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

The anatomy of a Plots plot

This section will describe the fundamental elements that build a figure from the Plots package. The main terminology will be helpful to us in future sections of this chapter, where we will expand on these concepts to understand Makie and Gadfly figures.

A plot from the Plots package has several components we can customize using attributes. We can think of a Plots figure as a plot that can contain subplots. Those subplots will have axes that define the plot area in which we can plot our series. We can customize each of those elements through different groups of attributes. Some attributes, especially background and foreground colors, pass their values across levels. For example, by default, the axis color, foreground_color_axis, matches the color defined for the subplot, foreground_color_subplot, which, in turn, matches the one defined for the plot through the foreground_color attribute.

Let’s explore the different parts that build a Plots figure...