# 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>)`

Code language: Python (python)

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)`

Code language: Python (python)

Output:

`True`

Code language: Python (python)

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)`

Code language: Python (python)

Output:

`False`

Code language: Python (python)

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)`

Code language: Python (python)

Output:

`False`

Code language: Python (python)

### 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)`

Code language: Python (python)

Output:

`True`

Code language: Python (python)

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)`

Code language: Python (python)

Output:

`[False True]`

Code language: Python (python)

And axis-1:

`import numpy as np`

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

Code language: Python (python)

Output:

`[False True]`

Code language: Python (python)

## Summary

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