Representing Data - Data Points: Visualization That Means Something - page 472

High school attainment in 2000 is plotted on the horizontal axis, and attain-
ment in 2009 is on the vertical. There is an obvious upward trend, and you
can spot Washington, DC sticking out somewhat, indicating the higher rate
of improvement (and probably difference in demographics). You can also
see Texas and California lagging around the bottom-left corner. As shown
in previous charts—and I'm sure you're getting the hang of it now—you can
incorporate other visual cues such as color, symbols, or both to provide addi-
tional dimensions of information.

Note: If you want to annoy cartographers,
you can also call choropleth maps heat maps,
as they are often referred to. The heat map was
created to visualize 2-D data, and choropleth
maps are the geographic equivalent. I person-
ally keep the terms and methods separate.

Remember this is geographic data, so you must map it,
right? (Actually, just because location is attached to your
data, which seems like almost always these days, a map is
not always the most useful view, which is discussed in the
next chapter.) Figure 3-31 shows a handful of maps with
states colored using varying scales and metrics, which are
called choropleth maps.

Note that although each map uses the same method, the choice of scale can
change the map's focus and message. For example, the map on the top left
uses a quartile scale, which means the states were split into four even groups
based on a metric. In this case, the metric is the percentage of people with
a bachelor's degree in 2009. This makes a map with colors that are evenly
distributed.

However, the map that shows the same data on a linear scale, with just three
shades of green, shows darker shades in the Midwest and Northeast regions.
Compare this with the quartile map, and you still get the lighter areas in the
South, but the rest of the map tells a different story. Likewise, you can further
abstract the data by coloring states by whether they are below or above the aver-
age (top right) or whether percentages increased or decreased (bottom right).

As shown in Figure 3-32, you can also show several maps at once to see how
something has changed geographically over time. Since you've looked the data
from several perspectives already, you know that a high value in 2000 generally
means a higher value in 2009, because the states improved at similar rates.

You see about the same thing when you compare 1990 to 2000. In 1990, you
see a more lightly colored map, where several states showed 15 percent or
less of people 25 years or older with a bachelor's degree. Only Wyoming,
which had the highest percentage in 2009, shows a percentage higher than
25 percent. As you move left to right, the map gets darker, like you'd expect.