Color can be an incredibly effective tool to enhance data
visualizations. At the same time, poor color choices can ruin an
otherwise excellent visualization. Color needs to be applied to serve a
purpose, it must be clear, and it must not distract.
Encoding Too Much or Irrelevant Information
One common mistake is trying to give color a job that is too big for it
to handle, by encoding too many different items in different colors. As
an example, consider Figure 19-1. It
shows population growth versus population size for all 50 US states
and the District of Columbia. I have attempted to identify each state by
giving it its own color. However, the result is not very useful. Even
though we can guess which state is which by looking at the colored
points in the plot and in the legend, it takes a lot of effort to go
back and forth between the two to try to match them up. There are simply
too many different colors, and many of them are quite similar to each
other. Even if with a lot of effort we can figure out exactly which
state is which, this visualization defeats the purpose of coloring. We
should use color to enhance figures and make them easier to read, not to
obscure the data by creating visual puzzles.
Figure 19-1. Population growth from 2000 to 2010 versus population size in 2000, for all 50 US states and the District of Columbia. Every ...
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