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Lessons from organizing the kitchen cabinet

The first thing we know about kitchen cabinets is that they are not large enough. If you live in a small city apartment, you're always looking for ways to maximize your space. If your McMansion has a huge kitchen, you'll run out of space all the same, after splurging on the breadmaker, and the ice-cream maker, and the panini grill, and containers for garlic, onions, different shapes of pastas, and the peelers for apples, garlic, carrots, the egg-separator, the foam-maker, and so on.

Another thing we know is that no matter how many and how large the cabinets are, there is not enough premium space, by which we mean front-facing space within arm's reach. What has this to do with graphs and charts? We'll find out soon enough.


In this weekend's edition of New York Times (link 1, link 2), several climate scientists wrote about droughts in America: "widespread annual droughts, once a rare calamity, have become more frequent and are set to become the 'new normal'". What caught my eye was the following graphic showing precipitation levels, enticingly titled "21 Centuries of Rainfall in New Mexico". (See the full graphic here).



The blue lines going up represent years in which rainfall was higher than normal; the orange lines going down show years of below-normal rainfall. "Normal" is defined as the average rainfall between 1931 and 1990. Particularly useful were the annotations telling us in certain centuries, the number of years below normal.

I immediately needed to see the following chart:


This just takes the annotations and plotted them directly (I made up the data where they were not noted.)

What we are seeing here, at the scale of centuries, is that in the most recent period (only up to 1992), New Mexico is getting wetter.

Yes, this chart doesn't seem to support the scientists' assertion. In fact, I'm not sure why the NYT decided to insert this "news analysis" next to the opinion column. It's not that the analyst doesn't see the contradiction - he stated "the bigger picture, from El Malpais, suggests that the West has endured far drier periods. Uncomfortably drier."

I have major issues with this juxtaposition. If the NYT does not think the opinion column is correct science, it should decide not to print it. If the NYT thinks there are people who might object to the science, it should counter it by citing the work of other scientists (none is cited in the sidebar). While El Malpais may provide the longest measure of rainfall conditions, this is no basis to claim it measures "the bigger picture", and specifically it is shocking, perhaps reflecting the cultural bias of the newspaper, to see that this data from New Mexico tell us something about "the West" and somehow not about "the East". Why would it generalize to the West but not the East?


Back to the chart, and specifically kitchen cabinets.

We have two charts from one data set. The chart of blue and orange spikes contains every data point. The stacked column chart shows only aggregated data, specifically how many above-average and below-average years in each century. The first chart makes readers work very hard to get any information out of it. The designer recognizes this and adds useful notes, generally about the proportion of below-average years. Assuming that those proportions are the key to deciphering the chart, why not plot them directly?

The objection is that much information is lost by not including the rest of the data. One cannot deny it. For example, just looking at the stacked column chart, you cannot know that the late 1980s and early 1990s were extremely wet years in New Mexico, over three standard deviations above the norm, nor can you know that there was a mega-drought in the late 16th century lasting decades.

However, chart designers should realize that there is a shortage of front-facing, accessible space in the kitchen cabinets. Putting more into a chart means some of the information will be pushed to the back, or out of arm's reach. If you need a ladder to get to that cabinet, what would you put in it? Would you rather leave it empty? I know I would.

As good as Bolt

The accomplished graphics team at NYT outdid themselves with this feature on the 100m dash through Olympic history (link). You should really go and check out the full presentation.


About_100m_winnersThey start with a data table like the one shown on the right. It's a boring list of names and winning times by year and by medal type. What can one do to animate this data? The NYT team found many ways.

The presentation consists of a static dot plot plus a short movie.

They found many ways to convey the meaning of the tenths and hundredths of a second that separate the top performers. In the dot plot, for example, they did not draw the actual winning times. Instead, they converted the differences in winning times into distances. Here is the right section of the chart:


We are drawn into compressing time and place, having Usain Bolt race all of the former winners and assuming everyone ran the same race they did in real life. The dot plot tells us how far ahead of each past winner Bolt is.

Some time ago, I wrote about the "audiolization" of duration data, in another piece about a NYT chart (link). They deployed this strategy beautifully at the end of the short film. The runners were aligned like keys on a piano, and the resulting sound is like playing a scale across the keyboard. Lovely, that is to say.



The authors bring in a number of other data points to create reference points for understanding this data. For example, if you blink, you might miss the national jerseys worn by each winner in the hypothetical competition:


 Later, the dominance of American runners is plainly shown via white lanes:


 The perspective hides the relative impotency of American sprinters in recent Olympics. This view of the surge of Caribbean runners makes up for it:



Next, they compared the times for U.S. age group record holders to Olympic winning times. This is a fun way to look at the data. (Pardon the strutting Play button.)


They play with foreground/background here in an effective way. The 15- and 16-year-old age-group record holder is said to be "good enough for a bronze as recently as 1980".

Fun aside, think twice before you repeat this "insight". It falls into the category of those things that sound impressive but are quite meaningless. For one thing, the gap between the two runners is affected by a multitude of factors: the age of the runner (which is elevated here over and above other factors), the nationality of the runner, and the time of the run. This last point is key: if we compare the 15-to-16-year-old 100m record time from 1980 to the winning times of Olympic medalists from that year, the gap would be much wider.

Also, pay attention to the distribution of runners. It gets very crowded very quickly near the top end of the scale. In other words, while the gap as measured in part-seconds may seem small, the gap as measured in individual athletes would be very wide -- we'd find loads of athletes whose times fit into the gap illustrated here.


According to the dot plot, in some years, like the 1950s, there were no gold medalists. Looking at the data here, I think this is an overplotting effect, where two times were so close that the dots were literally on top of each other. This creates the situation where one of the dots will be on top of the other, and which one is on top is a feature of the software you're using. Jittering is one common strategy to deal with this problem, or we can just place the gold, silver and bronze dots on their own levels. The latter strategy would look exactly like the over-the-top view used in the short film:


(We'll also note that this view has time running left to right, which is perhaps more natural than time running bottom up, as in the dot plot. However, we are used to seeing runners cross the finish line from left to right on a TV screen so this is a case of eight ounces and half a pound.)

In the short film, I find the gigantic play/pause button at the center of the screen an annoyance, ruining my enjoyment. (I'm using Firefox and a Mac.)


Now, go check out the entire feature (link), and applaud the effort.