In this tutorial, we will look at how to check if an element in a Numpy array is a NaN (not a number) value or not with the help of some examples.

## How to test if an element is NaN or not in a Numpy array?

You can use the `numpy.isnan()`

function to check (element-wise) if values in a Numpy array are NaN or not. The following is the syntax –

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# test for nan - pass scaler value or numpy array np.isnan(a)

If you apply the `numpy.isnan()`

function to a scalar value, it returns a boolean value (True if the value is NaN otherwise False). If you apply it to an array, it returns a boolean array.

## Examples

Let’s now look at some examples of using the above function to test for NaN.

### Example 1 – Check if a value is NaN or not using `numpy.isnan()`

First, let’s pass scaler values to the `numpy.isnan()`

function.

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Let’s create two variables – one containing a NaN value and the other containing a non-Nan value respectively and then apply the `numpy.isnan()`

function on each of these values.

import numpy as np # create two variables a = 21 b = np.nan # check if nan print(np.isnan(a)) print(np.isnan(b))

Output:

False True

We get `False`

as the output for the value `21`

and `True`

as the output for the NaN value.

### Example 2 – Element-wise check for NaN in a Numpy array using `numpy.isnan()`

If you apply the `numpy.isnan()`

function on an array, it will return a boolean array containing with `True`

for values that are NaN and `False`

for the non-Nan values.

Let’s create a 1-D array and apply the `numpy.isnan()`

function to it.

# create a numpy array ar = np.array([1, 2, np.nan, 4, 5, np.nan, np.nan]) # element-wise check for nan value in ar np.isnan(ar)

Output:

array([False, False, True, False, False, True, True])

We get a boolean array as an output. You can see that in the boolean array we get `True`

for NaN values in the original array and `False`

for the other values.

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## Summary

In this tutorial, we looked at how we can use the `numpy.isnan()`

function to check if an element is NaN or not in a Numpy array. Keep in mind that if you pass a scaler value, it returns a boolean value and if you pass a 1-D array it returns a boolean array.

You might also be interested in –

- Numpy – Check If Element is an Infinity or Not
- Check If Two Numpy Arrays are Equal
- Numpy – Set All Zeros to NaN

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