Learning D3

This week I have been getting up to speed on one of the most powerful ways to visualize any datasets in any way you could imagine on the browser – using D3.

D3 describes itself as

“D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.” – Homepage

This might seem on the face of it just another Javascript jQuery style graphing library like highcharts, Chart.js etc. I thought this too but this couldn’t be further from the truth. D3 focuses on pure data driven development, leaving you to create the entire visual side from scratch using the power of SVG.

This allows you to create graphs from the very ground up, giving unlimited customisation options and never leaving you trying to work around the limitations of the library. There is a steep learning curve if like myself, you haven’t done much with SVG before. I recommend getting cheatsheets for both the library & SVG and get as in-depth material to learn from that you can find/afford.

There is multiple sites including the original D3 site and that offer hundreds and hundreds of detailed & amazing examples of what you can accomplish if you just start with D3 & the browser, it doesn’t even have any dependencies whatsoever – allowing you to get straight into the fight.

Data sourced from:

This is a chart I created using just HTML, CSS, SVG & D3 in only a modest amount of lines. There is a tooltip highlight that shows the actual figures of the data point you hover.

Tooltip highlight on scatter points in D3

Here is the code from the app.js file, containing all the D3 for plotting & interaction.

document.addEventListener('DOMContentLoaded', function(){ // Just make sure DOM is ready.
    // Padding, width & height for SVG element - used to calculate everything else.
    var padding = 40;
    var width = 700;
    var height = 700;

    // Setup scales for X, Y position, colour & radius of points.
    var yScale = d3.scaleLinear()
                  .domain(d3.extent(regionData, d => d.subscribersPer100))
                  .range([height - padding, padding]);

    var xScale = d3.scaleLinear()
                  .domain(d3.extent(regionData, d => d.medianAge))
                  .range([padding, width - padding]);

    var colourScale = d3.scaleLinear()
                  .domain(d3.extent(regionData, d => d.medianAge))
                  .range(['lightgreen', 'black']);

    var radiusScale = d3.scaleLinear()
                  .domain(d3.extent(regionData, d => d.growthRate))
                  .range([2, 20]);

    // Register the axis & individual ticks for the grid.
    var xAxis = d3.axisBottom(xScale)
                  .tickSize(-height + 2 * padding)

    var yAxis = d3.axisLeft(yScale)
                  .tickSize(-width + 2 * padding)

    // Draw each axis.'svg')
      .attr('transform', 'translate(0, '+ (height - padding)+')')
      .attr('transform', 'translate('+padding+', 0)')

    // Plotting the data.'svg')
        .attr('width', width)
        .attr('height', height)
        .attr('cx', d => xScale(d.medianAge))
        .attr('cy', d => yScale(d.subscribersPer100))
        .attr('fill', d => colourScale(d.medianAge))
        .attr('r', d => radiusScale(d.growthRate))
        .attr('stroke', 'black');

    // Axis labels & Title'svg')
        .attr('x', width / 2)
        .attr('y', height - padding)
        .attr('dy', '1.5em')
        .style('text-anchor', 'middle')
        .text('Median Age');'svg')
      .attr('transform', 'rotate(-90)')
      .attr('x', - height / 2)
      .attr('y', padding)
      .attr('dy', '-1.5em')
      .style('text-anchor', 'middle')
      .text('Subscribers per 100');'svg')
      .attr('x', width / 2)
      .attr('y', padding - 20)
      .attr('font-size', '1.5em')
      .style('text-anchor', 'middle')
      .text('Regional Statistical Data');

    // Transition hover & Tooltip for each plotted point.
    var circle = d3.selectAll("circle");
    circle.on('mouseover', function(d) {
        let r ='r');'r', r*1.1);

        let html  = '&nbsp;<strong>Region:</strong> ' + d.region + '<br />' +
                    '&nbsp;<strong>Median Age:</strong> ' + d.medianAge + '<br/>' +
                    '&nbsp;<strong>Subscribers per 100:</strong> ' + d.subscribersPer100 + '<br />' +
                    '&nbsp;<strong>Growth Rate:</strong> ' + d.growthRate + '<br />';

            .style('left', (d3.event.pageX + 15) + 'px')
            .style('top', (d3.event.pageY - 28) + 'px')
            .style('opacity', .9)
    }).on('mouseout', function(d) {
        let r ='r');'r', r/1.1);
            .style('opacity', 0);

    // Append tooltip div to body for use later.
    var tooltip ="body").append("div")
      .attr("class", "tooltip")
      .style("opacity", 0);

}, false);

As you can see, the level of detail on drawing the graph from the axis to the points and the text labelling them is all thought of and catered for by D3 – even if it can seem alien to someone who is used to a world of high-level Javascript plotting libraries.

If you want to get the full code for each file to run/modify this yourself, you can get it here:

I am continuing on to learn the advanced D3 module of my current studying but I think its important people realise that although it can be challenging to get into advanced SVG drawing (opposed to generating automatically) that D3 is wholly worthwhile!

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