Forum Discussion

Anonymous's avatar
Anonymous
Not applicable
7 years ago

Quick measure for a "multivariable" variable

Hi,

 

I have created a measure that can display different variables in the same view by clicking in a filter. However, I have had problems trying to create Quick Measures for this variable like Average, MoM% and others. To give you some context let's go through what I have at the moment:

 

Table

Using this table, I created a workaround to select many variables with one filter. The way to do this was the 

New Table
Measure to use many variables in one graphResult

 

Now, my problem is that I havent found the way to obtain the next calculations using Quick Measures such as Average, MoM%, etc.

 

What I want is a calculation for MoM% and Average as example for this exact problem, that way I could continue to create all the other measures that I need.

 

 

Thanks in advance,

 

IC

3 Replies

  • Anonymous's avatar
    Anonymous
    Not applicable

    Hi Anonymous ,

    I'd like to suggest you do unpivot column on query edit, then you can simply write formula to summary these values based on their category fields.

    Unpivot columns (Power Query)

    If you confused on coding formula, please share some sample data for test.

    Regards,

    Xiaoxin Sheng

    • Anonymous's avatar
      Anonymous
      Not applicable

      That is exactly what I dont want to do. My table has more than 10 million rows and that would make it even bigger. I wanted a visualization where I could have all the variables together as you saw before in order to reduce the size of my table.

       

      I wanted to know if I could apply the quick measure to that calculated measure or not. Could you create a formula/workaround?

       

       

      Thanks in advance,

       

       

      IC

      • Anonymous's avatar
        Anonymous
        Not applicable

        HI Anonymous ,

        Unfortunately, unpivot column features not able apply to measure formulas. You also can't use measure as category to expand detail records.

        Regards, 

        Xiaoxin Sheng