I am trying to use matlotlib to control the appearance of outliers in a "notched" box plot generated using seaborn. My code looks as follows:
ax = sns.boxplot(y= "class", x = "Proba",hue = "Stage", data = df_tidy, notch = True,
showmeans= True, meanprops={"marker": ".", "markerfacecolor":"red", "markeredgecolor": "red"},
flierprops = dict(markerfacecolor = '.1', markersize = .0018, linestyle = "none", markeredgecolor='steelblue'),
boxprops=dict(alpha=.7), width=.3)
However, I have a fairly large # of outliers that make the boxplot look a little unappealing aesthetically; specifically I am seeing a near continuous stream of outliers beyond the whiskers. Unfortunately, I am unable to generate fictitious data for this example as it requires one to have many outliers within an otherwise large dataset for this to happen.
I tried to "improve" this somewhat using an alternative color for the outliers and reduce their size, but it did not improve the result much. One option that worked modestly well was to set the "linestyle" argument within flierprops to "dotted".
However, is there a way to pass a "jitter" argument to flierprops dictionary? Can somebody suggest a way to make the outliers jitter?