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Gavin_Shales
Frequent Visitor

Compare an Individual Average against the overall Average

Hi,

 

I am trying to create a visual chart to compare an indivdual average payment against the overall average payment. In this case, in my current data I currently have an AmoutPayable column and a VetName column. I want to be able to see what the average payment is for a specific Vet and compare that against the Average across all Vets.

 

The end goal is to view this in a trend line so that I can see at what stage an Individual vet became higher than the average.

 

I have searched for this answer on the forum but as I am very new to Power BI I was unable to find the solution. Please bare my limited knowledge in mind with your responses.

 

Thank you all very much.

 

 

1 ACCEPTED SOLUTION
v-qiuyu-msft
Community Support
Community Support

Hi @Gavin_Shales,

 

Assume the sample data likes below: 

 

z1.PNG

 

We can create measures: 

 

AvgPerVet = CALCULATE(AVERAGE(Table1[AmoutPayable ]),FILTER(ALL(Table1),'Table1'[VetName]=MAX('Table1'[VetName])))

 

AvgAllVet = CALCULATE(AVERAGE(Table1[AmoutPayable ]),ALL(Table1))

 

Then create a line and clustered column chart below. You can see attached pbix file. 

 

z2.PNG

 

Best Regards,
Qiuyun Yu 

Community Support Team _ Qiuyun Yu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

1 REPLY 1
v-qiuyu-msft
Community Support
Community Support

Hi @Gavin_Shales,

 

Assume the sample data likes below: 

 

z1.PNG

 

We can create measures: 

 

AvgPerVet = CALCULATE(AVERAGE(Table1[AmoutPayable ]),FILTER(ALL(Table1),'Table1'[VetName]=MAX('Table1'[VetName])))

 

AvgAllVet = CALCULATE(AVERAGE(Table1[AmoutPayable ]),ALL(Table1))

 

Then create a line and clustered column chart below. You can see attached pbix file. 

 

z2.PNG

 

Best Regards,
Qiuyun Yu 

Community Support Team _ Qiuyun Yu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

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