+       "...     ...           ...                 ...          ...           ...   \n",
+       "2554   2554         66433   Wrightsville Boro            1            52   \n",
+       "2555   2555         66434            Yoe Boro            1            23   \n",
+       "2556   2556         66435        Yorkana Boro            0             6   \n",
+       "2557   2557         66436     York Haven Boro            0             9   \n",
+       "2558   2558         67301   Philadelphia City         1157        102556   \n",
+       "\n",
+       "      total_killed_injured  \n",
+       "0                      205  \n",
+       "1                      217  \n",
+       "2                      242  \n",
+       "3                      314  \n",
+       "4                      395  \n",
+       "...                    ...  \n",
+       "2554                    53  \n",
+       "2555                    24  \n",
+       "2556                     6  \n",
+       "2557                     9  \n",
+       "2558                103713  \n",
+       "\n",
+       "[2559 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 159,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Reset index\n",
+    "\n",
+    "df.reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "id": "0c7e9e2e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Rearrange the order of columns\n",
+    "\n",
+    "df = df[['MUNICIPALITY', 'MUNICIPALITY_NAME', 'total_killed_injured', 'INJURY_COUNT', 'FATAL_COUNT']]\n",
+    "\n",
+    "#Sort values in descending order\n",
+    "\n",
+    "df = df.sort_values('total_killed_injured', ascending = False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 162,
+   "id": "7ce8d16c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Rename columns\n",
+    "\n",
+    "renamed_columns = {'MUNICIPALITY':'Penn Dot municipal ID number', 'MUNICIPALITY_NAME': 'Municipality Name', 'total_killed_injured':'Total number of people killed or injuried in crashes from 2014 to 2024', 'INJURY_COUNT':'Total people injuried in crashes from 2014 to 2024', 'FATAL_COUNT':'Total people killed in crashes from 2014 to 2024'}\n",
+    "df = df.rename(columns = renamed_columns)\n",
+    "\n",
+    "#Reset index and rename index column\n",
+    "\n",
+    "df_crash = df.reset_index(drop = True)\n",
+    "df_crash.index = range(1, len(df_crash) + 1)\n",
+    "df_crash = df_crash.rename_axis('Index')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 163,
+   "id": "c1d94d27",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((2559, 5),\n",
+       " Index(['Penn Dot municipal ID number', 'Municipality Name',\n",
+       "        'Total number of people killed or injuried in crashes from 2014 to 2024',\n",
+       "        'Total people injuried in crashes from 2014 to 2024',\n",
+       "        'Total people killed in crashes from 2014 to 2024'],\n",
+       "       dtype='object'),\n",
+       " Penn Dot municipal ID number                                               int64\n",
+       " Municipality Name                                                         object\n",
+       " Total number of people killed or injuried in crashes from 2014 to 2024     int64\n",
+       " Total people injuried in crashes from 2014 to 2024                         int64\n",
+       " Total people killed in crashes from 2014 to 2024                           int64\n",
+       " dtype: object)"
+      ]
+     },
+     "execution_count": 163,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#View dataframe\n",
+    "\n",
+    "df_crash.shape, df_crash.columns, df_crash.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "id": "10a32ef0",
+   "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>Penn Dot municipal ID number</th>\n",
+       "      <th>Municipality Name</th>\n",
+       "      <th>Total number of people killed or injuried in crashes from 2014 to 2024</th>\n",
+       "      <th>Total people injuried in crashes from 2014 to 2024</th>\n",
+       "      <th>Total people killed in crashes from 2014 to 2024</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Index</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>67301</td>\n",
+       "      <td>Philadelphia City</td>\n",
+       "      <td>103713</td>\n",
+       "      <td>102556</td>\n",
+       "      <td>1157</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2301</td>\n",
+       "      <td>Pittsburgh City</td>\n",
+       "      <td>21800</td>\n",
+       "      <td>21604</td>\n",
+       "      <td>196</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>39301</td>\n",
+       "      <td>Allentown City</td>\n",
+       "      <td>10556</td>\n",
+       "      <td>10496</td>\n",
+       "      <td>60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>25302</td>\n",
+       "      <td>Erie City</td>\n",
+       "      <td>7610</td>\n",
+       "      <td>7545</td>\n",
+       "      <td>65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>35302</td>\n",
+       "      <td>Scranton City</td>\n",
+       "      <td>6781</td>\n",
+       "      <td>6730</td>\n",
+       "      <td>51</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>46104</td>\n",
+       "      <td>Lower Merion Twp</td>\n",
+       "      <td>5896</td>\n",
+       "      <td>5870</td>\n",
+       "      <td>26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>6301</td>\n",
+       "      <td>Reading City</td>\n",
+       "      <td>5772</td>\n",
+       "      <td>5729</td>\n",
+       "      <td>43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9202</td>\n",
+       "      <td>Bensalem Twp</td>\n",
+       "      <td>5752</td>\n",
+       "      <td>5680</td>\n",
+       "      <td>72</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>36101</td>\n",
+       "      <td>Manheim Twp</td>\n",
+       "      <td>4604</td>\n",
+       "      <td>4574</td>\n",
+       "      <td>30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>48301</td>\n",
+       "      <td>Bethlehem City</td>\n",
+       "      <td>4233</td>\n",
+       "      <td>4208</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Penn Dot municipal ID number   Municipality Name  \\\n",
+       "Index                                                     \n",
+       "1                             67301   Philadelphia City   \n",
+       "2                              2301     Pittsburgh City   \n",
+       "3                             39301      Allentown City   \n",
+       "4                             25302           Erie City   \n",
+       "5                             35302       Scranton City   \n",
+       "6                             46104    Lower Merion Twp   \n",
+       "7                              6301        Reading City   \n",
+       "8                              9202        Bensalem Twp   \n",
+       "9                             36101         Manheim Twp   \n",
+       "10                            48301      Bethlehem City   \n",
+       "\n",
+       "       Total number of people killed or injuried in crashes from 2014 to 2024  \\\n",
+       "Index                                                                           \n",
+       "1                                                 103713                        \n",
+       "2                                                  21800                        \n",
+       "3                                                  10556                        \n",
+       "4                                                   7610                        \n",
+       "5                                                   6781                        \n",
+       "6                                                   5896                        \n",
+       "7                                                   5772                        \n",
+       "8                                                   5752                        \n",
+       "9                                                   4604                        \n",
+       "10                                                  4233                        \n",
+       "\n",
+       "       Total people injuried in crashes from 2014 to 2024  \\\n",
+       "Index                                                       \n",
+       "1                                                 102556    \n",
+       "2                                                  21604    \n",
+       "3                                                  10496    \n",
+       "4                                                   7545    \n",
+       "5                                                   6730    \n",
+       "6                                                   5870    \n",
+       "7                                                   5729    \n",
+       "8                                                   5680    \n",
+       "9                                                   4574    \n",
+       "10                                                  4208    \n",
+       "\n",
+       "       Total people killed in crashes from 2014 to 2024  \n",
+       "Index                                                    \n",
+       "1                                                  1157  \n",
+       "2                                                   196  \n",
+       "3                                                    60  \n",
+       "4                                                    65  \n",
+       "5                                                    51  \n",
+       "6                                                    26  \n",
+       "7                                                    43  \n",
+       "8                                                    72  \n",
+       "9                                                    30  \n",
+       "10                                                   25  "
+      ]
+     },
+     "execution_count": 164,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Print table\n",
+    "\n",
+    "df_crash.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "29802c61",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Export data to CSV file\n",
+    "\n",
+    "df_crash.to_csv('C:/Document/Projects/CCLA ASM/PennDot_Bicycle_Crashes.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b75de359",
+   "metadata": {},
+   "source": [
+    "## 2. Data Visualization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d965b171",
+   "metadata": {},
+   "source": [
+    "### a. Top 10 Municipalities with Highest Cyclists Fatalities and Serious Injury in Pennsylvania from 2014 to 2024"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 172,
+   "id": "d391398b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get top 10 municipalities\n",
+    "top10_crashes = df_crash.head(10)\n",
+    "\n",
+    "# Plot\n",
+    "bar_graph = top10_crashes.plot(\n",
+    "    x='Municipality Name',\n",
+    "    y=[\n",
+    "        'Total people injuried in crashes from 2014 to 2024',\n",
+    "        'Total people killed in crashes from 2014 to 2024'\n",
+    "    ],\n",
+    "    kind='barh',\n",
+    "    stacked=True\n",
+    ")\n",
+    "\n",
+    "# Style THIS axis\n",
+    "bar_graph.legend(loc='upper left')\n",
+    "bar_graph.set_xlabel('Number of people')\n",
+    "bar_graph.set_ylabel('Municipality Name')\n",
+    "bar_graph.set_title('Top 10 Municipalities with Highest Fatalities & Injuries in PA (2014–2024)')\n",
+    "\n",
+    "# (optional) show the largest at the top and fix layout\n",
+    "bar_graph.invert_yaxis()\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "738f8a4e",
+   "metadata": {},
+   "source": [
+    "### b, Number of Cyclists Killed and Severely Injured in Crashes with Automobiles from 2014 to 2024"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 176,
+   "id": "d31a1f42",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   Year  INJURY_COUNT\n",
+      "0  2014         79925\n",
+      "1  2015         82292\n",
+      "2  2016         83109\n",
+      "3  2017         80869\n",
+      "4  2018         78303\n",
+      "5  2019         76366\n",
+      "6  2020         61361\n",
+      "7  2021         69784\n",
+      "8  2022         67146\n",
+      "9  2023         66774\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "base_dir = r\"C:/Users/maidn/OneDrive - Dickinson College/Dickinson/senior/DATA 400/mini project data\"\n",
+    "years = range(2014, 2024)\n",
+    "\n",
+    "rows = []\n",
+    "for y in years:\n",
+    "    fp = fr\"{base_dir}/Statewide_{y}/CRASH_{y}.csv\"\n",
+    "    dfy = pd.read_csv(fp, usecols=['INJURY_COUNT'], low_memory=False)\n",
+    "    inj = pd.to_numeric(dfy['INJURY_COUNT'], errors='coerce').fillna(0).sum()\n",
+    "    rows.append({'Year': y, 'INJURY_COUNT': inj})\n",
+    "\n",
+    "yearly = pd.DataFrame(rows)\n",
+    "\n",
+    "print(yearly)  # sanity check\n",
+    "\n",
+    "ax = yearly.plot(x='Year', y='INJURY_COUNT', kind='line', marker='o', legend=True)\n",
+    "ax.set_xlabel('Year')\n",
+    "ax.set_ylabel('People injured')\n",
+    "ax.set_title(f'People Injured in Crashes ({years.start}–{years.stop-1})')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb21f034",
+   "metadata": {},
+   "source": [
+    "### c, Number of People Killed in Crashes from 2014 to 2024"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 175,
+   "id": "d2775af0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   Year  FATAL_COUNT\n",
+      "0  2014         1195\n",
+      "1  2015         1200\n",
+      "2  2016         1188\n",
+      "3  2017         1137\n",
+      "4  2018         1190\n",
+      "5  2019         1059\n",
+      "6  2020         1129\n",
+      "7  2021         1230\n",
+      "8  2022         1179\n",
+      "9  2023         1209\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "base_dir = r\"C:/Users/maidn/OneDrive - Dickinson College/Dickinson/senior/DATA 400/mini project data\"\n",
+    "years = range(2014, 2024)\n",
+    "\n",
+    "rows = []\n",
+    "for y in years:\n",
+    "    fp = fr\"{base_dir}/Statewide_{y}/CRASH_{y}.csv\"\n",
+    "    dfy = pd.read_csv(fp, usecols=['FATAL_COUNT'], low_memory=False)\n",
+    "    inj = pd.to_numeric(dfy['FATAL_COUNT'], errors='coerce').fillna(0).sum()\n",
+    "    rows.append({'Year': y, 'FATAL_COUNT': inj})\n",
+    "\n",
+    "yearly = pd.DataFrame(rows)\n",
+    "\n",
+    "print(yearly)  # sanity check\n",
+    "\n",
+    "ax = yearly.plot(x='Year', y='FATAL_COUNT', kind='line', marker='o', legend=True)\n",
+    "ax.set_xlabel('Year')\n",
+    "ax.set_ylabel('People injured')\n",
+    "ax.set_title(f'People Killed in Crashes ({years.start}–{years.stop-1})')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "260d60cb",
+   "metadata": {},
+   "source": [
+    "### c. Number of People Killed in Crashes from 2014 to 2024"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 170,
+   "id": "cea7e8df",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "veh_map = {\n",
+    "    'AUTOMOBILE_COUNT':  'Automobile',\n",
+    "    'SMALL_TRUCK_COUNT': 'Small truck',\n",
+    "    'HEAVY_TRUCK_COUNT': 'Heavy truck',\n",
+    "    'BUS_COUNT':         'Bus',\n",
+    "    'VAN_COUNT':         'Van',\n",
+    "    'MOTORCYCLE_COUNT':  'Motorcycle',\n",
+    "    'BICYCLE_COUNT':     'Bicycle',\n",
+    "}\n",
+    "\n",
+    "# totals per vehicle type (only columns that exist)\n",
+    "totals = pd.Series({lbl: df_copy[col].sum()\n",
+    "                    for col, lbl in veh_map.items()\n",
+    "                    if col in df_copy.columns}).sort_values(ascending=False)\n",
+    "\n",
+    "title = (f\"Vehicles involved in crashes ({int(df_copy['Year'].min())}–{int(df_copy['Year'].max())})\"\n",
+    "         if 'Year' in df_copy.columns else \"Vehicles involved in crashes\")\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(8, 6))\n",
+    "wedges, _ = ax.pie(\n",
+    "    totals.values,\n",
+    "    startangle=90,\n",
+    "    wedgeprops={'width': 0.45, 'edgecolor': 'white'}  # donut style\n",
+    ")\n",
+    "ax.set(aspect='equal', title=title)\n",
+    "\n",
+    "# legend with percentages\n",
+    "labels = [f\"{k}: {v/totals.sum():.1%}\" for k, v in totals.items()]\n",
+    "ax.legend(wedges, labels, title=\"Vehicle type (share)\",\n",
+    "          loc=\"center left\", bbox_to_anchor=(1.02, 0.5), frameon=False)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f06831b5",
+   "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": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/MelanieDuong_MiniProject_Idea 1.pdf b/MelanieDuong_MiniProject_Idea 1.pdf
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