numpy corrcoef - compute correlation matrix while ignoring missing data

Question

I am trying to compute a correlation matrix of several values. These values include some \'nan\' values. I\'m using numpy.corrcoef. For element(i,j) of the output correla

Answer 1

This will work, using the masked array numpy module:

import numpy as np
import numpy.ma as ma

A = [1, 2, 3, 4, 5, np.NaN]
B = [2, 3, 4, 5.25, np.NaN, 100]

print(ma.corrcoef(ma.masked_invalid(A), ma.masked_invalid(B)))

It outputs:

[[1.0 0.99838143945703]
 [0.99838143945703 1.0]]

Read more here: https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html