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D3.js 4.x Data Visualization

You're reading from   D3.js 4.x Data Visualization Learn to visualize your data with JavaScript

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787120358
Length 308 pages
Edition 3rd Edition
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Authors (2):
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Aendrew Rininsland Aendrew Rininsland
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Aendrew Rininsland
Swizec Teller Swizec Teller
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Swizec Teller
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Started with D3, ES2017, and Node.js 2. A Primer on DOM, SVG, and CSS FREE CHAPTER 3. Shape Primitives of D3 4. Making Data Useful 5. Defining the User Experience - Animation and Interaction 6. Hierarchical Layouts of D3 7. The Other Layouts 8. D3 on the Server with Canvas, Koa 2, and Node.js 9. Having Confidence in Your Visualizations 10. Designing Good Data Visualizations

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() 
    .size([ 
      this.innerWidth - 150, 
      this.innerHeight, 
    ]); 

  const links = layout(root) 
    .descendants() 
    .slice(1); 
}

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...

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