Calculating average values in groups of 3 on most recent entries

[RSip]

Hello,

at this moment I have a table which looks similar to this:

Date               Liters             Group          

2022-08-30    65.22             1                    

2022-08-28    33.12             1                    

2022-08-27    42.29             1                    

2022-08-26    43.69             1                   

2022-08-25    78.22             1                   

2022-08-23    28.79             1                    

2022-08-20    46.58             1                    

2022-08-19    45.27             1                    

2022-08-18    19.62             1   

In my table I filter out 36 most recent records for each group and I am looking for a way to measure average values in 'Liters' column in groups of 3, for instance when we take first 3 rows: (65.22+33.12+42.29)/3=46.88. That way I would get 12 different values from 36 rows. Another problem with this table is that the values are taken from sharepoint and are always receiving new records, but this statistic needs to be done on 36 most recent entries. Filtering by hand is very time consuming, so I am looking for ways to make this automatic.  If anyone has any ideas, how this can be done, your help would be appreaciated.  

[amitchandak · Accepted solution]

@RSip , Create a column rank first

Rank = rankx(filter(Table, [group] = earlier([Group]) ), [Date], , desc, dense)

now you can use filter rank <=3 in measure

or create another column

Sum= AverageX(filter(Table, [group] = earlier([Group]) && [Rank] <=3),[Liters] )

Or create measure like

cnt = countx(filter(allselected(Table),[group] = max([Group])), [Date]) 

Sum= AverageX(filter(Values(Table[group]), [cnt ]<=3),calculate(Sum([Liters])) )

[RSip]

Thank you very much. It solved the problem.