When we asked Visualize This author Nathan Yau what makes a great infographic—as we’d done with so many others—his response was, “Good data and a designer that understands it. You can always tell when someone doesn’t really know much about what they’re displaying, and if you don’t understand, then how are you supposed to explain anything to your readers?” Essentially, you must always know what you are saying before you try to say it.


So, before we get into designing with data, we need to discuss what data types and relationships we encode with charts and graphs. Keep in mind that we didn’t write this section with the intention of creating the definitive set of best practices for designing with data. There are already a number of books that address this. Stephen Few’s Show Me the Numbers: Designing Tables and Graphs to Enlighten and Dona Wong’s The Wall Street Journal Guide to Information Graphics are two great books that cover this subject matter quite well. To clarify, this section is meant to be but a primer, and a chance for you to learn a thing or two about some of the most common mistakes that you probably see on a daily basis—without even realizing it. And ideally, you’ll be able to implement these practices when it comes to your own design.


Most people recognize about seven types of quantitative data, but in order to keep this chapter succinct, as well as address our primary aims, we’ll only discuss two of them: discrete and continuous

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