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Hi, Im new in powerBi and Im working in some datat wherein I need to calculate per row with multiple colums.
at 1 row for example, i have data like 1.00 1.25 2.00 3.00 4.50 5.00
now i have to add this, manually i can do it by saying column a + column b.... etc. but i dont know how to compute via sum
i tried sumx but i have error that says - The expression refers to multiple columns. Multiple columns cannot be converted to a scalar value.
thanks for the help.
Solved! Go to Solution.
Have you tried the proper syntax using SUMX?
MeassureName = SUMX(TableName, TableName[column a] +TableName[column b] +TableName[column c] ...)
That should do the trick.
Br,
Magnus
This tutorial shows an example of how to do so: https://www.statology.org/power-bi-sum-multiple-columns/
You can find the solution in the below link
https://community.powerbi.com/t5/Desktop/SUM-row-by-row/m-p/22938#M7278
Thank you Thiyags.
I actually have used that manual iteration but am looking for some sum formula.
would like also to do similar calculation like standard deviation by row, etc.
Have you tried the proper syntax using SUMX?
MeassureName = SUMX(TableName, TableName[column a] +TableName[column b] +TableName[column c] ...)
That should do the trick.
Br,
Magnus
I have tried this formula but its showing over all value in every cell of that column
Calculate(SUMX(TableName, TableName[column a] +TableName[column b] +TableName[column c] ...) thias would work
Yes its work for me when i used dax like below
Hi,
The same syntax i used for summing up the data in my table, but it is summing up data of individual column first and then adding to summed up data of another column.
Please Suggest any solution if you have on this.
In addition to Magnus' correct recommendation, you may also like to consider unpivoting your data into a single column of values.
ID, A, B, C, D, E
1, 5, 7, 5, 6, 3
2, 3, 9, 2, 6, 4
Is better stored like this
ID, Type, Value
1, A, 5
1, B, 7
1, C, 5
1, D, 6
1, E, 4
2, A, 3
2, B, 9
2, C, 2
2, D, 6
2, E, 4
This second design will be much more performant and compressed. You can then also use a simple SUM(Table[Value])
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