Junk Charts

Reading

Here are some things I have been reading while I'm traveling (the posting schedule will be erratic):

Does the vaccine matter?  Shannon Brownlee and Jeanne Lenzer investigates for The Atlantic.  About 100 million Americans get the flu shot each year; what benefit does it confer?  This is an excellent article.

Some provocative quotes:

Flu comes and goes with the seasons, and often it does not kill people directly, but rather contributes to death by making the body more susceptible to secondary infections like pneumonia or bronchitis. For this reason, researchers studying the impact of flu vaccination typically look at deaths from all causes during flu season, and compare the vaccinated and unvaccinated populations.

The estimate of 50 percent mortality reduction is based on “cohort studies,” which compare death rates in large groups, or cohorts, of people who choose to be vaccinated, against death rates in groups who don’t. But people who choose to be vaccinated may differ in many important respects from people who go unvaccinated—and those differences can influence the chance of death during flu season. [Ed: people who can afford the flu shot vs. those who can't; people who are more health-conscious vs. those who aren't, etc.]

“For a vaccine to reduce mortality by 50 percent and up to 90 percent in some studies means it has to prevent deaths not just from influenza, but also from falls, fires, heart disease, strokes, and car accidents. That’s not a vaccine, that’s a miracle.”

In the flu-vaccine world, Jefferson’s call for placebo-controlled studies is considered so radical that even some of his fellow skeptics oppose it. ... “It is considered unethical to do trials in populations that are recommended to have vaccine,” a stance that is shared by everybody from the CDC’s Nancy Cox to Anthony Fauci at the NIH. They feel strongly that vaccine has been shown to be effective and that a sham vaccine would put test subjects at unnecessary risk of getting a serious case of the flu.

Another pie chart, Fox News (via FlowingData, thanks to reader Katherine M for the pointer; also via Wonkette and reader omegatron).

Yet another pie chart, Business Insider.  Not on the same scale as the one above but still why?

Clean Water Act Violations, New York Times. Can we trust tap water?  As usual, a set of small bars would work better than concentric circles.

How does your state compare to California? (via Pew and Mother Jones) This is a nice illustration that often it is better to plot data derived from the raw data, as opposed to the raw data itself.  Since the designer decided to hide the information, let's figure out what were the cut-off points for the color categories.  If the size of each category is not the same, the designer needs to explain the scale.  Also, the two shades of light blue are hard to tell apart.  But all in all, a good effort here.

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.

Getting the Nobel wrong

Why do we pay so much attention to seemingly inconsequential details of a chart's scale, colors, labels, etc.?

Here's why. (Reader Omegatron pointed us to the FAIL blog that captured this beauty.)

Notice the messed-up horizontal scale, in particular, the failure to start the axis at 0.  The result: the tiniest difference presented as a wide gulf.

The graph, published by the Washington Post, has since been fixed.  See here.  Nevertheless, the comments left by readers lent witness to the confusion.  I copied the first bunch that mentioned the graphical display - there were plenty of for-and-against-the-prize comments, many assuming that the poll result was as lop-sided as the chart seemed to indicate.

By starting at a base of 45% (as of this reading), your graphic grossly misrepresents the results of your poll. The "no" bar is four times as big as the "yes" bar, giving the visual impression that the vote must have gone 80-20 against Obama's Nobel. On the contrary, as of now the vote is 53-47 against. Whoever produced this graphic should re-read Edward Tufte's "The Visual Display of Quantitative Information."

Posted by: threefab | October 9, 2009 8:33 AM

Someone made comment that the graph is misleading, but it really isn't if you know how to read a graph.

This type of graph highlights the difference, not the complete number of votes and is appropriate when viewing percentages.

Posted by: gconrads | October 9, 2009 8:39 AM

why is graph not drawn to scale? The vote is 51 - 49 no and the graph looks like an overwhelming number of "voters' said no

Posted by: spitts1 | October 9, 2009 8:41 AM

The graph is purposely designed to make it appear that there are a huge number of no votes and demonstrates obvious bias.

Posted by: fingersfly | October 9, 2009 8:41 AM

I'm looking at the graphic here and cannot figure out what you guys are trying to show?
The tiny slice of blue is supposed to be 50% and the huge slice of red is supposed to be 50% and the scale at the bottom is......
WHAT?

Posted by: Tomcat3 | October 9, 2009 8:53 AM

It is my understanding that the President did not "win", but was "awarded" the prize...much like a bonus given to you from your employer...deserving or not. In addition, I could not help but notice that after casting my vote, the graphic scale indicated 49% yes and 51% no; however, the graph lines seemed much more disproportionate for only a 2% spread with emphasis on “no”…

Posted by: jonbwnfd | October 9, 2009 9:40 AM

Why does the graph make the vote look so lopsided?

Posted by: subwayguy | October 9, 2009 9:48 AM

The graph is not lopsided .. the numbers are. Read the posts and you will see the posts are against the idea not for.

Posted by: T-Tom | October 9, 2009 9:53 AM 

Who designed the bar graph? The difference between the "yes" votes and the "no" votes is two percentage points, yet the "no" bar is three times as long as the "yes" bar.

In fact, "yes" is 49% and "no" is 51%: the graph is supposed to illustrate reality, not. . . well, just what DOES it illustrate?

Posted by: cmcintyr | October 9, 2009 10:02 AM

Inconsequential detail?  Big fail?  You decide.

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?

Pie Cubed

Omegatron also did away with a set of cascading pie charts on Wikipedia, a particularly ineffective use of this chart type.  Whenever there are more than two or three categories, the necessary use of many colors can really make one's head spin.

Here, the cascade is being used like a log scale, to artificially elevate the small pieces, which unfortunately are also the least significant pieces of the energy pie.  There is no reason for nuclear, bio-mass, hydro and "others" to add to 100% except that the author decides to group them together.  The 41% nuclear or the 41% solar heating in the second and third charts, respectively, have no meaning in the larger context.

In deference to the original author, Omegatron's new version preserves the arbitrary three-level cascade.  He converts to stacked bar charts, which brings out the differences better.


He also sensibly exposes the original proportions rather than the arbitrary relative proportions.  For example, nuclear energy accounts for 6% of the total, not 41% of the arbitrary "others" bucket which in turn contains 14% of the total.

I'd prefer an even cleaner presentation with unstacked bar charts.  This can be done in either one chart with all eleven categories, or in two charts, as shown below.  The two-chart version assumes that the reader have two key questions: alternative energy sources as a proportion of the total, and the mix of different sources within the alternative category.

With the ordinary bar chart, many fewer colors are needed, and there is no need to print out each data point, nor a need to use guides to point to labels and data.  The trouble of the latter is its tendency to draw attention to the least important aspects of the data.

With this further example, I continue to find the Wikipedia rule to discourage text annotations on graphs bewildering.   Such a rule apparently does not apply to data labels, as can be seen here.  Of course, a graph without any labeling of categories is robbed of meaning but if labels can be saved, so should annotations!

Community outreach

Omegatron re-cycled some Wiki charts and we are happy to report that they are great improvements over the originals.  I welcome other readers to alert us when you have done your bit of community outreach, by ridding the world of chartjunk.  The email address is the name of the blog at gmail for any submissions.

Not surprisingly, the originals were pie charts.

The recycled art: (can be seen here and here)

Why are pie charts such poor tools for communications?  Think about where we can place the message, and you'll find that this chart type is far too rigid.  In a pie chart, the key resource is the relative size of the sectors, followed by the number of sectors, and sometimes the size of the total pie.  Other than those, there are little else useful in a pie chart.

The histograms used by Omegatron are much more flexible.  There can be information encoded in the height of the bars, the width of the bars, the total area, the relative distribution of bar areas, the existence and location of peaks and troughs, etc. etc.

For comparing data collected in slightly different formats, the pie charts are hopeless.  Notice that the lowest category on the left (pink) corresponds to 8 weeks or less, which would include two and a half sectors on the right plus potentially a missing sector for 4 weeks or less.  The histograms below handle this easily.

Omegatron asked for some feedback.  I think the new ones are significantly better.  A few minor points:

• Instead of coloring the background to the chart, I'd color the bars themselves into green/yellow/orange according to the trimester
• I'd put the trimester labels under the horizontal axis, close to the "week" labels 
• The charts obviously need to identify the country and year of the data (which I added).  Omegatron pointed me to an inexplicable Wiki convention of not putting text inside charts (see here).  I must disagree with this convention.  Annotations on charts are some of the most useful things.
• If these two charts are to be placed side by side for comparison, then we need to sort out the vertical scale.  It cannot be the absolute number of abortions but some kind of relative scale in proportion to the population size, or some similar metric. 
• In addition, if comparison is the point, I'd suggest an overlapping histogram with bars having no fill.  

Great work!  And I love to see more of it! 

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:

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.

Spinning the climate

Mike L. pointed us to this pair of "climate change model pie charts", with the brief comment "Yuck".


What they are doing is to use the spinning wheel analogy to present probabilities (odds).  Not a good use of pies either.  Histograms do the job with minimal fuss:

 

I collapsed the 2-2.5 and 2.5-3 degrees sectors since every other one is a one-degree interval.  We see immediately that the effect of the policy is to shift the probability distribution to changes of fewer degrees.


Reference: "Climate change odds much worse than thought", Science Daily, May 20 2009.