A lot of data people see design as just a way to make your graphics look pretty. That’s certainly part of it, but design is also about making your graphics readable, understandable, and usable. You can help people understand your data better than if they were to look at a default graph. You can clear clutter, highlight important points in your data, or even evoke an emotional response. Data graphics can be entertaining, fun, and informative. Sometimes it’ll just be the former, depending on your goal, but no matter what you try to design—visualization, information graphic, or data art—let the data guide your work.
When you have a big dataset, and you don’t know where to begin, the best place to start is with a question. What do you want to know? Are you looking for seasonal patterns? Relationships between multiple variables? Outliers? Spatial relationships? Then look back to your data to see if you can answer your question. If you don’t have the data you need, then look for more.
When you have your data, you can use the skills you learned from the examples in this book to tell an interesting story. Don’t stop here, though. Think of the material you worked through as a foundation. At the core of all your favorite data graphics is a data type and a visualization method that you now know how to work with. You can build on these for more advanced and complex graphics. Add interactions, combine plots, or complement your graphics with photographs and words to add more context. ...