Statistical Graphics and
Data Visualization

But as I saw this "novel decision tree plot" on an advertisement by C&H for Paul's R Graphics book, I got inspired again ...

Now here is "The Bad":

Let me explain, what went wrong with the R graphics:

1. A tree, which is just a special graph, consists of nodes and edges
   A full featured barchart in a leaf is certainly a doubtfull glyph for a leaf/node!
2. The size of the nodes must be read as text ...
3. Side by side barcharts are among the weaker representations to display a proportion
4. The numbering of the nodes is non-standard and does not help reading the information
5. Now think of a tree with, say, 10 inner nodes and 11 leaves! How big must the plotting device be to display so much (overhead) information?

This representation is much clearer. Not to overstress Tufte, but the data-ink-ratio in the KLIMT plot is hard to beat!

I personally would prefer the next display (which only takes two key-strokes to change from the first plot!), which puts leaves on the "correct" level and has proportionally sized nodes.

Well, here it finally is:
The R Graphics book. Probably the ultimate resource for contructing R graphics.

What you don't get is anything on statistical graphics. The book won't give you any advise on an efficient use of graphics for statistical data analysis or diagnostics of statistical models. At most, it gives several examples of nifty info graphics - which is still nice.

(For those of you who always wanted to know how to create a crossword in R - that's it!)