Reputation: 567
I have been going through several solutions, but I am not able to find a solution I need.
I have two numpy
arrays. Let's take a small example here.
x = [1,2,3,4,5,6,7,8,9]
y = [3,4,5]
I want to compare x and y, and remove those values of x that are in y.
So I expect my final_x to be
final_x = [1,2,6,7,8,9]
I found out that np.in1d returns a boolean array the same length as x
that is True where an element of x
is in y
and False otherwise. But how do I use it, if not any other method to get my final_x
.??
Upvotes: 2
Views: 2950
Reputation: 1362
You can use built-in sets:
final_x = set(x) - set(y)
and subtract the second from the first. You can convert final_x
to a list
or numpy.array
if you feel so inclined.
Upvotes: 0
Reputation: 53678
If you really do have numpy arrays then you can use numpy.setdiff1d
as below
import numpy as np
x = np.array([1,2,3,4,5,6,7,8,9])
y = np.array([3,4,5])
z = np.setdiff1d(x, y)
# array([1, 2, 6, 7, 8, 9])
Upvotes: 6
Reputation: 250891
Simply pass the negated version of boolean array returned by np.in1d
to array x
:
>>> x = np.array([1,2,3,4,5,6,7,8,9])
>>> y = [3,4,5]
>>> x[~np.in1d(x, y)]
array([1, 2, 6, 7, 8, 9])
Upvotes: 3