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]) .

Parameters

axes : None, tuple of ints, or `n` ints

• 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

out : ndarray

View of a, with axes suitably permuted.

Returns a view of the array with axes transposed.

See Also

ndarray.T

Array property returning the array transposed.

ndarray.reshape

Give a new shape to an array without changing its data.

transpose

Equivalent function

Examples

This example is valid syntax, but we were not able to check execution

>>> a = np.array([[1, 2], [3, 4]])
... a
array([[1, 2],
       [3, 4]])

This example is valid syntax, but we were not able to check execution

>>> 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 :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

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