How I can i conditionally change the values in a numpy array taking into account nan numbers?

The fact that you have np.nan in your array should not matter. Just use fancy indexing:

x[x>0] = new_value_for_pos
x[x<0] = new_value_for_neg

If you want to replace your np.nans:

x[np.isnan(x)] = something_not_nan

More info on fancy indexing a tutorial and the NumPy documentation.

Try:

a[a>0] = 1
a[a<0] = -1

to add or subtract to current value then (np.nan not affected)

import numpy as np

a = np.arange(-10, 10).reshape((4, 5))

print("after -")
print(a)

a[a<0] = a[a<0] - 2
a[a>0] = a[a>0] + 2


print(a)

output

[[-10  -9  -8  -7  -6]
 [ -5  -4  -3  -2  -1]
 [  0   1   2   3   4]
 [  5   6   7   8   9]]

after -

[[-12 -11 -10  -9  -8]
 [ -7  -6  -5  -4  -3]
 [  0   3   4   5   6]
 [  7   8   9  10  11]]