Graphics Programs Reference
In-Depth Information
But wait, there's more! You don't have to stop there. If you incorporate
another dimension of data, you can see changes over both time and space.
In Chapter 4, “Visualizing Patterns over Time,” you visualized time more
abstractly with lines and plots, which is useful, but when location is
attached to your data, it can be more intuitive to see the patterns and
changes with maps. It's easier to see clustering or groups of regions that
are near in physical distance.
The best part is that you can incorporate what you've already learned to
visualize your data over space and time.
Small Multiples
You saw this technique in Chapter 6, “Visualizing Relationships,” to visual-
ize relationships across categories, and it can be applied to spatial data,
too, as shown in Figure 8-24. Instead of small bar graphs, you can use
small maps, one map for each slice of time. Line them up left to right or
stack them top to bottom, and it's easy for your eyes to follow the changes.
FIGurE 8-24 Small multiples with maps
For example, in late 2009, I designed a graphic that showed unemployment
rates by county (Figure 8-25). I actually used a variation of the code you
just saw in the previous section, but I applied it to several slices of time.
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