/NumPy 1.17

# numpy.ma.stack

`numpy.ma.stack(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_seq object>`

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. `stacked : ndarray` The stacked array has one more dimension than the input arrays.

`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.

#### Notes

The function is applied to both the _data and the _mask, if any.

#### 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]])
```