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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

Composing Gadfly plots

In the Exploring data with Gadfly section of Chapter 5, Introducing the Grammar of Graphics, we saw how to create small multiples and horizontally stack plots. For the latter, we used the hstack function, which takes a series of Gadfly plots, and stacks them horizontally, creating one row and multiple columns. We can use the vstack function to arrange the subplot vertically and create multiple rows. We can combine the result of vstack using hstack, or vice versa, to create a grid. However, it is also possible to use the gridstack function for that. The input of gridstack is a matrix of plots that indicates the position of each subplot in the grid.

In this section, we have noted the three main functions offered by Gadfly to arrange multiple plots into a single figure. Let’s summarize what we’ve learned so far.

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