How to normalize a 2-dimensional numpy array in python less verbose?

Broadcasting is really good for this:

row_sums = a.sum(axis=1)
new_matrix = a / row_sums[:, numpy.newaxis]

row_sums[:, numpy.newaxis] reshapes row_sums from being (3,) to being (3, 1). When you do a / b, a and b are broadcast against each other.

You can learn more about broadcasting here or even better here.

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