In Python, NaN stands for **Not a Number**. It’s a special value that represents missing or undefined data. Checking for NaN values in your data is important as NaNs can affect the results of your calculations or cause errors. This tutorial will demonstrate how to check for NaN values in an if condition in Python.

### Imports required

To work with NaN values effectively, we need to import the numpy module in Python.

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import numpy as np |

### Recognizing NaN

The numpy module has a special function, **np.nan**, which creates a NaN value.

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x = np.nan |

### Checking for NaN

In a Python if condition, the numpy function **np.isnan()** checks if a value is NaN.

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if np.isnan(x): print("NaN value found!") |

In the above code snippet, if ‘x’ is NaN, the text “NaN value found!” will be printed.

### A Word of Caution

Be careful to not check for NaN values with `==`

operator in Python because it always returns False.

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if x == np.nan: print("This will not be printed") |

Despite ‘x’ being NaN in the above code, the equality condition `x == np.nan`

is False and nothing is printed.

## Full code

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import numpy as np x = np.nan if np.isnan(x): print("NaN value found!") if x == np.nan: print("This will not be printed") |

## Output

NaN value found!

## Conclusion

Always use the **numpy.isnan()** function to verify NaN values in Python. The `==`

operator isn’t capable of checking NaN values correctly. Thanks for reading, and happy coding!