Python 如何打印拆分的索引？

因此，我有一些8列和许多行的数据，我想用5个拆分来执行K-Fold拆分。我已经这样做了，但我现在要做的是，对于每个分割，打印出它所在的分割编号。请参阅代码以获得更好的解释

kf = KFold(n_splits=5) #Define the split - into 5 folds 

#Define empty arrays for each technique
kf_train = []
kf_test = []

#Iterate through each feature in 
for kf_train, kf_test in kf.split(df):
    print('Split # ????')
    for col_name, col_data in df.iteritems():
        print('Feature: ', col_name)
        print('Mean: ', np.mean(col_data))
        print('Standard Deviation: ', np.std(col_data))
        print('\n')

所以它说的

print（'Split#？'）

就是我的问题所在。为了获得以下输出，我应该写些什么：

Split#1
特色：XXX
平均数：3.3
标准：3.3
分裂#2
等

您可以使用

枚举

为您提供索引和值

# Iterate through each feature in 
for idx, kf_vals in enumerate(kf.split(df)):
    print('Split #%s' % idx)
    kf_train, kf_test = kf_vals
    for col_name, col_data in df.iteritems():
        print('Feature: ', col_name)
        print('Mean: ', np.mean(col_data))
        print('Standard Deviation: ', np.std(col_data))
        print('\n')

---

您可以使用

enumerate

为您提供索引和值

# Iterate through each feature in 
for idx, kf_vals in enumerate(kf.split(df)):
    print('Split #%s' % idx)
    kf_train, kf_test = kf_vals
    for col_name, col_data in df.iteritems():
        print('Feature: ', col_name)
        print('Mean: ', np.mean(col_data))
        print('Standard Deviation: ', np.std(col_data))
        print('\n')

---

添加

枚举

可以解决您的问题：

for i, (kf_train, kf_test) in enumerate(kf.split(df)):
    print('Split #{}'.format(i))
    for col_name, col_data in df.iteritems():
        print('Feature: ', col_name)
        print('Mean: ', np.mean(col_data))
        print('Standard Deviation: ', np.std(col_data))
        print('\n')

---

供参考：.

添加一个

枚举应能解决您的问题：

for i, (kf_train, kf_test) in enumerate(kf.split(df)):
    print('Split #{}'.format(i))
    for col_name, col_data in df.iteritems():
        print('Feature: ', col_name)
        print('Mean: ', np.mean(col_data))
        print('Standard Deviation: ', np.std(col_data))
        print('\n')

供参考：