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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

Summary

This chapter has taught us the different behaviors of interactive visualizations and which plotting packages offer them. We have seen how to exploit the interactivity provided by the Plotly and PlotlyJS backends of Plots. We learned how to use Observables, Interact, or Pluto to gain interactivity when rendering Plots figures with the default GR backend. Then, we also explored the enhanced and fully customizable interactive behaviors that Makie offers us, including mouse interaction.

Using different Julia packages, we created the same interactive plot—an arc with a varying internal angle. That gave us a good idea about the differences and similarities of those libraries to achieve interactive plots. Therefore, you will now be able to choose the best-suited combination of packages for your interactive data visualizations. This chapter only skimmed all the different libraries’ options, functions, and widgets; we recommend looking at their documentation for more...

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