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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, :]
>>> row_v.shape
(1, 2)
>>> row_v
array([[0, 3]])
>>> # Insert a new length 1 dimension at the end
>>> col_v = v[:, np.newaxis]
>>> col_v.shape
(2, 1)
>>> col_v
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)