NumPy logic functions: not_equal() function

Last update on August 19 2022 21:50:38 (UTC/GMT +8 hours)

numpy.not_equal() function

The not_equal() function is used to return (x1 != x2) element-wise.

Syntax:

numpy.not_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'not_equal'>

Version: 1.15.0

Parameter:

Name	Description	Required / Optional
x1, x2	Input arrays. array_like	Required
out	A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. ndarray, None, or tuple of ndarray and None	Optional
where	Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. array_like	Optional
**kwargs	For other keyword-only arguments	Required

Returns:
out : ndarray or scalar - Output array, element-wise comparison of x1 and x2. Typically of type bool, unless dtype=object is passed.
This is a scalar if both x1 and x2 are scalars.

NumPy.not_equal() method Example-1:

>>> import numpy as np
>>> np.not_equal([4.,3.], [4., 5.])

Output:

array([False,  True])

NumPy.not_equal() method Example-2:

>>> import numpy as np
>>> np.not_equal([2, 5], [[2, 3],[2, 4]])

Output:

array([[False,  True],
       [False,  True]])

Python - NumPy Code Editor:

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