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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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Aendrew Rininsland Aendrew Rininsland
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Aendrew Rininsland
Swizec Teller Swizec Teller
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Swizec Teller
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with D3, ES2017, and Node.js FREE CHAPTER 2. A Primer on DOM, SVG, and CSS 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

Scales


We've already used scales many times -- we had a chant, if you remember; what was that again?

SURPRISE POP QUIZ:

INPUT!: [ ] DOMAIN! [ ] NOT DOMAIN!
OUTPUT!: [ ] RANGE! [ ] NOT RANGE!

If you got INPUT! = DOMAIN! and OUTPUT! = RANGE!, you are totally correct!

The reason we use scales is to avoid math. This makes our code shorter, easier to understand, and more robust, as mistakes in high school mathematics are some of the hardest bugs to track down.

To reiterate a point I've hopefully been hammering home since Chapter 1, Getting Started with D3, ES2017, and Node.js, a function's domains are those values that are defined (the input), and the range are those values it returns. The following figure is borrowed from Wikipedia:

Here, X is the domain, Y is the range, and the arrows are the functions. We need a bunch of code to implement this manually:

   let shape_color = shape => { 
     if (shape == 'triangle') { 
       return 'red'; 
     } else if (shape == 'line') { 
       return 'yellow...
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