numpy.ndarray.transpose
- 
ndarray.transpose(*axes)
- 
Returns a view of the array with axes transposed. For a 1-D array, this has no effect. (To change between column and row vectors, first cast the 1-D array into a matrix object.) For a 2-D array, this is the usual matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and a.shape = (i[0], i[1], ... i[n-2], i[n-1]), thena.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0]).Parameters: axes : None, tuple of ints, or nints- None or no argument: reverses the order of the axes.
- tuple of ints: iin thej-th place in the tuple meansa‘si-th axis becomesa.transpose()‘sj-th axis.
- 
nints: same as an n-tuple of the same ints (this form is intended simply as a “convenience” alternative to the tuple form)
 Returns: out : ndarray View of a, with axes suitably permuted.See also - ndarray.T
- Array property returning the array transposed.
 Examples>>> a = np.array([[1, 2], [3, 4]]) >>> a array([[1, 2], [3, 4]]) >>> a.transpose() array([[1, 3], [2, 4]]) >>> a.transpose((1, 0)) array([[1, 3], [2, 4]]) >>> a.transpose(1, 0) array([[1, 3], [2, 4]])
    © 2008–2016 NumPy Developers
Licensed under the NumPy License.
    https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ndarray.transpose.html