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# 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])