numpy.stack

numpy.stack(arrays, axis=0, out=None) [source]

Join a sequence of arrays along a new axis.

The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last dimension.

New in version 1.10.0.

Parameters:	arrays : sequence of array_like Each array must have the same shape. axis : int, optional The axis in the result array along which the input arrays are stacked. out : ndarray, optional If provided, the destination to place the result. The shape must be correct, matching that of what stack would have returned if no out argument were specified.
Returns:	stacked : ndarray The stacked array has one more dimension than the input arrays.

See also

concatenate

Join a sequence of arrays along an existing axis.

split

Split array into a list of multiple sub-arrays of equal size.

block

Assemble arrays from blocks.

Examples

>>> arrays = [np.random.randn(3, 4) for _ in range(10)]
>>> np.stack(arrays, axis=0).shape
(10, 3, 4)

>>> np.stack(arrays, axis=1).shape
(3, 10, 4)

>>> np.stack(arrays, axis=2).shape
(3, 4, 10)

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

>>> np.stack((a, b), axis=-1)
array([[1, 2],
       [2, 3],
       [3, 4]])