如何替换基于另一列的numpy数组中的值? [英] How to replace values in a numpy array based on another column?

问题描述

让我说以下内容:

import numpy as np

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

如何根据第2列中的值更改第3列中的值?例如，如果第3列== 3，则第2列=9.

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]]

我看过 np.any()，但是我不知道如何在适当的位置更改数组.

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

推荐答案

您可以使用 Numpy的切片和索引来实现这一目标.取第三列为 3 的所有行，并将每行的第二列更改为 9 :

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]])

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