distinct labels in a column used to sum values in another column then divided by a distinct count

[TheDrDetroit]

I have a column that has 3 different labels (FTE, Contractor, TBD). 

I need to sum numeric values in another column (capacity utilization) that are specific to each of the 3 labels.  Total FTE utilization, etc.  

Then I need to divide the summed FTE utilization by a distinct count in another column.  I'm stuck and need help. 

[speedramps]

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[TheDrDetroit]

Thanks for the clarifying question.

I have a column (A) that has three possible labels (FTE, Contractor, TBD).

I have another column (B) that has values from 0.0 to 1.0 (capacity utilization rates).

I have another column with FTE names (C).

I need to get an average of FTE utilization rates.

This is complicated because the same FTE name can be listed more than once.

[speedramps]

We want to help you but your description is too vaugue. Please write it again clearly.

Please just give a simple non technical functional decscription of what you want, then let us suggest the solution. Thank you.

Provide example input data as table text (not a screen print) so we can import the data to build a solution for you.
Also provide the example desired output, with a clear description of the process flow.
Remember not to share private data ... we don't want you to get into trouble. 😧
Take time and care to use the same table and field names in the input, output and description so we can understand your problem and help you.
Try keep it simple and ask one question per ticket.
You will get a quick response if you put time, care and effort into writing clear problem descriptions.

Vaugue descriptions can waste your time and ourtime.

Look foward to helping you when the above information is forthcoming

[TheDrDetroit]

I have a list in sharepoint, please see the image below.  I need to calculate the average utilization rate of each FTE.  This is complicated due to the each FTE may be filling more than one role, meaning that their name might be listed more than once.