{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <img align=\"left\" src=\"https://github.com/lux-org/lux-resources/blob/master/icon/table.png?raw=True\" width=\"30\">\n",
    "    <h1 style=\"padding-left: 40px;\">Visualizations of dataframes beyond simple tables</h1>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import lux\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"https://github.com/lux-org/lux-datasets/blob/master/data/hpi_cleaned.csv?raw=True\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <img align=\"left\" src=\"https://github.com/lux-org/lux-resources/blob/master/icon/steering-wheel.png?raw=True\" width=\"30\">\n",
    "    <h1 style=\"padding-left: 40px;\">Steering analysis with intent</h1>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.intent = [\"Inequality\",\"AvrgLifeExpectancy\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <img align=\"left\" src=\"https://github.com/lux-org/lux-resources/blob/master/icon/fix.png?raw=True\" width=\"30\">\n",
    "    <h1 style=\"padding-left: 40px;\">Data Manipulation + Vis without changing a line of your Pandas code</h1>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "covid = pd.read_csv(\"https://github.com/lux-org/lux-datasets/blob/master/data/covid_cleaned.csv?raw=True\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = covid.merge(df,left_on=[\"Entity\",\"Code\"],right_on=[\"Country\",\"cca3\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 🤔 Some interesting findings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.intent = [\"Inequality\",\"AvrgLifeExpectancy\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://github.com/lux-org/lux-resources/blob/master/doc_img/hpi-covid-outlier.png?raw=True\" width=\"250\"></img>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <img align=\"left\" style=\"margin-top: -10px;\" src=\"https://github.com/lux-org/lux-resources/blob/master/icon/present.png?raw=True\" width=\"50\">\n",
    "    <h1 style=\"padding-left: 55px;\">Exporting visualization insight to edit and share</h1>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.exported"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(df.exported[0].to_code(\"altair\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can copy-and-paste the output Altair code into a separate cell. Then let's tweak the plotting code a bit before sharing this insight with our colleagues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import altair as alt\n",
    "\n",
    "c = \"#e7298a\"\n",
    "chart = alt.Chart(df,title=\"Check out this cool insight!\").mark_circle().encode(\n",
    "    x=alt.X('Inequality',scale=alt.Scale(domain=(0.04, 0.51)),type='quantitative', axis=alt.Axis(title='Inequality')),\n",
    "    y=alt.Y('AvrgLifeExpectancy',scale=alt.Scale(domain=(48.9, 83.6)),type='quantitative', axis=alt.Axis(title='AvrgLifeExpectancy'))\n",
    ")\n",
    "highlight = df[(df[\"Inequality\"]>0.35)&(df[\"stringency_level\"]==\"High\")]\n",
    "\n",
    "hchart = alt.Chart(highlight).mark_point(color=c,size=50,shape=\"cross\").encode(\n",
    "    x=alt.X('Inequality',scale=alt.Scale(domain=(0.04, 0.51)),type='quantitative', axis=alt.Axis(title='Inequality')),\n",
    "    y=alt.Y('AvrgLifeExpectancy',scale=alt.Scale(domain=(48.9, 83.6)),type='quantitative', axis=alt.Axis(title='AvrgLifeExpectancy')),\n",
    ")\n",
    "\n",
    "text = alt.Chart(highlight).mark_text(color=c,dx=-35,dy=0,fontWeight=800).encode(\n",
    "    x=alt.X('Inequality',scale=alt.Scale(domain=(0.04, 0.51)),type='quantitative', axis=alt.Axis(title='Inequality')),\n",
    "    y=alt.Y('AvrgLifeExpectancy',scale=alt.Scale(domain=(48.9, 83.6)),type='quantitative', axis=alt.Axis(title='AvrgLifeExpectancy')),\n",
    "    text=alt.Text('Country')\n",
    ")\n",
    "\n",
    "chart = chart.encode(color=alt.Color('stringency_level',type='nominal'))\n",
    "chart = chart.properties(width=160,height=150)\n",
    "\n",
    "(chart + hchart + text).configure_title(color=c)\n"
   ]
  }
 ],
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