Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
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.
Solved! Go to 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 , 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])) )
Thank you very much. It solved the problem.
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
113 | |
97 | |
85 | |
70 | |
61 |
User | Count |
---|---|
151 | |
121 | |
104 | |
87 | |
67 |