/NumPy 1.17

# 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.

Note

Previous to NumPy 1.13.0, neither `axis < -a.ndim - 1` nor `axis > a.ndim` raised errors or put the new axis where documented. Those axis values are now deprecated and will raise an AxisError in the future.

Parameters: `a : array_like` Input array. `axis : int` Position in the expanded axes where the new axis is placed. `res : ndarray` View of `a` with the number of dimensions increased by one.

`squeeze`
The inverse operation, removing singleton dimensions
`reshape`
Insert, remove, and combine dimensions, and resize existing ones

#### 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)
```
```>>> y = np.expand_dims(x, axis=1)  # Equivalent to x[:,np.newaxis]
>>> y
array([,
])
>>> y.shape
(2, 1)
```

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

```>>> np.newaxis is None
True
```