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

Radar charts

Radar charts are line charts plotted on a radial axis. They can be used with one or more datasets that contain at least three values each. There is only one axis, which starts from the center. Each line begins and ends at the same point and, for that reason, radar charts are usually used to display values that are either cyclic in nature (such as hours, months, schedules, or repeating events), a sequential list of categories which end at the same place where it begins (such as round-trip), or categories that have no specific order. A radar chart can be used to compare different datasets by revealing strong and weak points, or showing outliers and commonality in data. It usually works best with a small number of datasets (that is, no more than three or four).

Radar charts are usually a poor choice for large datasets. In these cases, it's usually better to use a Cartesian line chart or a bar chart. Radial distances are also harder to perceive, although this limitation can be minimized...