How do np.nan and None behave differently?

Question

I want to know whether there is any difference between using np.nan and None while using pandas dataframe or numpy arrays. If there is, where exactly does this difference matter?

`np.nan` is a valid `float`, so can be an element of a `float` `dtype` `numpy` array. `None` is a Python object, and can only be an element of an `object` `dtype` array. — hpaulj, Apr 29 '19 at 03:53

score -1 · Answer 1 · edited Apr 29 '19 at 04:18

-1

Np.nan means not a number and None can be applied in general to the other cases. np.nan can be used as a bool for example:

if('Hello' == np.nan)

edited Apr 29 '19 at 04:18

Alec

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answered Apr 29 '19 at 03:41

Freison Castro

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You can do `'hello' == None` too... – gmds Apr 29 '19 at 03:42
Generally `is None` is the recommended test. – hpaulj Apr 29 '19 at 07:00

How do np.nan and None behave differently?

1 Answers1