Book Image

Learning Responsive Data Visualization

By : Erik Hanchett, Christoph Körner
Book Image

Learning Responsive Data Visualization

By: Erik Hanchett, Christoph Körner

Overview of this book

Using D3.js and Responsive Design principles, you will not just be able to implement visualizations that look and feel awesome across all devices and screen resolutions, but you will also boost your productivity and reduce development time by making use of Bootstrap—the most popular framework for developing responsive web applications. This book teaches the basics of scalable vector graphics (SVG), D3.js, and Bootstrap while focusing on Responsive Design as well as mobile-first visualizations; the reader will start by discovering Bootstrap and how it can be used for creating responsive applications, and then implement a basic bar chart in D3.js. You will learn about loading, parsing, and filtering data in JavaScript and then dive into creating a responsive visualization by using Media Queries, responsive interactions for Mobile and Desktop devices, and transitions to bring the visualization to life. In the following chapters, we build a fully responsive interactive map to display geographic data using GeoJSON and set up integration testing with Protractor to test the application across real devices using a mobile API gateway such as AWS Device Farm. You will finish the journey by discovering the caveats of mobile-first applications and learn how to master cross-browser complications.
Table of Contents (16 chapters)
Learning Responsive Data Visualization
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Helpful tools for creating maps in D3


Drawing maps requires a combination of knowledge and good understanding of GIS, GeoJSON, Projections, and so on as well as techniques and skills for creating the maps. In this section, we will look at a few selected tools that facilitate the generation of interactive maps with D3.

Color scales

As we discussed in the first section, the colors and color scales that the author chooses can have a huge impact for the reader to perceive the visualization. Therefore, I want to show how we can efficiently create color scales in D3.

Scales can map a certain domain of values to a range of different values using interpolation. We usually use this to create scales for axes. Axes, however, map a domain of values onto a pixel range. In our case, we want to use these scales on colors to map a value domain to a color range. We can achieve this using these color interpolation functions:

  • d3.interpolateRgb: RGB and HEX values, such as #00FF00

  • d3.interpolateHsl: HSL values...