Mastering D3.js - Data Visualization for JavaScript Developers

352 Pages·2014·3.51 MB·English

by  Pablo Navarro Castillo

Mastering D3.js
Bring your data to life by creating and deploying
complex data visualizations with D3.js
Pablo Navarro Castillo
BIRMINGHAM - MUMBAI
Mastering D3.js
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First published: August 2014
Production reference: 1180814
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ISBN 978-1-78328-627-0
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Cover image by Artie Ng ([email protected])
Credits
Author Project Coordinator
Pablo Navarro Castillo Harshal Ved
Reviewers Proofreaders
Andrew Berls Simran Bhogal
Simon Heimler Maria Gould
Lars Kotthoff Ameesha Green
Nathan Vander Wilt Paul Hindle
Commissioning Editor Indexers
Edward Gordon Hemangini Bari
Mariammal Chettiyar
Acquisition Editors Rekha Nair
Nikhil Chinnari
Priya Subramani
Mohammad Rizvi
Production Coordinator
Content Development Editor Arvindkumar Gupta
Sankalp Pawar
Cover Work
Technical Editors Arvindkumar Gupta
Indrajit A. Das
Humera Shaikh
Copy Editors
Dipti Kapadia
Deepa Nambiar
Stuti Srivastava
About the Author
Pablo Navarro Castillo is a mathematical engineer and developer. He earned
his Master's degree in Applied Mathematics from École des Mines de Saint-Etienne
in France. After working for a few years in operations research and data analysis,
he began to work as a data visualization consultant and developer.
He has collaborated with Packt Publishing as a technical reviewer for Data Visualization
with D3.js and Data Visualization with D3.js Cookbook. In 2014, he founded Masega, which
is a data visualization agency based in Santiago, Chile, where he currently works.
I wish to thank the Packt Publishing team for their collaboration
in the inception and development of this book. I am also grateful
to the technical reviewers, whose insightful comments and kind
suggestions have been essential to improve the content and
examples of every chapter.
To Miriam, for her patience and continuous support.
About the Reviewers
Andrew Berls is a Ruby and JavaScript developer who lives in Santa Barbara, CA.
He has developed dashboards for www.causes.com using D3.js to visualize social
networks and recently acted as a reviewer for Data Visualization with D3.js Cookbook,
Packt Publishing. Andrew recently completed his degree in Computer Science at the
University of California, Santa Barbara. When he's not programming, you can find
him attempting to cook or hiking up a mountain.
Andrew regularly blogs about web technologies at http://www.andrewberls.com.
Simon Heimler is currently studying and working as a research assistant at
the University of Applied Research in Augsburg in the field of Semantic Content
Management. He has a degree in Interactive Media and over a decade of experience
with web design and development.
Lars Kotthoff is a postdoctoral researcher at University College Cork, Ireland,
where he uses artificial intelligence methods to make software faster and better.
When he is not researching ways to make computers more intelligent, he plays
around with JavaScript visualizations. He has extensive experience with D3.js.
Nathan Vander Wilt is a freelance software developer. He offers clients a wide
range of expertise, including everything from creating HTML5 and native application
interfaces to developing low-level control software for embedded and wireless
systems. He especially enjoys solving problems such as peer-to-peer syncing or the
many challenges of digital cartography. In order to stay sane in the suburbs, Nate also
enjoys raising plants, fish, snails, honeybees, chickens, and rabbits with his family.
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Table of Contents
Preface 1
Chapter 1: Data Visualization 7
Defining data visualization 9
Some kinds of data visualizations 10
Infographics 12
Exploratory visualizations 13
Dashboards 14
Learning about data visualization 15
Introducing the D3 library 16
Summary 20
Chapter 2: Reusable Charts 21
Creating reusable charts 21
Creating elements with D3 22
Binding data 23
Encapsulating the creation of elements 25
Creating the svg element 26
The barcode chart 27
Accessor methods 28
Chart initialization 29
Adding data 30
Adding the date accessor function 32
Updating the dataset 35
Fixing the enter and exit transitions 36
Using the barcode chart 37
Creating a layout algorithm 40
The radial layout 40
Computing the angles 43
Using the layout 45
Summary 47