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frithjof_v
Community Champion
Community Champion

Average of averages within group

Hi,

 

I am trying to make a measure to calculate the average per city. It shall be the average of the visible values in the "Average of amount" column per city.

 

As shown below:

frithjof_v_0-1716738222079.png

 

I have just hardcoded the values in the rightmost column, to show what I am trying to achieve.

 

How can I make such a measure in DAX?

 

 

 

The data looks like this:

frithjof_v_6-1716735688318.png

 

Thank you! 😀

1 ACCEPTED SOLUTION
frithjof_v
Community Champion
Community Champion

This measure solved it:

 

Avg per city = 
CALCULATE(
    AVERAGEX(
        SUMMARIZE(
            Sales, 
                Sales[City], 
                Sales[Product], 
                "AvgAmount", AVERAGE(Sales[Amount])
        ),
        [AvgAmount]
    ), 
    ALLSELECTED(Sales[Product])
)

 

View solution in original post

4 REPLIES 4
frithjof_v
Community Champion
Community Champion

This measure solved it:

 

Avg per city = 
CALCULATE(
    AVERAGEX(
        SUMMARIZE(
            Sales, 
                Sales[City], 
                Sales[Product], 
                "AvgAmount", AVERAGE(Sales[Amount])
        ),
        [AvgAmount]
    ), 
    ALLSELECTED(Sales[Product])
)

 

HKIndia
Helper I
Helper I

I think, Is this the result you want. I am getting this result without any creating measure you can see in values section in rigtht side changed to average instead of Sum. let me know if it resolved your query 

HKIndia_0-1716737302996.png

 

Thank you @HKIndia,

 

I noticed there was an over-simplification in the sample data. I think that is why the row subtotals gave the seemingly correct answers.

 

However, that was not my intention. I have corrected the sample data now. 

frithjof_v
Community Champion
Community Champion

Here is the sample data in CSV format (semi-colon separated):

 

 

City;Product;Amount
Oslo;Apple;10
Copenhagen;Apple;20
Stockholm;Apple;30
Helsinki;Apple;40
Reykjavik;Apple;50
Oslo;Banana;50
Copenhagen;Banana;40
Stockholm;Banana;30
Helsinki;Banana;20
Reykjavik;Banana;10
Reykjavik;Grape;20
Helsinki;Grape;30
Stockholm;Grape;40
Copenhagen;Grape;50
Oslo;Grape;60
Reykjavik;Orange;5
Helsinki;Orange;10
Stockholm;Orange;15
Copenhagen;Orange;20
Oslo;Orange;25
Oslo;Carrot;5
Copenhagen;Carrot;10
Stockholm;Carrot;15
Helsinki;Carrot;20
Reykjavik;Carrot;25
Oslo;Potato;35
Copenhagen;Potato;45
Stockholm;Potato;55
Helsinki;Potato;65
Reykjavik;Potato;75
Reykjavik;Turnips;10
Helsinki;Turnips;20
Stockholm;Turnips;40
Copenhagen;Turnips;50
Oslo;Turnips;60
Reykjavik;Cauliflower;15
Helsinki;Cauliflower;25
Stockholm;Cauliflower;35
Copenhagen;Cauliflower;45
Oslo;Cauliflower;55
Oslo;Fine;35
Copenhagen;Fine;45
Stockholm;Fine;55
Helsinki;Fine;65
Reykjavik;Fine;75
Oslo;Whole grain;45
Copenhagen;Whole grain;55
Stockholm;Whole grain;65
Helsinki;Whole grain;75
Reykjavik;Whole grain;85
Reykjavik;Rhye;85
Helsinki;Rhye;75
Stockholm;Rhye;65
Copenhagen;Rhye;55
Oslo;Rhye;45
Reykjavik;Oat;75
Helsinki;Oat;65
Stockholm;Oat;55
Copenhagen;Oat;45
Oslo;Oat;55
Reykjavik;Grape;10
Helsinki;Grape;5
Stockholm;Grape;15
Copenhagen;Grape;20
Oslo;Grape;10
Reykjavik;Orange;10
Helsinki;Orange;20
Stockholm;Orange;10
Copenhagen;Orange;30
Oslo;Orange;25
Oslo;Carrot;10
Copenhagen;Carrot;25
Stockholm;Carrot;10
Helsinki;Carrot;25
Reykjavik;Carrot;15
Oslo;Potato;10
Copenhagen;Potato;50
Stockholm;Potato;30
Helsinki;Potato;20
Reykjavik;Potato;10
Reykjavik;Turnips;25

 

 

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