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
Credits
About the Authors
About the Author2
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
3
Shape Primitives of D3

Understanding your audience


Your audience is one of the most critical things to consider when beginning a new data visualization project. This has two parts: the first is from an editorial perspective (what is the audience's background knowledge of the topic at hand? What types of charts will the audience be able to recognize and properly read? How do these charts work within the broader contexts of this story and other work published?), while the second is technological (what platforms and devices will be used to consume this content?).

It's really important to tentatively sketch out any bespoke data visualization before you start writing code, and this can take many forms. On the one hand, it never hurts to figure out the rough shape of your data before committing to a particular visualization style. Frequently, I've been asked for pie charts with a few small outlier values highlighted, which totally doesn't work (the rest of the chart dwarfs the outliers). You don't necessarily need to...