This grouped bar chart is constructed from a CSV file storing the populations of different states by age group. The chart employs conventional margins and a number of D3 features:
xxxxxxxxxx<style>.axis .domain { display: none;}</style><svg width="960" height="500"></svg><script src="https://d3js.org/d3.v4.min.js"></script><script>// Commented version of// https://bl.ocks.org/mbostock/3887051// Variablesvar svg = d3.select("svg"), margin = {top: 20, right: 20, bottom: 30, left: 40}, width = +svg.attr("width") - margin.left - margin.right, height = +svg.attr("height") - margin.top - margin.bottom;// SVG G to provide D3 Margin Conventionvar g = svg.append("g").attr("transform", "translate(" + margin.left + "," + margin.top + ")");// X0 (horizontal axis) represents the state categoriesvar x0 = d3.scaleBand() .rangeRound([0, width]) .paddingInner(0.1);// X1 (horizontal axis) represents the age group categoriesvar x1 = d3.scaleBand() .padding(0.05);// Y (vertical axis) represents the population in millionsvar y = d3.scaleLinear() .rangeRound([height, 0]);// Z represents the color scheme to be used for the various age groupsvar z = d3.scaleOrdinal() .range(["#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]);// Define variable to give us access to AJAX callback function datavar outsideData;// CSV AJAX call to ingest data// data file requested: data.csv// function to process data: function(d, i, columns) {...}// function to be used on call back: function(error, data) {...}d3.csv("data.csv", function(d, i, columns) { for (var i = 1, n = columns.length; i < n; ++i) d[columns[i]] = +d[columns[i]]; return d;}, function(error, data) { if (error) throw error; // assign internal data variable to outsideData variable so we can see data // once the AJAX callback function has been run. outsideData = data; // Get the keys by taking a slice off of the column headings // (means remove the element 0, and return array from index 1 to end) // Returns array containing: // "Under 5 Years", "5 to 13 Years", "14 to 17 Years", // "18 to 24 Years", "25 to 44 Years", "45 to 64 Years", // "65 Years and Over" var keys = data.columns.slice(1); // Finish defining the X0 (horizontal) state categories scale x0.domain(data.map(function(d) { return d.State; })); // Finish defining the X1 (horizontal) state categories scale // Use the bandwidth of each state to set to range of x1 // The rounding gives a nice visual effect x1.domain(keys).rangeRound([0, x0.bandwidth()]); // Finish defining the Y axis // Note the following: // - d3.max(data...) // - d3.max(keys, ...) // => Think of it as a nested for loop // => loop through each state and then within each state loop through each age group y.domain([0, d3.max(data, function(d) { return d3.max(keys, function(key) { return d[key]; }); })]).nice(); // Double Data Join // First data join will give us the states // - Each g receives state and age group object // Second data join will give us the rectangles // - Within the data join, we build a new object from scratch // - These will be the specific age groups // - Each rectangle receives the specific age group per state // - By the end of this, we have a small bar chart for each agre group. g.append("g") .selectAll("g") .data(data) .enter().append("g") .attr("transform", function(d) { return "translate(" + x0(d.State) + ",0)"; }) .selectAll("rect") .data(function(d) { return keys.map(function(key) { return {key: key, value: d[key]}; }); }) .enter().append("rect") .attr("x", function(d) { return x1(d.key); }) .attr("y", function(d) { return y(d.value); }) .attr("width", x1.bandwidth()) .attr("height", function(d) { return height - y(d.value); }) .attr("fill", function(d) { return z(d.key); }); // Create the X Axis g.append("g") .attr("class", "axis") .attr("transform", "translate(0," + height + ")") .call(d3.axisBottom(x0)); // Create the Y Axis g.append("g") .attr("class", "axis") .call(d3.axisLeft(y).ticks(null, "s")) .append("text") .attr("x", 2) .attr("y", y(y.ticks().pop()) + 0.5) .attr("dy", "0.32em") .attr("fill", "#000") .attr("font-weight", "bold") .attr("text-anchor", "start") .text("Population"); // Create the legend g's // Note the data join // Note the transform translate based on the selection element index var legend = g.append("g") .attr("font-family", "sans-serif") .attr("font-size", 10) .attr("text-anchor", "end") .selectAll("g") .data(keys.slice().reverse()) .enter().append("g") .attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; }); // Create rectangles for each legend g // Pass rect index to Z color ordinal scale legend.append("rect") .attr("x", width - 19) .attr("width", 19) .attr("height", 19) .attr("fill", z); // Create text for each legend g // Use the data that it inherts to create the SVG text legend.append("text") .attr("x", width - 24) .attr("y", 9.5) .attr("dy", "0.32em") .text(function(d) { return d; });});</script> https://d3js.org/d3.v4.min.js