Discrete Points in Time
Temporal data can be categorized as discrete or continuous. Knowing which category your data belongs to can help you decide how to visualize it. In the discrete case, values are from specific points or blocks of time, and there is a finite number of possible values. For example, the percentage of people who pass a test each year is discrete. People take the test, and that’s it. Their scores don’t change afterward, and the test is taken on a specific date. Something like temperature, however, is continuous. It can be measured at any time of day during any interval, and it is constantly changing.
In this section you look at chart types that help you visualize discrete temporal data, and you see concrete examples on how to create these charts in R and Illustrator. The beginning will be the main introduction, and then you can apply the same design patterns throughout the chapter. This part is important. Although the examples are for specific charts, you can apply the same principles to all sorts of visualization. Remember it’s all about the big picture.
The bar graph is one of the most common chart types. Most likely you’ve seen lots of them. You’ve probably made some. The bar graph can be used for various data types, but now take a look at how it can be used for temporal data.
Figure 4-3 shows a basic framework. The time axis (the horizontal one, that is, x-axis) provides a place for points in time that are ordered chronologically. In this case the points ...