difference between measure with filters applied

[Anonymous]

Hi,

I am trying to calculate the difference for categoryies in the table below. My idea was that once i added up the number propensity added measure and the number propsentiy moved measure i would get the difference. Yet what i get is 0 when i add these 2 measures together. For example I want to get a column that has my excellent for my new table to be 96-54=42, very good being 450-322 = 128 etc. The number of rows here are just a countrow measure which i do not see a way to help me get the difference.

Number Propensity Added = CALCULATE(COUNT(DONOR_TABLE[Propensity Category]),FILTER(DONOR_TABLE,DONOR_TABLE[Propensity Category] <> DONOR_TABLE[Propensity Category Old]))+0

Number propensity Removed =

-CALCULATE(COUNT(DONOR_TABLE[Propensity Category Old]),FILTER(DONOR_TABLE,DONOR_TABLE[Propensity Category]<>DONOR_TABLE[Propensity Category Old]))+0

Any help is much appreciated!

[Whitewater100]

Hi:

Do you have a data model or just a table? Depending on that this maneuveur can be three measures:

New Total = SUM(Table[Donor Added])

Old Total = SUM(TableName[Donor Removed])

Change = [New Total] - [Old Total]) 

If you want to share sample data in pbix or excel, please do. Thanks..

[Anonymous]

Hi:

Both the donor added and donor removed are measures and they can not be manipulated by the sum function. The way that i created these 2 measures are in the description. 

Sadly i can not share data, as it is confidential.