Largest average dviation per product in a column

[sigridr]

Hi, 

I have a (large) table that looks something like this: 

In this random example, the average weight deviations are: 

Product A: +2,2 % // 

Product B: +3,6 % // 

Product C: -0,33 % 

I need a measure to, in this case, pick put "Product B" for the largest average weight deviation. 

Any suggestions? 

Product	Weight	Actual weight	Deviation
Product A			+1 %
Product B			+3,2 %
Product C			+ 0,4 %
Product A			+ 5 %
Product B			+ 2,9 %
Product C			- 0,4 %
Product A			+ 0,6 %
Product B			+ 4,7 %
Product C			-1 %

[v-rongtiep-msft · Accepted solution]

Hi @sigridr ,

Please have a try.

Create measures.

Measure = AVERAGEX(FILTER(ALL('Table'),'Table'[Product]=SELECTEDVALUE('Table'[Product])),'Table'[Weight Actual])

measure2=maxx(all(table),[measure])

Or a column.

column = AVERAGEX(FILTER(ALL('Table'),'Table'[Product]=EARLIER('Table'[Product])),'Table'[Weight Actual])

measure=maxx(all(table),table[column])

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[sigridr]

I think I can do it with this formula: 

MaksProd = VAR MaxAvProd =

 MAX ( 'Table'[AverageWeight] )

RETURN

 CALCULATE (

 SELECTEDVALUE ( 'Table'[ProductName] ),

 'Table'[AverageWeight] = MaxAvProd

 )


But then I just need to create a column with the averages per product (that shows the value 2,2 for each row with product A and so on.. ) 

hmm...

[sigridr]

I tried this: 

Kolonne =

AVERAGEX(

    KEEPFILTERS(VALUES('Table'[ProductName])),

    CALCULATE(AVERAGE('Table'[Weightdifference]))

) 

But then I get a circular dependency issue.... :'(