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Interactive Visualization and Plotting with Julia

Interactive Visualization and Plotting with Julia

By : Diego Javier Zea
3.9 (10)
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Interactive Visualization and Plotting with Julia

Interactive Visualization and Plotting with Julia

3.9 (10)
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)
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1
Section 1 – Getting Started
6
Section 2 – Advanced Plot Types
12
Section 3 – Mastering Plot Customization

Creating plotting recipes

The Plots ecosystem offers the RecipesBase package so that you can add plotting recipes. It is handy as a package developer since it offers minimum loading overhead for your package. It has no dependencies and enables access to Plots’ plotting capabilities. To that end, the package exports the @recipe macro, which takes a function definition that describes our recipe. We have different recipe types, depending on the type signature of the defined method, as the system uses Julia’s multiple dispatch.

The @recipe macro has a special syntax for setting attribute values. We can use the --> operator to select a different default value for the attribute. This states that the attribute should take the given value if the user has not set it. We can use the := operator instead to force a given value for an attribute. Both operators take the attribute on the left-hand side and the desired value on the right-hand side. For example, the following code...

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