Create a Masked array with elements greater than a specified value

Last update on April 30 2025 12:54:49 (UTC/GMT +8 hours)

4. Mask Elements Greater Than Specified Value

Write a NumPy program that creates a masked array where all elements greater than a specified value are masked.

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])

# Specify the value above which elements will be masked
threshold_value = 5

# Create a mask where all elements greater than the specified value are masked
mask = data > threshold_value

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

# Print the original array and the masked array
print("Original Array:")
print(data)

print("\nMasked Array (elements > 5 are masked):")
print(masked_array)

Output:

Original Array:
[ 1  2  3  4  5  6  7  8  9 10]

Masked Array (elements > 5 are masked):
[1 2 3 4 5 -- -- -- -- --]

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.

Specify Threshold Value:

Define the threshold value above which elements will be masked (e.g., 5).

Create the Mask:

Create a Boolean mask array where True indicates the values greater than the threshold value.

Create the Masked Array:

Use "np.ma.masked_array()" to create a masked array from the regular array and the mask.

Finally display the original array and the masked array to verify the operation.

For more Practice: Solve these Related Problems:

Write a Numpy program to create a masked array by masking all elements greater than a specified threshold in a 1D array.
Write a Numpy program to mask elements in a 2D array that exceed a given value and then visualize the masked array.
Write a Numpy program to generate a masked array from a random array where elements above the 75th percentile are masked.
Write a Numpy program to mask elements greater than a computed dynamic threshold (e.g., mean plus one standard deviation) in an array.

Go to:

Previous: Compute Mean of a Masked array ignoring Masked values in NumPy.
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Python-Numpy Code Editor:

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