Difference between numpy.array shape (R, 1) and (R,)

Question

In numpy, some of the operations return in shape (R, 1) but some return (R,). This will make matrix multiplication more tedious since

Answer 1

1) The reason not to prefer a shape of (R, 1) over (R,) is that it unnecessarily complicates things. Besides, why would it be preferable to have shape (R, 1) by default for a length-R vector instead of (1, R)? It's better to keep it simple and be explicit when you require additional dimensions.

2) For your example, you are computing an outer product so you can do this without a reshape call by using np.outer:

np.outer(M[:,0], numpy.ones((1, R)))