Substitue row in Numpy if a condition is met

November 9, 2021

I have a matrix in NumPy as:

[[10 10]
 [11 10]
 [12 10]
 [13 10]
 [14 10]]

My goal is to replace a row if a particular condition on the left element is met.

For example,

I have values: z= 13, x=1, y=0. I’d like something as:

If one of the left elements is equal to z then replace the row with [x y]

So far I wrote something like this:

values = np.array([[10 10]
     [11 10]
     [12 10]
     [13 10]
     [14 10]])
z = 13
x = 1
y = 0
values = np.where(values == [z, ], np.array([x, y]), values)

The code works well for replacing the left element (x is updated), but y for some reason stays the same or gets the value of another row somehow.

Does anyone know what could I do? Or if there is another method whatsoever?

>Solution :

Try values[values[:, 0] == z] = [x, y] — i.e., rows whose 1st entry is z are set to [x, y].

import numpy as np

values = np.array([[10, 10],
     [11, 10],
     [12, 10],
     [13, 10],
     [14, 10]])
z = 13
x = 1
y = 0

values[values[:, 0] == z] = [x, y]

print(values)