def matrix_entry(i, j): return stats.correlation(lin_alg.get_col(data, i), get_col(data, j))
def scale(data_matrix): '''returns mean and sd of each column''' num_rows, num_cols = lin_alg.shape(data_matrix) means = [stats.mean(lin_alg.get_col(data_matrix, j)) for j in range(num_cols)] stdevs = [stats.standard_deviation(lin_alg.get_col(data_matrix, j)) for j in range(num_cols)] return means, stdevs