Error when running Kruskal Wallis test in for loop

Question

log_fc

primer  ID_1    category    Avg_logfc
primer_1    42  test_1  1.88444044
primer_2    43  test_1  0.8730141
primer_3    44  test_1  1.10542821
primer_4    45  test_1  0.79234524
primer_1    11  test_2  0.33098178
primer_2    12  test_2  0.66117247
primer_3    13  test_2  0.62520437
primer_4    14  test_2  0.21972443
primer_1    94  test_3  -0.96924447
primer_2    95  test_3  1.4806643
primer_3    96  test_3  1.83216384
primer_4    97  test_3  1.93774891

I have a data (log_fc) and I am trying to do Kruskal Wallis test based on each category. I am getting the same test statistic output for all data frames. I have four primers (primer1, primer2, primer3, primer4) in each experiment and I want to test the distribution of log_fc values for these primers in each category.

The code I tried


for g, group in log_fc.groupby("category"):
    logfc_matrix = group[["ID_1", "Avg_logfc", "category"]]
    d = logfc_matrix[['Avg_logfc']]
    # Primer 1
    f1 = d.iloc[0].values
    # Primer 2
    f2 = d.iloc[1].values
    # Primer 3
    f3 = d.iloc[2].values
    # Primer 4
    f4 = d.iloc[3].values
    
    kw_test_results = ss.kruskal(f1, f2, f3, f4)
    print(kw_test_results)

I got same test output for all 3 categories, when the distribution of the log_fc values are different in each category.

KruskalResult(statistic=3.0, pvalue=0.3916251762710877)                                 
KruskalResult(statistic=3.0, pvalue=0.3916251762710877)                 
KruskalResult(statistic=3.0, pvalue=0.3916251762710877)

Error when running Kruskal Wallis test in for loop

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