The few following lines, i believe, show how the numpy.ndarray.T or numpy.ndarray.transpose() don't change the structure of the data only the way they're displayed. Which is sometimes a problem when handling big quantities of data which you need to look at a certain way for sorting problems among others.

>>> import numpy as np
>>> x=np.array([[0,1,2],[1,2,3]])
>>> x=x.T
>>> print x
[[0 1]
 [1 2]
 [2 3]]
>>> y=np.array([[0,1],[1,2],[2,3]])
>>> print y
[[0 1]
 [1 2]
 [2 3]]
>>> y.view('i8,i8')
array([[(0, 1)],
       [(1, 2)],
       [(2, 3)]],
      dtype=[('f0', '<i8'), ('f1', '<i8')])
>>> x.view('i8,i8')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: new type not compatible with array.

Numpy is not part of the Python standard library.  You'll need to engage with the numpy community on this question.  (I say engage with them on the question, not report a bug to them, because I highly doubt this is a bug...there's probably some way to do what you want, so I suggest asking a question first rather than reporting a bug).