Let’s look at the tools in our tool belt, the hammers and power drills of making a viz, if you will. We have the preattentive attributes of color, form, and spatial position (also movement, but we’ll leave that one out for now). This means we can encode data using color, shape, size, and position, and then we can encode relationships between our data points using the gestalt principles of enclosure, proximity, similarity, symmetry, connection, closure, and continuity. We have all different types and categorizations of data, and we have the mighty tools of color and typography, which we’ve learned how to wield properly. You’re ready to start thinking about charts now.
In this chapter, we’ll take a deep dive into what makes a chart “good.” Then, we’ll talk about some ways we can make bar charts more interesting and engaging, sometimes without even using bars! Finally, we’ll wrap up with a few tips to make map-based data visualizations in such a way that they aren’t accidentally telling stories you hadn’t intended to tell.