kruskal(data=None, dv=None, between=None, detailed=False)
Kruskal-Wallis H-test for independent samples.
Name of column containing the dependent variable.
Name of column containing the between factor.
'H': The Kruskal-Wallis H statistic, corrected for ties
'p-unc': Uncorrected p-value
'dof': degrees of freedom
The Kruskal-Wallis H-test tests the null hypothesis that the population median of all of the groups are equal. It is a non-parametric version of ANOVA. The test works on 2 or more independent samples, which may have different sizes.
Due to the assumption that H has a chi square distribution, the number of samples in each group must not be too small. A typical rule is that each sample must have at least 5 measurements.
NaN values are automatically removed.
Compute the Kruskal-Wallis H-test for independent samples.
>>> from pingouin import kruskal, read_dataset >>> df = read_dataset('anova') >>> kruskal(data=df, dv='Pain threshold', between='Hair color') Source ddof1 H p-unc Kruskal Hair color 3 10.58863 0.014172