NumPy: Test whether any array element along a given axis evaluates to True

Last update on March 24 2025 13:39:51 (UTC/GMT +8 hours)

Test Any Element is True

Write a NumPy program to test whether any array element along a given axis evaluates to True.
Note: 0 evaluates to False in python.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library with an alias 'np'
import numpy as np

# Checking if any elements along a specified axis evaluate to True or non-zero
print(np.any([[False,False],[False,False]]))  # Evaluates to False because all elements in the array are False
print(np.any([[True,True],[True,True]]))     # Evaluates to True because at least one element in the array is True

# Checking if any elements in an iterable evaluate to True or non-zero
print(np.any([10, 20, 0, -50]))  # Evaluates to True because at least one element in the list is non-zero and evaluates to True
print(np.any([10, 20, -50]))     # Evaluates to True because all elements in the list are non-zero and evaluate to True

Sample Output:

False                                                                  
True                                                                   
True                                                                   
True

Explanation:

In the above code –

print(np.any([[False,False],[False,False]])): np.any checks if any element of the input array is True. In this case, all elements are False, so the output is False.

print(np.any([[True,True],[True,True]])): np.any checks if any element of the input array is True. In this case, all elements are True, so the output is True.

print(np.any([10, 20, 0, -50])): np.any checks if any element of the input array is non-zero. In this case, there are non-zero elements in the array (10, 20, and -50), so the output is True.

print(np.any([10, 20, -50])): np.any checks if any element of the input array is non-zero. In this case, all elements are non-zero, so the output is True.

For more Practice: Solve these Related Problems:

• Utilize np.any to determine if at least one element in an array evaluates to True.
• Apply np.any along different axes of a multi-dimensional array to observe varying results.
• Create a custom implementation that mimics np.any using vectorized operations.
• Test arrays with mixed data types to ensure proper boolean conversion before applying np.any.

Python-Numpy Code Editor: