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Anonymous's avatar
Anonymous
Not applicable
2 years ago
Solved

Total column problem

Hello, here is my problem:
In this visual the Total column does not calculate the average of the values, I don't know why.
Here's the DAX code of the measure and the image.

% Rdt Dorage =
Var QteProd = Calculate (SUM(Performance[QteProd]))
Var QteConso = Calculate (SUM(Performance[QteConso]))
Var Result = QteProd / QteConso  
Return
    IF(ISERROR(QteProd) || ISERROR(QteConso) || ISBLANK(QteProd) || ISBLANK(QteConso),
    BLANK(),
    Result
    )

 

Need Help
  • Anonymous's avatar
    Anonymous
    1 year ago

    rajendraongole1 
    Sorry for my response time.
    I solved the problem : 
    - The data is a measure doing a ratio (Qte Prod / Qte Conso) and there was for the 06 May 2024 data for Qte Prod but no data for Qte Conso, so the total take the Qte Prod data from the 06 May in the average calcul of the month (May). 
    This is why it's more than 100%.

3 Replies

  • rajendraongole1's avatar
    rajendraongole1
    Super User
    2 years ago

    Hi Anonymous - Can you please share some sample data for work around?, it helps to analyze and share expections.

  • Anonymous's avatar
    Anonymous
    Not applicable
    2 years ago

    Hi Anonymous 

     

    Here I create a set of sample:

     

    Then add a measure:

    MEASURE =
VAR _vtable =
    SELECTCOLUMNS (
        'Table',
        'Table'[ID],
        'Table'[Value],
        'Table'[tot],
        "_outcome", 'Table'[Value] / 'Table'[tot]
    )
RETURN
    AVERAGEX ( _vtable, [_outcome] )

    The result is as follow:

    (13.33%+46.67%+36.84%+81.82%+42.86%+57.14%+66.67%+8.33%+23.08%)/9 = 41.86%

     

    Best Regards

    Zhengdong Xu
    If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

     

     

  • Anonymous's avatar
    Anonymous
    Not applicable
    1 year ago

    rajendraongole1 
    Sorry for my response time.
    I solved the problem : 
    - The data is a measure doing a ratio (Qte Prod / Qte Conso) and there was for the 06 May 2024 data for Qte Prod but no data for Qte Conso, so the total take the Qte Prod data from the 06 May in the average calcul of the month (May). 
    This is why it's more than 100%.