dataset_curation/denver.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Denver, USA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Source of original dataset:** https://data.drcog.org/data?q=crash\\&categories[0]=Transportation\n",
    "\n",
    "**Location of accidents:** Latitude, Longitude\n",
    "\n",
    "**Date of accidents:** Date\n",
    "\n",
    "**Outcome of accidents:** FATALITIES, SERIOUSLY_INJURED, PDO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('max_columns', None)\n",
    "pd.set_option('display.max_colwidth', -1)\n",
    "import numpy as np\n",
    "from plotly import graph_objects as go\n",
    "import plotly.express as px\n",
    "from itertools import chain\n",
    "import matplotlib.pyplot as plt\n",
    "import pyproj\n",
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setup input files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = \"../data/denver/\"\n",
    "metadata_file = data_dir + \"Meta_Data.xlsx\"\n",
    "data_file = data_dir + \"traffic_accidents.csv\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read original data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(data_file)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create Datetime column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Date'] = pd.to_datetime(data['REPORTED_DATE'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setup latitude & longitude column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Latitude'] = data['GEO_LAT']\n",
    "data['Longitude'] = data['GEO_LON']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some key statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Accidents between '+str(data['REPORTED_DATE'].min())+' and '+str(data['REPORTED_DATE'].max()))\n",
    "\n",
    "total_accidents = data.shape[0]\n",
    "print(\"There are a total of \"+str(total_accidents)+\" accidents.\")\n",
    "\n",
    "fatalities = data[\"FATALITIES\"].sum()\n",
    "print(\"There are a total of \"+str(fatalities)+\" fatalities.\")\n",
    "\n",
    "serious_injuries = data[\"SERIOUSLY_INJURED\"].sum()\n",
    "print(\"There are a total of \"+str(serious_injuries)+\" seriously injured.\")\n",
    "\n",
    "bicycles = data[\"BICYCLE_IND\"].sum()\n",
    "print(\"There are a total of \"+str(bicycles)+\" bicycles involved in all the accidents.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Slice all bicycle accidents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_bicycles = data[data['BICYCLE_IND']>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_bicycles.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(data_bicycles.shape)\n",
    "data_bicycles.to_csv('cycling_safety_denver.csv')\n",
    "print('Wrote file to: cycling_safety_denver.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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