Data compare to average.

[MartaBak]

Hello, 

I have two problems 😞

FIRST I need to compare 'sum of all ID email per employee' with 'all team average'

Table[Data]

employee	DATE	id EMAIL
X	20.02.2024	123456
Y	20.02.2024	123456
Z	20.02.2024	123456
Z	20.02.2024	123456
Z	20.02.2024	123456
Z	20.02.2024	123457
Z	20.02.2024	123458
Z	20.02.2024	123459
X	20.02.2024	123459
X	20.02.2024	123459
Y	20.02.2024	123459
X	20.02.2024	112345
X	20.02.2024	112549
Y	20.02.2024	123584
Z	20.02.2024	123695

example : 

sum of e-mail = 15

amount of employess =3 (X,Y,Z)

ave. email = 15/3=5

x -> 5 emails

y-> 3 emails

z -> 7 emails

employee participation X =5/5 = 100% , Y= 3/5 = 60%, Z=7/5= 140%

Output

EMPLOYEE	lp	%
X	5	100%
Y	3	60%
Z	7	140%
AVERAGE	5	100%

SECOND : I would like the summed average value to be provided in the pivot table for the average calculated in the query above, but only for non-empty records ( I don't want emty records to lower the average )

My output : AVERAGE COUNT WITHOUT non empty records ( below )

	X	Y	Z	AVERAGE	X	Y	Z
01.01.2024	4	9	5	6	67%	150%	83%
02.01.2024	5	5	6	5	94%	94%	113%
03.01.2024	6	8	2	5	113%	150%	38%
04.01.2024	2	2	5	3	67%	67%	167%
05.01.2024	5	5	8	6	83%	83%	133%
06.01.2024	8		3	6	145%	0%	55%
07.01.2024		3	9	6	0%	50%	150%
08.01.2024	6		6	6	100%	0%	100%
09.01.2024	5	2	2	3	167%	67%	67%
10.01.2024	4	4		4	100%	100%	0%
11.01.2024	2	6		4	50%	150%	0%
12.01.2024	6	9		8	80%	120%	0%
AVERAGE WITH ALL RECORDS					89%	86%	75%
AVERAGE COUNT WITHOUT non empty records					97%	103%	101%

[Anonymous · Accepted solution]

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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