Set numpy array rows column values to column values of another array

Question

I am trying to select rows with values in their first two columns matching with those of another array and set their last columns values to the last column values of that array.

I've specifically tried to do something like this:

import numpy as np

array_1 = np.zeros((10,3), order = "F", dtype = int)

array_2 = np.zeros((5,3), order = "F", dtype = int)

array_1[:5][:,0] = 1
array_1[:5][:,1] = 1

array_2[:,0] = 1
array_2[:,1] = 1
array_2[:,2] = 3

array_1[:,2][np.where((array_1[:,0] == array_2[:,0]) & (array_1[:,1] == array_2[:,1]))] = array_2[:,2]

The objective is to set the value of column 2 of rows matching to 3. (same as array_2)

I've also tried to do the same thing with masking.

It always complaints about a shape mismatch, so I assume I am doing something wrong since the objective is only to change the value of one particular column, for those row matches.

What is the way to do this?

They are different but I was hoping for this to not matter to the operation since I am only targeting the elements of the one that the other also has. — mangotango
– mangotango, Commented May 10, 2021 at 22:41
What are the shapes for array_1[:,0].shape and array_2[:,0].shape? If they are different, you cannot compare them. — m.i.cosacak
– m.i.cosacak, Commented May 10, 2021 at 23:16
Please provide a minimal reproducible example. A small example of array_1 and array_2 that demonstrates the problem and is representative of your actual arrays. — GoodDeeds
– GoodDeeds, Commented May 11, 2021 at 2:16
I have updated the code with a minimal reproducible example. — mangotango
– mangotango, Commented May 11, 2021 at 11:40

mangotango · Accepted Answer · 2021-05-11 20:35:06Z

1

I was able to solve it like this:

import numpy as np

array_1 = np.zeros((10,3), order = "F", dtype = int)

array_2 = np.zeros((5,3), order = "F", dtype = int)

array_1[:5][:,0] = 1
array_1[:5][:,1] = 1

array_2[:,0] = 1
array_2[:,1] = 1
array_2[:,2] = 3

m = (array_1[:,:2][:,None] == array_2[:,:2]).all(-1).any(1)

array_1[:,2][m] = array_2[:,2]

edited May 11, 2021 at 20:35

answered May 11, 2021 at 19:17

mangotango

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