NumPy: Test whether all elements in an array evaluate to True

NumPy: Array Object Exercise-23 with Solution

Test All Elements are True

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

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

Sample Output:

False                                                                  
True                                                                   
False                                                                  
True

Explanation:

In the above code –

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

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

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

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

Python-Numpy Code Editor:

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