Making Data Visual

Chapter 5. Single Views

It does not necessarily take a sophisticated visual representation to make a compelling point or understand a complex dataset. Many of the most discussed, most viral, and most interesting visualizations are based on basic chart types. In this chapter, we’ll take a look at some of the familiar core chart types. This is well-trodden territory—a sample of some different approaches can be found in “Further Reading”, including attempts to taxonomize the space in different ways.

This chapter takes a somewhat different approach to organizing core chart types. It is organized around the things that the analyst knows, and wants to know, about the data. This follows from the process of operationalizing the data (Chapter 2), interviewing users (Chapter 3), and understanding the data’s shape and the actions we can take with it (Chapter 4). The operationalization has helped reveal something about how the data is structured and what questions there are about it. This knowledge can be used to select chart types based on specific data questions.

Depending on the analyst’s task and question, visualizations can emphasize different results from the same dataset. For example, the United States Consumer Financial Protection Bureau (CFPB) has released information about consumer complaints and how they were resolved across a number of different financial products. Among other columns, the data describes the class of financial products to which a complaint applies and the type ...