Check for Masked elements in NumPy Masked array

Last update on March 26 2025 13:12:59 (UTC/GMT +8 hours)

20. Check for Presence of Masked Elements

Write a NumPy program that creates a masked array and checks if any masked elements are present.

Sample Solution:

Python Code:

import numpy as np
import numpy.ma as ma

# Create a 2D NumPy array of shape (5, 5) with random integers
array_2d = np.random.randint(0, 100, size=(5, 5))

# Define a condition to mask elements less than 20
condition = array_2d < 20

# Create a masked array from the 2D array using the condition
masked_array = ma.masked_array(array_2d, mask=condition)

# Check if any masked elements are present
has_masked_elements = masked_array.mask.any()

# Print the original array, the masked array, and whether any masked elements are present
print('Original 2D array:\n', array_2d)
print('Masked array (values < 20 are masked):\n', masked_array)
print('Any masked elements present?:', has_masked_elements)

Output:

Original 2D array:
 [[52 75 32 47 50]
 [39  1 45 63 62]
 [95 36 75 41 10]
 [40 59 51 76 11]
 [48 27 33 88 94]]
Masked array (values < 20 are masked):
 [[52 75 32 47 50]
 [39 -- 45 63 62]
 [95 36 75 41 --]
 [40 59 51 76 --]
 [48 27 33 88 94]]
Any masked elements present?: True

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Imported numpy.ma as "ma" for creating and working with masked arrays.
• Create 2D NumPy Array:
• Create a 2D NumPy array named array_2d with random integers ranging from 0 to 99 and a shape of (5, 5).
• Define Condition:
• Define a condition to mask elements in the array that are less than 20.
• Create Masked Array:
• Create a masked array from the 2D array using ma.masked_array, applying the condition as the mask. Elements less than 20 are masked.
• Check for Masked Elements:
• Check if any masked elements are present in the masked array using the any method on the mask attribute.
• Finally print the original 2D array, the masked array, and whether any masked elements are present.

For more Practice: Solve these Related Problems:

• Write a Numpy program to check if any elements in a masked array are masked using np.ma.is_masked and report the result.
• Write a Numpy program to verify the presence of masked elements in a 2D masked array and then count them.
• Write a Numpy program to create a masked array and then use logical operations to determine if all elements are unmasked.
• Write a Numpy program to implement a custom function that returns a boolean indicating whether a masked array has any masked entries.

Python-Numpy Code Editor:

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