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Added Wealth of Nations example
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‎examples/Wealth of Nations.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This is a `bqplot` recreation of Mike Bostock's [Wealth of Nations](https://bost.ocks.org/mike/nations/). This was also done by [Gapminder](http://www.gapminder.org/world/#$majorMode=chart$is;shi=t;ly=2003;lb=f;il=t;fs=11;al=30;stl=t;st=t;nsl=t;se=t$wst;tts=C$ts;sp=5.59290322580644;ti=2013$zpv;v=0$inc_x;mmid=XCOORDS;iid=phAwcNAVuyj1jiMAkmq1iMg;by=ind$inc_y;mmid=YCOORDS;iid=phAwcNAVuyj2tPLxKvvnNPA;by=ind$inc_s;uniValue=8.21;iid=phAwcNAVuyj0XOoBL_n5tAQ;by=ind$inc_c;uniValue=255;gid=CATID0;by=grp$map_x;scale=log;dataMin=194;dataMax=96846$map_y;scale=lin;dataMin=23;dataMax=86$map_s;sma=49;smi=2.65$cd;bd=0$inds=;modified=60). It is originally based on a TED Talk by [Hans Rosling](http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Required imports"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from bqplot import (LogScale, LinearScale, OrdinalColorScale, ColorAxis, Axis, Scatter, CATEGORY10,\n",
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" Figure)\n",
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"from bqplot.default_tooltip import Tooltip\n",
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"from ipywidgets import VBox, IntSlider, Button\n",
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"from IPython.display import display\n",
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"import os\n",
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"import numpy as np\n",
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"from time import sleep"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Cleaning and Formatting JSON Data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false,
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"scrolled": false
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},
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"outputs": [],
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"source": [
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"data = pd.read_json(os.path.abspath('data_files/nations.json'))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def clean_data(data):\n",
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" for i in [0, 1, 3]:\n",
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" data = data.drop(data[data.ix[:, i].apply(len) <= 4].index)\n",
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" return data\n",
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"\n",
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"def extrap_data(data):\n",
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" for i in [0, 1, 3]:\n",
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" data.ix[:, i] = data.ix[:, i].apply(extrap_interp)\n",
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" return data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def extrap_interp(data):\n",
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" data = np.array(data)\n",
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" x_range = np.arange(1800, 2009, 1.)\n",
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" y_range = np.interp(x_range, data[:, 0], data[:, 1])\n",
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" return y_range"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"data = clean_data(data)\n",
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"data = extrap_data(data)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"income_min, income_max = np.min(data.ix[:, 0].apply(np.min)), np.max(data.ix[:, 0].apply(np.max))\n",
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"life_exp_min, life_exp_max = np.min(data.ix[:, 1].apply(np.min)), np.max(data.ix[:, 1].apply(np.max))\n",
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"pop_min, pop_max = np.min(data.ix[:, 3].apply(np.min)), np.max(data.ix[:, 3].apply(np.max))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Defining Scales"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"x_sc = LogScale(min=income_min, max=income_max)\n",
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"y_sc = LinearScale(min=life_exp_min, max=life_exp_max)\n",
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"c_sc = OrdinalColorScale(domain=data['region'].unique().tolist(), colors=CATEGORY10[:6])\n",
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"size_sc = LinearScale(min=pop_min, max=pop_max)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Defining the Axes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"ax_y = Axis(label='Life Expectancy', scale=y_sc, orientation='vertical', side='left')\n",
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"ax_x = Axis(label='Income per Capita', scale=x_sc)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Creating a Slider for the years"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"year_slider = IntSlider(min=1800, max=2008, step=1, description='Year', value=1800)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Creating a Button for the animation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"animate_button = Button(description='Play', background_color='MediumSeaGreen', color='Black', icon='fa-play')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Helper functions for parsing the data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def _get_index_data(data, index=0):\n",
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" return data[index]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"def get_data():\n",
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" income = data.ix[:, 0].apply(lambda x: _get_index_data(x, year_slider.value-1800))\n",
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" life_exp = data.ix[:, 1].apply(lambda x: _get_index_data(x, year_slider.value-1800))\n",
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" pop = data.ix[:, 3].apply(lambda x: _get_index_data(x, year_slider.value-1800))\n",
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" return income, life_exp, pop"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"cap_income, life_exp, pop = get_data()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Creating the Tooltip to display the required fields"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"tt = Tooltip(fields=['name', 'x', 'y'], labels=['Country Name', 'Income per Capita', 'Life Expectancy'])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Creating the Scatter Mark with the appropriate size and color parameters passed"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"wealth_scat = Scatter(x=cap_income, y=life_exp, color=data['region'], size=pop, names=data['name'],\n",
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" display_names=False, scales={'x': x_sc, 'y': y_sc, 'color': c_sc, 'size': size_sc},\n",
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" default_size=4112, tooltip=tt, animate=True, stroke='Black')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Creating the Figure"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"fig = Figure(marks=[wealth_scat], axes=[ax_x, ax_y], title='Health and Wealth of Nations', fig_color='White',\n",
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" animation_duration=100)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Defining the callback for the slider"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"def year_changed(new):\n",
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" wealth_scat.x, wealth_scat.y, wealth_scat.size = get_data()\n",
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" \n",
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"year_slider.observe(year_changed, 'value')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Defining the callback for the button"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def button_clicked(value):\n",
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" animate_button.visible = False\n",
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" for i in range(1800, 2009, 1):\n",
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" year_slider.value = i\n",
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" sleep(0.05)\n",
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" animate_button.visible = True\n",
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"\n",
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"animate_button.on_click(button_clicked)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Displaying the GUI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"display(VBox([animate_button, fig, year_slider]))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.11"
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},
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"widgets": {
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"state": {},
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"version": "2.0.0-dev"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

‎examples/data_files/nations.json

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