Amazon Redshift will no longer support the use of Python UDFs after June 30, 2026. We will start enforcing it in phases. For more information on the details of Python end of life and migration options, see the [ blog post ](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/) that was published on June 30, 2025. 

# EXP function
<a name="r_EXP"></a>

The EXP function implements the exponential function for a numeric expression, or the base of the natural logarithm, `e`, raised to the power of expression. The EXP function is the inverse of [LN function](r_LN.md). 

## Syntax
<a name="r_EXP-synopsis"></a>

```
EXP(expression)
```

## Argument
<a name="r_EXP-argument"></a>

 *expression*   
The expression must be an `INTEGER`, `DECIMAL`, or `DOUBLE PRECISION` data type. 

## Return type
<a name="r_EXP-return-type"></a>

`DOUBLE PRECISION`

## Example
<a name="r_EXP-example"></a>

The following example uses the TICKIT sample database. For more information, see [Sample database](c_sampledb.md).

Use the EXP function to forecast ticket sales based on a continuous growth pattern. In this example, the subquery returns the number of tickets sold in 2008. That result is multiplied by the result of the EXP function, which specifies a continuous growth rate of 7% over 10 years. 

```
SELECT (SELECT SUM(qtysold) 
FROM sales, date
WHERE sales.dateid=date.dateid
AND year=2008) * EXP((7::FLOAT/100)*10) qty2018;

+-------------------+
|      qty2018      |
+-------------------+
| 695447.4837722216 |
+-------------------+
```