Maintaining NaN value when going from python list to numpy array?

Question

In my code, I must go from a large nested list (python list of python lists) and in each sublist, some entries may be the numpy values NaN. When I create this nested list it looks something like this:

import numpy as np
nested_list = [[np.nan, 19], ['a', np.nan]]
>>> print(nested_list)
[[nan, 19], ['a', nan]]

I expect when I evaluate the equality of a NaN element of the sublist against itself, I should get False due to it being a null value which I do:

>>>print(nested_list[1][1] == nested_list[1][1])
False

Now, I want to turn this nested list into a 2d numpy array, but when I do, the NaN values just turn into strings and do not retain their null-ness:

arr = np.array(list_of_lists)
>>>print(arr)
[['nan' '19']
 ['a' 'nan']]
>>>print(arr[1][1] == arr[1][1])
True

How do I keep NaN from being turned into a string?

Why do you want a numpy array? Why not stick with the list, where a mix of types is natural. — hpaulj
– hpaulj, Commented Aug 12, 2021 at 19:44
@hpaulj I had some previous code written when the object I'm dealing with is a numpy array from the start, but the code I'm writing now necessitates me starting with a list, so I wanted to convert back to what the code already knew how to deal with. — cameronpoe
– cameronpoe, Commented Aug 12, 2021 at 19:52
Just beware that an object dtype array is quite different from a regular numeric array. — hpaulj
– hpaulj, Commented Aug 12, 2021 at 20:05

Lukas S · Accepted Answer · 2021-08-12 19:21:21Z

1

You can do it like this

import numpy as np

nested_list = [[np.nan, 19], ['a', np.nan]]
np.array(nested_list, dtype='object')

answered Aug 12, 2021 at 19:21

Lukas S

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