numpy.intersect1d

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

>>> np.intersect1d([1, 3, 4, 3], [3, 1, 2, 1])
array([1, 3])

To intersect more than two arrays, use functools.reduce:

>>> from functools import reduce
>>> reduce(np.intersect1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2]))
array([3])