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  • Book Overview & Buying Learn D3.js
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Learn D3.js

Learn D3.js - Second Edition

By : Helder da Rocha
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Learn D3.js

Learn D3.js

By: Helder da Rocha

Overview of this book

Learn D3.js, Second Edition, is a fully updated guide to building interactive, standards-compliant data visualizations for the web using D3.js v7 and modern JavaScript. Whether you're a developer, designer, data journalist, or analyst, this book will help you master the core techniques for transforming data into compelling, meaningful visuals. Starting with fundamentals like selections, data binding, and SVG, the book progressively covers scales, axes, animations, hierarchical data, and geographical maps. Each chapter includes short examples and a hands-on project with downloadable code you can run, modify, and use in your own work. This new edition introduces improved chapter structure, updated code samples using ES2019 standards, and better formatting for readability. Chapters were completely rewritten to focus on the most important topics first, with suggested exercises after each section, complete with commented solutions and online step-by-step tutorials. All code snippets are drawn from real-world D3 data visualization projects available in a GitHub repository, which also includes bonus content on integrating D3 into applications and migrating legacy code. With its practical approach, this book remains one of the most respected resources for learning D3.js and creating interactive data visualizations with JavaScript.
Table of Contents (27 chapters)
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1
Part 1: Getting Started with D3
3
Chapter 2: Essential JavaScript for D3 (Online)
4
Chapter 3: Essential SVG for D3 (Online)
6
Part 2: Core D3
17
Part 3: Advanced D3

Colors

Selecting an effective color scheme for data visualization involves more than aesthetics. Besides distinguishing and suggesting associations between sets of data, they communicate information through aspects such as hue, contrast, saturation, or lightness. They are critical to guarantee the accuracy of a chart, based on how they are perceived when displayed across different devices, printed, or interpreted by visually impaired viewers. The choice of colors is never neutral. They may attract or repel the viewer from relevant information.

Colors that vary in lightness and saturation suggest a sequential relationship (stronger/weaker, hotter/colder). Opposing data is often depicted using divergent color palettes, where extremes are shown using complementary colors. If your data represents different categories, a qualitative or categorical color scheme will serve it better. Depending on your audience and the purpose of your chart, you may also consider accessibility issues such...

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Learn D3.js
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