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
About the Authors
About the Author2
About the Reviewer
Customer Feedback
Shape Primitives of D3

Clarity, honesty, and a sense of purpose

There are two big schools of thinking in terms of data visualization at the moment: there's the ultra-minimalist philosophy espoused by Alberto Cairo and Edward Tufte, where the primary goal of data visualization is to reduce confusion, and then there are those who use data to create beautiful things that uphold design over communication. If you couldn't tell by the title of this section, I generally believe that the former is far more appropriate in most cases. As somebody wishing to visually communicate data, the absolute worst thing you can do is mislead an audience, whether intentionally or not; not only do you lose credibility with your audience once they discover how they've been misled, but you also increase public skepticism over the ability of data to communicate the truth.

Axes and scales are the one of the easiest things to get wrong. You should usually start them at zero, because not doing so can dramatically distort the shape of the chart...