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Return the default fill value for the argument object in Numpy
To return the default fill value for the argument object, use the ma.default_fill_value() method in Python Numpy. The default filling value depends on the datatype of the input array or the type of the input scalar −
| datatype | default |
|---|---|
| bool | True |
| int | 999999 |
| float | 1.e20 |
| complex | 1.e20+0j |
| object | '?' |
| string | 'N/A' |
For structured types, a structured scalar is returned, with each field the default fill value for its type. For subarray types, the fill value is an array of the same size containing the default scalar fill value.
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([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)Create a masked array and mask some of them as invalid −
maskArr = ma.masked_array(arr, mask =[[1, 1, 0], [ 0, 0, 0], [0, 1, 0], [0, 1, 0]])
print("
Our Masked Array...
", maskArr)Get the type of the masked array −
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("
Number of elements in the Masked Array...
",maskArr.size)To return the default fill value for the argument object, use the ma.default_fill_value() method in Python Numpy. The default filling value depends on the datatype of the input array or the type of the input scalar 7minus;
print("
The default fill value...
",np.ma.default_fill_value(maskArr))
Example
# Python ma.MaskedArray - Return the default fill value for the argument object
import numpy as np
import numpy.ma as ma
# Create an array with int elements using the numpy.array() method
arr = np.array([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)
# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[1, 1, 0], [ 0, 0, 0], [0, 1, 0], [0, 1, 0]])
print("
Our Masked Array...
", maskArr)
# Get the type of the masked array
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("
Number of elements in the Masked Array...
",maskArr.size)
# To return the default fill value for the argument object, use the ma.default_fill_value() method in Python Numpy
# The default filling value depends on the datatype of the input array or the type of the input scalar
print("
The default fill value...
",np.ma.default_fill_value(maskArr))Output
Array... [[65 68 81] [93 33 76] [73 88 51] [62 45 67]] Our Masked Array... [[-- -- 81] [93 33 76] [73 -- 51] [62 -- 67]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 3) Number of elements in the Masked Array... 12 The default fill value... 999999
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