Book Image

Learn Chart.js

By : Helder da Rocha
Book Image

Learn Chart.js

By: Helder da Rocha

Overview of this book

Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice. This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript. By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js.
Table of Contents (14 chapters)
Title Page
Copyright and Credits
About Packt

Numeric Cartesian scales

There are two types of numeric scales. In all charts that use numeric scales, type:'linear' is the default, but it's not always the best option. A linear chart is best to compare data points of the same magnitude, but when the samples contain some values that are hundreds of times larger than others, data correlations may be hard to find.

Linear scales

A linear scale was used to for the following scatter chart, which plots the populations of several countries, comparing their population in 1980 (axis) with their population in 2015 (axis). The data is from the United Nations (see Data/WPP2017_UNH.csv in the GitHub repository for this chapter). The median line represents the points where the population is the same. Countries that appear in the shaded area above the middle line experienced a decrease in population:

A chart showing population increase/decrease from 1980 to 2015. Due to the different order of magnitude between China, India, and the rest of the world...