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Sum sold quantity for different prices for a same product SKU
Hello!
I've been asked to display the sold quantity of a product SKU for different price ranges this SKU have been sold.
The problem is that I need to display the different prices in columns, instead of lines. It means that for each Price column I need a corresponding column for the quantity, as shown in the picture below (expected result).
Each product has a same "reference code" that might hold different SKUs and a different "Original Price" (the first price registration).
The data model already holds a field record for each different price the product was sold, with that said I managed to show the different prices using FirstSortedValue by specifying the rank order (1 for Price 1 / 2 for Price 2 / etc.), but I can't make the calculation correspond to the Price X, it either sums everything or it shows only for 1 line if I add FirstSortedValue inside a set analysis.
I assume I have to work with Aggr and Sum. I tried different combinations, but I just can't get it to work.
The closest I got was this, but it only shows the correct value for a single line:
Sum({<NFTipoMovimento = {'Venda'}, PrecoEpoca = {"$(=(FirstSortedValue(Distinct PrecoEpoca, PrecoEpoca, 1)))"} >} [ProdutoQuantidade])
PS:
PrecoEpoca = Different price ranges the product has been sold
ProdutoQuantidade = Units solds
ProdutoReferencia = Reference code (1 level above SKU)
%ProdutoSKU = SKU code
PrecoOriginal = First price registration for that SKU
Any help is appreciated.
SOS
Accepted Solutions


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Perhaps I am misunderstanding your data structure, but if you have a list of sales lines, and each of them has a quantity and a price, wouldn't this be a pivot table with the Price field as the pivot dimension?


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Perhaps I am misunderstanding your data structure, but if you have a list of sales lines, and each of them has a quantity and a price, wouldn't this be a pivot table with the Price field as the pivot dimension?

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Hey!
Thank you for the reply.
It crossed my mind to use a pivot table, but I thought it wouldn't give me the expected result.
I've just played a bit with it and I think it might be the solution indeed.
Thanks for the tip!!!
