Forum Discussion
Help with DAX formula?
Hello,
I have the following table:
Product Period Quantity
Apples Jan 10
Apples Feb 20
....
Oranges Jan 20
Oranges Feb 10
...
And I have this summary table for periods, where I want to see if Apples are greater than oranges for each period.
Period Apples>Oranges?
Jan No
Feb Yes
... ...
Any suggestions on best way to do it?
Thanks.
Anonymous - Well you could put Period in a table visualization along with this measure:
Measure = VAR __Apples = SUMX(FILTER('Table',[Product]="Apples"),[Quantity]) VAR __Oranges = SUMX(FILTER('Table',[Product]="Oranges"),[Quantity]) RETURN IF(__Apples > __Oranges,"Yes","No")
4 Replies
- Greg_DecklerCommunity Champion
Anonymous - Well you could put Period in a table visualization along with this measure:
Measure = VAR __Apples = SUMX(FILTER('Table',[Product]="Apples"),[Quantity]) VAR __Oranges = SUMX(FILTER('Table',[Product]="Oranges"),[Quantity]) RETURN IF(__Apples > __Oranges,"Yes","No") - amitchandakSuper User
Anonymous , Create a measure like
if(calculatet(sum(table[Quantity]), filter(Table, Table[Product] ="Apples")) -calculatet(sum(table[Quantity]), filter(Table, Table[Product] ="Oranges")) >0 , "Yes", "No")
- AnonymousNot applicable
Hi @ Anonymous ,
According to my understanding, you want to specify whether Applesāquantity is greater than Orangesā, right?
You could use the following formula:
Apples>Oranges? = VAR _minus = CALCULATE ( SELECTEDVALUE ( 'Great'[Quantity] ), ALLEXCEPT ( Great, Great[Period] ), 'Great'[Product] = "Apples" ) - CALCULATE ( SELECTEDVALUE ( 'Great'[Quantity] ), ALLEXCEPT ( Great, Great[Period] ), 'Great'[Product] = "Oranges" ) RETURN IF ( _minus > 0, "Yes", "No" )My visualization looks like this:
Is the result what you want? If you have any questions, please upload some data samples and expected output.
Please do mask sensitive data before uploading.
Best Regards,
Eyelyn Qin
- AnonymousNot applicable
Hi Anonymous ,
Did I answer your question ? Please mark my reply as solution. Thank you very much.
If not, please upload some insensitive data samples and expected output.
Best Regards,
Eyelyn Qin