Claus O. Wilke - Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures

by Claus O. Wilke

Copyright 2019 Claus O. Wilke. All rights reserved.

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If you are a scientist, an analyst, a consultant, or anybody else whohas to prepare technical documents or reports, one of the most importantskills you need to have is the ability to make compelling datavisualizations, generally in the form of figures. Figures will typicallycarry the weight of your arguments. They need to be clear, attractive,and convincing. The difference between good and bad figures can be thedifference between a highly influential or an obscure paper, a grant orcontract won or lost, a job interview gone well or poorly. And yet,there are surprisingly few resources to teach you how to make compellingdata visualizations. Few colleges offer courses on this topic, and thereare not that many books on this topic either. (Some exist, of course.)Tutorials for plotting software typically focus on how to achievespecific visual effects rather than explaining why certain choices arepreferred and others not. In your day-to-day work, you are simplyexpected to know how to make good figures, and if youre lucky you havea patient adviser who teaches you a few tricks as youre writing yourfirst scientific papers.

In the context of writing, experienced editors talk about ear, theability to hear (internally, as you read a piece of prose) whether thewriting is any good. I think that when it comes to figures and othervisualizations, we similarly need eye, the ability to look at a figureand see whether it is balanced, clear, and compelling. And just as isthe case with writing, the ability to see whether a figure works or notcan be learned. Having eye means primarily that you are aware of alarger collection of simple rules and principles of good visualization,and that you pay attention to little details that other people mightnot.

In my experience, again just as in writing, you dont develop eye byreading a book over the weekend. It is a lifelong process, and conceptsthat are too complex or too subtle for you today may make much moresense five years from now. I can say for myself that I continue toevolve in my understanding of figure preparation. I routinely try toexpose myself to new approaches, and I pay attention to the visual anddesign choices others make in their figures. Im also open to changing mymind. I might today consider a given figure great, but next month Imight find a reason to criticize it. So with this in mind, please donttake anything I say as gospel. Think critically about my reasoning forcertain choices and decide whether you want to adopt them or not.

While the materials in this book are presented in a logical progression,most chapters can stand on their own, and there is no need to read thebook cover to cover. Feel free to skip around, to pick out a specificsection that youre interested in at the moment, or one that covers aparticular design choice youre pondering. In fact, I think you will getthe most out of this book if you dont read it all at once, but ratherread it piecemeal over longer stretches of time, try to apply just a fewconcepts from the book in your figuremaking, and come back to read aboutother concepts or reread sections on concepts you learned about a while back. Youmay find that the same chapter tells you different things if you rereadit after a few months have passed.

Even though nearly all of the figures in this book were made with R andggplot2, I do not see this as an R book. I am talking about generalprinciples of figure preparation. The software used to make the figuresis incidental. You can use any plotting software you want to generatethe kinds of figures Im showing here. However, ggplot2 and similarpackages make many of the techniques Im using much simpler than otherplotting libraries. Importantly, because this is not an R book, I do notdiscuss code or programming techniques anywhere in this book. I want youto focus on the concepts and the figures, not on the code. If you arecurious about how any of the figures were made, you can check out the bookssource code at its GitHub repository.