NumPy

numpy.expand_dims

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.

Parameters
aarray_like

Input array.

axisint or tuple of ints

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

Deprecated since version 1.13.0: 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: A tuple of axes is now supported. Out of range axes as described above are now forbidden and raise an AxisError.

Returns
resultndarray

View of a with the number of dimensions increased.

See also

squeeze

The inverse operation, removing singleton dimensions

reshape

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

doc.indexing, atleast_1d, atleast_2d, atleast_3d

Examples

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

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
array([[1],
       [2]])
>>> 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
array([[[1],
        [2]]])

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

>>> np.newaxis is None
True

Previous topic

numpy.broadcast_arrays

Next topic

numpy.squeeze