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

Data formats

Data used in visualizations is usually distributed in a standard format that can be shared. Even when the data is served from a database, the data is usually delivered in some standard format. Popular proprietary formats, such as Excel spreadsheets, are common, but most statistical data is stored or delivered in CSV, XML, or JSON formats.


CSV stands for comma-separated values. It's a very popular data format for public data. A CSV file is a text file that emulates a table. It usually contains one header row with the names of the columns, and one or more data rows containing value fields. Rows are separated by line breaks, and the comma-separated fields in each row form columns. It maps perfectly to an HTML table. This is a simple CSV file containing the population and land area of seven continents (Data/sample.csv):

 "North America",579024000,24490000