DataFrame感到困惑，抛出“系列对象没有属性'iterrows'”

Question

在DataFrame上执行操作时遇到一种模糊的错误。上下文是这样的：

res2 = group.z.agg(['mean', 'std', len])
res2 = res2.drop(res2[np.isnan(res2.len)].index).drop(res2[res2.len <= 5.].index)
print(type(res2))
res2 = res2.transform(uncert)

首先，我正在这样做。印刷品给出

<class 'pandas.core.frame.DataFrame'>

到目前为止，一切都很好。现在，我在转换中调用的“ uncert”函数如下所示：

def uncert(df):
   values = []
   for index, row in df.iterrows():
       print(row.mean, row.std)
       #values.append(ufloat(row['mean'], row['std']))
   #df['uval'] = Series(values, index=df.index)
   return df

注释掉这两行以检查发生了什么。现在，抛出一个错误：

AttributeError                            Traceback (most recent call last)
<ipython-input-4-e41277533a08> in <module>()
     66     res2 = res2.drop(res2[np.isnan(res2.len)].index).drop(res2[res2.len <= 5.].index)
     67     print(type(res2))
---> 68     res2 = res2.transform(uncert)
     69 
     70     print('Method 2:\n', res2, "\n\n")

.
.
.


<ipython-input-6-e41277533a08> in uncert(df)
     13 def uncert(df):
     14     values = []
---> 15     for index, row in df.iterrows():
     16         print(row.mean, row.std)
     17         #values.append(ufloat(row['mean'], row['std']))

.
.
.
AttributeError: ("'Series' object has no attribute 'iterrows'", 'occurred at index mean')

Aaa，这种情况对我来说没有意义，因为我正在对DataFrame对象执行操作。框架看起来像这样：

                     mean       std    len
(-0.001, 29.409]    2.198392  0.027809   40.0
(29.409, 75.024]    1.950194  0.008493   49.0
(78.625, 203.464]   1.766212  0.014613  145.0
(205.264, 215.468]  1.604461  0.008790   10.0 

有人知道或经历过类似的事情吗？