Most efficient way to update specific columns in numpy

Question

Whats the most efficient way to update a specific column in numpy? For simplicity, say i have:

[[0 2]
 [1 2]
 [2 2]]

Then I would like to add 2 on every element on the second column.

[[0 4]
 [1 4]
 [2 4]]

This can be simply done with a loop, but I was wondering if theres a numpy function I could use that would be more efficient. Assuming the array is quite large.

Try this: a[:, 1] += 2 You may want to read about Numpy indexing — MaxU - stand with Ukraine
– MaxU - stand with Ukraine, Commented Nov 26, 2017 at 20:55
Arithmetic (and much much more) operations are vectorized in numpy, so just use arr[:,1] += 2. — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Nov 26, 2017 at 20:55

James · Accepted Answer · 2017-11-26 20:56:28Z

2

You can reference a column using:

a = np.array([[0 2]
              [1 2]
              [2 2]]

a[:,1] += 2

answered Nov 26, 2017 at 20:56

James

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