w3resource

Convert Masked NumPy array to Regular array with NaN

NumPy: Masked Arrays Exercise-12 with Solution

Write a NumPy program to create a masked array and convert it back to a regular NumPy array, replacing the masked values with NaN.

Sample Solution:

Python Code:

import numpy as np
import numpy.ma as ma

# Create a 2D NumPy array of shape (4, 4) with random integers
array_2d = np.random.randint(0, 100, size=(4, 4)).astype(float)

# Define the condition to mask elements greater than 50
condition = array_2d > 50

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

# Convert the masked array back to a regular NumPy array, replacing masked values with NaN
regular_array_with_nan = masked_array.filled(np.nan)

# Print the original array, the masked array, and the converted array
print('Original 2D array:\n', array_2d)
print('Masked array (elements > 50 are masked):\n', masked_array)
print('Converted array with NaN for masked values:\n', regular_array_with_nan)

Output:

Original 2D array:
 [[43. 64.  0. 39.]
 [74. 96. 79. 66.]
 [14. 14.  1. 85.]
 [17. 65. 98. 76.]]
Masked array (elements > 50 are masked):
 [[43.0 -- 0.0 39.0]
 [-- -- -- --]
 [14.0 14.0 1.0 --]
 [17.0 -- -- --]]
Converted array with NaN for masked values:
 [[43. nan  0. 39.]
 [nan nan nan nan]
 [14. 14.  1. nan]
 [17. nan nan nan]]

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 (4, 4).
    • Converted the array to float type using .astype(float) to ensure compatibility with 'np.nan'.
  • Define Condition:
    • Define a condition to mask elements in the array that are greater than 50.
  • Create Masked Array:
    • Create a masked array from the 2D array using ma.masked_array, applying the condition as the mask. Elements greater than 50 are masked.
  • Convert Masked Array to Regular Array with NaN:
    • Converted the masked array back to a regular NumPy array using the filled method, replacing the masked values with NaN.
  • Print the original 2D array, the masked array, and the converted array with NaN for masked values.

Python-Numpy Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Find indices of Unmasked elements in Masked NumPy array.
Next: Perform Masked multiplication on a Masked array in NumPy.

What is the difficulty level of this exercise?

Test your Programming skills with w3resource's quiz.



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://www.w3resource.com/python-exercises/numpy/convert-masked-numpy-array-to-regular-array-with-nan.php