xorbits.numpy.union1d#

xorbits.numpy.union1d(ar1, ar2, aggregate_size=None)[source]#

Find the union of two arrays.

Return the unique, sorted array of values that are in either of the two input arrays.

Parameters

  • ar1 (array_like) – Input arrays. They are flattened if they are not already 1D.

  • ar2 (array_like) – Input arrays. They are flattened if they are not already 1D.

Returns

union1d – Unique, sorted union of the input arrays.

Return type

ndarray

See also

numpy.lib.arraysetops

Module with a number of other functions for performing set operations on arrays.

Examples

>>> np.union1d([-1, 0, 1], [-2, 0, 2])  
array([-2, -1,  0,  1,  2])

To find the union of more than two arrays, use functools.reduce:

>>> from functools import reduce  
>>> reduce(np.union1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2]))  
array([1, 2, 3, 4, 6])

This docstring was copied from numpy.