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Key benefits

Learn to use static and interactive plots to explore data with Julia

Become well versed with the various plotting attributes needed to customize your plots

Create insightful and appealing plots using data interactions, animations, layouts, and themes

Description

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.

Who is this book for?

Data analysts looking to explore Julia's data visualization capabilities will find this book helpful, along with scientists and academics who want to generate and communicate knowledge and improve their teaching material. This data visualization book will also interest Julia programmers willing to delve into the language plotting ecosystem and improve their visualization skills. Basic programming knowledge is assumed — but the book will introduce you to Julia's important features. Familiarity with mathematical and statistical concepts will help you make the most of some of the chapters.

What you will learn

Create interactive plots with Makie, Plots, Jupyter, and Pluto

Create standard statistical plots and visualize clustering results

Plot geographically distributed and biological data

Visualize graphs and networks using GraphRecipes and GraphPlots

Find out how to draw and animate objects with Javis, Plots, and Makie

Define plot themes to reuse plot visual aspect customizations

Arrange plots using Plots, Makie, and Gadfly layout systems

Define new plot types and determine how Plots and Makie show objects

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Interactive Visualization and Plotting with Julia

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Hands-On Design Patterns and Best Practices with Julia

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Total NZ$ 195.97

Mark Kittisopikul Aug 30, 2022

"Interactive Visualization and Plotting with Julia" by Diego Javier Zea provides a comprehensive overview of plotting and visualization in Julia. This book is impressive because of both its breadth and depth in exploring graphics and figure creation in the Julia programming language.For breadth, the book covers Julia's many plotting packages including Plots.jl, Makie.jl, and Gadly.jl. Individual Plots.jl backends including GR.jl and PyPlot.jl are compared and contrasted with each other. Additionally, using interactive notebooks via both Jupyter and Pluto.jl are discussed. Even specialized plotting packages such as UnicodePlots.jl for in-terminal plots are demonstrated with colorful, high-resolution figures.The book goes in depth on a number of domain specific topics including statistical plots, geographically distributed data, graphs, and biological data. It also describes how to customize plots and recipes. Zea continues with examples of detailed tweaks to plots and even occasionally demonstrates the effect of possible values for individual keywords. For example, the author shows the effect of 19 distinct possibilities for legend position options in Plots.jl. The depth and attention to detail in this text rivals each package's own documentation."Interactive Visualization and Plotting with Julia" is important asset for anyone creating visualizations with the Julia language, especially for publication. The large and meticulous approach to the minutiae of plotting packages makes this an invaluable resource for the Julia user.

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Kyle Protho Aug 29, 2022

Julia is a great programming language with a ton of potential. The only thing holding it back is the lack of resources and documentation. This book helps to fill that gap (and some!).There are plenty of examples and explanations for programmers of all levels to understand more about creating visualizations with Julia.Most importantly though: even if/when more development and upgrades occur in the Julia ecosystem, one thing I value about this book is that it will equip you with the Julia-specific knowledge and context necessary to keep up with those changes. You not only learn about visualizations, you learn about declaring functions, specifying argument types (a valuable feature of Julia functions), and creating reproducible production environments. These skills will help you keep up with the frequent upgrades and changes occurring in the Julia ecosystem.A valuable addition to my Julia library collection that I would recommend to programmers at any level.

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David Knickerbocker Mar 27, 2023

This book is a great introduction to doing data analysis with the Julia programming language. I come from Python and found this to be a very easy and quick transition. I was able to go from no knowledge to the beginnings of graph analysis in about an hour, and I was curious about Julia’s graph/network ecosystem and wanted to dabble.This is what I needed. I have another book that goes into more detail on the language, but I wanted to see implementation. Very good. Thank you for writing this book. It definitely helped me.

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Timothee Poisot Sep 04, 2022

Plotting in Julia is evolving really rapidly, and newcomers to the language can be overwhelmed with the number of choices available. In this book, Diego Javier Zea gives a comprehensive and accessible overview of different packages, their applications to the different types of data, and how to leverage interactive visualization systems. It is now part of the recommended readings for several classes I teach, and grad students in my research group consult it fairly often.My only gripe with the book is that (as is sadly often the case), Packt (who provided me with a paperback copy for review) seems to have a rather low standard of copy editing. This has been noted by a few other reviewers. It is very sad to see that the obviously intensive and serious work done by the author was not matched by the publisher, especially for a book that will very likely become a required reading for new Julia users.

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Orco Sep 05, 2022

Under the premise an image is worth a thousand words (or data points) , visualization and plotting are all the rage (suffice to say there was a workshop on this topic during the last Julia Conf), and below I present (what to my taste are) the strong and weak aspects of this new book.++ PLUSESThe author admittedly has an extensive knowledge of the plotting and visualization packages offered in Julia. Proof of it is the plethora of available packages and backends which can be combined to produce a plot, depending on the target medium (i.e. do you need to plot in a desktop window, a web page, or a document?). Another aspect where the book shines is the examples addressed which make intensive use of plotting and visualization for different areas, e.g. statistics, geo-informatics, bio-informatics, etc.Provides some theoretical framework/reference behind the composition and design (decisions) of plots (i.e. the grammar of graphics). This conceptual support makes the willy nilly decisions redundant, and takes you to a more conscious process as to what and how to represent the data you’re working with.Although the current standard for a book about programming is to accompany it with a sample code repository available, a pleasant surprise has been the consistent use of Pluto Notebooks, in my opinion a very didactic interactive resource (I dare say better than the by now popular Jupyter)-- MINUSESThere were some passages where I kind of got lost in the details (e.g, the transformations applied to the input data-set discussed in working with Dataframes and tidy data on Chapter 5). Sometimes the prose looked a bit too verbose when describing the steps to do the plot (more like a handbook/Cookbook). On other hand, I guess the term plot recipes already conveys this stile of writing?This is not per se a minus, although you need intermediate domain knowledge. The title requires previous knowledge in some areas, and has a specific niche in that sense: the book is aimed for (sic) “researchers and data analysts”, so right off the bat, you should have been exposed before to other languages used to wrangle data (e.g. R o Python), and/or have an intermediate knowledge of Julia as language. Otherwise, you’ll be staring at the wall/roof trying to figure out what array comprehensions, destructuring, splat operator, or keyword argument(s) mean (to name a few).Besides, a course or two in probability , statistics, and graph theory will help you to stand firm when you read terms like density functions, bi-variate distributions, or regressions in the text.Unlike hyperlinks to web-sites, cross-references (one section of the book referring forwards or backwards to another) did not have hyperlinks for easy navigation, (not at least in the PDF version I’ve got). A real pity, since the text has quite some of these. Maybe in the hard copy, some bookmarks will do the trick anyway.

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Interactive Visualization and Plotting with Julia: Create impressive data visualizations through Julia packages such as Plots, Makie, Gadfly, and more

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