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

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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.

numpy python
2 Answers

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)
user_29887300

Another similar way:

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

output:

array([[2, 1, 0, 1],
       [1, 0, 0, 1]])
user_49759810
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