Numpy MaskedArray.filled() method - Python

Numpy MaskedArray.filled() method - Python

Last Updated : 26 Mar, 2020

numpy.MaskedArray.filled() function return a copy of self, with masked values filled with a given value. However, if there are no masked values to fill, self will be returned instead as an ndarray.

Syntax : numpy.MaskedArray.filled(self, fill_value = None) Parameters : fill_value : [scalar, optional] The value to use for invalid entries, by default is None. If None, the fill_value attribute of the array is used instead. Return : filled_array : [ndarray] A copy of self with invalid entries replaced by fill_value or self itself as an ndarray if there are no invalid entries to be replaced.

Code #1 :

Python3

# Python program explaining
# numpy.MaskedArray.filled() function

# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma

arr = geek.ma.array([2, 4, 6, 8, 10], mask =[0, 0, 1, 0, 1],
                                          fill_value = -999)
gfg = arr.filled()

print(gfg)

Output :

[   2    4 -999    8 -999]

Code #2 :

Python3

# Python program explaining
# numpy.MaskedArray.filled() function

# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma

arr = geek.ma.array([1, 2, 3, 4, 5], mask =[1, 0, 1, 0, 0], 
                                         fill_value = -999)
gfg = arr.filled()

print(gfg)

Output :

[-999    2 -999    4    5]

Numpy MaskedArray.filled() method - Python

sanjoy_62

Improve

Article Tags :

Practice Tags :

Similar Reads

Python | Numpy getmaskarray() method

With the help of numpy.getmaskarray() method, we can get the masked matrix in the form numpy array which shows masked values by using numpy.getmaskarray() method. Syntax : numpy.getmaskarray(array) Return : Return masked values in the form of numpy array. Example #1 : In this example we can see that

Python | Numpy MaskedArray.__mod__

What is a mask? A boolean array, used to select only certain elements for an operation Python3 # A mask example import numpy as np x = np.arange(5) print(x) mask = (x > 2) print(mask) x[mask] = -1 print(x) Output: [0 1 2 3 4] [False False False True True] [ 0 1 2 -1 -1] numpy.ma.MaskedArray class

Numpy MaskedArray asarray() method | Python

numpy.ma.asarray() function is used when we want to convert input to a masked array of the given data-type. No copy is performed if the input is already a ndarray. If arr is a subclass of MaskedArray, a base class MaskedArray is returned. Syntax : numpy.ma.asarray(arr, dtype=None, order=None) Parame

Python | Numpy MaskedArray.__le__

numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__le__ operator we can find that which element in an array is less than or equal to the value which is provided in the parameter. Syntax: numpy.MaskedArra

Numpy MaskedArray asanyarray() method | Python

numpy.ma.asanyarray() function is used when we want to convert input to a masked array, conserving subclasses. If arr is a subclass of MaskedArray, its class is conserved. No copy is performed if the input is already an ndarray. Syntax : numpy.ma.asanyarray(arr, dtype=None) Parameters : arr : [array

python | Numpy masked_equal() method

With the help of numpy.ma.masked_equal() method, we can get the mask a value that in an array by using numpy.ma.masked_equal() method. Syntax : numpy.ma.masked_equal(array, value) Return : Return the array after removing mask value. Example #1 : In this example we can see that by using numpy.ma.mask

Python | Numpy MaskedArray.__eq__

numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__eq__ operator we can find that which element in an array is equal to the value which is provided in the parameter. Syntax: numpy.MaskedArray.__eq__ Retu

Python | Numpy MaskedArray.__ne__

numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__ne__ operator we can find that which element in an array is not equal to the value which is provided in the parameter. Syntax: numpy.MaskedArray.__ne__

Python | Numpy MaskedArray.__ge__

numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__ge__ operator we can find that which element in an array is greater than or equal to the value which is provided in the parameter. Syntax: numpy.MaskedA

Python | Numpy MaskedArray.__lt__

numpy.ma.MaskedArray class is a subclass of ndarray designed to manipulate numerical arrays with missing data. With the help of Numpy MaskedArray.__lt__ operator we can find that which element in an array is less than the value which is provided in the parameter. Syntax: numpy.MaskedArray.__lt__ Ret