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mrothschild
Continued Contributor
Continued Contributor

What is the basic DAX equivalent of INDEX MATCH?

For those much more familiar with Excel than PowerBI, I've used the following as an Excel equivalent for a simple way of conducting a weighted average calculation (similar to a simple SUMPRODUCT)

_SUMPRODUCT example = 

VAR _DESIREDROWS =
    FILTER (
        [Table Name],
        [Column of Data to filter on]  > [filter metric]
    )
RETURN
    DIVIDE (
        SUMX (
            _DESIREDROWS,
            [Value] * [Unit weighting]
        ),
        SUMX (
            _DESIREDROWS,
            [Unit weighting]
        )
    )

 

The above portion allows one to filter the data to a certain criteria, and the lower allows to calculate a weighted average, say for a baseball team's batting average.  

 

What would be the equivalent measure for INDEX MATCH?

for example, let's say one had a baseball team of players with a typical matrix of various statistical categories - batting average, home runs, etc.

 

In Excel, the programming would be =INDEX([entire table],MATCH( {player name},[column of player names],0),MATCH ( {statistical category}, [row of statistical categories],0))

 

 

1 ACCEPTED SOLUTION
Greg_Deckler
Super User
Super User

@mrothschild I put together an Excel to DAX translation series which might help:

Excel to DAX Translation - Microsoft Power BI Community


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2 REPLIES 2
Greg_Deckler
Super User
Super User

@mrothschild I put together an Excel to DAX translation series which might help:

Excel to DAX Translation - Microsoft Power BI Community


@ me in replies or I'll lose your thread!!!
Instead of a Kudo, please vote for this idea
Become an expert!: Enterprise DNA
External Tools: MSHGQM
YouTube Channel!: Microsoft Hates Greg
Latest book!:
The Definitive Guide to Power Query (M)

DAX is easy, CALCULATE makes DAX hard...

AH - MAZING!

 

I started learning PowerBI and DAX almost 3 years ago, and how I wished that guide was around when I was first learning - but so happy that I know about it now!  I think it will help me go much further.

 

Thanks

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