Advanced Maps - Communicating Data with Tableau - page 246

Why are these so effective? If we refer back to our data encoding effectiveness diagram ( Fig-
ure 1-6 ), we'll get a clue as to why shapes on maps can be such a powerful communication
tool: notice that the two most effective encodings for nominal values are position and shape.
Think of the proverbial tiger in the savannah: we are very quick to spot images and to associ-
ate them with the place in which we saw them. It's just how our brain works.
We can also see from Figure 1-6 that we wouldn't want to use shapes to encode quantitative
or ordinal values. Think of the way shapes are used in the world around us: we use traffic
signs with different shapes to indicate the type of action to be performed (like stop or yield),
but we don't use the shapes themselves to tell us the speed limit, for example. This is an is-
sue of nominal versus quantitative information.
Let's consider a few examples of how we can make good use of shapes on maps to commu-
nicate data.
If I wanted to communicate where the 32 different professional football teams are located in
the United States, I could simply provide a list of team names and locations in table form, as
shown in Figure 11-1 , obtained from Wikipedia .
As accurate as this list may be, it's not very useful or interesting. Our brains just can't pro-
cess it very efficiently for a whole host of tasks, such as determining whether there are any
clusters of teams, or figuring out which areas of the country have relatively few teams.
Alternatively, I could show a map of the team names using Tableau, as shown in Figure 11-2 ,
by connecting to the table, double-clicking on City , dragging Team(s) to the Text shelf, and
changing the Marks type from Automatic to Text .