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

Question

This question already has an answer here:

Numpy: Should I use newaxis or None? (1 answer)

Closed 8 years ago.

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?

Answer 1

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

Answer 2

Look here:

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

numpy.newaxis is None.