Average of multiple measures

[Anonymous]

Currently I use 3 measures to calculate an average percentage using a (x+y+z)/3 method. 

The problem I have however is that there will be no values for one of the measures in some instances but the total will still be divided by three.

Is there a formula that I can use to calculate the average of the three measures whilst ignoring any measures that contain no values?

[Proday83]

I have to say thanks too!

[PowerBI_NuB]

Thanks for your help. This saved me a ton of time. 

[AlB]

Hi @Anonymous 

Something like

Measure =
VAR Count_ =
    [Measure1] <> BLANK () + [Measure2] <> BLANK () + [Measure3] <> BLANK ()
    // Check how many are non-blank
RETURN
    DIVIDE ( [Measure1] + [Measure2] + [Measure3], Count_ ) // And divide by that count

[Anonymous]

Thank you for your response @AlB 

I have inputed the suggested code however now, when updating the visuals, I recieve the following error:

Do you have any ideas? 

No values in any of the measures or related values are categorised as TRUE/FALSE so I'm lost!

[AlB · Accepted solution]

It's the comparisons that yield the booleans . Cast them to int:

Measure =
VAR Count_ =
    INT ( [Measure1] <> BLANK () )
        + INT ( [Measure2] <> BLANK () )
        + INT ( [Measure3] <> BLANK () )
RETURN
    DIVIDE ( [Measure1] + [Measure2] + [Measure3], Count_ )

or otherwise:

Measure =
VAR Count_ =
    IF ( [Measure1] <> BLANK (), 1, 0 )
        + IF ( [Measure2] <> BLANK (), 1, 0 )
        + IF ( [Measure3] <> BLANK (), 1, 0 )
RETURN
    DIVIDE ( [Measure1] + [Measure2] + [Measure3], Count_ )

[Rober131]

THANK YOU SO MUCH FOR THIS ONE!!!

I didn't ask the question, but this formula definitely came through for me!! 

I was able to take 7 different measures, get an average, and then get an "overall average" of all of them combined!!!

[Cre8]

 You saved my day! THANKS A LOT!

[bibu_]

Awesome, Thanks a ton for this!

[KevinM_CGC]

Thank you for this solution it is exactly what I was looking for...

[mbjerggaard]

Hey, this works great.

Measure =
VAR Count_ =
    INT ( [Measure1] <> BLANK () )
        + INT ( [Measure2] <> BLANK () )
        + INT ( [Measure3] <> BLANK () )
RETURN
    DIVIDE ( [Measure1] + [Measure2] + [Measure3], Count_ )

 But if i want to add the ALL function to this, ignoring filtering - how would that be done?

[AlB]

Hi  Something like

CALCULATE([Measure1], ALL (Table1) )

applied to each of the measures should work. You would need to provide more details for a more accurate answer though

Please mark the question solved when done and consider giving kudos if posts are helpful.

Cheers  

[Anonymous]

Works a charm. 

Thank you for your help.

- Cameron

---

@AlB wrote:

It's the comparisons that yield the booleans . Cast them to int:

Measure =
VAR Count_ =
    INT ( [Measure1] <> BLANK () )
        + INT ( [Measure2] <> BLANK () )
        + INT ( [Measure3] <> BLANK () )
RETURN
    DIVIDE ( [Measure1] + [Measure2] + [Measure3], Count_ )

or otherwise:

Measure =
VAR Count_ =
    IF ( [Measure1] <> BLANK (), 1, 0 )
        + IF ( [Measure2] <> BLANK (), 1, 0 )
        + IF ( [Measure3] <> BLANK (), 1, 0 )
RETURN
    DIVIDE ( [Measure1] + [Measure2] + [Measure3], Count_ )

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