I am a novice in python and trying to perform the Kruskal Wallis test for multiple columns divided into two Groups (C2 & S1).
Till now, I have been able to do the Kruskal Wallis test for a single column with the following code. (I collected through the internet)
import pandas as pd
df =pd.read_excel( 'C2_S1_sorted_2.xlsx')
#collected through internet
import scipy.stats as ss
data = [df.loc[ids, '3-HYDROXYPHENYLACETATE-DEGRADATION-PWY: 4-hydroxyphenylacetate degradation'].values for ids in df.groupby('Group').groups.values()]
H, p = ss.kruskal(*data)
p
I tried to use "while loop" to loop over all columns but till now not been able to do so. I also went through almost all questions related to this in StackOverflow, but I am unable to solve my problem.
Can anyone please help me in doing this? I am sorry if this is a very basic question.
Below is how my data looks like.
Group 1CMET2-PWY: N10-formyl-tetrahydrofolate biosynthesis 3-HYDROXYPHENYLACETATE-DEGRADATION-PWY: 4-hydroxyphenylacetate degradation 7ALPHADEHYDROX-PWY: cholate degradation (bacteria, anaerobic)
C2 889.944 0 0
C2 931.451 0 0
C2 795.362 0 0
C2 840.724 0 0
C2 732.173 0 0
C2 908.025 0.843261 0
C2 733.818 0.518661 0
C2 842.462 1.82225 0
C2 843.887 0 0
C2 823.395 0 0
C2 713.35 0.699201 0.534327
C2 859.136 0.604455 0
C2 871.477 0 0
C2 763.695 0 0
C2 835.966 0 0
C2 781.925 0 0
C2 1010.87 0 0
C2 936.106 0 0
C2 738.947 1.9034 0
C2 988.541 0 0
S1 838.256 0 0
S1 758.363 0 0
S1 1022.51 0 0
S1 1016.61 0 0
S1 908.64 0 0
S1 941.786 0 0
S1 999.038 0 0
S1 914.317 0 0
S1 1053.07 0 0
S1 876.61 0 0
S1 793.693 0 0
S1 916.2 0 0
S1 1108.61 0 0
S1 938.456 0 0
S1 825.406 0 0
S1 1332.52 0 0
S1 1198.65 0 0
S1 1005.4 0 0
S1 826.529 0 0
S1 1170.82 0.624429 0
