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

Polar area charts

Polar area charts are like bar charts rendered on a radial axis. A bar chart is usually a better option if you need precision, but you might choose a polar area chart for its visual effects.

To create a polar area chart, you set up the data the same way you would for a bar chart, then change the type to polarArea. As in the radar chart, there is only one scale property and axis to configure.

In the following example, we use a polar area chart to compare the volumes of the world's oceans. It is based on the bar chart with the same data we created in Chapter 3, Chart.js – Quick Start.

 const labels = ["Arctic", "Southern", "North Atlantic", "South 
                Atlantic", "Indian", "South Pacific", "North Pacific"];
 const volume = [18750, 71800,146000,160000,264000,329000,341000]; 
 // km3*10^3 = 1;

 const chartObj = {
     labels: labels,
     datasets: [
             label: "Volume",