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Hello everyone, I need help to calculate 7 Days Rolling Average for missing data.
I have MAIN table with Date, Users, Points, Categories, Subcategories, and Products columns. I also hace Calendar table.
My Measures:
Avg_Point_per_User_per_Day = SUM(MAIN[Points])
/
DISTINCTCOUNT(MAIN[User])
/
DISTINCTCOUNT(MAIN[Date])
7_Days_Rolling_Avarage =
VAR Last_Date = LASTDATE(Calendar[Date].[Date])
VAR RollingAvg =
AVERAGEX (
DATEBETWEEN (Calendar[Date].[Date],
DATEADD (Last_Date, -7,DAY),
Last_Date), [Avg_Point_per_User_per_Day]
RETURN IF (Last_Date > TODAY() , BLANK(), RollingAvg)
The issue that I have is
When I apply Categories to the table, I have some data that do not have data. So, The [7_Days_Rolling_Avarage] returns (47+ 68 + 43 + 49 + 65)/5 ; (68 + 43 + 49 + 65 + 59)/5
What I expect is it would skip the missing date and return (47+ 68 + 43 + 49 + 65 + 59 + 62)/7
I came with another measure
Rolling_7_Days =
VAR Sevendays = CALCULATETABLE ( TOPN (7,
SUMMARIZE (MAIN, MAIN [Date],
“point”, SUM (MAIN [POINTS]) / DISTINCTCOUNT (MAIN [Users])),
MAIN[Date] , DESC),
FILTER (ALL (MAIN[Date]) , MAIN[Date] <= SELECTEDVALUE (MAIN[Date])))
RETURN
SUMX( Sevendays, [points]) / COUTROWS (Sevendays)
This one worked but it took almost 10 minutes to pull out the data.
Please help,
Thank you
Solved! Go to Solution.
Hi @Harry_Tran ,
Try this:
TopN_Rolling_7days 2 =
VAR t =
CALCULATETABLE (
TOPN (
7,
SUMMARIZE (
MAIN,
MAIN[Category],
MAIN[Date],
"Avg_", [Avg_Point_per_User_per_Day]
),
[Date], DESC
),
FILTER ( ALLSELECTED ( MAIN[Date] ), MAIN[Date] <= MAX ( MAIN[Date] ) )
)
RETURN
SUMX ( t, [Avg_] ) / COUNTROWS ( t )
Best regards
Icey
If this post helps, then consider Accepting it as the solution to help other members find it faster.
Hi @Harry_Tran ,
Try this:
TopN_Rolling_7days 2 =
VAR t =
CALCULATETABLE (
TOPN (
7,
SUMMARIZE (
MAIN,
MAIN[Category],
MAIN[Date],
"Avg_", [Avg_Point_per_User_per_Day]
),
[Date], DESC
),
FILTER ( ALLSELECTED ( MAIN[Date] ), MAIN[Date] <= MAX ( MAIN[Date] ) )
)
RETURN
SUMX ( t, [Avg_] ) / COUNTROWS ( t )
Best regards
Icey
If this post helps, then consider Accepting it as the solution to help other members find it faster.
Believe this is duplicated with:
Regards
Miguel Félix
Proud to be a Super User!
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