pandas: CI: NumPy logical reductions (any, all) fail on DataFrame with NumPy master

https://travis-ci.org/pandas-dev/pandas/jobs/348215410#L2717

[gw1] linux -- Python 3.6.4 /home/travis/miniconda3/envs/pandas/bin/python
self = <pandas.tests.frame.test_analytics.TestDataFrameAnalytics object at 0x7f86fa5d54a8>
axis = 0
    @pytest.mark.parametrize("axis", [0, 1, None])
    def test_clip_against_frame(self, axis):
        df = DataFrame(np.random.randn(1000, 2))
        lb = DataFrame(np.random.randn(1000, 2))
        ub = lb + 1
    
>       clipped_df = df.clip(lb, ub, axis=axis)
pandas/tests/frame/test_analytics.py:2066: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/core/generic.py:5605: in clip
    if np.any(pd.isnull(lower)):
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
self = 0    False
1    False
dtype: bool
    def __nonzero__(self):
        raise ValueError("The truth value of a {0} is ambiguous. "
                         "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
>                        .format(self.__class__.__name__))
E       ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().