Junk Charts

Which software is responsible for this?

@guitarzan wants us to see this chart from north of the border, and read the comments. Please hold your nose first.

 

Here's one insightful comment: "I think it's insane to debate the ages 18 or 19. Why not cap it off at the much more rounded and sensible numbers 18.2 or 19.4??"

Reminds me of signs that say this elevator holds 13 people, or this auditorium holds 147 people safely.

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I mean, which software package enables this chart?

For the vertical axis, it appears that the major gridlines are specified to 0.4 with minor gridlines at 0.2 apart. The lower limit of the vertical axis was specifically set to 17, which violates the start-at-zero rule for bar charts.

The software also allows the yx-axis labels to be printed twice, one in super tiny font in the expected locations, and the other turned sideways and printed into the bars.

And Canadians, please tell us why the provinces were ordered in this way.

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This data calls for a simple map, with two colors.

 

What's wrong with this food picture?

Here's a chart in the November edition of Bloomberg Markets:

Curiosities include: how they split up the lamb chop, why an onion is chosen to represent "fresh vegetables/melons"?

The chart contains some strange data that make readers feel nervous. For example, the fish image seems to say 88 percent of seafood eaten in the States are imported, and yet the two largest importing countries listed below (China and Vietnam) together account for only 22.5 percent. So the residual 65.5 percent must be split among at least 10 countries each accounting for not more than 6.5 percent of the total.

Then when you look at vegetables, Mexico and Canada together supply 72 percent. But the onion graphic tells us it's less than 20 percent. The categorization seems to be different between the top and the bottom layers. We have "fruit and nuts" / "fresh vegetables/melons" on the one side, and "fruit" / "vegetables" on the other side.

And why are melons combined with fresh vegetables rather than fruit?

Staggering excess

Business Insider calls this stacked bar chart "staggering" (link).  Maybe they are referring to its complexity.

Is there a reason to include all the fine details? The details serve little purpose other than to shout at readers that there is a lot of data behind this chart. It is impossible to compare the different drugs on the individual harmful effects based on reading this chart. All we can see is the comparison of total harm. (By the way, I can't explain why anabolic steriods rated 10 would be sandwiched between khat and ectasy both rated 9.)

It turns out there is an easy way to fix this chart. We turn to the original Lancet paper which contained this chart, by David Nutt (link). The 16 categories of harm are nicely organized into a tree structure:

Instead of taking data from the right side of this tree, we can take data from the aggregated levels. The sacrifice in detail comes with a major benefit in clarity. In the original paper, Nutt produced a chart that aggregated everything to two levels:

 

 

 

 

 

 

 

It's amazing how much more we learn from this chart even though it has less data than the previous one. (I'd still remove the data labels since they are redundant when one has the axis labels.)

Similarly, we can plot a chart at the level of physical, psychological, social, etc., and it would still be much more readable than the "staggering" one.

PS. Apparently, David Nutt is a controversial character. See Wiki (link).

Bloomberg issues a health warning dressed up as a fast-food menu

NYC mayor Michael Bloomberg is getting mixed reviews for his proposal to ban super-sized sugary drinks. Reader John O. wasn't impressed with this graphical effort (link):

 

The key problem: this picture is not scary at all. The reason it's not horrifying is that there is no context. People who have knowledge about healthy eating habits will get the message but that's preaching to the choir.

If you know that the recommended consumption of daily sugars for adults is roughly 20-36 grams, then you can see that one sugary drink of 12 ounces or higher would take you over the daily limit. A 64-ounce drink would give you more than 7 times what you need in a day. That's a powerful message but you won't know it from this chart. Not from the sugar cubes doubling as shadows, which is a cute, creative concept.

Also, make use of the chart-title real estate! Instead of "Sugar & Calories per Fountain Drink", say something memorable. "Fountain drinks make you fat and sick".

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There is something else fishy about this graphic. What are the most prominent data being displayed?

You got it. They're 7, 12, 16, 32, 64. Where have we seen this type of data display?

Yup. This format is lifted from a menu in a Starbucks or a McDonald's (without prices).

Is this a health warning? Or a restaurant menu?

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John wrote:

Also slightly confused about the slightly non-linear relationship between calories and drink size.  Maybe volume of ice is held constant...

It is in fact a proportional relationship. The confusion arises from the non-linear increase in cup size from 7 to 64 ounces. The math is roughly 11 calories per ounce, and 3g of sugar per ounce. I wonder if it is better to show those two numbers instead of the ten not-very-memorable numbers shown on the chart itself.

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In case you're wondering, the heights (thus areas) of the cups have no relationship with any of the data, not calories, not sugars, and not the cup size.

 

PS. John also wrote: "The soda cup graph reminds me of the chart from Pravda that Tufte cites in 'Cognitive Style of Powerpoint'. " If you know what he's talking about, please post a link to the chart. Thanks.

Look what I found: two amazing charts

While doing some research for my statistics blog, I came across a beauty by Lane Kenworthy from almost a year ago (link) via this post by John Schmitt (link).

How embarrassing is the cost effectiveness of U.S. health care spending?

When a chart is executed well, no further words are necessary.

I'd only add that the other countries depicted are "wealthy nations".

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Even more impressive is this next chart, which plots the evolution of cost effectiveness over time. An important point to note is that the U.S. started out in 1970 similar to the other nations.

Let's appreciate this beauty:

• Let the data speak for itself. Time goes from bottom left to upper right. As more money is spent, life expectancy goes up. However, the slope of the line is much smaller for the US than the other countries. There is no need to add colors, data labels, interactivity, animation, etc.
• Recognize what's important, what's not. The US line is in a different color, much thicker and properly made the foreground of the chart.
• Rather than clutter up the chart, the other 19 lines are anonymized. They all have the same color and thickness, and all given one aggregate label. This is an example of overcoming loss aversion (see this post for more): it is ok to suppress some of the data.
• The axis labeling is superb. Tufte preaches this clean style. There is no need to use regularly-spaced axis labels... use data-informed labels. Unfortunately, software is way behind on this issue. You can do this in R but that's about it.

 

Is that my third leg?

We look at another idea from the visualization project "Gaps in the US Healthcare System" (link). This was a tip from reader Jordan G. (link). One of the bright points about this project is the conscious attempt to try something different although the end result is not always successful.

A tree-like branching chart was used to represent cancer death rates, broken down by racial group, gender and type of cancer, in that order.

The tree structure loses its logic after the race and gender splits. Why link different types of cancers (the gray squares) together in a sequence? Stranger still is the existence of a third branch coming out of every race node (the four closest to the center). One branch is male, the other branch is female, what's the third leg? It appears to be prostate cancer which is male only--why doesn't it go with the male branch?

It's not easy to find the connection between what's depicted here, and the idea of "gaps" in the US healthcare system. I think the question is ill-posed to begin with.  The rate of death reflects both the possible differential quality of healthcare between groups and the differential incidence of cancers between groups so no visualization tricks could be used to find reliable answers to the question being posed.

The chart fails the first corner of the Trifecta checkup. The chart type also does not fit the data.

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The following chart plots the same data in a Bumps style.

I separated the male and female data since certain cancers are limited to one gender, and the gender difference is not likely to be the primary interest. The gender difference, incidentally, is clearly observed: the male death rates are generally about twice as high as the female rates of the same type of cancer, except for colorectal.

In terms of the "race gap", we find that black death rates are generally quite a bit higher than white death rates, especially for prostate cancer but except for lung cancer in females.

Asians and American Indians have practially the same death rates but in both cases the sample sizes are small.

The raw data can be found at the CDC website here.

 

High-effort graphics

Jon Quinton made a chart for Cancer Research UK, which is quite an eyeful.

The full infographic is here.

Below is a close-up of the key of this chart:

Where would this chart fall in my "return on effort matrix"? It is an extremely high-effort chart; I got tired trying to figure out what all those dimensions mean.

Is it a high-reward or a low-reward chart? It depends on why you're reading the chart. For most readers, I suspect it's low-reward.

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In my view, the best charts are high-reward, low-effort. I'd emphasize that by effort, I mean effort by the reader. In general, the effort by the chart designer is inversely proportional to that by the reader.

In some special cases, high-effort charts may have high reward justifying the destruction of some brain cells.

Low-effort, low-reward charts are harmless.

More on the return-on-effort matrix here.

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One simple improvement to a chart like this one is to produce separate charts for men and women. Outside academia, it seems to me almost all use cases for this chart would involve only one gender.

 

Flour, egg and milk

Reader Julien D. found this collection of Venn diagrams by Stephen Wildish (link), including this one:

A restaurant gem

Felix Salmon spoke highly of this Wall Street Journal chart, and I agree.

Why do I like this? Although it's a basic chart, they did many little things well.

• They are brave enough to not print any of the actual data on the chart. In other words, no loss aversion.

• The legend is integrated onto the chart, not banished to some corner or border, requiring readers to stray from the graph. For added effect, the A, B, C labels imitate the actual signs posted outside the restaurants.

• Simple and effective use of colors

• Sensible scales. It's even better if they would thin out the horizontal scale for the C rating, say make it 10-point intervals instead of 5-point intervals. Although this is hard to accomplish using conventional software, an axis with different intervals in different regions is surprisingly effective.

• Using pencil-thin columns. The same chart with thicker columns would be both uglier and less effective.

(I'm not sure I like the up and right arrows on the axis titles. Is it better to remove the arrows and center the text?)

 

Return this plate, I want my pie chart

Reader Brad E. reminds me about the USDA's attempt to "improve" the visual presentation of dietary standards. As reported here, the food pyramid failed its mission and is retired. Here comes MyPlate!

 
According to this report, the government wants to impart these key points:

• MyPlate offers a visual reminder to make healthy food choices when you choose your next meal.
• It can help prioritize food choices and remind us to make fruits and vegetables half of our plates each meal.
• On the other side of the plate – and beside it – we see the other important food groups for a healthy meal: whole grains, lean proteins, and low fat dairy.

We have been warned not to think of this as a pie chart.

What do we call a circular chart in which the area of the circle is partitioned into separate regions?

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How does one say return MyPlate to the kitchen fast enough? The biggest problem here is that the key points are out of sync with the chart details. The MyPlate diet, as depicted, has less than the recommended amounts of fruits and vegetables! Since those two important food groups only equal grains and proteins, the presence of dairy means that fruits and vegetables form less than half of this diet.

The core message is that one should split one's diet in half, with fruits and veggies on the one side and grains, proteins and dairy on the other. If this is so, the following chart gets this point across with minimal probability of confusion:

If, on the other hand, the above chart is deemed too simple, and the message really does require proportions of each of the five food categories, then the sad truth is that a pie chart would have conveyed the message better.

MyPlate serves up strange portions that cannot be properly sized. How big is the "dairy" circle compared to any of the quadrants? How does one judge the irregularly-sized quadrants (grains and vegetables)? If there is any use for the pie chart, it is to display simple concepts with limited dimensions.