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Data Visualization with D3 4.x Cookbook

You're reading from   Data Visualization with D3 4.x Cookbook Visualization Strategies for Tackling Dirty Data

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786468253
Length 380 pages
Edition 2nd Edition
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Author (1):
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Nick Zhu Nick Zhu
Author Profile Icon Nick Zhu
Nick Zhu
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Table of Contents (15) Chapters Close

Preface 1. Getting Started with D3.js FREE CHAPTER 2. Be Selective 3. Dealing with Data 4. Tipping the Scales 5. Playing with Axes 6. Transition with Style 7. Getting into Shape 8. Chart Them Up 9. Lay Them Out 10. Interacting with Your Visualization 11. Using Force 12. Knowing Your Map 13. Test Drive Your Visualization Appendix. Building Interactive Analytics in Minutes

Introduction


In this chapter, we will explore the most essential question in any data visualization project: how data can be represented in both programming constructs, and its visual metaphor. Before we start on this topic, some discussion on data visualization is necessary. In order to understand what data visualization is, first we will need to understand the difference between data and information.

Data consists of raw facts. The word raw indicates that the facts have not yet been processed to reveal their meaning...Information is the result of processing raw data to reveal its meaning.

   -Rob P., S. Morris, and Coronel C. 2009

This is how data and information are traditionally defined in the digital information world. However, data visualization provides a much richer interpretation of this definition since information is no longer the mere result of processed raw facts but rather a visual metaphor of the facts. As stated by Manuel Lima, in his Information Visualization Manifesto...

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