-
numpy.intersect1d(ar1, ar2, assume_unique=False)
[source] -
Find the intersection of two arrays.
Return the sorted, unique values that are in both of the input arrays.
Parameters: ar1, ar2 : array_like
Input arrays.
assume_unique : bool
If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.
Returns: intersect1d : ndarray
Sorted 1D array of common and unique elements.
See also
-
numpy.lib.arraysetops
- Module with a number of other functions for performing set operations on arrays.
Examples
12>>> np.intersect1d([
1
,
3
,
4
,
3
], [
3
,
1
,
2
,
1
])
array([
1
,
3
])
To intersect more than two arrays, use functools.reduce:
123>>>
from
functools
import
reduce
>>>
reduce
(np.intersect1d, ([
1
,
3
,
4
,
3
], [
3
,
1
,
2
,
1
], [
6
,
3
,
4
,
2
]))
array([
3
])
-
numpy.intersect1d()

2025-01-10 15:47:30
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