Why "None" has the same effect as "np.newaxis"?

Question

Why None has the save effect of np.newaxis? For example, using:

np.arange(10)[:,None]

or:

np.arange(10)[:,np.newaxis]

both create:

array([[0],
       [1],
       [2],
       [3],
       [4],
       [5],
       [6],
       [7],
       [8],
       [9]])

Does anyone know the reason for np.newaxis==None?

score 12 · Accepted Answer · answered Aug 10 '13 at 16:29

12

Thats because numpy.newaxis is an alias for None as it says in the documentation: None can also be used instead of newaxis.

answered Aug 10 '13 at 16:29

jabaldonedo

3

It's simply because `newaxis` is more explicit about what it would do, intsead of `None` – Jon Clements Aug 10 '13 at 16:33

score 3 · Answer 2 · answered Aug 10 '13 at 16:33

3

Look here:

>>> import numpy
>>> print(numpy.newaxis)
None
>>>

numpy.newaxis is None.

answered Aug 10 '13 at 16:33

2 Answers2