{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "URL: https://docs.bokeh.org/en/latest/docs/examples/topics/geo/texas_hover_map.html\n",
    "\n",
    "Most examples work across multiple plotting backends, this example is also available for:\n",
    "\n",
    "* [Matplotlib - texas choropleth example](../matplotlib/texas_choropleth_example.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import holoviews as hv\n",
    "from holoviews import opts\n",
    "hv.extension('bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Declaring data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.sampledata.us_counties import data as counties\n",
    "from bokeh.sampledata.unemployment import data as unemployment\n",
    "\n",
    "counties = [dict(county, Unemployment=unemployment[cid])\n",
    "            for cid, county in counties.items()\n",
    "            if county[\"state\"] == \"tx\"]\n",
    "\n",
    "detailed_name = 'detailed_name' if counties[0].get('detailed_name') else 'detailed name' # detailed name was changed in Bokeh 3.0\n",
    "choropleth = hv.Polygons(counties, ['lons', 'lats'], [(detailed_name, 'County'), 'Unemployment'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "choropleth.opts(\n",
    "    opts.Polygons(logz=True, tools=['hover'], xaxis=None, yaxis=None,\n",
    "                   show_grid=False, show_frame=False, width=500, height=500,\n",
    "                   color_index='Unemployment', colorbar=True, toolbar='above', line_color='white'))"
   ]
  }
 ],
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  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
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 "nbformat_minor": 4
}