# percentileDiscOver


The `percentileDiscOver` function calculates the percentile based on the actual numbers in `measure`. It uses the grouping and sorting that are applied in the field wells. The result is partitioned by the specified dimension at the specified calculation level. The `percentileOver` function is an alias of `percentileDiscOver`.

Use this function to answer the following question: Which actual data points are present in this percentile? To return the nearest percentile value that is present in your dataset, use `percentileDiscOver`. To return an exact percentile value that might not be present in your dataset, use `percentileContOver` instead. 

## Syntax


```
percentileDiscOver (
     measure
   , percentile-n
   , [partition-by, …]
   , calculation-level
)
```

## Arguments


 *measure*   
Specifies a numeric value to use to compute the percentile. The argument must be a measure or metric. Nulls are ignored in the calculation. 

 *percentile-n*   
The percentile value can be any numeric constant 0–100. A percentile value of 50 computes the median value of the measure. 

 *partition-by*   
(Optional) One or more dimensions that you want to partition by, separated by commas. Each field in the list is enclosed in \$1 \$1 (curly braces), if it is more than one word. The entire list is enclosed in [ ] (square brackets).

 *calculation-level*   
 Specifies where to perform the calculation in relation to the order of evaluation. There are three supported calculation levels:  
+ PRE\$1FILTER
+ PRE\$1AGG
+ POST\$1AGG\$1FILTER (default) – To use this calculation level, you need to specify an aggregation on `measure`, for example `sum(measure)`.
PRE\$1FILTER and PRE\$1AGG are applied before the aggregation occurs in a visualization. For these two calculation levels, you can't specify an aggregation on `measure` in the calculated field expression. To learn more about calculation levels and when they apply, see [Order of evaluation in Amazon Quick](https://docs.aws.amazon.com/quicksight/latest/user/order-of-evaluation-quicksight.html) and [Using level-aware calculations in Quick](https://docs.aws.amazon.com/quicksight/latest/user/level-aware-calculations.html).

## Returns


The result of the function is a number. 

## Example of percentileDiscOver
Example

The following example helps explain how percentileDiscOver works.

**Example Comparing calculation levels for the median**  
The following example shows the median for a dimension (category) by using different calculation levels with the `percentileDiscOver` function. The percentile is 50. The dataset is filtered by a region field. The code for each calculated field is as follows:  
+ `example = left( category, 1 )` (A simplified example.)
+ `pre_agg = percentileDiscOver ( {Revenue} , 50 , [ example ] , PRE_AGG)`
+ `pre_filter = percentileDiscOver ( {Revenue} , 50 , [ example ] , PRE_FILTER) `
+ `post_agg_filter = percentileDiscOver ( sum ( {Revenue} ) , 50 , [ example ], POST_AGG_FILTER )`

```
example   pre_filter     pre_agg      post_agg_filter
------------------------------------------------------
0            106,728     119,667            4,117,579
1            102,898      95,946            2,307,547
2             97,629      92,046              554,570  
3            100,867     112,585            2,709,057
4             96,416      96,649            3,598,358
5            106,293      97,296            1,875,648
6             97,118      64,395            1,320,672
7             99,915      90,557              969,807
```

**Example The median**  
The following example calculates the median (the 50th percentile) of `Sales` partitioned by `City` and `State`.   

```
percentileDiscOver
(
  Sales, 
  50,
  [City, State]
)
```
The following example calculates the 98th percentile of `sum({Billed Amount})` partitioned by `Customer Region`. The fields in the table calculation are in the field wells of the visual.  

```
percentileDiscOver
(
  sum({Billed Amount}), 
  98,
  [{Customer Region}]
)
```
The following screenshot shows the how these two examples look on a chart.   

![\[alt text not found\]](http://docs.aws.amazon.com/quick/latest/userguide/images/percentilOver-50-98.png)