{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import holoviews as hv\n",
    "import pandas as pd\n",
    "\n",
    "from holoviews import dim\n",
    "from bokeh.sampledata.gapminder import regions, life_expectancy\n",
    "\n",
    "hv.extension('bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Declaring data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "group1 = 'South Asia'\n",
    "group2 = 'East Asia & Pacific'\n",
    "\n",
    "group1_countries = list(regions[regions.Group==group1].index)\n",
    "group2_countries = list(regions[regions.Group==group2].index)\n",
    "\n",
    "group1_df = life_expectancy.loc[group1_countries]\n",
    "group1_df['Region'] = group1\n",
    "group2_df = life_expectancy.loc[group2_countries]\n",
    "group2_df['Region'] = group2\n",
    "\n",
    "data = pd.concat([group1_df, group2_df]).reset_index().melt('Region', life_expectancy.columns, var_name='Year', value_name='Life Expectancy')\n",
    "\n",
    "violin = hv.Violin(data, ['Year', 'Region'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "violin.opts(split='Region', xrotation=90, responsive=True, min_height=500, show_legend=True, violin_width=1.5, legend_position='bottom_right', title='Life Expectancy by Year for Asian subregions', fontscale=1.5)"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
