[Python] Can I improve my Numpy solution to an exercise?

I have been asked to use the following set of column indices: y = np.array([3, 0, 4, 1])

to turn into 1 all the elements in the following matrix: x = np.zeros(shape = (4, 5)) that have y as starting column and rows given by the position of y. Just to be clear.

The final result has to be the following:

[[0. 0. 0. 1. 1.] [1. 1. 1. 1. 1.] [0. 0. 0. 0. 1.] [0. 1. 1. 1. 1.]]

For example:

y[0] = 3,

then row 0, columns 3 and 4 need to be equal to 1.

I did it like this:

for (idx, num) in enumerate(y): x[idx, num:] = 1

Can this result be written differently and/or improved by using other Numpy functions (for example, using vectorization)?

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