>>> some_data = np.array([('foo', 3.5, 2.15), ('bar', 2.8, 5.3), ('baz', 1.2, 3.7)], 
                     dtype=[('col1', '<U20'), ('A', '<f8'), ('B', '<f8')])
>>> ab = some_data[['A', 'B']]

>>> np.__version__
'1.13.3'
>>> ab.dtype
dtype([('A', '<f8'), ('B', '<f8')])
>>> ab.view(('<f8', 2))
FutureWarning: Numpy has detected that you may be viewing or writing to an array returned by selecting multiple fields in a structured array. 

This code may break in numpy 1.13 because this will return a view instead of a copy -- see release notes for details.
array([[ 3.5 ,  2.15],
       [ 2.8 ,  5.3 ],
       [ 1.2 ,  3.7 ]])

>>> np.__version__
'1.15.0.dev...'
>>> ab.dtype
dtype({'names':['A','B'], 'formats':['<f8','<f8'], 'offsets':[80,88], 'itemsize':96})
>>> ab.view(('<f8', 2))
ValueError: Changing the dtype to a subarray type is only supported if the total itemsize is unchanged