My favorite part of data visualization workshops?

The airports. Kidding.

Watching jaws drop when folks are introduced to small multiples layouts for the first time. Definitely!

What are small multiples?

Small multiples layouts include 2 or 3 or 4 or more graphs – of the same size and scale – to allow for easy comparisons.

Why use a small multiples layout?

Old way: making a single aggregate chart that only displays means, medians, or frequencies from a bunch of different data series combined.

New and improved way: designing a small multiples layout that gives viewers the information they really care about – the disaggregated data for their particular company, city, organization, or school.

Additional benefits:

• To compare changes over time, like the social network map below.
• To compare changes across different groups.
• To add context. Is an organization doing well? Who can really know for sure unless you compare the organization to a few others using a small multiples layout?

What can be made into a small multiples?

Anything. 

Bar charts, histograms, geographic maps, line charts, social network maps, and more.

Just make a collage of several small charts. It’s really that easy.

You can make these in nearly any software program. If they aren’t part of your software program’s menu of default options, don’t be afraid to dive in and use a little elbow grease.

Here are a handful of the million+ ways to incorporate small multiples layouts into your charting repertoire:

Want to make small multiples on your own?

Join my mailing list and I’ll send you visualization resources like the charts and slides used in today’s post.

Or, join an upcoming webinar, like this how-to webinar on December 8th where I give live demos and let you keep a bunch of Excel templates. Templates!? You bet.

But sometimes we don’t want to summarize, we want to highlight the variety in scores and remind readers that the chart is actually made up of individual people, not just the mean or median. Long live the messy data, the dispersion, the distribution, the spread!

I could tell you a few descriptive statistics: min = 26%, max = 100%, Q1 = 64%, Q3 = 83%, median = 74%, mean = 73%, standard deviation = 15%. Or, I could show you the spread in this unit-chart-turned-histogram.

Unit charts are not your new go-to chart. They do not replace bar charts. They are not appropriate for all datasets. They’re best for those few moments when you choose to emphasize individual units of data. A unit could be 1 person, or 10 people, or 1 school, and so on. Units can be represented in circles or squares or triangles. Units can be stacked on top of each other to form a histogram, or they can be plotted along a line.

The dataviz challenge: Re-create the chart in in Excel, R, or some other free software program. Then, tweet a screenshot to @annkemery. Bonus: Make a unit chart for your own data. Or, do you emphasize individual differences with other chart types? Share your ideas with the community!

The prize for playing: A professional development opportunity and bragging rights. I’ll post the how-to guide in a couple weeks.

Want to learn more? I’m presenting about charting techniques at the American Evaluation Association’s annual conference on Thursday, October 17, 2013 at 11am in Washington, DC. Hope to see you there!