This is documentation for an old release of NumPy (version 1.14). Read this page Search for this page in the documentation of the latest stable release (version 2.2).

numpy.intersect1d

numpy.intersect1d(ar1, ar2, assume_unique=False)

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])