Graphics Reference
In-Depth Information
typeface, is known for its neutral look that lends to fact presentation, whereas
Comic Sans has developed into a meme and a way to avoid being taken seri-
ously. Serif typefaces such as Baskerville and Palatino are reminiscent of vin-
tage graphics. You should probably avoid Wingdings for most practical uses.
Again though, a lot has to do with personal preference, so experiment and see
what you like—especially because it's so easy to do with modern software.
Remember the visual hierarchy, though. Headers typically stand out visually,
so a larger, bold font often works, whereas tick labels are usually smaller and
demand less attention, so the typeface should still be readable at a relatively
small size. Sans-serif fonts often work well for the latter because serif fonts
with a lot of flourish can be harder to read in confined spaces. Although, this
is nowhere near a rule.
DO THE MATH
After you get data, the natural first step is to visualize it directly, but after that,
it might be useful to do some math for a different point of view. This can shift
focus toward something more interesting in the data and in some cases, avoid
guesswork as readers try to interpret your graphics.
For example, summary statistics, such as mean or median, can serve as a quick
point of reference or to provide a sense of scale, as shown in Figure 5-39.
Violent crime rates for each state are shown, and bars are colored based on
whether they are above the national average. The distributions of rates isn't
especially complex in this example, but it helps you get a sense of where each
state lies relative to the national average.
As an additional step, you can transform the data based on a reference point,
rather than just show it in the context of the raw data. Figure 5-40 shows global
gas prices, which you saw in the previous chapter, relative to average gas price
in the United States. Purple indicates higher gas prices, and green indicates
countries where gas prices were lower. The two maps show the same data
but tell different stories via subtraction and division. The first map focused
on worldwide comparisons, whereas this map provides a simple connection
between the data and U.S. readers.
What about Figure 5-29 that shows the unemployment rate over time? Maybe
you're more interested in annual changes than you are monthly unemployment
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