# Python | Numpy MaskedArray .__ divmod__

` numpy.ma.MaskedArray class ` is a subclass of ndarray for manipulating numeric arrays with missing data. Using Numpy MaskedArray .__ divmod__ we get two arrays, one of which has elements that are divisible by the values ​​provided in the numpy.ma .__ divmod __ () method, and the second — elements that perform a mod operation with the same value as in numpy. .ma .__ divmod __ () method.

Return: Return divmod (self, value).

Example # 1:
In this example, we can see that using the MaskedArray method .__ divmod __ ( ) we get two arrays. One with a division with the value that is passed as a parameter, and the other with the mod values.

 ` # import important module in python ` ` import ` ` numpy as np ` `   # make an array with NumPy ```` gfg = np.ma.array ([ 1 , 2 , 3 , 4 , 5 ] )    # applying the MaskedArray method .__ divmod __ ()   print (gfg .__ divmod __ ( 3 ))  ```

Exit:

` (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 an important module into 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 the MaskedArray method .__ divmod __ () 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 Fals e 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)) `