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Hi,
I have a simple table like this:
| ID | Cat |
| 1 | A |
| 2 | A |
| 3 | B |
| 4 | C |
| 5 | D |
| 6 | D |
I want to only view the ID's where Cat is double or more in a table, by using a measure as filter on a table.
The result should look like this:
| ID | Cat | Msr |
| 1 | A | 1 |
| 2 | A | 1 |
| 3 | B | 0 |
| 4 | C | 0 |
| 5 | D | 1 |
| 6 | D | 1 |
The following DAX shows the correct COUNT (in total 4 ID's), but when placed on a table, the table is entirely empty. It does not show 1's or 0's per row:
COUNTX(
SUMMARIZE(
NATURALINNERJOIN( --With this JOIN I get back to the Table[ID] level
--This is important because that's the level I want the 1's and 0's to be working.
FILTER(
--Here I get all the Table[Cat] that have been used multiple times.
SUMMARIZE(Table, Table[Cat], "IDs", COUNT(Table[ID]))
,[IDs] > 1
)
,SUMMARIZE(Table, Table[Cat], Klant[ID])
)
,Table[ID]
), 1
)
When I drag this into the example table, the entire table is BLANK.
If I remove the NATURALJOIN and remove the Table[ID] column, it does show me the 1's and 0's, but this is on the level of Table[Cat], I want this to work at the level of Table[ID].
I need a measure instead of a calculated column in this model.
Does anyone have any suggestion how to tackle this?
Kind regards,
Igor
Solved! Go to Solution.
Hi @Titatovenaar2 ,
According to your description, here are my steps you can follow as a solution.
(1) My test data is the same as yours.
(2) We can create a measure.
Measure =
var _Cat = CALCULATE(COUNT('Table'[Cat]),ALLEXCEPT('Table','Table'[Cat]))
return
IF(_Cat > 1,1,0)
(3) Then the result is as follows.
Best Regards,
Neeko Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Titatovenaar2 ,
According to your description, here are my steps you can follow as a solution.
(1) My test data is the same as yours.
(2) We can create a measure.
Measure =
var _Cat = CALCULATE(COUNT('Table'[Cat]),ALLEXCEPT('Table','Table'[Cat]))
return
IF(_Cat > 1,1,0)
(3) Then the result is as follows.
Best Regards,
Neeko Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Works perfect and fast, thanks!
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