# Adding length 1 dimensions with newaxis#

NumPy has a nice shortcut for adding a length 1 dimension to an array. It is a little brain-bending, because it operates via array slicing:

```
import numpy as np
```

```
v = np.array([0, 3])
v.shape
```

```
(2,)
```

```
# Insert a new length 1 dimension at the beginning
row_v = v[np.newaxis, :]
print(row_v.shape)
row_v
```

```
(1, 2)
```

```
array([[0, 3]])
```

```
# Insert a new length 1 dimension at the end
col_v = v[:, np.newaxis]
print(col_v.shape)
col_v
```

```
(2, 1)
```

```
array([[0],
[3]])
```

Read this last slicing operation as “do slicing as normal, except, before
slicing, insert a length 1 dimension at the position of `np.newaxis`

”.

In fact the name `np.newaxis`

points to the familiar Python `None`

object:

```
np.newaxis is None
```

```
True
```

So, you also use the `np.newaxis`

trick like this:

```
row_v = v[None, :]
row_v.shape
```

```
(1, 2)
```