Junk Charts

Visual analogies

Many a startling faux pas in graphics start with the desire to utilize visual analogies: the recent shopping mall chart is a good example.  There is something inviting about making a chart about shopping malls look like a shopping mall, or a chart about breakfast foods look like a donut, and so on.

The New York Times (or maybe OECD) makes a chart about economic cycles look like, you guess it, cycles.  Don't really have too much to say about this one - except these two points:

• Much of the validity of the chart depends on the theory behind it.  Do the two variables being tracked (amount produced relative to trend; change in production in last 6 months) capture everything?
• The focus on generating cycles visually left out one of the most important dimension - that of time scale.   For this chart to work, we would like to know not just where we are in the cycle but how much time we'd spend at each point in the cycle.  The interactive charts (graphs 4, 5, 6, 7) show us that the cycles are traversed not at constant speed.  A proper rendering of this data needs to play up the time scale.

If you have ideas of how to improve this, feel free to comment.

Reference: "Turning a corner?", New York Times, July 2 2009.  

Round up

Here are some interesting reading from other places:

Tag clouds have caught on since we approved them a while ago.  One interesting use was at the Life Vicarious blog.  They use it to compare the inclinations of three New York-based restaurant reviewers.  What they should have done is to remove irrelevant words like  "one", "also", "many", "make"/"made", etc.  In statistics, this is called removing "noise" which helps bring out the "signal".

Andrew Gelman discussed the NYT article that reported the finding of unexpected male bias in the children of Asian American families.  He can be counted on to make useful comments on any accompanying graphics.  He rightly pointed out that this is one example of not starting at zero: the relevant baseline is 100 since the metric is essentially the over-age of males relative to females.  I also agree that a line chart with a longer time series plotting percentages rather than over-age would work better.

The racetrack chart made an appearance at Flowing Data.  This one is even more busy and just as impossible to decipher.

The case of the shrinking mall

I had a similar reaction when reading this chart but I will let our reader take center stage.

Top portion

Bottom portion

The back of today's New York Times' Week in Review section devotes half of its space to a lame infographic that wastes space and has a major error (which has been corrected lazily in the version now online at http://www.nytimes.com/interactive/2008/10/14/opinion/20090531_OPCHART.html ) The chart shows the recent decline (or in some cases, rise) of retail sales at 27 common mall chains. My main objection is that the top half of the chart is useless. Yes, it provides a baseline from which shrinkage in area (visual metaphor of income = floor space) in the bottom half can represent the relative declines in sales, but this is redundantly handled better by color. The only part of the chart that I got any information from was the bottom half, and it took me a while before I figured out why the top half was even there. Meanwhile, the error in the printed version is that the +5-10% stores were colored light green while the +0-5% store (Burger King) was colored dark green. It should have been vice-versa. The online version simply swapped the colors in the legend, rather than on the map itself, which works logically but begs the question: why do you have dark red at one end of the spectrum and light green at the other, with dark green in the middle? Thank you for listening-- just blowing off a little steam here. It's a lot of wasted space and I'll bet the New York Times paid a lot for it.

Reference: "Op-Chart: The Fall of the Mall", New York Times. (Ed: I am not sure why the date is given as October 2008.)

Spinning multi-color

New York Times has a great pointer to the Global Warming Art website.  The author Robert Rohde wants to popularize environmental science by visualization of the data.  There are many interesting charts and well worth repeated visits.

These pie charts cry out for some re-dressing:

The pie charts, the colors, the whole works.  Most troubling is that each pie has its own sorting scheme, and because the text labels were not reproduced in the smaller pies, the reader is sent scrambling around to find the right labels.

In addition, these pie charts, as with almost every other pie chart, fail the self-sufficiency test.  Without all the data printed next to each sector, the reader is simply unable to judge the size of each sector.

Further, the aggregate data (larger pie) may not be as relevant after realizing that the smaller pies show very different patterns.  The following junkart version tries to bring out this fact by treating both dimensions (type of greenhouse gas; source of emission) equitably.

While I picked on this particular chart, I must say I support Robert's effort and wish him luck in this very well-intentioned project.

Inspired by Tetris

What should we call this one?  A Tetris chart, perhaps.

In particular, pay attention to the rightmost three pieces: while the shapes look completely different, the actual proportions ranged from 6 to 8 percent.

The Tetris chart fails our self-sufficiency test. The only way to read it is to read the data labels.

Since the proportions add up to 100 percent, this multiple-choice question appears to allow only one answer, even though, as the text said, there were two acceptable answers!  It would be useful to label those two choices separately.  We'd also want to see how the question was phrased.

Seen differently, the Tetris chart is a 4x25 matrix with each cell representing one hundredth of the respondents.

Reference: "Name, Please?  High School Seniors Mostly Don't Know", New York Times, April 19 2009.

Some things never fall

It's New York City.  House prices do not fall.  Enjoy the graphic!

Click here for the interactive version

Reference: "For Housing Crisis, the End Probably Isn't Near", New York Times, April 21 2009.

PS. Memo to grammar teachers: When did they start using contractions in titles? 

Pure delight

 My favorite Bumps chart in the New York Times ...

For the purist, this is the original rank-based version.

With judicious use of color and background/foreground, this makes for a good story.

The color scheme here, however, is a bit bland.  Green for improvement, blue for decline and orange for USA.

Note, for example, New Zealand and England both suffered similar drastic drops as the US.

It would be better to (for example) split out the large improvements and large declines, or to split out the developed world versus the developing world.

This chart is created like this probably because the accompanying piece makes only passing reference to this chart so there is not a clear message to the creator what to do with the data.  

Interestingly, there were no ties in 1960 but quite a few ties in 2004.  I wonder why.  I'd shift the dot to the mid-point between ranks rather than move them up to the higher rank.

All in all, a much more engaging way to present this data than the reams of table found in say the UN World Development Report.

Reference: "Vital Statistics: U.S. Still Struggling With Infant Mortality", New York Times, April 6 2009.

Colorful maps

Bernard L. loved the recent NYT take on immigration in America.

The very pretty maps are found here.

An amazing amount of data is being visualized here.  Mousing on the map will pick up the specific data for each county.  There is a bar up top for discovering the evolution over time.  It would be great if there is an animation button so the map can be played out without clicking.  An animated gif will also do (similar to the disease map we featured some time ago).

The colors on the first map represent the origin of the top ethnic group in each county.  Within each group, the tint of the color further displays the percentage of the population that group accounts for.  The subgroups appear to be 0-2%, 2-5%, over 5%.  The last subgroup is very wide.

Not so keen on the second map with all those bubbles.  They show the number of people from each country by county.  The bubble size is proportional to population.  Every version of this map looks the same because the population is concentrated in the cities and the interior is sparsely populated, no matter what ethnic group.

Regardless, this is another laudable effort by the crew at the Times.

Reference: "Immigration Explorer", New York Times, March 10 2009.

Exemplary

From Bernard L., another exemplary effort by the Times.  This one really got me excited.  

The set of line graphs shows how demographics of students in American schools have evolved in the last two decades.  Here, I selected New York City schools, and the tool sensibly decided to compare those with New York State schools (gray line).

There is so much to learn from one simple chart:

• The blue and gray lines are almost parallel everywhere, which tells us that in terms of the change in demographic composition, New York City pretty much resembled New York State during this entire period.
• However, in terms of demographic composition, rather than the change in composition, New York City schools are very different from the rest of the state, in that the proportion of white is lower by a third while that of minorities are much higher, especially black and Hispanic students.
• State-wide (as well as city-wide), black and white students have been declining as a proportion while Hispanics and Asians have increased. 
• The extent of the change is immediately visible, Asians have jumped from 7% to 14% for example.  

  
From a graph design perspective, the execution is very clean.  Data labels are limited to the first and last values.  A small multiples concept is used with the ethnic groups placed side by side.  A great awareness of foreground and background as well.  And imagine how much data has been visualized here, and be impressed.  You can look at any county in the country.

Here's one where the county change does not exactly mirror the state change (Napa in California):

Reference: "Diversity in the classroom", New York Times, March 12 2009.

Deep dive

The chart on the right which compares the unemployment picture across past recessions has many good features.



It uses a very sensible metric, counting the percentage change from peak employment.  I have mentioned the superiority of this type of presentation compared to plotting a time series of unemployment rates.  The following is an example of a standard graphic using gray bands to indicate recessions.  The difference is obvious.

Here is the previous post that dealt with the drop in market capitalization of banks since the peak which screamed out for this type of treatment.

It handles the foreground-background issue very well.  A number of similar charts is circulating in which every single line has a different color.  Here, the designer clearly tells us the current recession is the foreground and all the past recessions form the background.  It looks as if the 1981-3 recession is slightly highlighted with a darker orange to draw attention to the fact that it is most similar to the current situation.  I find this unnecessary because the association is clear even without the darker hue; however, the designer does this with a very light touch so this is just a question of taste.

I would label the horizontal axis starting at 0. 


Reference: "Job Losses Hint at Vast Remaking of Economy", New York Times, Mar 8 2009.