An exploration of radar charts from a recent Nature article, tracing the path from radars to fitted sigmoidal curves to alternate derived summary views.

Here’s another case in the wild of beeswarm jitter using clamped bounds that hide the distribution of the data. This one has a twist in that a large proportion of the data values are zero.

Comparing NCAA football players’ NFL draft rates with their high school composite ratings

Someone once quipped that I only read journal articles by looking at the pictures. I admit the graphs are the first things I look at. Next I check the data availability statement, to see if I can better understand the graphs with a little exploratory analysis. After that, I might also read the text of…

Throughout my quests for raw data, I’ve learned a few techniques for find data lurking behind the charts. This walk-through shows a few of them,

I built a “Data Strips” app to experiment with new ways of graphically summarizing the distribution of a single variable.. You can try it out or access the code on GitHub. This post will introduce the app and summarize the views.

Do the insights gained from ternary data organization require a ternary chart?

In my never-ending search for good way to view data distributions, one task is to take apart box plots seen in the wild and compare them with different visualizations.

I’ve spent way too much time trying to understand this now-retracted study, but find a couple interesting results in the data not related to ceiling heights.

Taking a refreshed look at Sloane’s Gap, including a flattened version for better comparing outliers.