Spotting Differences - Data Points: Visualization That Means Something - page 261

FIGurE 7-27 Dot plot showing results of multidimensional scaling
Not bad. each dot represents a state. One problem, though: You don't
know what state is which. You need labels, so like before use text() to put
state names in place of the dots, as shown in Figure 7-28.
plot(x, y, type=”n”)
text(x, y, labels=education$state)
That's kind of cool. You see a couple of clusters emerge, with one on the
left and the other on the right. United States is on the bottom of the right
cluster, toward the middle, which seems about right. At this point, it's up
to you to figure what the clusters mean, but it's a good jumping off point in
your data exploration escapades.
You could, for example, color the states by dropout_colors like you did with
the parallel coordinates, as shown in Figure 7-29. It doesn't tell you much,
but it does confirm what you saw in Figure 7-25.