Fill Masked values in NumPy array with specified number

Last update on March 26 2025 13:17:14 (UTC/GMT +8 hours)

2. Masked Array Fill

Write a NumPy program that creates a masked array and fills the masked values with a specified number.

Sample Solution:

Python Code:

import numpy as np  # Import NumPy library

# Create a regular NumPy array
data = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])

# Create a mask to specify which values to mask
mask = np.array([False, True, False, True, False, True, False, True, False, True])

# Create a masked array using the regular array and the mask
masked_array = np.ma.masked_array(data, mask=mask)

# Fill the masked values with a specified number (e.g., -1)
filled_array = np.ma.filled(masked_array, fill_value=-1)

# Print the original masked array and the filled array
print("Original Masked Array:")
print(masked_array)

print("\nFilled Array:")
print(filled_array)

Output:

Original Masked Array:
[1 -- 3 -- 5 -- 7 -- 9 --]

Filled Array:
[ 1 -1  3 -1  5 -1  7 -1  9 -1]

Explanation:

• Import NumPy Library:
• Import the NumPy library to handle array operations.
• Create a Regular Array:
• Define a NumPy array with integer values from 1 to 10.
• Define the Mask:
• Create a Boolean mask array where True indicates the values to be masked.
• Create the Masked Array:
• Use “np.ma.masked_array()” to create a masked array from the regular array and the mask.
• Fill Masked Values:
• Use "np.ma.filled()" to replace masked values in the masked array with a specified number (e.g., -1).
• Finally print the original masked array and the filled array to verify the operation.

For more Practice: Solve these Related Problems:

• Write a Numpy program to create a masked array and then fill the masked values with zero.
• Write a Numpy program to fill the masked values of a 2D masked array with the median of the unmasked elements.
• Write a Numpy program to replace masked elements with a user-defined constant in a masked array derived from a random dataset.
• Write a Numpy program to fill a masked array's masked values with the maximum value from its unmasked data.

Python-Numpy Code Editor:

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