Statistical Graphics and
Data Visualization

We got this from Friedrich who is just finishing a sabbatical in Paris:

Michael came up with the idea of a challenge. Here's what he wrote:

Here's a graph you may find interesting, published yesterday in Le Monde.
The manifest goal is to compare estimates of les manifestants at les manifestations according to the unions vs. the police throughout France. An admirable goal for a newspaper, and done with some sensitivity to graphic principles, in a style reminiscent of les Albums: color-coding key (but no scale), time-series sub-graph, numbers included for those who want/need them.

But what do we see, and is there anything we could see better by some other display or encoding of these numbers? Obviously, either the police in Paris can't count or deliberately misrepresent things, or the unions there have enormously dilated pupils. Is the over-count ratio greater in Paris than in Marseilles? Were the police in Mont de Marsan all en cong'e? Is Dijon the place with the closest correspondence between the estimates? Presumably, they used count ~ area (or sqrt radius); should they have used a different power for better perceptual comparison? What is missing from this display? e.g, how did the turnout in Toulouse compare to that in Nante or Rennes, taking population into account?
best,
-Michael

You can download the data here. Any comments are welcome and of course, any attempt of a better visualization will be posted here!

Have fun!

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Here are two posts:

Michael sent this graphics:

He wrote:
"Here is a simple log-log scatterplot that answers some of the questions posed originally. On a log scale, the relation is fairly linear, with a slope of 1.19, indicating that union estimates are on average about 154% of those by the police. I've labelled only those cities that have a log-residual greater than 0.15, and scaled the axes so that the line of equality is approx. 45 deg."

Romain's (updated) suggestion is:

(See also his comment!)

There are many stories and myths about the sinking of the Titanic.

We recently compiled the data on the lifeboats (721 passengers who entered a lifeboat) and a nice pattern came out in the fluctuation diagram of "launch sequence no." against "class".

(female passengers highlighted)

The "fate" of the lifeboats is listed under http://www.encyclopedia-titanica.org/lifeboats/

What can be learned from the fluctuation diagram?

• 1st class was served with the first 6 boats
• The next 4 boats were mainly 2nd class
• Boats 11-14 had many 3rd class passengers
• Boats 3 and 12 were less filled and almost no men entered these boats
• Boats 18-20 are not well filled
• ...

There is more to see, when reading the story and the graphics side by side.

This time no fancy graph, but a nice example of "less can be more". I took this month's example from the R Graph Gallery.
Here's "The Bad":

Above graphics tries to depict a r by s table in a 3-d view. Uwe's example has several problems

• The 3-d view make a judgement of the heights almost impossible
• The chosen view point (seems to be the default) puts 2 to 3 bars into a row, which makes it even harder to read the plot
• What does the gray shading of the bars mean?
• Why use meaningless random data for the example ... (if there is nothing to interpret in the data, it is hard to prove that the plot has problems in interpreting the data displayed)

"The Good" uses Bertin's "Accident" data. It is a simple fluctuation diagram of Age vs. Vehicle which performs very well to display simple tables:
Sizes of tiles are simply proportional to the counts in the category. Patterns and trends are easy to depict, though it lacks the fancy 3-d property ...

(There will be a "Statgraphics 101" on Mosaic plots and alike soon ...)

There is a gallery of R graphics at http://addictedtor.free.fr/graphiques/index.php.

The nice thing of this gallery is that you can get the sources of all examples, so this can be a good starting point for your own custom graphics in R.

There is a similar page - not so sleek - at http://zoonek2.free.fr/UNIX/48_R/04.html which is a bit more instructive.

None of the pages raise the question whether the presented graphics are useful though ...