ill be the last dimension.

    .. versionadded:: 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.

    dtype : str or dtype
        If provided, the destination array will have this dtype. Cannot be
        provided together with `out`.

        .. versionadded:: 1.24

    casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
        Controls what kind of data casting may occur. Defaults to 'same_kind'.

        .. versionadded:: 1.24


    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.
    block : Assemble an nd-array from nested lists of blocks.
    split : Split array into a list of multiple sub-arrays of equal size.

    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([4, 5, 6])
    >>> np.stack((a, b))
    array([[1, 2, 3],
           [4, 5, 6]])

    >>> np.stack((a, b), axis=-1)
    array([[1, 4],
           [2, 5],
           [3, 6]])

    c