Python | Numpy numpy.ndarray.__xor__() Last Updated : 11 Mar, 2019 Comments Improve Suggest changes Like Article Like Report With the help of Numpy numpy.ndarray.__xor__() method, we can get the elements that is XOR by the value that is provided as a parameter in numpy.ndarray.__xor__() method. Syntax: ndarray.__xor__($self, value, /) Return: self^value Example #1 : In this example we can see that every element is xor by the value that is passed as a parameter in ndarray.__xor__() method. Python3 # import the important module in python import numpy as np # make an array with numpy gfg = np.array([1, 2, 3, 4, 5]) # applying ndarray.__xor__() method print(gfg.__xor__(2)) Output: [3 0 1 6 7] Example #2 : Python3 # import the important module in python import numpy as np # make an array with numpy gfg = np.array([[1, 2, 3, 4, 5], [6, 5, 4, 3, 2]]) # applying ndarray.__xor__() method print(gfg.__xor__(1)) Output: [[0 3 2 5 4] [7 4 5 2 3]] Comment More infoAdvertise with us Next Article NumPy Array in Python J jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-ndarray Practice Tags : python Similar Reads Python | Numpy MaskedArray.__xor__ numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__xor__ method we can get the elements that is XOR by the value that is provided as a parameter. Syntax: numpy.MaskedArray.__xor__($self, value, /) Return 1 min read Python | Numpy MaskedArray.__rxor__ numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__rxor__ method we can get the elements that is XOR with the value that is provided as a parameter. Syntax: numpy.MaskedArray.__rxor__($self, value, /) Re 1 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read numpy.asarray() in Python numpy.asarray()function is used when we want to convert input to an array. Input can be lists, lists of tuples, tuples, tuples of tuples, tuples of lists and arrays. Syntax : numpy.asarray(arr, dtype=None, order=None) Parameters : arr : [array_like] Input data, in any form that can be converted to a 2 min read numpy.asanyarray() in Python numpy.asanyarray()function is used when we want to convert input to an array but it pass ndarray subclasses through. Input can be scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Syntax : numpy.asanyarray(arr, dtype=None, order=None) Parameters : arr : [array_ 2 min read Like