In my dataset, I have five (ordinal) groups with an x-amount of measurement. Because homoscedasticity is violated, I performed the Friedman chi-square test to see if there are any statistical differences between the groups:
fried = stats.friedmanchisquare(*[grp for idx, grp in df.iteritems()]))
This returned a statistical difference, but now I would like to find out between which groups the differences exist. In
R there is a nice solution for this (Friedman's test and post-hoc analysis, https://www.r-statistics.com/2010/02/post-hoc-analysis-for-friedmans-test-r-code/), where they use the Wilcoxon-Nemenyi-McDonald-Thompson test, but I am unable to find one for Python.
Is there a possibility to do post-hoc analyses for the Friedman test? Alternatively, what would we be a good alternative for the Friedman test that does allow me to compare between groups, e.g. a generalized estimating equation?