Small Multiples — Big Clarity

The other day I was reading about Kay Weeks, a mother of triplets and a teacher at Martin High School in Arlington, Texas. Ms. Weeks guessed that her school just might be breaking a record for multiples graduating this June, and she was right. There were 18 sets of twins and two sets of triplets in the senior class — a Guinness Book record.

I was exhausted just reading about all those small multiples, so I had a cocktail and took a nap.

And then it hit me: I know about another type of small multiples, ones that don’t make me want to drink or sleep (my “Eureka!” moments are not exactly earth-shattering, I admit, but I revel in them all the same).

If you are up on your data visualization terms, you know that it was Edward Tufte, a statistician and Yale University professor, and a pioneer in the field of information design and data visualization, who coined the term “small multiples.” (You may be familiar with other names for this type of display: Trellis Chart, Lattice Chart, Grid Chart or Panel Chart.)

I think of small multiples as displays of data that use the same basic graphic (a line or bar graph for example) to display different parts of a data set. The beauty of small multiples is that they can show rich, multi-dimensional data without attempting to jam all the information into one, highly complex chart like this one:

Now take a look at the same data displayed in a chart of small multiples:

What problems does a small multiples chart help solve?

1. Multiple Variables. Trying to display three or more variables in a single chart is challenging. Small multiples enable you to display a lot of variables, with less risk of confusing or even losing your viewers.

2. Confusion. A chart crammed with data is just plain confusing. Small multiples empower a viewer to quickly grasp the meaning of an individual chart and then apply that knowledge to all the charts that follow.

3. Difficult Comparisons. Small multiples also make it much easier to compare constant values across variables and reveal the range of potential patterns in the charts.

Now, before you construct a small multiples data display, here are a few additional pointers:

1. Arrangement. The arrangement of small multiples charts should reflect some logical measurement or organizing principle, such as time, geography, or another interconnecting sequence.

2. Scale. Icons and other images in small multiple displays should share the same measure, scale, size, and shape. Changing even one of these factors undermines the viewers’ ability to apply the understanding gained from the first chart to subsequent charts or display structures.

3. Simplicity. As with most things in life, simplicity in the small multiples chart is crucial. Users should be able to easily process information across many charts, and see and understand the story in the data.

Just the thought of small multiples of children being under my care should frighten adults and children alike. (It is true: I have been known to forget to feed my own child on more than one occasion.) It is much safer for me to stick to the data visualization type of small multiples — they are simple and straightforward, and require very little feeding. Best of all, I don’t need a cocktail or a nap before I can face them.