Book Image

D3.js 4.x Data Visualization - Third Edition

By : Aendrew Rininsland, Swizec Teller
Book Image

D3.js 4.x Data Visualization - Third Edition

By: Aendrew Rininsland, Swizec Teller

Overview of this book

Want to get started with impressive interactive visualizations and implement them in your daily tasks? This book offers the perfect solution-D3.js. It has emerged as the most popular tool for data visualization. This book will teach you how to implement the features of the latest version of D3 while writing JavaScript using the newest tools and technique You will start by setting up the D3 environment and making your first basic bar chart. You will then build stunning SVG and Canvas-based data visualizations while writing testable, extensible code,as accurate and informative as it is visually stimulating. Step-by-step examples walk you through creating, integrating, and debugging different types of visualization and will have you building basic visualizations (such as bar, line, and scatter graphs) in no time. By the end of this book, you will have mastered the techniques necessary to successfully visualize data and will be ready to use D3 to transform any data into an engaging and sophisticated visualization.
Table of Contents (18 chapters)
Title Page
About the Authors
About the Author2
About the Reviewer
Customer Feedback
Shape Primitives of D3

Muster the cluster!

Another type of similar diagram is a dendrogram, which uses D3's cluster layout and puts all leaf nodes of a tree at the same depth. Let's create that now. Comment out the westerosChart.init() line in main.js and add this beneath it:

westerosChart.init('cluster', 'data/GoT-lineages-screentimes.json');

Go back to chapter6/index and add the following:

westerosChart.cluster = function Cluster(_data) { 
  const data = getMajorHouses(_data); 
  const stratify = d3.stratify() 
    .parentId(d => d.fatherLabel) 
    .id(d => d.itemLabel); 

  const root = stratify(data); 

  fixateColors(houseNames(root), 'id'); 

  const layout = d3.cluster() 
      this.innerWidth - 150, 

  const links = layout(root) 

This should look familiar already--we get our data, create a stratify generator, then use it on our data. We then create a cluster layout, give it a size (though, here we subtract 150 pixels...