Junk Charts

Small multiples re-imagineered

This chart gave me trouble.  I kept staring at it, staring.  Searching for the legend.  What could the several lines, in different colors, represent?  Take a look yourself.

Well, it turns out all three graphs were duplicates.  A different line was given dark blue to highlight a particular amusement park.

I have not seen this tactic used before.  This is like a small multiples concept except that every chart contains the same data.  Is it better than having just one chart?

Reference: "Will Disney Keep Us Amused?", New York Times, Feb 10 2008.

PS. [4/6/2008]  Here are two alternative charts contributed by our readers.  See comments below.

Derek suggested using sparklines:

Zuil reverted to basics:

Trying too hard

In the course of business and governing, a lot of charts are generated.  An anonymous tipster pointed us to a set created by the "Communities and Local Government" division in the UK government.  Judging from the content, this division has responsibility for economic development in local neighborhoods.

Below are a pair of exhibits.  Truly they are trying too hard!  What we see is a hybrid scatter-bubble chart.  Between the jargon, the acronyms (LAD, LSOA), the boxed text, the multi-color circles, the colored axis labels and lack of title, the reader is plunged into a state of confusion.

The chart can be unraveled.  Each district was evaluated based on two measures of "gaps in worklessness".  The vertical axis compares each district to the national average; positive numbers indicate an above-average district relative to the nation.  The horizontal axis compares the most deprived 10% neighborhood within each district to the local average; positive numbers indicate worst neighborhoods improving. 

Thus, the policy goal would be to move all districts into the upper right quadrant.  The multi-color bubbles were designed to show us the state of the nation.  On the left chart, 41% of the districts (or population?) reside in the improving districts while 19% live in deteriorating areas.

The following strategies can help improve readability:

• use English on the axis
• relegate technical definitions to the legend
• add succinct title to tell the story
• use color on the data rather than on axis or data labels
• use color to draw attention to the upper right quadrant
• remove bubbles
• define acronyms

 

Chart cleanup

Anna E. submitted this great example from Yahoo! Green.  A well-meaning chart but stuffed with redundancy.

Much appear to be going on and yet the entire chart contains 15 data points, Boston's ranks on each of 15 categories.  The bar lengths convey the same information as the data labels.  The legend provides a catchy name for different levels of ranks (0-10 = "leader"; 10-20 = "advances"; etc.).  The colors merely reiterate the catchy titles.  Similarly, the colored squares repeat the information in the bars.

In the name of green, we cleaned up this chart:

As a standalone graph, the categories should be ordered by Boston's ranks.  Here, we assume that cross-referencing cities is needed so we leave the order unchanged.

Playful and exploratory

I share reader Bernard L.'s enthusiasm for this very imaginative chart, courtesy of the graphics people at NYT.  The chart captures the ebb and flow of weekly movie receipts over the last two decades.

The details that particularly interest me include:

• The addition of area colors (on top of lines) serves to highlight box office successes; this really helps readers sort out the massive amount of data
• Nicely spaced text (and dots) does not interfere with our reading of the chart
• The hiding of text for less important films, plus taking advantage of interactivity to show their titles if the reader mouses over the respective areas

All of the above indicate a keen sense of foreground versus background.  Besides, the authors had the good sense to speak of inflation-adjusted box office sales; I'm tired of the movie industry proclaiming higher sales each year when ticket prices are rising, and the population is growing.

This is another chart where more data do not easily translate into better communication (see my guest post at Flowing Data).  While I like the playful nature of the interactive chart, it is left to the reader to discover the information buried in the data, such as the assertion in the header that Oscar-winning films typically take time to attain box-office success while many blockbusters do not Oscars make.

In this presentation, it is challenging to compare the total receipts of one film versus another (this requiring comparing oddly shaped, partially obscured areas).  It is also hard to compare across years since the data is spread out over a lot of space.

There may really be two types of graphics: the one like the example here which is a dictionary and designed for exploration; and the other kind where the designer has selected a subset of the data to make a specific point.

Reference: "The ebb and flow of movies", New York Times, Feb 23 2008.

Color scale

This map from the Economist illustrates pretty well the movement of population from middle America outwards from 2000-6.  The message reaches us despite the large volume of data painted.  (The gray shadow though was more than a little distracting.)

The map piqued my curiosity in two areas:

How did they determine the color scale?  The average change over all counties (6.4%) was obviously used.  Standard deviation was not since the ranges of change were unequal in size.

Was within-county percent change the best criterion?  As is, an 80% drop in a 2,000-people county looks the same as an 80% drop in a 200,000-strong county.

Reference: "The Great Plains drain", Economist, Jan 17 2008.

PS. I am traveling and so posting will be limited.

Football rankings 1.1

Long-time reader Jon sent in a different view of the QB data.  He uses a nifty tool in Excel to generate a parallel coordinates plot (also called profile plot) on which pairs of QBs can be highlighted and compared.

This chart exploits the foreground background concept very nicely.  One way to deal with abundant data is to highlight only those bits that matter to the question at hand, and relegating the rest to the background.

The gray lines in the background provide context without grabbing undue attention. He also converted every metric to a scale between 0 and 1, similar to what we did with our version.

The Eli Manning / Philip Rivers comparison shows that both QBs were below average on most of these metrics, with Manning near the bottom of each.

Maps and dots

Happy New Year

The cosmos of university ranking got more interesting recently with the advent of the "brain map" by Wired magazine.  This new league table counts the total number of winners of five prestigious international prizes (Nobel, Fields, Lasker, Turing, Gairdner) in the past 20 years (up to 2007); and the researcher found that almost all winners were affiliated with American institutions.

As discussed before, the map is a difficult graphical object; it acts like a controlling boss.  In this brain map, the concentration of institutions in the North American land mass causes over-crowding, forcing the designer to insert guiding lines drawing our attention in myriad directions.  These lines scatter the data asunder, interfering with the primary activity of comparing universities.

The chain of dots object cannot stand by itself without an implicit structure (e.g. rows of 10).  This limitation was apparent in the hits and misses chart as well.  Sticking fat fingers on paper to count dots is frustrating.  Simple bars allow readers to compare relative strength with less effort.

In the junkart version, we ditched the map construct completely,  retaining only the east-west axis.  [For lack of space (and time), I omitted the US East Coast and Washington-St. Louis.]  With this small multiples presentation, one can better contrast institutions.

To help comprehend the row structure, I inserted thin strikes to indicate zero awards. A limitation of the ranking method is also exposed: UC-SF has a strong medical school and not surprisingly, it has received a fair share of Nobel (medicine), Lasker and Gairdner prizes; but zero Lasker and Gairdner could be due to less competitive medical schools or none at all!

Reference: "Mapping Who's Winning the Most Prestigious Prizes in Science and Technology", Wired magazine, Nov 2007.

The punch line

Mike K submitted this great entry months ago.  It's a map depicting stock market correction across the globe during the summer.  You have to click on the link to the WSJ website in order to see the interactive element.



Here are Mike's comments and mine:

Why it's bad:

First, to see the detail you have to click on the countries one by one. Hard to do a comparison of two countries. This makes it close to FlashJunk.

The color scheme is supposed to help but:

Second, the colors are too close together to allow easy comparisons of, say, Canada and Australia.

In addition, the binning of the colors is uneven and oddly chosen.  In the middle of the scale, each color shift represents 1% but at the edge, it is 5%, or more.

Third, area of these countries, or their geographic location, isn't really that relevant. Market cap might be. Then tiny-but-richly-capitalistic Netherlands wouldn't have to be shown in the middle of the Atlantic, as if the dikes had all burst and Amsterdam had floated out to sea.

Indeed, it begs the question: what were the gold dots suppose to signify? (Hint: it's not location.)

Fourth, why the selectivity? There's stock markets in Turkey, and in Russia, and in Ireland and in Thailand. (Oh, wait, they show the one in Thailand -- except they put it in Myanmar instead.)

Finally, the chart lacks a punch line. 

In the junkart version, I want to test the hypothesis of a global contagion so I plot the data in order of closing times of individual stock markets.  (I just guessed the closing times based on the map.)  Not much here though.

Source: "Global Correction", Wall Street Journal, August 2007.

The absolutely meaningless pie chart

Simon J., from New Zealand, sent this in during the recent Rugby Cup but I didn't notice it till now.  As he stated, "they do a good job confirming our views of pie charts!"  Dropkicks is a site about rugby, and other sports popular in the south Pacific.

So here is our light entertainment for Thanksgiving week:

This chart accompanied a very serious statistical analysis to address the monumental question of whether some countries were borrowing strength from foreign players.  If this is your cup of tea, follow this link.

P.S. Today I started the Junk Charts Core Collection, which include books I recommend on graphics, statistics, data mining and related topics (top right).  Some categories are sparse right now as I build out the collection.  If you have favorites, let me know and I will include them.  (I am using the Amazon interface to organize the list; if you buy books, you are buying from them.  I am not becoming a bookstore.)

11/19: Amazon seems to be having problems serving up the images.  I have turned off the image for now.  You can follow the text link above to see the book collection.

11/20: the image is up again

Light entertainment

Christopher P submitted this chart, which is great for our light entertainment series.

Apparently it came from the Netherlands and showed how privileged their citizens are compared to the rest of the world.  It would appear that they need to reverse the color scheme (and font size?) to highlight the privileged.  Comments welcome.

Source: AdsoftheWorld.com