Designing Data Visualizations

Chapter 4. Choose Appropriate Visual Encodings

Choosing Appropriate Visual Encodings

As we discussed in Data, once you know the “shape” of your data, you can encode its various dimensions with appropriate visual properties. Different visual properties vary—or may be modified—in different ways, which makes them good for encoding different types of data. Two key factors are whether a visual property is naturally ordered, and how many distinct values of this property the reader can easily differentiate. Natural ordering and number of distinct values will indicate whether a visual property is best suited to one of the main data types: quantitative, ordinal, categorical, or relational data. (Spatial data is another common data type, and is usually best represented with some kind of map.)

Natural Ordering

Whether a visual property has a natural ordering is determined by whether the mechanics of our visual system and the “software” in our brains automatically—unintentionally—assign an order, or ranking, to different values of that property. The “software” that makes these judgments is deeply embedded in our brains and evaluates relative order independent of language, culture, convention, or other learned factors; it’s not optional and you can’t^[6] design around it.

For example, position has a natural ordering; shape doesn’t. Length has a natural ordering; texture doesn’t (but pattern density does). Line thickness or weight has a natural ordering; line style (solid, dotted, dashed) doesn’t. ...