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I have data like below, part number and various models sold (different rows) , I would like to see parts number vs sum of all models sold, Ex PART Number 7163743 and Sales Population 3418
Part Number : = OPC PN
OPC SN Prefix = Models
Sales Population = Each Model SoLD
This is how I would like to see , parts vs sum of all models sold (= All Population)
Solved! Go to Solution.
Hi,
To your visual, drag OPC PN to the row labels, write this measure and drag it to the visual.
=SUM(Data[Sales population])
Hope this helps.
Hi @santu1021 ,
You could create a measure like the following DAX:
Measure =
CALCULATE ( SUM ( 'Table'[Sales] ), ALLEXCEPT ( 'Table', 'Table'[OPC PN] ) )
Hello. That happened to me and he only showed me the counts.
You can see that in the visualizations that shows it automatically, if they do not generate the sum automatically as you want; It is because the data is not in numerical format. What you should do is go to the data section...
Select the column where you have the numeric data and change the data type
Hi @santu1021 ,
You could create a measure like the following DAX:
Measure =
CALCULATE ( SUM ( 'Table'[Sales] ), ALLEXCEPT ( 'Table', 'Table'[OPC PN] ) )
Your input data and output do not seem to have the relation. The information you have provided is not making the problem clear to me. Can you please explain with an example.
Appreciate your Kudos.
Sorry !! for not being clear on the explanation.
I have huge data, OPC PN Vs Each Individual model sold (= Sales population). See one sample below.
I would like to see them OPC PN Vs Suom of model sold, like below.
Hi,
To your visual, drag OPC PN to the row labels, write this measure and drag it to the visual.
=SUM(Data[Sales population])
Hope this helps.
Can you just put "OPC PN" and default aggregation sum of "Sales - Population" into a table visual and then rename the columns in the visual?
Or are you asking about the 8 year rolling or ?
Thank You !!
I'm not takeing about 8yrs roll-out - ingnore it.
Can you please send screen shots ? It is not clear for me.
Thank You,
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