Python | Numpy MaskedArray.__divmod__ Last Updated : 02 Apr, 2019 Summarize Comments Improve Suggest changes Share Like Article Like Report numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__divmod__ we will get two arrays one is having elements that is divided by value that is provided in numpy.ma.__divmod__() method and second is having elements that perform mod operation with same value as provided in numpy.ma.__divmod__() method. Syntax: numpy.MaskedArray.__divmod__ Return: Return divmod(self, value). Example #1 : In this example we can see that by using MaskedArray.__divmod__() method we get two arrays. One is with divided with value that is passed as parameter and other with mod values. Python3 1== # import the important module in python import numpy as np # make an array with numpy gfg = np.ma.array([1, 2, 3, 4, 5]) # applying MaskedArray.__divmod__() method print(gfg.__divmod__(3)) Output: (masked_array(data = [0 0 1 1 1], mask = [False False False False False], fill_value = 999999), masked_array(data = [1 2 0 1 2], mask = [False False False False False], fill_value = 999999) ) Example #2: Python3 1== # import the important module in python import numpy as np # make an array with numpy gfg = np.ma.array([[1, 2, 3, 4, 5], [6, 5, 4, 3, 2]]) # applying MaskedArray.__divmod__() method print(gfg.__divmod__(3)) Output: (masked_array(data = [[0 0 1 1 1] [2 1 1 1 0]], mask = [[False False False False False] [False False False False False]], fill_value = 999999), masked_array(data = [[1 2 0 1 2] [0 2 1 0 2]], mask = [[False False False False False] [False False False False False]], fill_value = 999999) ) Comment More infoAdvertise with us Next Article Python | Numpy MaskedArray.__iand__() S Shivam_k Follow Improve Article Tags : Python Python-numpy Python numpy-ndarray Practice Tags : python Similar Reads Python | Numpy MaskedArray.__div__ numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__div__ we can divide a particular value that is provided as a parameter in the MaskedArray.__div__() method. Syntax: numpy.MaskedArray.__div__ Return: Di 1 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 Python | Numpy MaskedArray.__add__ numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__add__ we can add a particular value that is provided as a parameter in the MaskedArray.__add__() method. Value will be added to each and every element i 1 min read Python | Numpy MaskedArray.__iand__() numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__iand__we can get the elements that is anded by the value that is provided as a parameter in the MaskedArray.__iand__() method. Syntax: numpy.MaskedArray 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 MaskedArray.__floordiv__ numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__floordiv__ operator we can divide a particular value that is provided as a parameter to this function. Syntax: numpy.MaskedArray.__floordiv__ Return: Di 1 min read Like