pingouin.kruskal

pingouin.
kruskal
(dv=None, between=None, data=None, detailed=False, export_filename=None)[source] KruskalWallis Htest for independent samples.
 Parameters
 dvstring
Name of column containing the dependant variable.
 betweenstring
Name of column containing the between factor.
 datapandas DataFrame
DataFrame
 export_filenamestring
Filename (without extension) for the output file. If None, do not export the table. By default, the file will be created in the current python console directory. To change that, specify the filename with full path.
 Returns
 statsDataFrame
Test summary
'H' : The KruskalWallis H statistic, corrected for ties 'punc' : Uncorrected pvalue 'dof' : degrees of freedom
Notes
The KruskalWallis Htest tests the null hypothesis that the population median of all of the groups are equal. It is a nonparametric 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.
Examples
Compute the KruskalWallis Htest for independent samples.
>>> from pingouin import kruskal, read_dataset >>> df = read_dataset('anova') >>> kruskal(dv='Pain threshold', between='Hair color', data=df) Source ddof1 H punc Kruskal Hair color 3 10.589 0.014172