Add new column to Numpy Array as a function of the rows

Question

I have a 2D Numpy Array, and I want to apply a function to each of the rows and form a new column (the new first column) with the results. For example, let

M = np.array([[1,0,1], [0,0,1]])

and I want to apply the sum function on each row and get

array([[2,1,0,1], [1,0,0,1]])

So the first column is [2,1], the sum of the first row and the second row.

Answer 1

You can generally append arrays to each other using np.concatenate when they have similar dimensionality. You can guarantee that sum will retain dimensionality regardless of axis using the keepdims argument:

np.concatenate((M.sum(axis=1, keepdims=True), M), axis=1)

This is equivalent to

np.concatenate((M.sum(1)[:, None], M), axis=1)