numpy.any() in Python

numpy.any() checks whether at least one element in an array evaluates to True. It returns a Boolean value or a Boolean array when an axis is specified.

Example: This example checks whether an array contains at least one non-zero value.

import numpy as np
arr = [0, 0, 5]
print(np.any(arr))

True

Explanation: np.any() returns True because the array contains the non-zero value 5.

Syntax

numpy.any(a, axis=None, out=None, keepdims=<no value>, *, where=<no value>)

Parameters:

• a: Input array or array-like object.
• axis: Axis along which the elements are evaluated. By default, all elements are checked.
• out (Optional): array where the result is stored.
• keepdims: If True, keeps the reduced axes in the result with size one.
• where (Optional): condition that specifies which elements are included.

Examples

Example 1: This example checks whether at least one value in a Boolean array is True.

import numpy as np
arr = [False, False, True]
print(np.any(arr))

True

Explanation: np.any(arr) returns True because the array contains one True value. 

Example 2: This example checks the values column-wise by setting axis=0.

import numpy as np
arr = np.array([[0, 1], [0, 0]])
print(np.any(arr, axis=0))

[False  True]

Explanation: axis=0 makes np.any() evaluate each column. The first column contains only zeros, while the second column contains 1.

Example 3: This example checks whether any value in the array is greater than 10.

import numpy as np
arr = np.array([4, 7, 12, 3])
print(np.any(arr > 10))

True

Explanation: arr > 10 creates a Boolean array and np.any() returns True because 12 satisfies the condition.