Python | Numpy ndarray.__ixor__() Last Updated : 27 Mar, 2019 Comments Improve Suggest changes Like Article Like Report With the help of Numpy ndarray.__ixor__() method, we can get the elements that is XOR by the value that is provided as a parameter in numpy.ndarray.__ixor__() method. Syntax: ndarray.__ixor__($self, value, /) Return: self^=value Example #1 : In this example we can see that every element is xor by the value that is passed as a parameter in ndarray.__ixor__() method. Python3 1== # import the important module in python import numpy as np # make an array with numpy gfg = np.array([1, 2, 3, 4, 5]) # applying ndarray.__ixor__() method print(gfg.__ixor__(2)) Output: [3 0 1 6 7] Example #2 : Python3 1== # import the important module in python import numpy as np # make an array with numpy gfg = np.array([[1, 2, 3, 4, 5], [6, 5, 4, 3, 2]]) # applying ndarray.__ixor__() method print(gfg.__ixor__(1)) Output: [[0 3 2 5 4] [7 4 5 2 3]] Comment More infoAdvertise with us Next Article Python | Numpy ndarray.__ixor__() J Jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-ndarray Practice Tags : python Similar Reads Python | Numpy ndarray.__ior__() With the help of Numpy ndarray.__ior__() method, we can get the elements that is OR by the value that is provided as a parameter in numpy.ndarray.__ior__() method. Syntax: ndarray.__ior__($self, value, /) Return: self|=value Example #1 : In this example we can see that every element is or by the val 1 min read Python | Numpy ndarray.__ipow__() With the help of Numpy ndarray.__ipow__() method, we will get all the elements powered with the value that is provided as a parameter in numpy.ndarray.__ipow__() method. Syntax: ndarray.__ipow__($self, value, /) Return: self**=value Example #1 : In this example we can see that every element get powe 1 min read Python | Numpy ndarray.__imod__() With the help of Numpy ndarray.__imod__(), every element in an array is operated on binary operator i.e mod(%). Remember we can use any type of values in an array and value for mod is applied as the parameter in ndarray.__imod__(). Syntax: ndarray.__imod__($self, value, /) Return: self%=value Exampl 1 min read Python | Numpy MaskedArray.__ixor__() numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__ixor__we can get the elements that is XOR by the value that is provided as a parameter in the MaskedArray.__ixor__() method. Syntax: numpy.MaskedArray._ 1 min read Python | Numpy ndarray.__iand__() With the help of Numpy ndarray.__iand__() method, we can get the elements that is anded by the value that is provided as a parameter in numpy.ndarray.__iand__() method. Syntax: ndarray.__iand__($self, value, /) Return: self&=value Example #1 : In this example we can see that every element is and 1 min read Python | Numpy ndarray.item() With the help of numpy.ndarray.item() method, we can fetch the data elements that is found at the given index on numpy array. Remember we can give index as one dimensional parameter or can be two dimensional. Parameters: *args : Arguments (variable number and type) -> none: This argument only works 2 min read Python | Numpy MaskedArray.__ior__() numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__ior__we can get the elements that is OR by the value that is provided as a parameter in the MaskedArray.__ior__() method. Syntax: numpy.MaskedArray.__io 1 min read numpy.ndarray.view() in Python numpy.ndarray.view() helps to get a new view of array with the same data. Syntax: ndarray.view(dtype=None, type=None)Parameters: dtype : Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a. type : Python type, opti 3 min read numpy.ndarray.fill() in Python numpy.ndarray.fill() method is used to fill the numpy array with a scalar value. If we have to initialize a numpy array with an identical value then we use numpy.ndarray.fill(). Suppose we have to create a NumPy array a of length n, each element of which is v. Then we use this function as a.fill(v). 2 min read numpy.ndarray.flat() in Python The numpy.ndarray.flat() function is used as a 1_D iterator over N-dimensional arrays. It is not a subclass of, Pythonâs built-in iterator object, otherwise it a numpy.flatiter instance. Syntax : numpy.ndarray.flat() Parameters : index : [tuple(int)] index of the values to iterate Return :  1-D i 3 min read Like