How to create data visualizations with D3

Giving ugly code a makeover
Our task is split between data and presentation. more groups of salaries */
Let’s implement! This splits the reusable data-processing algorithm from a specific presentation. All the files you need for this tutorial can be downloaded from here. The rest of the styling I’ll leave to you. We’ll take take data on the income of people, firms and countries, and visualise them in broad groups of   magnitude. It reflects the visualization: the previous group is included in the next for comparison, and we’ve calculated the number of unit blocks to display. [
key: “1000000”,
total: 2124000000000,
values: [
{ title: “Jimmy Carr”,
value: 2500000,
units: 25 }, /* … Now get out there and visualise! Here’s a sketch of the HTML/CSS implementation –   we append the top level groups to represent the salaryGroups from our layout:

var groups =“#viz”).selectAll(“.group”)

var groupsEntering = groups.enter()
Next we present the individual salary elements. Displaying its output is entirely up to you. A histogram layout might be passed an array of 1,500 objects, and return 10 arrays, each bucketing 150 objects. It’s testament to D3’s design that it comes in at under 150 lines of JS, HTML and CSSD3 is a toolkit for building data visualizations from scratch. To use it, we call it on our original dataset to create salaryGroups ready for binding. If you   try to visualise your data before you’ve wrangled it into the right shape you’ll end up with a mess. They’re standard JavaScript functions called with input data and returning new data formatted for display. var layout = blockLayout()
.group(function(value) {
if(value 1e6) return 1000;
if(value 1e9) return 1e6;
if(value 1e12) return 1e9;
return 1e12;

var salaryGroups = layout(listOfSalaries);
Rough code Sketch of the HTML/CSS implementation of the visualizationAt this point we’ve not actually displayed anything on screen. It’s tremendously powerful, and more than anything it’s tremendous fun. We want the units to flow inside a constrained track. Words: Tim Ruffles
Time Ruffles is an expert in JavaScript and a trainer. Our income data is in the format { value: 2500000, title: “Jimmy Carr” } our target format is below. This article originally appeared in net magazine issue 257. To configure our layout, we call .group(keyFunction) on the layout in a chaining style. D3 is best taught by example, so we’ll recreate xkcd’s ‘Money’ visualization. We need to break the incomes down into magnitude groups, and then visualise them as blocks. We’ll be making this visualization. Never again will you disappoint your designer by stuffing their expertly tuned Dribbble-fodder into a boring chart. We’ll wrap up the data part in what D3 calls a ‘layout’. This division of labour allows our layout to   be reused with different data sets, key functions and final visualizations.

Updated: 10.12.2014 — 06:25