BUG: skipna parameter in series.any() returns wrong result

#importing pandas module 
import pandas as pd 

#importing numpy module
import numpy as np

data=pd.DataFrame({'A':[1,2,3,4,0,np.nan,3],
                  'B':[3,1,4,5,0,np.nan,5]})

data.any(axis=1,skipna=True)

Expected output: 0 True 1 True 2 True 3 True 4 False 5 True 6 True dtype: bool

Returned output:

0 True 1 True 2 True 3 True 4 False 5 False 6 True dtype: bool

As written in documentation, If an entire row/column is NA, the result will be NA But NA isn’t returned in any of the cases (Keeping skipna True or False)

[jorisvandenbossche]

Skipna should be the same as the operation on the values with NAs removed (is that right @jorisvandenbossche?).

I suppose this as well. any/all can be seen as reductions like sum or prod, so we should probably follow their design.

So I think @dsaxton is right that it is only the documentation that is incorrect.

[dsaxton]

My opinion: I think the problem is the documentation; the result is actually correct. If you ask if any of an empty set of statements is True, the answer is no. This is consistent with numpy:

In [1]: import numpy as np

In [2]: np.any([])
Out[2]: False