a.transpose(*axes)
For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector, an additional dimension must be added. :None:None:`np.atleast2d(a).T`
achieves this, as does :None:None:`a[:, np.newaxis]`
. For a 2-D array, this is a standard 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])
, then a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])
.
None or no argument: reverses the order of the axes.
tuple of ints: :None:None:`i`
in the :None:None:`j`
-th place in the tuple means a
's :None:None:`i`
-th axis becomes :None:None:`a.transpose()`
's :None:None:`j`
-th axis.
:None:None:`n`
ints: same as an n-tuple of the same ints (this form is intended simply as a "convenience" alternative to the tuple form)
Returns a view of the array with axes transposed.
ndarray.T
Array property returning the array transposed.
ndarray.reshape
Give a new shape to an array without changing its data.
transpose
Equivalent function
>>> a = np.array([[1, 2], [3, 4]])This example is valid syntax, but we were not able to check execution
... a array([[1, 2], [3, 4]])
>>> a.transpose() array([[1, 3], [2, 4]])This example is valid syntax, but we were not able to check execution
>>> a.transpose((1, 0)) array([[1, 3], [2, 4]])This example is valid syntax, but we were not able to check execution
>>> a.transpose(1, 0) array([[1, 3], [2, 4]])See :
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