Let's add another layer and look at at year and age in a single matrix: In [55]: yrages np.array (data.iloc,0:2]) print(yrages.shape) yrages[0] #note that winning year and age are columns 0 and 1, respectively. (89, 2) Out [55]: array ([1928, 22) Complete the method below to return a matrix where both dimensions are centered i.e. avg of each feature, age and year, is 0. No looping In 1: def center2d(x): return the max of given 1D array # YOUR CODE HERE raise NotImplementedError() In [57]: #test area p - np.arange (0,10).reshape (5,2) Out [571: array(, 11, [2, 31, 4, 51, [6, 71, [8, 91]) In [ ] : "" "Check that method returns the correct output for several Inputs """ #assert np.arange(o,10).reshape (5,2) q-np.array(-4,-4.], -2., 2.1, 0, 0, np.testing.assert_allclose (center2d(p), q) 2., 2., 4., 4.11)