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Are you referring to the violin plot? https://en.wikipedia.org/wiki/Violin_plot https://en.wikipedia.org/wiki/Violin_plot and in Matplotlib as https://matplotli
by eesmith 10mo ago
Are you referring to the violin plot? https://en.wikipedia.org/wiki/Violin_plot https://en.wikipedia.org/wiki/Violin_plot and in Matplotlib as https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.violinplot.html https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot....
It's in essence a histogram for the distribution, with smoothing, and mirrored on each side.
It looks nice, but is not without well-deserved opposition because 1) the use of smoothing can hide the actual distribution, 2) mirroring contains no extra information, while taking up space, and implying the extra space contains information, and 3) when shown vertically, too often causes people to exclaim it looks like a vulva.
In an HN discussion on the topic, medstrom at https://news.ycombinator.com/item?id=40766519 https://news.ycombinator.com/item?id=40766519 points to a half-violin plot at https://miro.medium.com/v2/1*J3Q4JKXa9WwJHtNaXRu-kQ.jpeg https://miro.medium.com/v2/1*J3Q4JKXa9WwJHtNaXRu-kQ.jpeg with the histogram on the left, and the half-violin on the right, which gives you a chance to see side-by-side presentation of the same data.
- Tarq0n 10mo agoHistograms aren't necessarily a true depiction of the distribution. Bin count or width has a large impact on what details get shown.
- eesmith 10mo agoSure. Very few distributions have lovely square edges, which otherwise indicate some very high frequencies in the distribution, or quantized values. But that also means we are used to seeing histograms and their bin count and widths in order to estimate possible variances from the true distribution;. While it's much harder to do the same with violin plots.
- eru 10mo agoYou could plot the cumulative distribution function to avoid these problems with histograms.