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Calculating Percentage within a Row

Hi all,


I am working on a POP&L that displays a dollar value by customer (row) and account number (column) and I want to include a column that calculates percent of net revenue (dollar value/net revenue). The accounts are broken out by category, so a customer's net revenue represents the sum of values in that customer's revenue category. The net revenue measure needs to ignore the column it is in because it should always sum the revenue category, but it should take into account the row it is in (customer) and any explicit filters applied.


ALLSELECTED() retains only explicit filters and ALLEXCEPT() retains the row filter, but I am having trouble combining them. I tried using an inner join to combine the commands, but the result usually only applies one of the commands.


Net Revenue by Customer  = CALCULATE(SUM([Amount]), FILTER(NATURALINNERJOIN(ALLEXCEPT('GL Entries', 'GL Entries'[Customer]), ALLSELECTED('GL Entries'), 'GL Entries'[Account Category] = "Revenue"))


I am looking for a formula for Net Revenue by Customer, where [% Net] = DIVIDE([Amount], [Net Revenue by Customer]). One way to know if it is working correctly is if the percent of net revenue in the total of the revenue column is 100%.


Any ideas?



GL Entries              
 CategoryRevenue     COGS     Total 
Account5100 - Sales 5200 - Returns Total 6100 - Purchases 6200 - Expenses Total   
CustomerAmount% NetAmount% NetAmount% NetAmount% NetAmount% NetAmount% NetAmount% Net
Cust 1$2000103%-$50-3%$1950100%-$1000-51%-$500-26%-$1500-77%$45023%
Cust 2$3000100%$00%$3000100%-$2000-67%-$500-17%-$2500-83%$50017%
Cust 3$1000111%-$100-11%$900100%-$400-44%-$550-61%-$950-106%-$50-6%
Cust 4$5000125%-$1000-25%$4000100%-$1000-25%-$2750-69%-$3750-94%$2506%
Cust 5$4000101%-$20-1%$3980100%-$1500-38%-$2000-50%-$3500-88%$48012%


Super User
Super User

@ratgdillon Not really enough information to go on, please first check if your issue is a common issue listed here:

Also, please see this post regarding How to Get Your Question Answered Quickly:

The most important parts are:
1. Sample data as text, use the table tool in the editing bar
2. Expected output from sample data
3. Explanation in words of how to get from 1. to 2.

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