NumPy any()

Summary: in this tutorial, you’ll learn how to use the numpy any() function that returns True if any element in an array evaluates True.

Introduction to the numpy any() function #

The numpy any() function returns True if any element in an array (or along a given axis) evaluates to True.

Here’s the syntax of the any function:

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

In this syntax, a is a numpy array or any object that can be converted to an array e.g., a list.

Typically, the input array contains numbers. In the boolean context, all non-zero numbers evaluate to True while zero evaluates to False. Therefore, the any() function returns True if any number in the array is nonzero or False if all numbers are zero.

NumPy any() function examples #

Let’s take some examples of using the any() function.

1) Using numpy any() function on 1-D array examples #

The following example uses the any() function to test whether any number in an array are non-zero:

import numpy as np

result = np.any([0, 1, 2, 3])
print(result)

Output:

True

The result is True because the array of three non-zero numbers.

import numpy as np


result = np.any(np.array([0, 0]))
print(result)

Output:

False

This example returns False because all numbers in the array are zero. In fact, you can pass any object that can be converted into a list to the any() function. For example:

import numpy as np


result = np.any([0, 0])
print(result)

Output:

False

2) Using numpy any() function with a multidimensional array example #

The following example uses the any() function to test if any elements of a multidimensional array evaluate to True:

import numpy as np

a = np.array([[0, 1], [2, 3]])
result = np.any(a)
print(result)

Output:

True

Also, you can evaluate elements along an axis by passing the axis argument like this:

import numpy as np

a = np.array([
    [0, 0],
    [0, 1]
])
result = np.any(a, axis=0)
print(result)

Output:

[False  True]

And axis-1:

import numpy as np

a = np.array([
    [0, 0],
    [0, 1]
])
result = np.any(a, axis=1)
print(result)

Output:

[False  True]

Summary #

  • Use the numpy any function to test whether any element in an array or along an axis evaluates to True.

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