How to replace values in a numpy array based on another column?

Question

Let say i have the following:

import numpy as np

data = np.array([
     [1,2,3],
     [1,2,3],
     [1,2,3],
     [4,5,6],         
     ])

How would I go about changing values in column 3 based on values in column 2? For instance, If column 3 == 3, column 2 = 9.

[[1,9,3],
 [1,9,3],
 [1,9,3],
 [4,5,6]]

I've looked at np.any(), but I can't figure out how to alter the array in place.

mdml · Accepted Answer · 2013-12-03 15:39:30Z

18

You can use Numpy's slicing and indexing to achieve this. Take all the rows where the third column is 3, and change the second column of each of those rows to 9:

>>> data[data[:, 2] == 3, 1] = 9
>>> data
array([[1, 9, 3],
       [1, 9, 3],
       [1, 9, 3],
       [4, 5, 6]])

answered Dec 3, 2013 at 15:39

mdml

23k8 gold badges61 silver badges66 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

Barbarossa Over a year ago

Does this copy the data, or does it alter data in place without reserving additional memory?

mdml Over a year ago

@Barbarossa: It alters the data in place, although additional memory is required to make the index with data[:, 2] == 3.

Collectives™ on Stack Overflow

How to replace values in a numpy array based on another column?

1 Answer 1

2 Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

2 Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related