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

Extracting and transforming data

If you are lucky enough to find your data in CSV, XML, or JSON, you can load it and start using it right away. But what if your data is only available as HTML tables, or worse, as a PDF file? In these cases, you need to extract your data and transform it into a usable format.

If it's a very simple HTML table, sometimes you can select it and copy and paste it into a spreadsheet and preserve the rows and columns. Then you can export it as a CSV. Sometimes you will need to do extra work, perhaps removing garbage characters, styles, and unnecessary columns. This is risky, since you may also lose data or introduce errors during the process.

Online tools

You can also use online tools that try to convert HTML tables into XML, CSV, and JSON. Let's try an example. The NASA JPL site has a Web page containing data about the moon and the planets in our solar system ( To use that data, you will need to have it in a standard format...