xorbits.numpy.expand_dims(a, axis)[source]#

Expand the shape of an array.

Insert a new axis that will appear at the axis position in the expanded array shape.

  • a (array_like) – Input array.

  • axis (int or tuple of ints) –

    Position in the expanded axes where the new axis (or axes) is placed.

    Deprecated since version 1.13.0(numpy): Passing an axis where axis > a.ndim will be treated as axis == a.ndim, and passing axis < -a.ndim - 1 will be treated as axis == 0. This behavior is deprecated.

    Changed in version 1.18.0(numpy): A tuple of axes is now supported. Out of range axes as described above are now forbidden and raise an AxisError.


result – View of a with the number of dimensions increased.

Return type


See also


The inverse operation, removing singleton dimensions


Insert, remove, and combine dimensions, and resize existing ones

doc.indexing, atleast_1d, atleast_2d, atleast_3d


>>> x = np.array([1, 2])  
>>> x.shape  

The following is equivalent to x[np.newaxis, :] or x[np.newaxis]:

>>> y = np.expand_dims(x, axis=0)  
>>> y  
array([[1, 2]])
>>> y.shape  
(1, 2)

The following is equivalent to x[:, np.newaxis]:

>>> y = np.expand_dims(x, axis=1)  
>>> y  
>>> y.shape  
(2, 1)

axis may also be a tuple:

>>> y = np.expand_dims(x, axis=(0, 1))  
>>> y  
array([[[1, 2]]])
>>> y = np.expand_dims(x, axis=(2, 0))  
>>> y  

Note that some examples may use None instead of np.newaxis. These are the same objects:

>>> np.newaxis is None  

This docstring was copied from numpy.