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
Contributors
Preface
Index

Chapter 5. Scales and Grid Configuration

In this chapter, you will learn how to configure the scales that control how your chart is displayed in a Cartesian or radial grid. Scales are used in all charts except pie and doughnut. Cartesian charts, such as line, bar, scatter, and bubble, use a pair of perpendicular axes, each one with a scale automatically calculated by Chart.js to position data points. Data in charts, such as polar area and radar, use a single scale, placing the data points at different positions that originate from the center. You can configure scales, altering the way the data points are presented, for example, by using a logarithmic scale instead of a default linear scale for numerical values. You may also choose a sequential time scale instead of a category scale. There are also many ways to configure styles and change the way axes, grid lines, ticks, and labels are shown in your chart.

In this chapter, we will cover the following topics:

  • Configuring scales
  • Cartesian axes...