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datasetleo
Helper I
Helper I

Excel - Get & Transform (Power Query) - Moving average grouped data w/ DAX

Hi,

 

Hi, Can someone assist on moving average when data is grouped? below is an example:

looking for moving average on data grouped by "item" column.

 

Thanks!

 

5.png

1 ACCEPTED SOLUTION
v-frfei-msft
Community Support
Community Support

Hi @datasetleo ,

 

We can create a measure as below by DAX.

Measure = 
VAR a =
    CALCULATE (
        SUM ( 'Table'[value] ),
        FILTER ( ALL ( 'Table' ), 'Table'[Monthno] <= MAX ( 'Table'[Monthno] ) ),
        VALUES ( 'Table'[item] )
    )
VAR b =
    CALCULATE (
        COUNTROWS ( 'Table' ),
        FILTER ( ALL ( 'Table' ), 'Table'[Monthno] <= MAX ( 'Table'[Monthno] ) ),
        VALUES ( 'Table'[item] )
    )
RETURN
    DIVIDE ( a, b )

Capture.PNG

 

Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.

View solution in original post

2 REPLIES 2
v-frfei-msft
Community Support
Community Support

Hi @datasetleo ,

 

We can create a measure as below by DAX.

Measure = 
VAR a =
    CALCULATE (
        SUM ( 'Table'[value] ),
        FILTER ( ALL ( 'Table' ), 'Table'[Monthno] <= MAX ( 'Table'[Monthno] ) ),
        VALUES ( 'Table'[item] )
    )
VAR b =
    CALCULATE (
        COUNTROWS ( 'Table' ),
        FILTER ( ALL ( 'Table' ), 'Table'[Monthno] <= MAX ( 'Table'[Monthno] ) ),
        VALUES ( 'Table'[item] )
    )
RETURN
    DIVIDE ( a, b )

Capture.PNG

 

Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.
ImkeF
Super User
Super User

This article describes how to create a rolling sum, just use List.Average instead: https://www.thebiccountant.com/2017/05/29/performance-tip-partition-tables-crossjoins-possible-power... 

Imke Feldmann (The BIccountant)

If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!

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