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veranceftw's avatar
veranceftw
Icon for Helper II rankHelper II
6 years ago
Solved

Group By two columns and associate with a third column

 

Hello, I have a sample dataset where:

- One actor belongs to only one Series

- This series repeats itself throughout some episodes with the same Actors

- This actors can score some points 

- I forgot to put in the image, but I also have a third column - season. Series and Episodes should also be grouped by a season

 

I want to know, the points that the whole series actors do per episode, a feature where each actor has the series score per episode. 

 

DEFINE 
VAR __me = all_series_stats[actor]
VAR __ptab =
    SUMMARIZE (
        all_series_stats,
        all_series_stats[series],
        all_series_stats[episode],
        all_series_stats[season],
        "Cnt", SUM ( all_series_stats[points] )
    )

I tried to do this, but I am having some problems associating the result with the correspondent actor

 

Any idea on how to do this?

 

Regards

 

 

  • Fowmy's avatar
    Fowmy
    6 years ago

    veranceftw 

    Add this as a new column in all_series_stats  table.

    Measure = 
    
    CALCULATE(
        SUM ( all_series_stats[points] ),
        ALLEXCEPT(
            all_series_stats,
            all_series_stats[series],
            all_series_stats[episode],
            all_series_stats[season]
        )
    )

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4 Replies

      • Fowmy's avatar
        Fowmy
        Icon for Super User rankSuper User

        veranceftw 

        Add this as a new column in all_series_stats  table.

        Measure = 
        
        CALCULATE(
            SUM ( all_series_stats[points] ),
            ALLEXCEPT(
                all_series_stats,
                all_series_stats[series],
                all_series_stats[episode],
                all_series_stats[season]
            )
        )

        ________________________

        Did I answer your question? Mark this post as a solution, this will help others!.

        Click on the Thumbs-Up icon on the right if you like this reply 🙂

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