Inconsistency between min and max in apply with multiindex
I have noticed an inconsistency between the min and max functions when using an apply between levels of a multiindex dataframe. Please see the console log below, and notice the Series return type in the case of the min function and scalar return type for the max function.

```
>>> df = pd.DataFrame({'A': [1, -1, 2, -2], 'B': [1, 1, 1, 1]}) 
>>> df.columns = [['A', 'B'], ['a', '']]
>>> df
   A  B
   a   
0  1  1
1 -1  1
2  2  1
3 -2  1
>>> print df.apply(lambda row: max(row['A', 'a'] * row['B'], 0), axis=1)  
0  1
1  0
2  2
3  0
>>> print df.apply(lambda row: min(row['A', 'a'] * row['B'], 0), axis=1)
0       0
1    [-1]
2       0
3    [-2]
dtype: object
```
