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#matrix is the feature matrix containing dependent variables
corr = np.corrcoef(matrix, rowvar=0) 
w, v = np.linalg.eig(corr)

w # list of eigen values #should not have any zero values in case of linearly independent rows

v[:,0] #first eigen vector
v[:,1] #second eigen vector
and so on