Data compare to average.

Hi MartaBak ,

Depending on the information you have provided, you can follow these steps below:

1.Add an index column.

2.Add two columns.

IP = 
VAR _1 =
    CALCULATE (
        MIN ( 'Table'[Index] ),
        FILTER ( 'Table', 'Table'[employee] = EARLIER ( 'Table'[employee] ) )
    )
VAR _2 =
    CALCULATE (
        COUNTROWS ( 'Table' ),
        FILTER ( 'Table', 'Table'[employee] = EARLIER ( 'Table'[employee] ) )
    )
RETURN
    IF ( _1 = 'Table'[Index], _2, BLANK () )

% = 
VAR _1 =
    COUNTROWS ( 'Table' )
VAR _2 =
    DISTINCTCOUNTNOBLANK ( 'Table'[employee] )
VAR _3 = _1 / _2
VAR _4 =
    CALCULATE (
        COUNTROWS ( 'Table' ),
        FILTER ( 'Table', 'Table'[employee] = EARLIER ( 'Table'[employee] ) )
    )
VAR _5 = _4 / _3
VAR _6 =
    CALCULATE (
        MIN ( 'Table'[Index] ),
        FILTER ( 'Table', 'Table'[employee] = EARLIER ( 'Table'[employee] ) )
    )
RETURN
    IF ( _6 = 'Table'[Index], _5, BLANK () )

Final output:

You can use the AVERAGEX function in a matrix to calculate the average of non-null data. For example, you can use the following formula to calculate the average of non-null data:

AVERAGE TOTAL =
AVERAGEX (
    FILTER ( 'Table', NOT ( ISBLANK ( 'Table'[Column] ) ) ),
    'Table'[Column]
)

This formula will filter out the null values and then calculate the average of the remaining data.

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Best Regards,

Ada Wang

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