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

Drawing shapes

The Plots package exports the Shape type to construct polygons. This section will teach us how to use it to create custom shapes with Plots. This will be helpful when drawing or while creating novel plotting types. We can also take advantage of Shape to design custom markers. The Shape constructor takes the vertices coordinates of the desired polygon. We can pass them in two different ways:

  • We can give a vector for each axis containing the vertex coordinates for that dimension. For example, we can call Shape(x, y) if the x and y variables are vectors of numbers of the same length. This is one of the ways we usually call the plot function; that is, plot(x, y).
  • We can give a single vector containing a tuple of numbers, with each tuple containing a vertex’s (x, y) coordinates. Interestingly, we can also call plot or other plotting functions such as scatter with that input. For example, plot([1, 2, 3], [6, 7, 5]) and plot([(1, 6), (2, 7), (3, 5)]) are...