I’m often asked about book recommendations for folks getting started in data visualization. A lot of excellent resources can be found online, and I list a few below, but there are a handful of physical books on my shelf that have built a foundation for the way I visually communicate and interpret data.
Advice to beginners
The best way to learn is to create and iterate on communicating about numbers in a visual way. You can choose numbers you find interesting (like Nate Silver), pick from a variety of research publications (like Mona Chalabi), or illustrate concepts and ideas (like Mike Bostock). You can even take something insanely boring, like work*, and challenge yourself to make a clear and concise visualization that maximizes information density, or allows you to identify patterns in a new way.
Sketch and draw your ideas, doodle data visualizations. The more you practice representing numbers as marks on the page, the more intuition you’ll build for the mapping that occurs behind the scenes on the computer.
When you learned to write, spelling, grammar, and punctuation only got you so far. You also had to learn to tell stories and communicate your ideas. The same follows for data visualization. Furthermore, with any good chart, you want to give your audience the best opportunity to explore and make discoveries on their own. You want to give them a way to make comparisons, identify trends or outliers, and pull together patterns from the data you’re representing to them.
Lastly, there is some art and design involved in any good visualization. The best data artists see themselves as such; they study things like color theory, composition, and visual perception.
On to the books!
There are excellent recipes and cookbooks out there to show you exactly how to produce [insert chart type here]s in [insert your programming language of choice here]. We’ll be focusing instead on books that build an intuition for how to make decisions about what chart type to use, and how to evaluate your own charts for readability, integrity and clarity. I’m listing these books in reverse chronology since the examples are more relevant and language is more accessible if you start that way.
- Storytelling with Data: A Data Visualization Guide for Business Professionals – Cole Nussbaumer Knaflic
- The Functional Art – Alberto Cairo
- Information Visualization: Perception for Design – Colin Ware
- Visualizing Data – William S. Cleveland
- Semiology of Graphics – Jacques Bertin
Storytelling with Data
I recommended this book as a starting point because it starts out with the key question: “What story are you trying to tell?” Cole Nussbaumer Knaflic breaks down key elements of any good story; what, why and how. You must make sure your visualizations answer these questions even when they’re removed from surrounding context.
She encourages summarizing what you’re trying to communicate to your audience in an articulate, complete, sentence. You’re encouraged to follow that by storyboarding, and then she takes you on a tour of effective visualization choices and techniques.
The Functional Art
Alberto Cairo is the modern data visualization equivalent of Michel Foucault, simultaneously a historian, a critic, and a philosopher of his field. This sometimes meandering book is full of opinions and frameworks*. You’ll benefit from reading his critique of various published charts and infographics, which he in turn generalizes and abstracts into salient points about effective data visualization.
An interesting device introduced in the book is the
Visualization wheel . It offers a number of axes for evaluating tradeoffs in data visualization, like abstraction – figuration, or density-lightness. These are closely related to the readability and utility of any chart. Cairo uses the visualization wheel when analyzing different chart types and execution in an enlightening way.
Information Visualization: Perception for Design
Ware’s book is a textbook, and is not for light reading. It may be a little more work to prise something immediately applicable out of this book than from the others on this list, but you will learn about the why of data visualization design. It’s critical to understand the way we consume and process visual information when we’re making decisions about how to communicate ideas and numbers visually.
The book will take you through topics like color theory, visual processing of symbols, and tie them to the neurosensory pathways involved. These are ideas are relayed into techniques that artists and designers use that you can apply to your work. For example, graphemes are the smallest meaningful unit in a writing system, but can be applied to a graphic system too.
This is the book I’d be petty about; if you wanted to borrow it I would make some excuse not to lend it to you. I love the way Cleveland writes, and this book is an excellent reference for a wealth of visualization methods with examples. The book is organized into sections by the type of data you’re representing: univariate, bivariate, trivariate, hypervariate, and multiway data.
Semiology of Graphics
Bertin’s book is much older than the rest but it has a special place on my shelf. This is the original book that offered a scientific framework for visualizing data. As a very technical thesis, there’s a fair amount of defining and redefining terms which can be hard to follow, but it pays off. There are lots of illustrations and the entire text is well researched. The frameworks, references to the theory of visual perception, and callouts to Bertin’s experience as a cartographer are well worth the mental lift.
Good stuff you can find online
Other books you should check out
- Show Me the Numbers: Designing Tables and Graphs to Enlighten – Stephen Few
- Grammar of Graphics – Leland Wilkinson
- Elements of Graphics – William S. Cleveland
- The Truthful Art – Alberto Cairo
- Visualize This – Nathan Yau
- Resonate: Present Visual Stories that Transform Audiences – Nancy Duarte
- The Visual Display of Quantitative Information – Edward Tufte
- Actually, I love my work! I hope you do too.
- I’m a shameless hoarder of frameworks