When using an ndarray to represent a matrix, how to modify a column based on the value of another column?
Question:
Numpy’s documentation suggests to use numpy arrays to represent matrices, so I’m looking at something like
import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
to represent
and I just can’t figure out from the documentation how I would update a column based on the value of another column. Say, how would I do something like: If, in any row, the value in the second column is > 3, then add 10 to the third? Ie, in my example, I’d like to obtain:
Alternatively, kindly advise if there is some conceptional misunderstanding on my part about ndarrays. I’m really new to this…
Answers:
The specific task you’re interested can be done as follows
arr[arr[:,1]>3,2] += 10
Numpy’s documentation suggests to use numpy arrays to represent matrices, so I’m looking at something like
import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
to represent
and I just can’t figure out from the documentation how I would update a column based on the value of another column. Say, how would I do something like: If, in any row, the value in the second column is > 3, then add 10 to the third? Ie, in my example, I’d like to obtain:
Alternatively, kindly advise if there is some conceptional misunderstanding on my part about ndarrays. I’m really new to this…
The specific task you’re interested can be done as follows
arr[arr[:,1]>3,2] += 10