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Labels are Used Sparingly

Labels are Used Sparingly

This post is about how to avoid inducing claustrophobia in your data visualizations. Too much text on a graph clutters it up, making readers feel suffocated. So let’s address the checklist item Labels are used sparingly.

Sometimes, too much text isn’t the issue. Take a look at this scatterplot, produced with Excel’s default Insert Chart option. It uses data from Radical Math and plots the percent of people of color living in each NYC area against the number of military recruits per 100,000 in those same areas. This version would score zero points because there is no intentional use of labels.

Here is an improvement:

ScatterplotLabelsBetter

This version would score 1 point. Why? I decluttered the graph a little by removing every other number from the y-axis and shifting the correlation notation from inside the graph to the subtitle. I also added in axis labels for clarification, better orienting the reader to the data at hand. (I altered the title and subtitle too, which I discuss in another post.)

But we could take this even one step further, for a full 2 points:

If we labeled every data point in this scatterplot, it would be impossible to read. But one of the first questions readers will have about the data is which NYC areas are outliers and which are on the trendline. So we can sparingly label selected data points to provide some context. For example, there’s little surprise that Rikers Island would have no military recruits, since it is mainly comprised of a jail. Of course, if this scatterplot was interactive, hovering a mouse over a dot or tapping it would reveal the name instead.

Bottom line: Use labels sparingly to simplify what you can and then emphasize key points to tell the story.

Check out my other posts related to the Data Visualization Checklist. And go see what Ann Emery has been publishing on the checklist, too!

2 thoughts on “Labels are Used Sparingly
  1. Brent Logan says:

    It surprised me to see the independent variable on the vertical axis. Or more honestly, it confused me. Wouldn’t it be better to transpose the plot?

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@usefuleval @AnnKEmery nature is coooool!

@visualisingdata maybe PowerPoint MVP @daveparadi knows why?

@usefuleval @AnnKEmery @ViaEvaluation I thought this was going to be a scatterplot, snowfall x drinks consumed.

@visualisingdata This happened to me the other day. All my pics gone. After I died, I resurrected myself & asked WTF? Really, what happened?

RT @ann_gero: Nice! @evergreendata: New post: Visualizing Likert-type Data with Aggregated Stacked Bars http://t.co/UOjybl3Nx5 #dataviz

Proposal for book 2 approved by @SAGE_Methods Time to start writing!

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