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. 

# PERCENTILE\_DISC window function
<a name="r_WF_PERCENTILE_DISC"></a>

PERCENTILE\_DISC is an inverse distribution function that assumes a discrete distribution model. It takes a percentile value and a sort specification and returns an element from the given set. 

For a given percentile value P, PERCENTILE\_DISC sorts the values of the expression in the ORDER BY clause and returns the value with the smallest cumulative distribution value (with respect to the same sort specification) that is greater than or equal to P. 

You can specify only the PARTITION clause in the OVER clause. 

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

```
PERCENTILE_DISC ( percentile )
WITHIN GROUP (ORDER BY expr)
OVER (  [ PARTITION BY expr_list ]  )
```

## Arguments
<a name="r_WF_PERCENTILE_DISC-arguments"></a>

 *percentile*   
Numeric constant between 0 and 1. Nulls are ignored in the calculation.

WITHIN GROUP ( ORDER BY *expr*)   
Specifies numeric or date/time values to sort and compute the percentile over. 

OVER   
Specifies the window partitioning. The OVER clause cannot contain a window ordering or window frame specification.

PARTITION BY *expr*   
Optional argument that sets the range of records for each group in the OVER clause.

## Returns
<a name="r_WF_PERCENTILE_DISC-returns"></a>

The same data type as the ORDER BY expression in the WITHIN GROUP clause.

## Examples
<a name="r_WF_PERCENTILE_DISC-examples"></a>

The following examples use the WINSALES table. For a description of the WINSALES table, see [Sample table for window function examples](c_Window_functions.md#r_Window_function_example). 

```
SELECT sellerid, qty, PERCENTILE_DISC(0.5) 
WITHIN GROUP (ORDER BY qty) 
OVER() AS MEDIAN FROM winsales;

+----------+-----+--------+
| sellerid | qty | median |
+----------+-----+--------+
| 3        | 10  | 20     |
| 1        | 10  | 20     |
| 1        | 10  | 20     |
| 4        | 10  | 20     |
| 3        | 15  | 20     |
| 2        | 20  | 20     |
| 2        | 20  | 20     |
| 3        | 20  | 20     |
| 1        | 30  | 20     |
| 3        | 30  | 20     |
| 4        | 40  | 20     |
+----------+-----+--------+

SELECT sellerid, qty, PERCENTILE_DISC(0.5) 
WITHIN GROUP (ORDER BY qty) 
OVER(PARTITION BY sellerid) AS MEDIAN FROM winsales;

+----------+-----+--------+
| sellerid | qty | median |
+----------+-----+--------+
| 4        | 10  | 10     |
| 4        | 40  | 10     |
| 3        | 10  | 15     |
| 3        | 15  | 15     |
| 3        | 20  | 15     |
| 3        | 30  | 15     |
| 2        | 20  | 20     |
| 2        | 20  | 20     |
| 1        | 10  | 10     |
| 1        | 10  | 10     |
| 1        | 30  | 10     |
+----------+-----+--------+
```

To find PERCENTILE\_DISC(0.25) and PERCENTILE\_DISC(0.75) for the quantity when partitioned by the seller ID, use the following examples.

```
SELECT sellerid, qty, PERCENTILE_DISC(0.25) 
WITHIN GROUP (ORDER BY qty) 
OVER(PARTITION BY sellerid) AS quartile1 FROM winsales;

+----------+-----+-----------+
| sellerid | qty | quartile1 |
+----------+-----+-----------+
| 4        | 10  | 10        |
| 4        | 40  | 10        |
| 2        | 20  | 20        |
| 2        | 20  | 20        |
| 3        | 10  | 10        |
| 3        | 15  | 10        |
| 3        | 20  | 10        |
| 3        | 30  | 10        |
| 1        | 10  | 10        |
| 1        | 10  | 10        |
| 1        | 30  | 10        |
+----------+-----+-----------+

SELECT sellerid, qty, PERCENTILE_DISC(0.75) 
WITHIN GROUP (ORDER BY qty) 
OVER(PARTITION BY sellerid) AS quartile3 FROM winsales;

+----------+-----+-----------+
| sellerid | qty | quartile3 |
+----------+-----+-----------+
| 3        | 10  | 20        |
| 3        | 15  | 20        |
| 3        | 20  | 20        |
| 3        | 30  | 20        |
| 4        | 10  | 40        |
| 4        | 40  | 40        |
| 2        | 20  | 20        |
| 2        | 20  | 20        |
| 1        | 10  | 30        |
| 1        | 10  | 30        |
| 1        | 30  | 30        |
+----------+-----+-----------+
```