Junk Charts

Disentangle

In an article called "Off the Charts", Floyd Norris wanted to let readers know that unemployment does not hit citizens equally -- it affects some age groups and men/women to differing degrees. 

As befits the article's title, he included several charts, from which I extracted the one shown on the right.  At first glance, this seems like a normal chart.

But when one pays attention, one notices that the chart is rather complicated.  This chart is like a piece of modern music, in which the composer allows two voices to jar and talk past one another.

Think of it as a data table vying for attention with a bar chart.  The data table is a cross-tabulation of the change in employment by age and gender.  In this view, the men sit on the left, and the women on the right.

Lurking around is a bar chart, for which the point of zero change sits in the middle.  Positive growth extends to the right, while negative growth points to the left.  The gender labels at the top are irrelevant  for this bar chart: the narrow black bars indicate women, the fat colored ones, men.  The data labels are also irrelevant: see, for example, the 45-54 age group, the label for females, at -2.3, should really be placed on the left side of the middle divide!

Here is how these two charts look, disentangled: (I have converted the bar chart to a dot chart.)

 

  

Reference: "Off the Charts: Job losses mount, enduring and deep", New York Times, Nov 14 2009.

Text of a novel, centered

How would a novel read if all the text were centered?  I am aware that most Westerners read from left to right, and some Easterners read from right to left.  Not until now am I educated on the third way, which is to center everything.

Here is the object of study, courtesy of the Wall Street Journal:

The point of the chart is to compare Samsung's revenues with those of key competitors in each category.  The comparative information is the difference in lengths between the pair of bars.  This difference is halved and then tagged on to each end of the bar.  This requires reading from outside in.

In order to double the fun, the data labels are pushed to opposite ends of the bars as well, perhaps to let us know that indeed, the companies under comparison are maximally different.

Furthermore, while the key comparison is between Samsung and its competitors, the Samsung bars experience a chameleon shift from blue to green to red to yellow.  The competitors' bars follow suit but wearing checkered skirts.

Because black labels jar with checkered fabric, the fabric must first be bleached before applying the labels (or price tags).

Beyond the amusement, there are some serious problems with the choice of data.  We are never told why Sony, Nokia, Intel and LG Display were chosen as foil to Samsung.  Are they the nearest competitors or the biggest player in the respective segment?  We question whether one quarter's revenue could be representative of the big picture.  We wonder about the effect of currency conversions since the chart encompasses at least three different currencies.  We ask if the definition of "consumer electronics" is the same between Samsung and Sony.

Reference: "Samsung's Swelling Size Brings New Challenges", Wall Street Journal, Nov 12 2009.

Life-enabling charts

In response to my call for positive examples, reader Merle H. sent in an example of how good charts can make our lives simpler and easier.

All of us have seen the following presentation of air travel data.

Not trying to pick on Travelocity - it's the same format whether you use Expedia or any of the airline sites.  For those customers who are looking to decide what dates to travel so as to minimize their air fare, this format is very cumbersome to use.

What about this fare chart at FuncTravel.com?

As you mouse along the line chart, the average fare for each day is visible.  Clicking on a particular day will fix the departure or return dates.

So much easier, isn't it?

A few caveats, though:

• Instead of just providing the historical averages, they should consider including information on variability, such as bars that indicate the middle 50% or 75% of prices.  Also, what about a sliding control for customers to decide which period of past history the averages should use?  More recent data may be more representative.
• This particular feature appeals to the price-sensitive, date-flexible customer segment.  Not everyone will pick itineraries based on those criteria.  There is an easy fix. If some controls are available for customers to indicate other preferences, e.g. exclude all British Airways flights, include only evening flights, etc., and the chart can update itself based on such selections, then the chart becomes a lot more flexible, and useful to many more customers.
• As with many automatically generated charts, the chosen labels on the vertical axis are laughable.  That should be relatively easy to fix, you'd think.
  

A great start.  I happen to notice that Travelocity has a beta feature that shows a similar chart.  A revolution in how travel sites present data to us is long overdue. 

Seth's Rules

(Via Gelman blog)

Prominent marketer Seth Godin came up with some sensible rules for making "graphs that work".  We pretty much agree with most of what he says here, unlike the last time he talked about charting.

One must recognize that he has a very specific type of chart in mind, the purpose of which is to facilitate business decisions.  And not surprisingly, he advocates simple, predictable story-telling.

His first rule: dispense with Excel and Powerpoint.  Agreed but to our dismay, there are not many alternatives out there that sit on corporate computers.  So we need a corollary: assume that Excel will unerringly pick the wrong option, whether it is the gridlines, axis labels, font sizes, colors, etc.  Spend the time to edit every single aspect of the chart!

His second rule: never show a chart for exploration or one that says nothing.  I used to call these charts that murmur but do not opine.  (See here, for example.)  This pretty much condemns the entire class of infographics as graphs that don't work.   This statement will surely drive some mad.  One of the challenges that face infographics is to bridge the gap between exploration and enlightenment, between research and insight.  As I said repeatedly, I value the immense amount of effort taken to impose structure and clarity on massive volumes of data -- but more is needed for these to jump out of the research lab.

In rules 3 and 4, Seth apparently makes a distinction between rules made to be followed and rules made to be broken.  In his view, time going left to right belongs to the former while not using circles belongs to the latter.  He gave a good example of why pictures of white teeth are preferred to pie charts, bravo.  I hope all those marketers are listening.

As readers know, I cannot agree with "don't connect unrelated events".  He's talking about using line charts only for continuous data.  This rule condemns the whole class of profile plots, including interaction charts in which statisticians routinely connect average values across discrete groupings.  The same rule has created the menace of grouped bar charts used almost exclusively to illustrate market research results (dozens to hundreds of pages of these for each study).  I'd file this under rules made to be broken!

What menace?

What menace?

What menace?

What menace?

Alright, I made my point.  If you don't work in market research, the mother lode of cross-tabs and grouped bars, consider yourself lucky.  If you do, will you start making line charts please?

Bubble after bubble

I finally checked the Junk Charts mailbox again, and I found an uprising against bubble charts and pie charts.   It appears that despite their shortcomings amply demonstrated here and elsewhere, editors everywhere continue to believe that the public has a lovefest with these creatures.

I will start off the parade with this one from the Wall Street Journal, purportedly showing that the Bank of England has continued to inject cash into the economy, and at ever increasing rates.  The headline said Bank of England to expand bond-buy plan.


This chart has a variety of problems, in addition to the use of overlapping bubbles.  As has been documented, it is almost impossible to gauge the relative sizes of circular areas, especially when they are overlapping.

If we remove all but one of the data labels, the chart is non-functional.  This is what we mean by not self-sufficient: the interpretation of this chart requires, indeed demands, that all the underlying data be printed on the same chart.  The only way readers can understand what is going on is by reading the data itself!

The horizontal axis (indicating time) is also non sensical.  The separation from month to month is variable.  Besides, and this is the key flaw of the chart, the projected number is a three-month total cumulative growth being treated like a monthly figure.

 

Since the Bank is projected to inject 175 50 billion extra pounds in the next three months, that would work out to be roughly 60 16 billion per month.  That would turn the story upside down: one would conclude that the Bank is gradually slowing the rate of injection.  The following bar chart points this out with little fuss:

 

When bars are used, there is no need to print every single data point.  The relative lengths of the bars can be estimated easily.  The months are equally spaced.

One final point: the exchange rate cited is not very helpful.  What would have been more useful for readers would be the scale of the cash injection with respect to each nation's GDP.

Reference: "Bank of England Expands Bond-Buy Plan", Wall Street Journal, Aug 7 2009.

PS. Per Andrew's comment, here is a line chart, where the growth/decline in the injection is encoded in the slope of the line segments:

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.)

The trouble with two lines

It's never a good idea to put two scales on one chart, and this is another example of what not to do:

The ugliest part of this chart are the duelling gridlines. Because neither axis starts at zero, it is difficult to access whether the number of newspapers was declining at a faster pace than the circulation was. Also, line charts would be better able to trace the evolution over time. The interspersed blue and red columns interfere with each other. Note that the designer lessened our pain by plotting every other year, thus halving the number of columns.

The junkart version also puts two data series on the same chart but on the same scale. Instead of plotting the raw data, we plot indices, with 2008 as 100. This reveals a pattern that was not apparent in the original chart. There appeared to have been four periods of evolution: up till 1980, both the number of newspapers and total circulation were at a plateau; from 1980 to 1990, the circulation stayed stable while the number of papers dropped drastically, indicating perhaps consolidation; then from 1990 to 2003, both series declined at roughly equal rates; and finally, the bottom dropped off the circulation from 2003.

See our previous discussion of dual axes here, here, and here

Reference: "Channel Shift: Online Circulars: the first step by retailers toward web-to-store harmony? ", Internet Retailer (print), May 2009. Data from the Newspapers Association of America.

Bonus 1: Thinking about the column interspersing trick some more, I realize that it is, em, possible, em, that one series was plotted for odd years and the other series plotted for even years!

Bonus 2: Here is the requested scatter plot (still indiced):

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.

Scale restoration

The original graph threw us off our sense of scale.  It seemed to be saying all these oil companies are roughly the same size but one grew much faster than the others.  The red color and the setting off of the data above the title of the chart seemed to announce some important find.

The junkart version on the right reversed everything to our normal sense of scale.  It is a version of the bumps chart, one of my favorites.

So we find that Total is the smallest of these oil companies, about half the size of ExxonMobil -- you wouldn't know that from those abysmal bubbles!   Adding to the problem is that the growth data is used to sort the companies while the actual production data is hidden in the data labels.

Total is indeed growing faster but BP is not far behind.  The fall of ExxonMobil and Royal Dutch Shell is equally intriguing.


Reference: "Total, the French Oil Company, Places Its Bets Globally", New York Times, Feb 21, 2009.

Green panels

This panel chart appeared in an article about solar panels in Business Week.  Not understanding this one at all.

Reference: "Solar: first a shakeout, then a boom", Business Week, Jan 12 2009.