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isin(element, test_elements, assume_unique=False, invert=False)

Notes

isin is an element-wise function version of the python keyword :None:None:`in`. isin(a, b) is roughly equivalent to np.array([item in b for item in a]) if a and :None:None:`b` are 1-D sequences.

:None:None:`element` and :None:None:`test_elements` are converted to arrays if they are not already. If :None:None:`test_elements` is a set (or other non-sequence collection) it will be converted to an object array with one element, rather than an array of the values contained in :None:None:`test_elements`. This is a consequence of the array constructor's way of handling non-sequence collections. Converting the set to a list usually gives the desired behavior.

versionadded

Parameters

element : array_like: Input array.
test_elements : array_like: The values against which to test each value of :None:None:`element`. This argument is flattened if it is an array or array_like. See notes for behavior with non-array-like parameters.
assume_unique : bool, optional: If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.
invert : bool, optional: If True, the values in the returned array are inverted, as if calculating :None:None:`element not in test_elements`. Default is False. np.isin(a, b, invert=True) is equivalent to (but faster than) np.invert(np.isin(a, b)) .

Returns

isin : ndarray, bool: Has the same shape as :None:None:`element`. The values :None:None:`element[isin]` are in :None:None:`test_elements`.

Calculates :None:None:`element in test_elements`, broadcasting over :None:None:`element` only. Returns a boolean array of the same shape as :None:None:`element` that is True where an element of :None:None:`element` is in :None:None:`test_elements` and False otherwise.

Examples

>>> element = 2*np.arange(4).reshape((2, 2))
... element
array([[0, 2],
       [4, 6]])

>>> test_elements = [1, 2, 4, 8]
... mask = np.isin(element, test_elements)
... mask
array([[False,  True],
       [ True, False]])

>>> element[mask]
array([2, 4])

The indices of the matched values can be obtained with nonzero :

>>> np.nonzero(mask)
(array([0, 1]), array([1, 0]))

The test can also be inverted:

>>> mask = np.isin(element, test_elements, invert=True)
... mask
array([[ True, False],
       [False,  True]])

>>> element[mask]
array([0, 6])

Because of how array handles sets, the following does not work as expected:

>>> test_set = {1, 2, 4, 8}
... np.isin(element, test_set)
array([[False, False],
       [False, False]])

Casting the set to a list gives the expected result:

>>> np.isin(element, list(test_set))
array([[False,  True],
       [ True, False]])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.isin numpy.in1d numpy.ma.extras.in1d numpy.ma.extras.isin

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