Designing Data Visualizations

Chapter 6. Apply Your Encodings Well

Now that you have a sense of what structure you’ll use to represent your data, and how it will be positioned on the page, it’s time to consider the other visual properties for encoding your data and to fine-tune your choices.

We’ll begin with a discussion of color, including some of the challenges that color selection presents, and the best uses of color. Then we’ll review other visual encoding properties—such as size, shape, lines, and text—and give suggestions for how each should be treated. Finally, we’ll present some common (and slightly humorous) pitfalls, and give advice for how to avoid them.

Color

Color is tricky. It’s very appealing, and as designers, we’re tempted to use it all the time. However, getting color right can be much more difficult than it seems.

As discussed in Natural Encodings in Chapter 4, color is not naturally ordered.^[32] It bears repeating here because it is such a common mistake: avoid using color (hue) for any sort of ranking or ordering of data. You can vary brightness or saturation quite effectively for uses such as heat maps and relative intensity, but please don’t vary color as a way to encode rank, order, intensity, or value.

In the defense of color, it can be an excellent property for labeling categorical data, or non-ordered categories for differentiation purposes. (Examples of non-ordered categories include operating system, gender, region, conference track, and genre.) Just be sure that you don’t need too many ...