Good additions there! Now, if you’re also interested in a normalized version of covariance, you could consider using np.corrcoef(a, b)[0][1]. This gives you the correlation coefficient, which scales the covariance by the standard deviations of a and b. It’s a quick way to assess how strongly related the two datasets are. So, if you’re looking for something beyond just python covariance, this could be a useful approach, especially when you’re comparing datasets with different scales.