Book Image

Interactive Visualization and Plotting with Julia

By : Diego Javier Zea
Book Image

Interactive Visualization and Plotting with Julia

By: Diego Javier Zea

Overview of this book

The Julia programming language offers a fresh perspective into the data visualization field. Interactive Visualization and Plotting with Julia begins by introducing the Julia language and the Plots package. The book then gives a quick overview of the Julia plotting ecosystem to help you choose the best library for your task. In particular, you will discover the many ways to create interactive visualizations with its packages. You’ll also leverage Pluto notebooks to gain interactivity and use them intensively through this book. You’ll find out how to create animations, a handy skill for communication and teaching. Then, the book shows how to solve data analysis problems using DataFrames and various plotting packages based on the grammar of graphics. Furthermore, you’ll discover how to create the most common statistical plots for data exploration. Also, you’ll learn to visualize geographically distributed data, graphs and networks, and biological data. Lastly, this book will go deeper into plot customizations with Plots, Makie, and Gadfly—focusing on the former—teaching you to create plot themes, arrange multiple plots into a single figure, and build new plot types. By the end of this Julia book, you’ll be able to create interactive and publication-quality static plots for data analysis and exploration tasks using Julia.
Table of Contents (19 chapters)
1
Section 1 – Getting Started
6
Section 2 – Advanced Plot Types
12
Section 3 – Mastering Plot Customization

Chapter 4: Creating Animations

Animations and interactive visualizations can tell stories that static plots cannot. Also, both are more engaging for the final audience. As shown in the previous chapter, interactive visualization can let us interact with a variable to visualize its impact, among other things. Instead, animations use the time dimension to encode that variable. The encoded variable can be time since animations are well suited to show how a process evolves through time. Another advantage of animations is that they are much easier to distribute than interactive visualizations.

In this chapter, we are going to learn how to create animations using Plots and Makie. We will also introduce Javis, a drawing library, which we will use to generate animations with Julia. Then, we will learn about the Animations package, which will help us move objects in our canvas. By the end of this chapter, you will know how to create and distribute simple animations using Plots, Makie, and...