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

Tailoring legends

The Plots package shows, by default, a legend with a label for each series. This section will discuss how we have to tailor those legends to match our needs. As we saw in Chapter 10, The Anatomy of a Plot, legends are part of Plots’ subplots. Therefore, as discussed in this chapter’s Exploring plot attributes section, we can look for the related attributes in plotattr(:Subplot). All those attributes have the legend prefix. Note that the legend attribute names use underscores to separate the words, but all offer aliases without underscores. For example, the legend_font_color attribute has the legendfontcolor alias.

As we previously explored in this chapter’s Formatting the fonts section, we can determine the font used for legend labels and titles using attributes. Those attributes have the following prefixes: legendfont or legend_font and legendtitlefont or legend_title_font. For example, we can use legend_font_color and legend_title_font_color...