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

Summary

In this chapter, we learned how to use StatsPlots, the library for drawing statistical plots in the Plots ecosystem. First, we learned how to visualize univariate and bivariate distributions using StatsPlots, Gadfly, and AlgebraOfGraphics. Then, we explored the basic statistical plots that we can combine to display joint and marginal distributions. Finally, we learned how StatsPlots can compare distributions across groups and visualize clustering results. What you’ve learned in this chapter, combined with the knowledge you acquired in Chapter 1, An Introduction to Julia for Data Visualization and Analysis, and Chapter 5, Introducing the Grammar of Graphics, will enable you to make the most of Julia for visualizing and exploring tabular data. In the next chapter, we will learn about the visualization of another data layout: graphs.