Setting numpy array values to NaN based on condition

Question

I'm working with a dataset where non existent values show up as a negative number. I want to convert these values to np.nan values but I can't figure out how. The condition for this is (array < 0).

An example of what would happen to the array would be:

import numpy as np

array = np.array([[-1,  1, -1,  1],
                  [ 1, -1, -1,  1],
                  [ 1, -1, -1, -1]])

To then be converted to:

np.array([[np.nan,      1, np.nan,      1],
          [     1, np.nan, np.nan,      1],
          [     1, np.nan, np.nan, np.nan]])

Cheers

Alex · Accepted Answer · 2018-02-14 23:00:16Z

7

np.nan is a float so you need to convert array to float before doing the boolean masking.

isinstance(np.nan, float)  # True

array = array.astype(float)
array[array < 0] = np.nan
array

outputs

array([[nan,  1., nan,  1.],
       [ 1., nan, nan,  1.],
       [ 1., nan, nan, nan]])

answered Feb 14, 2018 at 23:00

Alex

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