numpy covariance matrix

Question

Suppose I have two vectors of length 25, and I want to compute their covariance matrix. I try doing this with numpy.cov, but always end up with a 2x2 matrix.

Answer 1

What you got (2 by 2) is more useful than 25*25. Covariance of X and Y is an off-diagonal entry in the symmetric cov_matrix.

If you insist on (25 by 25) which I think useless, then why don't you write out the definition?

x=np.random.normal(size=25).reshape(25,1) # to make it 2d array.
y=np.random.normal(size=25).reshape(25,1)

cov =  np.matmul(x-np.mean(x), (y-np.mean(y)).T) / len(x)