Check if all elements in NumPy Array are False

This tutorial will discuss about unique ways to check if all elements in numpy array are false.

Table Of Contents

Technique 1: Using numpy.all() method

We can use the numpy.all() method to check if all elements of a NumPy array are False or not.

Compare the NumPy array with a boolean value False, and it will return a NumPy Array of boolean values. A True value in this boolean NumPy Array represents that the corresponding value in the original array is False. Then to confirm if all the values in this boolean array are True or not, pass this boolean array to the numpy.all() method. If it returns True, then it means that all the values in the orignal NumPy array are False.

Let’s see the complete example,

import numpy as np

# Create an example NumPy array of boolean values
arr = np.array([False, False, False, False, False])

# Check if NumPy array contains only False Values
if np.all(arr == False):
    print("All elements in NumPy Array are False")
else:
    print("Not all elements in NumPy Array are False")

Output

All elements in NumPy Array are False

Technique 2: Using numpy.count_nonzero() method

As False in Python evaluates to zero. So, we can call the count_nonzero() method of NumPy module to get the count of non-zero or non-False values in a NumPy Array. If it returns zero, then it means that all the values in NumPy array are False.

Let’s see the complete example,

import numpy as np

# Create an example NumPy array of boolean values
arr = np.array([False, False, False, False, False])

# Check if NumPy array contains only False Values
if np.count_nonzero(arr) == 0:
    print("All elements in NumPy Array are False")
else:
    print("Not all elements in NumPy Array are False")

Output

All elements in NumPy Array are False

Summary

We learned about two different ways to check if all values in a NumPy Array are False or not in Python.