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mrothschild's avatar
mrothschild
Continued Contributor
5 years ago
Solved

Matrix sub-total calculation?

Sample Excel data: https://docs.google.com/spreadsheets/d/1o55R8MKW263heweuKcZPIvEBgyBoC5hL/edit?usp=sharing&ouid=115111367427670973715&rtpof=true&sd=true   The attached file has a pivot table on i...
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  • mrothschild's avatar
    mrothschild
    5 years ago

    Final PBIX File here: https://drive.google.com/file/d/12_k_tO8BdrXV73Lbho_whabGP-jOlasP/view?usp=sharing

     

    Code to create the weighted average measure:

    WAVG Measure = 

VAR DESIRED_ROWS = 
    FILTER(
        'Table',
        'Table'[Column1] > 0      &&
        'Table'[Attribute (from a PowerQuery unpivot] = "attribute1 selected"  ||
        'Table'[Attribute (from a PowerQuery unpivot] = "attribute2 selected"  ||
        'Table'[Attribute (from a PowerQuery unpivot] = "attribute3 selected"  ||
    )

RETURN
    DIVIDE(
            SUMX (
                DESIRED_ROWS,
                'Table'[Denominator Column] * 'Table'[Value]
            ),
            SUMX (
                DESIRED_ROWS,
                'Table'[Denominator Column]
            )
    )

     

    Code to generate Matrix values from a weighted average measure:

    _A = 

// Note - below one can use any of the *X DAX functions, such as SUMX, AVERAGEX, MEDIANX, STDEVX.S, etc.
       
VAR OUTPUT =     
            AVERAGEX(
                SUMMARIZE (
                        ALLSELECTED('Table'),
                        'Table'[Row Column]
                    )
                , [WAVG Measure]
            )
        
RETURN
    OUTPUT

     

    Code to summarize the Matrix value [measure]

    _A Summarized = 

// Choose AVERAGEX or SUMX below depending on one's needs


VAR OUTPUT_CELL = 
    AVERAGEX(
      SUMMARIZE('Table','Table'[Matrix Row Column])
        , [WAVG measure]
    )
RETURN
    OUTPUT_CELL

     

     

mrothschild's avatar
mrothschild
Continued Contributor
5 years ago

lbendlin 

 

Some progress here.  New PBIX file: https://drive.google.com/file/d/1pG3ua4BOWyIJhhh4dOwG9ac8UPWqUsYo/view?usp=sharing

This is a before screenshot

 

 

 

By changing the first above STDVX [measure] to the following by adding ALLNOBLANKROW first thing after summarize

 

 

VAR DEPRECIATION_VOL_OBSERVED =
        
            STDEVX.S(
                SUMMARIZE (
                        ALLNOBLANKROW('Helivalues Transaction History'),
                        'Helivalues Transaction History'[Sale Year]
                    )
                , [Average Annualized Price change (weighted by Model Year Units)]
            )

 

 

 

I get **a** sub-total rather than NaN.  What that subtotal represents isn't entirely apparent, and isn't dynamic across the pivoted columns.  It's summarized as 5.76% for each column and the grand total, rather than the average of what I perceive to be the available data points.

 

 

 

The intended output is for the {A01} pivot tabled-column to produce the average of the pivot table column immediate to its left.  Based on what's shown {A01} should = 5.38% for 2016, 5.73% for 2017, 11.13% for 2018, 6.14% for 2019, and 6.14% for 2020.

lbendlin's avatar
lbendlin
Super User
5 years ago

"produce the average of the pivot table column immediate to its left"

 

Your measure has no idea what that means. "right" and "left" are meaningless unless you can help with an index column, or a guaranteed sort order.