Linear regression of arrays containing NANs in Python/Numpy

Question

I have two arrays, say varx and vary. Both contain NAN values at various positions. However, I would like to do a linear regression on both to show how much the two arrays c

Answer 1

You can remove NaNs using a mask:

mask = ~np.isnan(varx) & ~np.isnan(vary)
slope, intercept, r_value, p_value, std_err = stats.linregress(varx[mask], vary[mask])