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Hi,
Trying to create a new measure, TotalCount_Sum=39+2= 41.
Me a DAX dummy, can advise what is wrong with below DAX?
TotalCount_Sum = SUMMARIZE(data2 ,Data2[3Station] ,Data2[TotalCount],sum(Data2[TotalCount]) )
Solved! Go to Solution.
Hi @vincentakatoh,
SUMMARIZE function will return a table as the result, it is impossible to store these result in calculated column or measure.
You need to summary these records and return the result.
For example:
TotalCount_Sum = SUMX ( SUMMARIZE ( Data2, Data2[3Station], Data2[TotalCount], "TotalCount", SUM ( Data2[FailCount] ) ), [TotalCount] )
Reference:
Returns a summary table for the requested totals over a set of groups.
Notice: if your data contains any privacy data, please do mask sensitive data before sharing.
Regards,
Xiaoxin Sheng
Im having problems to sum abs error values.
As you can see 2928 is wrong the correct accumulated sum should be 23.968
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You need a name for your column as parameter 4, just enclose it in double quotes.
Can provide example, tried below but no success? Do I need to add as a Column or Measure?
TotalCount_Sum = SUMMARIZE(data2 ,Data2[3Station] ,Data2[TotalCount] ,"TotalCount", sum(Data2[FailCount]) )
I have this working for me:
Table = SUMMARIZE(Cars,Cars[Asset],Cars[Damage],"Sum",SUM(Cars[Column]))
Obviously different data set, but same thing.
Seems like what you have is correct, are you getting an error?
hi @Greg_Deckler,
Yes, Error msg "the expression refers to multiple columns. Multiple columns cannot be converted to a scalar value".
Also attached my sample file. If possible, appreciate if you can correct the dax and upload in link.
Hi @vincentakatoh,
SUMMARIZE function will return a table as the result, it is impossible to store these result in calculated column or measure.
You need to summary these records and return the result.
For example:
TotalCount_Sum = SUMX ( SUMMARIZE ( Data2, Data2[3Station], Data2[TotalCount], "TotalCount", SUM ( Data2[FailCount] ) ), [TotalCount] )
Reference:
Returns a summary table for the requested totals over a set of groups.
Notice: if your data contains any privacy data, please do mask sensitive data before sharing.
Regards,
Xiaoxin Sheng
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