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.

Make a 1 column array with the new values, and concatenate them. — hpaulj
– hpaulj, Commented Jul 22, 2021 at 23:30

Mad Physicist · Accepted Answer · 2021-07-22 23:34:42Z

5

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)

answered Jul 22, 2021 at 23:34

Mad Physicist

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Ehsan · Accepted Answer · 2021-07-23 02:07:54Z

1

Another similar way:

np.insert(M, 0, M.sum(1), 1)

output:

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

answered Jul 23, 2021 at 2:07

Ehsan

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