# PERCENTILEX.INCDAX Function (Statistical)

Returns the k-th (inclusive) percentile of an expression values in a table.

## Syntax

PERCENTILEX.INC ( <Table>, <Expression>, <K> )
Parameter Attributes Description
Table

Table over which the Expression will be evaluated.

Expression

Expression to evaluate for each row of the table.

K

Desired percentile value in the interval [0,1].

## Return values

Scalar A single variant value.

Percentile value.

## Remarks

PERCENTILEX.INC considers the blank values returned by Expression. This behavior is different from PERCENTILE.INC, which ignores the blank values.

» 1 related article
» 3 related functions

## Examples

```--  PERCENTILEX iterates the table and compute the expression for each row,
--  computing the k-th percentile
EVALUATE
{
( "Average Sales",         AVERAGEX ( Sales, Sales[Quantity] * Sales[Net Price] ) ),
( "Median Sales",          MEDIANX ( Sales, Sales[Quantity] * Sales[Net Price] ) ),
( "Percentile Sales 0.25", PERCENTILEX.INC ( Sales, Sales[Quantity] * Sales[Net Price], 0.25 ) ),
( "Percentile Sales 0.50", PERCENTILEX.INC ( Sales, Sales[Quantity] * Sales[Net Price], 0.50 ) ),
( "Percentile Sales 0.75", PERCENTILEX.INC ( Sales, Sales[Quantity] * Sales[Net Price], 0.75 ) )
}

```
Value1 Value2
Average Sales 305.21
Median Sales 114.21
Percentile Sales 0.25 22.99
Percentile Sales 0.50 114.21
Percentile Sales 0.75 345.60
```--
-- Different handling of blanks between PERCENTILE and PERCENTILEX
-- PERCENTILE ignores blank values
-- PERCENTILEX considers blank values
--
-- MEDIANX corresponds to PERCENTILEX.INC with k=0.50
DEFINE
TABLE SampleDataWithBlanks =
{ BLANK (), BLANK (), BLANK (), 1, 2, 3, 4 }

EVALUATE
{
( "PERCENTILE.INC 0.25", PERCENTILE.INC ( SampleDataWithBlanks[Value], 0.25 ) ),
( "PERCENTILE.INC 0.50", PERCENTILE.INC ( SampleDataWithBlanks[Value], 0.50 ) ),
( "PERCENTILE.INC 0.75", PERCENTILE.INC ( SampleDataWithBlanks[Value], 0.75 ) ),
( "PERCENTILEX.INC 0.25", PERCENTILEX.INC ( SampleDataWithBlanks, SampleDataWithBlanks[Value], 0.25 ) ),
( "PERCENTILEX.INC 0.50", PERCENTILEX.INC ( SampleDataWithBlanks, SampleDataWithBlanks[Value], 0.50 ) ),
( "PERCENTILEX.INC 0.75", PERCENTILEX.INC ( SampleDataWithBlanks, SampleDataWithBlanks[Value], 0.75 ) ),
( "MEDIANX", MEDIANX ( SampleDataWithBlanks, SampleDataWithBlanks[Value] ) )
}

```
Value1 Value2
PERCENTILE.INC 0.25 1.75
PERCENTILE.INC 0.50 2.5
PERCENTILE.INC 0.75 3.25
PERCENTILEX.INC 0.25 (Blank)
PERCENTILEX.INC 0.50 1
PERCENTILEX.INC 0.75 2.5
MEDIANX 1

## Related articles

• Statistical Patterns

DAX includes a few statistical aggregation functions, such as average, variance, and standard deviation. Other typical statistical calculations require you to write longer DAX expressions. Excel, from this point of view, has a much richer language. The Statistical Patterns are a collection of common statistical calculations: median, mode, moving average, percentile, and quartile. » Read more

## Related functions

Other related functions are:

Last update: Jul 12, 2024     » Show contributors

Contributors: Alberto Ferrari, Marco Russo, Ville-Pietari Louhiala, Kenneth Barber

Microsoft documentation: https://docs.microsoft.com/en-us/dax/percentilex-inc-function-dax

# Context Transition

This function performs a Context Transition if called in a Row Context. Click to read more.

# Row Context

This expression is executed in a Row Context. Click to read more.

# Not recommended

The use of this function is not recommended. See Remarks and Related functions for alternatives.

# Not recommended

The use of this parameter is not recommended.

# Deprecated

This function is deprecated. Jump to the Alternatives section to see the function to use.

# Volatile

A volatile function may return a different result every time you call it, even if you provide the same arguments. Click to read more.

# Deprecated

This parameter is deprecated and its use is not recommended.

# DirectQuery compatibility

Limitations are placed on DAX expressions allowed in measures and calculated columns.
The state below shows the DirectQuery compatibility of the DAX function.

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