Violin plots are massively overhyped, IMHO. If your data is simple and unimodal, use a boxplot. If the distribution is more complicated and you need some detail, use a histogram or a ridge plot. Violin plots are never the best option; they're curvy so a little more pretty but don't do a good job of conveying information.
> If your data is simple and unimodal, use a boxplot.
How is the reader to know you've used the right plot? How are they to know that you haven't hidden a bimodel dataset behind a box plot because it makes your conclusions easier?
> If the distribution is more complicated and you need some detail, use a histogram or a ridge plot. Violin plots are never the best option; they're curvy so a little more pretty but don't do a good job of conveying information.
They are just multiple, non-overlapping histograms plotted next to each other. They allow you to compare distributions without them getting in the way of each other.
I can understand if it's the fitted PDF that you think hides the original data. That is unnecessary IMHO.
They really help when you're working with huge numbers. It's just a different kind of density plot. A vertical histogram can be nice too. Or you can use color and overlay a few regular old histograms. Go wild.
Overlaid histos can be confusing because people don’t know if they are stacked or overlapped.
One solution is to smooth into a kde and then use transparency to indicate overlap, but that’s introducing more complexity than you want for a quick n dirty first pass
