Forum Discussion
Calculated value filtering on column in matrix
Hi everybody,
Basically I have to make a comparison between incomes and revenues.
The column that I am trying to calculate through a measure is revenues.
I need the value filtered only for the column and not for the row (it is calculated by summarizing the invoice amounts, that are per row).
I need this to make a comparison between every incomes and revenues of the period for every aging range. So, the result that I want to get is the same revenue value per each row filtered only by invoice date (the column). After that, I have created another measure which is the comparison % between the row incomes and the calculated revenue.
I have tried with:
Revenue = CALCULATE (SUM (Payments [Invoice Amount]); ALLSELECTED (Payments)), but I get the result in the screenshot
Revenue = CALCULATE (SUM (Payments [Invoice Amount]); ALLEXCEPT (Payments; Payments [Invoice Date])), but I've obtained the same result.
Do you have any suggestions?
Visual configuration
- Type: Matrix
- Rows: Aging (string)
- Columns: Invoice Date (hierarchical date)
- Values:
- Importo incasso --> Incomes (currency)
- Fatturato --> Revenue (currency measure)
- % Incassato --> Income on revenue (% measure)
This is what I've have obtained:
Thanks to everybody
I've found the solution:
Revenue = CALCULATE(SUM(Payments[Invoice Amount]); ALLEXCEPT(Payments; Payments[Invoice Date].[Year]; Payments[Invoice Date].[Quarter]; Payments[Invoice Date].[Month]; Payments[Invoice Date].[Day]; Payments[Company]))With that also drillthrough works properlyRegards,
6 Replies
Dario87 , As revenue might not have age and might work with invoice date, I would like see how the data is placed
Can you share sample data and sample output.
Hi amitchandak ,
thank you for your fast reply.
Here some sample rows of my dataset:
Id Delay Days Aging Invoice Date (yyyy-MM-dd) Invoice Amount Income 1 2 <=30 2018-01-23 50.00 50.00 2 45 30 <= 60 2017-07-03 34.00 34.00 3 78 60 <= 90 2019-04-21 12.00 12.00 4 5 <= 30 2020-05-03 45.00 5 0 <= 30 2017-09-09 25.00 25.00 And what I expect from my real table is to have 277,478,993.23 for each row of Fatturato 2017, 345,705,749.02 for each row of Fatturato 2018, ... including the total row
Here the result using the simple data set data
Let me know if you need any other information.
Regards,
Dario87 ,
I would suggest you create another date table named 'Calendar' and make relationship between 'Calendar' and 'Payments' table, then create slicer based on the date column in 'Calendar' table and create a measure using dax as below:
Revenue = CALCULATE ( SUM ( Payments[Invoice Amount] ); FILTER ( ALLEXCEPT ( 'Payments'; 'Payments'[Aging] ); 'Payments'[Date] IN VALUES ( 'Calendar'[Date] ) ) )Community Support Team _ Jimmy Tao
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
I've (near) obtained the required result by creating this misure:
Revenue = CALCULATE(SUM(Payments [Invoice Amount]); ALLEXCEPT(Payments; Payments [Invoice Date].[Year]))But if I visualize the grid with column Payments [Invoice Date] at year level, it works properly, when I drill down by column, the Revenue values are bound to [Invoice Date].[Year] so the value doesn't change dynamically.I've tried to set [Date] to ALLEXCEPT but seems that it doesn't have effects.I've found the solution:
Revenue = CALCULATE(SUM(Payments[Invoice Amount]); ALLEXCEPT(Payments; Payments[Invoice Date].[Year]; Payments[Invoice Date].[Quarter]; Payments[Invoice Date].[Month]; Payments[Invoice Date].[Day]; Payments[Company]))With that also drillthrough works properlyRegards,
