cancel
Showing results for
Did you mean:

Fabric is Generally Available. Browse Fabric Presentations. Work towards your Fabric certification with the Cloud Skills Challenge.

Continued Contributor

## Exclude distinct count with OR

I am trying to write DAX formula with following logic:

Count distinct "ClientID" if one has "Refused" in Consent column,

BUT, if one has "Consented" in Consent column, do not count (exclude) distinct "ClientID".

So, client 69 and 12468 should be excluded from counting.

This is my original DAX:

Refused = CALCULATE (

DISTINCTCOUNT( Table[ClientID] ),
Table[Consent] = "Refused"
)
---------------------------------------------------------------------------
Do  I just subtract like this?

Refused = CALCULATE (

( DISTINCTCOUNT(Table[ClientID] ),
(
( Table[Consent] = "Refused" )
-
(Table[Consent] = "Refused" && Table[Consent] = "Consented" )

)

)

I don't think it works.

I need to find the way to calculate the count ClientID level, not table level.

1 ACCEPTED SOLUTION
Solution Sage

Ok, thanks for clarifying.

``````Refused Not Consented =
VAR Refused =
DISTINCT (
SUMMARIZE (
FILTER ( 'Table', 'Table'[Consent] = "Refused" ),
'Table'[ClientID]
)
)
VAR Consented =
DISTINCT (
SUMMARIZE (
FILTER ( 'Table', 'Table'[Consent] = "Consented" ),
'Table'[ClientID]
)
)
RETURN
COUNTROWS ( EXCEPT ( Refused, Consented ) )``````

Regards

7 REPLIES 7
Solution Sage

Ok, thanks for clarifying.

``````Refused Not Consented =
VAR Refused =
DISTINCT (
SUMMARIZE (
FILTER ( 'Table', 'Table'[Consent] = "Refused" ),
'Table'[ClientID]
)
)
VAR Consented =
DISTINCT (
SUMMARIZE (
FILTER ( 'Table', 'Table'[Consent] = "Consented" ),
'Table'[ClientID]
)
)
RETURN
COUNTROWS ( EXCEPT ( Refused, Consented ) )``````

Regards

Continued Contributor

@Jos_Woolley  Thank you for your help. I am trying to understand the logic here. First, we are  counting all rows that have a word "Refused". Then, we are also counting all rows that have a word "Consented". Is it right? Then, what does the rest of statement mean? I think I understand what 'Except' means, but from what dataset (from all criteria - including others ('Historial', 'Not Eligible', etc.)? Or am I totally off the track? Thank you.

Solution Sage

The first part:

``````VAR Refused =
DISTINCT (
SUMMARIZE (
FILTER ( 'Table', 'Table'[Consent] = "Refused" ),
'Table'[ClientID]
)
)``````

defines the variable 'Refused' as the single-column table comprising the distinct values from the ClientID column for which the Consent column entry is "Refused".

The next variable is similarly defined, though for Consent column entries of "Consented".

The EXCEPT clause then returns a single-column table comprising all Client ID entries from the 'Refused' table which do not appear in the 'Consent' table.

Finally, the number of rows in this last table are counted.

Regards

Continued Contributor

@Jos_Woolley Thank you for your explanation. Now I understand what 'Except' does in DAX.

Solution Sage

You're welcome!

Regards

Solution Sage

Hi,

In the example you give, the only two possible entries in the 'Consent' column are 'Consented' and 'Refused'. As such, you can use:

``````Refused =
DISTINCTCOUNT ( 'Table'[ClientID] )
- CALCULATE (
DISTINCTCOUNT ( 'Table'[ClientID] ),
'Table'[Consent] = "Consented"
)``````

If other entries are in fact possible within the 'Consent' column then please update your post with a more realistic dataset.

Regards

Continued Contributor

@Jos_Woolley Sorry. actually, there are different options for the value in the  "Consent" column (like 'Historial', 'Not Eligible').

Announcements

#### Power BI Monthly Update - November 2023

Check out the November 2023 Power BI update to learn about new features.

#### Fabric Community News unified experience

Read the latest Fabric Community announcements, including updates on Power BI, Synapse, Data Factory and Data Activator.

#### The largest Power BI and Fabric virtual conference

130+ sessions, 130+ speakers, Product managers, MVPs, and experts. All about Power BI and Fabric. Attend online or watch the recordings.

Top Solution Authors
Top Kudoed Authors