{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Auto Accidents(1975-2017)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import cuxfilter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cuxfilter\n",
    "from cuxfilter import charts\n",
    "from cuxfilter.layouts import feature_and_base"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#update data_dir if you have downloaded datasets elsewhere\n",
    "DATA_DIR = './data'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download required datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cuxfilter.sampledata import datasets_check\n",
    "datasets_check('auto_accidents', base_dir=DATA_DIR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cux_df = cuxfilter.DataFrame.from_arrow('./data/auto_accidents.arrow')\n",
    "cux_df.data['ST_CASE'] = cux_df.data['ST_CASE'].astype('float64')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define Charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add mappings for day of week\n",
    "label_map = {\n",
    "    1: 'Sunday',\n",
    "    2: 'Monday',\n",
    "    3: 'Tuesday',\n",
    "    4: 'Wednesday',\n",
    "    5: 'Thursday',\n",
    "    6: 'Friday',\n",
    "    7: 'Saturday',\n",
    "    9: 'Unknown'\n",
    "}\n",
    "cux_df.data['DAY_WEEK_STR'] = cux_df.data.DAY_WEEK.map(label_map)\n",
    "gtc_demo_red_blue_palette = [ \"#3182bd\", \"#6baed6\", \"#7b8ed8\", \"#e26798\", \"#ff0068\" , \"#323232\" ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Uncomment the below lines and replace MAPBOX_TOKEN with mapbox token string if you want to use mapbox map-tiles. Can be created for free here -https://www.mapbox.com/help/define-access-token/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "chart1 = cuxfilter.charts.scatter(x='dropoff_x', y='dropoff_y', aggregate_col='DAY_WEEK', aggregate_fn='mean',\n",
    "                                        tile_provider=\"CartoLight\",\n",
    "                                         color_palette=gtc_demo_red_blue_palette,pixel_shade_type='linear', unselected_alpha=0.2)\n",
    "\n",
    "# Since cuxfilter 23.08, bar charts work with str columns\n",
    "chart2 = cuxfilter.charts.bar('DAY_WEEK_STR')\n",
    "\n",
    "chart3 = cuxfilter.charts.multi_select('YEAR')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a dashboard object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = cux_df.dashboard([chart1, chart2], sidebar=[chart3], layout=cuxfilter.layouts.feature_and_base,theme = cuxfilter.themes.default, title='Auto Accident Dataset')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#run dashboard inline within the notebook cell\n",
    "d.app()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Starting the dashboard"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. d.show('current_notebook_url:current_notebook_port') remote dashboard\n",
    "\n",
    "2. d.app() inline within the notebook cell\n",
    "\n",
    "Incase you need to stop the server:\n",
    "\n",
    "- d.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![auto-accidents](../../../_images/auto-accidents.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export the queried data into a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "queried_df = d.export()"
   ]
  }
 ],
 "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}