worst code ever

sum_predicted0 = 0.0
sum_groundtruth0 = 0.0
for i in range(df0.shape[0]):
    probs = array([float(df0.iloc[i]['p(T1)'])*100,
                   float(df0.iloc[i]['p(T2)'])*100,
                   float(df0.iloc[i]['p(T3)'])*100,
                   float(df0.iloc[i]['p(T4)'])*100,
                   float(df0.iloc[i]['p(T5)'])*100,
                   float(df0.iloc[i]['p(T6)'])*100,
                   float(df0.iloc[i]['p(T7)'])*100,
                   float(df0.iloc[i]['p(T8)'])*100,
                   float(df0.iloc[i]['p(T9)'])*100])

    sum_predicted0 += math.log(np.max(probs))

    if fold0.iloc[i]['Q3 Theme'] == 1:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T1)'])
    elif fold0.iloc[i]['Q3 Theme'] == 2:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T2)'])
    elif fold0.iloc[i]['Q3 Theme'] == 3:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T3)'])
    elif fold0.iloc[i]['Q3 Theme'] == 4:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T4)'])
    elif fold0.iloc[i]['Q3 Theme'] == 5:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T5)'])
    elif fold0.iloc[i]['Q3 Theme'] == 6:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T6)'])
    elif fold0.iloc[i]['Q3 Theme'] == 7:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T7)'])
    elif fold0.iloc[i]['Q3 Theme'] == 8:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T8)'])
    elif fold0.iloc[i]['Q3 Theme'] == 9:
        sum_groundtruth0 += math.log(df0.iloc[i]['p(T9)'])




avg_predicted = (-sum_predicted0/df0.shape[0] +
                 -sum_predicted1/df1.shape[0] +
                 -sum_predicted2/df2.shape[0] +
                 -sum_predicted3/df3.shape[0] +
                 -sum_predicted4/df4.shape[0] +
                 -sum_predicted5/df5.shape[0] +
                 -sum_predicted6/df6.shape[0] +
                 -sum_predicted7/df7.shape[0] +
                 -sum_predicted8/df8.shape[0] +
                 -sum_predicted9/df9.shape[0]
                 ) / 10

avg_gt = (-sum_groundtruth0/df0.shape[0] +
          -sum_groundtruth1/df1.shape[0] +
          -sum_groundtruth2/df2.shape[0] +
          -sum_groundtruth3/df3.shape[0] +
          -sum_groundtruth4/df4.shape[0] +
          -sum_groundtruth5/df5.shape[0] +
          -sum_groundtruth6/df6.shape[0] +
          -sum_groundtruth7/df7.shape[0] +
          -sum_groundtruth8/df8.shape[0] +
          -sum_groundtruth9/df9.shape[0]) /10