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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def perform_pca(A):
 """ Computes eigenvalues and eigenvectors of covariance matrix of A. The rows of a correspond to observations, the columns to variables. """

    # First subtract the mean
    M = (A-numpy.mean(A.T, axis=1)).T
    # Get eigenvectors and values of covariance matrix
    return numpy.linalg.eig(numpy.cov(M))