Return a copy of self, with masked values filled with a given value in Numpy



To return a copy of self, with masked values filled with a given value, use the ma.MaskedArray.filled() method. The "fill_value" parameter is the value to use for invalid entries. Can be scalar or non-scalar.

The fill_value is the value to use for invalid entries. Can be scalar or non-scalar. If non-scalar, the resulting ndarray must be broadcastable over input array. Default is None, in which case, the fill_value attribute of the array is used instead.

The method returns a copy of self with invalid entries replaced by fill_value (be it the function argument or the attribute of self), or self itself as an ndarray if there are no invalid entries to be replaced.

Steps

At first, import the required library −

import numpy as np
import numpy.ma as ma

Create an array with int elements using the numpy.array() method −

arr = np.array([[49, 85, 45], [67, 33, 59]])
print("Array...
", arr) print("
Array type...
", arr.dtype)

Get the dimensions of the Array −

print("Array Dimensions...
",arr.ndim)

Create a masked array and mask some of them as invalid −

maskArr = ma.masked_array(arr, mask =[[0, 0, 1], [ 0, 1, 0]])
print("
Our Masked Array
", maskArr) print("
Our Masked Array type...
", maskArr.dtype)

Get the dimensions of the Masked Array −

print("
Our Masked Array Dimensions...
",maskArr.ndim)

Get the shape of the Masked Array −

print("
Our Masked Array Shape...
",maskArr.shape)

Get the number of elements of the Masked Array −

print("
Elements in the Masked Array...
",maskArr.size)

Return a copy of self, with masked values filled with a given value, use the ma.MaskedArray.filled() method. The "fill_value" parameter is the value to use for invalid entries. Can be scalar or nonscalar −

print("
Return Value...
",maskArr.filled(fill_value = 111))

Example

# Python ma.MaskedArray - Return a copy of self, with masked values filled with a given value

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[49, 85, 45], [67, 33, 59]])
print("Array...
", arr) print("
Array type...
", arr.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr.ndim) # Create a masked array and mask some of them as invalid maskArr = ma.masked_array(arr, mask =[[0, 0, 1], [ 0, 1, 0]]) print("
Our Masked Array
", maskArr) print("
Our Masked Array type...
", maskArr.dtype) # Get the dimensions of the Masked Array print("
Our Masked Array Dimensions...
",maskArr.ndim) # Get the shape of the Masked Array print("
Our Masked Array Shape...
",maskArr.shape) # Get the number of elements of the Masked Array print("
Elements in the Masked Array...
",maskArr.size) # To return a copy of self, with masked values filled with a given value, use the ma.MaskedArray.filled() method # The "fill_value" parameter is the value to use for invalid entries. Can be scalar or non-scalar. # If non-scalar, the resulting ndarray must be broadcastable over input array print("
Return Value...
",maskArr.filled(fill_value = 111))

Output

Array...
[[49 85 45]
[67 33 59]]

Array type...
int64

Array Dimensions...
2

Our Masked Array
[[49 85 --]
[67 -- 59]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(2, 3)

Elements in the Masked Array...
6

Return Value...
[[ 49 85 111]
[ 67 111 59]]

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