Violin plots have an interesting reputation (https://xkcd.com/1967/ https://xkcd.com/1967/, https://www.reddit.com/r/labrats/comments/91ex4u/is_it_just_me_or_do

Violin plots have an interesting reputation (https://xkcd.com/1967/ https://xkcd.com/1967/, https://www.reddit.com/r/labrats/comments/91ex4u/is_it_just_me_or_do_these_graphs_look_like_vulvae/ https://www.reddit.com/r/labrats/comments/91ex4u/is_it_just_..., https://jabde.com/2022/12/22/banned-violin-plots/ https://jabde.com/2022/12/22/banned-violin-plots/). For showing distributions, I much prefer strip plots (https://seaborn.pydata.org/generated/seaborn.stripplot.html https://seaborn.pydata.org/generated/seaborn.stripplot.html), perhaps with opacity, or swarm plots (https://seaborn.pydata.org/generated/seaborn.swarmplot.html https://seaborn.pydata.org/generated/seaborn.swarmplot.html) - no averaging with an unknown kernel, no hiding distributions behind a box plot, and the data is directly visible. We also directly see whether it is based on 5, 100, or many more points. When using histograms, binning is usually more straightforward than kernels. And in any case, the mirror reflection of a histogram is not needed.