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Hi Guys, I have data like this:
Company | Category | Sub-Category | Product Name | sales |
ACOMP | FOOD | 1 | A | 1000 |
ACOMP | FOOD | 1 | B | 1500 |
ACOMP | FOOD | 1 | C | 2000 |
ACOMP | FOOD | 2 | D | 3000 |
ACOMP | RETAIL | 2 | E | 2000 |
ACOMP | RETAIL | 2 | F | 1000 |
BCOMP | RETAIL | 3 | G | 1000 |
BCOMP | RETAIL | 3 | H | 5000 |
BCOMP | SERVICE | 4 | I | 2500 |
BCOMP | SERVICE | 4 | J | 1000 |
The case when I put the slicer based on Product name, the value also keep SUM of Product Name.
My Expectation result, when I put the slicer based on Product Name can show SUM of Group in a Card Visual, looks like:
Sorry for my explanation in Excel mode, that's to make it clear enough.
Does someone know how to this calculation in Dax
Thanks in advance for your help.
BR
Solved! Go to Solution.
Hi @tian
I think you need to create an unrelated Product Name table. Then build a slicer by this table and create measures.
Product Name = VALUES('Table'[Product Name])
Measure codes:
% Sub-Category =
VAR _SelectProductName =
SELECTEDVALUE ( 'Product Name'[Product Name] )
VAR _SubCategory =
CALCULATE (
MAX ( 'Table'[Sub-Category] ),
FILTER ( ALL ( 'Table' ), 'Table'[Product Name] = _SelectProductName )
)
VAR _SalesbyGroup =
CALCULATE (
SUM ( 'Table'[sales] ),
FILTER ( ALL ( 'Table' ), 'Table'[Sub-Category] = _SubCategory )
)
VAR _Total =
CALCULATE ( SUM ( 'Table'[sales] ), ALL ( 'Table' ) )
RETURN
DIVIDE ( _SalesbyGroup, _Total )
% Category =
VAR _SelectProductName =
SELECTEDVALUE ( 'Product Name'[Product Name] )
VAR _Category =
CALCULATE (
MAX ( 'Table'[Category] ),
FILTER ( ALL ( 'Table' ), 'Table'[Product Name] = _SelectProductName )
)
VAR _SalesbyGroup =
CALCULATE (
SUM ( 'Table'[sales] ),
FILTER ( ALL ( 'Table' ), 'Table'[Category] = _Category )
)
VAR _Total =
CALCULATE ( SUM ( 'Table'[sales] ), ALL ( 'Table' ) )
RETURN
DIVIDE ( _SalesbyGroup, _Total )
% Company =
VAR _SelectProductName =
SELECTEDVALUE ( 'Product Name'[Product Name] )
VAR _Company =
CALCULATE (
MAX ( 'Table'[Company] ),
FILTER ( ALL ( 'Table' ), 'Table'[Product Name] = _SelectProductName )
)
VAR _SalesbyGroup =
CALCULATE (
SUM ( 'Table'[sales] ),
FILTER ( ALL ( 'Table' ), 'Table'[Company] = _Company )
)
VAR _Total =
CALCULATE ( SUM ( 'Table'[sales] ), ALL ( 'Table' ) )
RETURN
DIVIDE ( _SalesbyGroup, _Total )
Result is as below.
Best Regards,
Rico Zhou
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @tian
I think you need to create an unrelated Product Name table. Then build a slicer by this table and create measures.
Product Name = VALUES('Table'[Product Name])
Measure codes:
% Sub-Category =
VAR _SelectProductName =
SELECTEDVALUE ( 'Product Name'[Product Name] )
VAR _SubCategory =
CALCULATE (
MAX ( 'Table'[Sub-Category] ),
FILTER ( ALL ( 'Table' ), 'Table'[Product Name] = _SelectProductName )
)
VAR _SalesbyGroup =
CALCULATE (
SUM ( 'Table'[sales] ),
FILTER ( ALL ( 'Table' ), 'Table'[Sub-Category] = _SubCategory )
)
VAR _Total =
CALCULATE ( SUM ( 'Table'[sales] ), ALL ( 'Table' ) )
RETURN
DIVIDE ( _SalesbyGroup, _Total )
% Category =
VAR _SelectProductName =
SELECTEDVALUE ( 'Product Name'[Product Name] )
VAR _Category =
CALCULATE (
MAX ( 'Table'[Category] ),
FILTER ( ALL ( 'Table' ), 'Table'[Product Name] = _SelectProductName )
)
VAR _SalesbyGroup =
CALCULATE (
SUM ( 'Table'[sales] ),
FILTER ( ALL ( 'Table' ), 'Table'[Category] = _Category )
)
VAR _Total =
CALCULATE ( SUM ( 'Table'[sales] ), ALL ( 'Table' ) )
RETURN
DIVIDE ( _SalesbyGroup, _Total )
% Company =
VAR _SelectProductName =
SELECTEDVALUE ( 'Product Name'[Product Name] )
VAR _Company =
CALCULATE (
MAX ( 'Table'[Company] ),
FILTER ( ALL ( 'Table' ), 'Table'[Product Name] = _SelectProductName )
)
VAR _SalesbyGroup =
CALCULATE (
SUM ( 'Table'[sales] ),
FILTER ( ALL ( 'Table' ), 'Table'[Company] = _Company )
)
VAR _Total =
CALCULATE ( SUM ( 'Table'[sales] ), ALL ( 'Table' ) )
RETURN
DIVIDE ( _SalesbyGroup, _Total )
Result is as below.
Best Regards,
Rico Zhou
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
@tian , based on what I got
measure = divide(sum(Table[Sales]), calculate(sum(Table[Sales]), all(Table)))
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