Junk Charts

Progress and retrogress

Joran E. pointed to this "icky" chart he found on Clive Crooks' blog at the Atlantic. 


He ordered a "junkchart treatment", so here it comes.

First we wanted to process the triangles, dots and squares to make sense of this data.  We noted that the data came from a single year (2005) so the chart did not trace the development of the education sector over time.  But wait, it used a different route to get at the same idea.  The author compared different generations within each country to see if more and more citizens took university degrees.  So each vertical "arrow" was kind of a historical record of different generations within a country.  Under this criterion, Korea and Japan had come a long way while the US and China stagnated.

The chart is quite impossible to read as designed.  There is little reason to sort by 25-34-year-old proportion when the message concerns improvement over generations.  Besides, what about countries that apparently retrogressed?  (like Russia and Germany)

For this data, I returned to my favored bumps chart.  Here is version one.  There are two ways to read this chart: across countries, we note that most of the European states (blue) had similar profiles showing roughly a constant rate of growth.  The Asian duo of Japan and Korea (brown) had the most marked growth.  Of North America (black), Canada diverged from the US since the 35-44 generation.

Alternatively, we can focus on the change generation-over-generation.  From 55-64 to 45-54, almost all countries in this sample (except Japan) grew at the same rate.  Then between 45-54 and 35-44, the two Asian countries clearly set the pace.  The generation between 35-44 and 25-34 is most interesting: Korea has not slowed, Japan has slowed a little but still grew as fast as Canada.  A trio of European countries (Spain, Ireland, France) outpaced their neighbors.

Below I show version two.  This one combines bumps chart with small multiples.  North America, Europe and Asia/Australia are now in separate charts.  This removes clutter.

 

Gauging the water level

This set of charts covered the back page of one of New York Times' sections this weekend.

Regular readers will share my enthusiasm for the top chart.  It makes a clear, cogent case to support the article's thesis concerning the rise of bottled water.  Various renditions of this type of chart have appeared here, for example.

Specifically, the smart use of color to cluster the line objects helps interpret the trends.  Blue sets out the two primary interests.  (It's a mystery to me why the gray lines were separated into darker and lighter hues.)

The twenty-year horizon used is another nice touch. I'd remove the gridlines although they aren't too distracting here.

Sadly, the second graphic does not meet the high standard of the first.  The biggest problem concerns the red rectangle, purportedly showing how much of the bottled water was imported.  The choice of differently-sized bottles as objects makes it impossible to gauge what proportion of the total was imported.  If the rectangle was placed over 1-litre bottles instead, it would look smaller.

Source: "A Battle Between the Bottle and the Faucet", New York Times, July 15, 2007.

Airline bumps and bump charts

The Harvard Social Science Statistics blog pointed to an NYT article about revenue optimization in the airline industry.  Huge props to the Times for explaining the science (and art and politics) of one of the most successful applications of operations research.

In short, valuable business travellers want refundable tickets.  Because of this and other reasons, about 10% of booked tickets become no shows.  Airlines recoup the loss by over-booking.  Implicitly, they trade off the potential for dissatifying a few unlucky passengers (who would be bumped from their flights) and the potential for flying with 10% empty seats (in addition to unsold seats).  Optimization algorithms (constantly tuned by entry-level staff) try to strike a balance.

Recently, because the average percentage of seats sold has been going up, the room for such maneuvreing has been squeezed, leading to higher bump rates, and more travellers being stranded.  There is some variation across airlines due to the level of sophistication of their revenue optimization algorithms, corporate strategy, etc.

The following charts present data by airline of the bump rates in 2005 and 2006.  One would be interested in answering questions such as:

• Which airlines have the best (or worst) bump rate?
• Are some airlines consistently better (or worse) at controlling the bump rate?
• Which airlines have improved (or worsened) from year to year?
• Are the differences of practical significance?

The original chart shown on the left does not reveal the answers readily.  My favourite bumps chart offers them up clearly (well, except on the question of significance).

The biggest problem, though, is the header: number of passengers per 10,000 bumped.  The data plotted appeared to be the reverse: the number of bumps per 10,000 passengers.  Otherwise, there would have been more bumped passengers than passengers!

Source: "Bumped Fliers and No Plan B", New York Times, May 30, 2007.

Bumps charts and NYT

I just cannot resist another post on Bumps charts since  NYT finally started using them.  Here are two recent examples:

This first chart illustrates the change in property taxes in different municipalities since 1998, as compared to the national average.

A wealth of information is revealed:

• All these places charge more than the national average today
• New York City used to charge less than average but that ended in 2003
• The tax rates are clustered into three groups, about 6%, about 5% and below 4%.  The variance between different places has decreased during these years
• A sharp rise was recorded in all these places in 2001-3 although New York City lagged slightly.  The sharp rise was not observed nationwide

Reference: "Gain in Income is Offset by Rise in Property Taxes", New York Times, Aug 8 2006.

The second example is much cleaner as it involves only one period.  Bolding the "no one" line is particularly effective, bringing out the author's point well.

However, I'd have put the "no one" label on the right, just like the other labels, but bolded.

One could also argue that the real story is the simultaneous decline of "friend", "co-worker" and "neighbor" and rise of "no one" and "spouse".

Finally, it'd be interesting to see the multi-period version as the smooth linear trends are rather incredulous.

Reference: New York Times Magazine, July 16 2006.