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<!DOCTYPE html> <html class="ocks-org do-not-copy"> <meta charset="utf-8"> <title>The Wealth & Health of Nations</title> <style> @import url(../style.css?aea6f0a); #chart { margin-left: -40px; height: 506px; } text { font: 10px sans-serif; } .dot { stroke: #000; } .axis path, .axis line { fill: none; stroke: #000; shape-rendering: crispEdges; } .label { fill: #777; } .year.label { font: 500 196px "Helvetica Neue"; fill: #ddd; } .year.label.active { fill: #aaa; } .overlay { fill: none; pointer-events: all; cursor: ew-resize; } </style> <header> <aside>March 13, 2012</aside> <a href="../" rel="author">Mike Bostock</a> </header> <h1>The Wealth & Health of Nations</h1> <p id="chart"></p> <aside>Mouseover the year to move forward and backwards through time.</aside> <p class="attribution">Source: <a href="https://github.com/RandomEtc/mind-gapper-js">Tom Carden</a>, <a href="https://gapminder.org">Gapminder</a>. <p>This is a recreation in <a href="https://d3js.org/">D3</a> of Gapminder’s <a href="https://gapminder.org/world/">Wealth & Health of Nations</a>, made famous by Hans Rosling’s memorable <a href="https://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html">2006 TED talk</a>. It shows the dynamic fluctuation in per-capita income (<i>x</i>), life expectancy (<i>y</i>) and population (radius) of 180 nations over the last 209 years. Nations are colored by geographic region; mouseover to read their names. <p>As <a href="https://randometc.github.com/mind-gapper-js/">Tom Carden</a> noted, there’s a surprising amount of work that goes into making something look simple. For one, data collected in recent years is consistent, while data prior to 1950 is sparse; although potentially misleading, these visualizations use <a href="https://en.wikipedia.org/wiki/Lerp_(computing)">linear interpolation</a> for missing data points. The lookup for the two interpolation values at each frame is accelerated using <a href="https://en.wikipedia.org/wiki/Binary_search_algorithm">bisection</a> of sorted arrays per dimension. <p>Interested to see how this chart was implemented? <a href="view-source:https://bost.ocks.org/mike/nations/">View source!</a> Want a fun project? Try adding a <a href="https://github.com/mbostock/d3/wiki/Voronoi-Geom">Voronoi overlay</a> (as in this <a href="https://mbostock.github.com/d3/talk/20111116/airports.html">airport diagram</a>) to improve mouseover interaction on small targets. Or try a static version, using trails instead of motion. <script src="//d3js.org/d3.v3.min.js" charset="utf-8"></script> <script> // Various accessors that specify the four dimensions of data to visualize. function x(d) { return d.income; } function y(d) { return d.lifeExpectancy; } function radius(d) { return d.population; } function color(d) { return d.region; } function key(d) { return d.name; } // Chart dimensions. var margin = {top: 19.5, right: 19.5, bottom: 19.5, left: 39.5}, width = 960 - margin.right, height = 500 - margin.top - margin.bottom; // Various scales. These domains make assumptions of data, naturally. var xScale = d3.scale.log().domain([300, 1e5]).range([0, width]), yScale = d3.scale.linear().domain([10, 85]).range([height, 0]), radiusScale = d3.scale.sqrt().domain([0, 5e8]).range([0, 40]), colorScale = d3.scale.category10(); // The x & y axes. var xAxis = d3.svg.axis().orient("bottom").scale(xScale).ticks(12, d3.format(",d")), yAxis = d3.svg.axis().scale(yScale).orient("left"); // Create the SVG container and set the origin. var svg = d3.select("#chart").append("svg") .attr("width", width + margin.left + margin.right) .attr("height", height + margin.top + margin.bottom) .append("g") .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); // Add the x-axis. svg.append("g") .attr("class", "x axis") .attr("transform", "translate(0," + height + ")") .call(xAxis); // Add the y-axis. svg.append("g") .attr("class", "y axis") .call(yAxis); // Add an x-axis label. svg.append("text") .attr("class", "x label") .attr("text-anchor", "end") .attr("x", width) .attr("y", height - 6) .text("income per capita, inflation-adjusted (dollars)"); // Add a y-axis label. svg.append("text") .attr("class", "y label") .attr("text-anchor", "end") .attr("y", 6) .attr("dy", ".75em") .attr("transform", "rotate(-90)") .text("life expectancy (years)"); // Add the year label; the value is set on transition. var label = svg.append("text") .attr("class", "year label") .attr("text-anchor", "end") .attr("y", height - 24) .attr("x", width) .text(1800); // Load the data. d3.json("nations.json", function(nations) { // A bisector since many nation's data is sparsely-defined. var bisect = d3.bisector(function(d) { return d[0]; }); // Add a dot per nation. Initialize the data at 1800, and set the colors. var dot = svg.append("g") .attr("class", "dots") .selectAll(".dot") .data(interpolateData(1800)) .enter().append("circle") .attr("class", "dot") .style("fill", function(d) { return colorScale(color(d)); }) .call(position) .sort(order); // Add a title. dot.append("title") .text(function(d) { return d.name; }); // Add an overlay for the year label. var box = label.node().getBBox(); var overlay = svg.append("rect") .attr("class", "overlay") .attr("x", box.x) .attr("y", box.y) .attr("width", box.width) .attr("height", box.height) .on("mouseover", enableInteraction); // Start a transition that interpolates the data based on year. svg.transition() .duration(30000) .ease("linear") .tween("year", tweenYear) .each("end", enableInteraction); // Positions the dots based on data. function position(dot) { dot .attr("cx", function(d) { return xScale(x(d)); }) .attr("cy", function(d) { return yScale(y(d)); }) .attr("r", function(d) { return radiusScale(radius(d)); }); } // Defines a sort order so that the smallest dots are drawn on top. function order(a, b) { return radius(b) - radius(a); } // After the transition finishes, you can mouseover to change the year. function enableInteraction() { var yearScale = d3.scale.linear() .domain([1800, 2009]) .range([box.x + 10, box.x + box.width - 10]) .clamp(true); // Cancel the current transition, if any. svg.transition().duration(0); overlay .on("mouseover", mouseover) .on("mouseout", mouseout) .on("mousemove", mousemove) .on("touchmove", mousemove); function mouseover() { label.classed("active", true); } function mouseout() { label.classed("active", false); } function mousemove() { displayYear(yearScale.invert(d3.mouse(this)[0])); } } // Tweens the entire chart by first tweening the year, and then the data. // For the interpolated data, the dots and label are redrawn. function tweenYear() { var year = d3.interpolateNumber(1800, 2009); return function(t) { displayYear(year(t)); }; } // Updates the display to show the specified year. function displayYear(year) { dot.data(interpolateData(year), key).call(position).sort(order); label.text(Math.round(year)); } // Interpolates the dataset for the given (fractional) year. function interpolateData(year) { return nations.map(function(d) { return { name: d.name, region: d.region, income: interpolateValues(d.income, year), population: interpolateValues(d.population, year), lifeExpectancy: interpolateValues(d.lifeExpectancy, year) }; }); } // Finds (and possibly interpolates) the value for the specified year. function interpolateValues(values, year) { var i = bisect.left(values, year, 0, values.length - 1), a = values[i]; if (i > 0) { var b = values[i - 1], t = (year - a[0]) / (b[0] - a[0]); return a[1] * (1 - t) + b[1] * t; } return a[1]; } }); </script>
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