# Excel ISNA function

## Summary

The Excel ISNA function is designed to check if a cell contains the #N/A error, which indicates that a value is not available. This function is particularly useful in managing lookup functions like VLOOKUP, HLOOKUP, or MATCH that might return #N/A when they fail to find a match. ISNA enables users to identify #N/A errors specifically, allowing for more refined error handling and data analysis.
##### Syntax
```				```
=ISNA(value)
```
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• value: The cell reference or expression you want to test for the #N/A error
##### Return value
• TRUE if the specified cell or expression results in an #N/A error
• FALSE if it contains any other value or error type

## How to use

ISNA is straightforward to use and can be directly applied to a formula or cell reference to check for the presence of an #N/A error. It’s commonly used in combination with IF to provide alternative results or actions when #N/A errors are detected, improving the clarity and functionality of your spreadsheets.

## Examples

##### Simple ISNA
Detecting #N/A Errors in Lookup Results: To check if a VLOOKUP function results in an #N/A error.
```				```
=ISNA(VLOOKUP(A1, B2:C100, 2, FALSE))

```
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If the VLOOKUP searching for the value in A1 within B2:C100 does not find a match, resulting in an #N/A error, this formula returns TRUE, indicating the presence of the #N/A error.
##### ISNA with Conditional Logic
Providing Custom Messages for #N/A Errors: Using ISNA within an IF statement to handle #N/A errors gracefully.
```				```
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This formula attempts a VLOOKUP and checks for an #N/A error using ISNA. If an #N/A error is detected, it displays “Value not found”; otherwise, it shows the result of the VLOOKUP.
##### ISNA in Data Cleaning
Identifying and Marking #N/A Errors for Review: To flag cells with #N/A errors for further investigation or correction.
```				```
=IF(ISNA(A1), "Check data", A1)
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This applies ISNA to cell A1 and flags it with “Check data” if an #N/A error is found, otherwise displaying the cell’s actual content, aiding in data validation and cleaning processes.