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.
# 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:
# 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)
)
