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I have 2 tables, Table1 and Table2. I have created 2 table visuals showing the top3 and top5 C_names based on the ID count. Now i need to compare these topN visuals and return only C_names present in table2. In this example this has to be timmy and max.
Table1
Table2
Top3
Top5
Solved! Go to Solution.
@Brighton10 if you have two source table as following
| t1 |
|----|---------|
| ID | C_name |
|----|---------|
| a1 | tim |
| a1 | sarah |
| a2 | sarah |
| a2 | Alaine |
| a2 | max |
| a3 | alex |
| a4 | mike |
| a5 | mike |
| a5 | michael |
| a5 | Timmy |
| a5 | Alaine |
| a6 | Alaine |
| t2 |
|-----|------------|
| ID | C_name |
|-----|------------|
| a1 | Timmy |
| a1 | sarah |
| a2 | Timmy |
| a2 | Alaine |
| a2 | max |
| a2 | max |
| a3 | Timmy |
| a4 | mike |
| a5 | mike |
| a5 | Alaine |
| a5 | Timmy |
| a5 | Alaine |
| a6 | Alaine |
| a7 | unrelated1 |
| a7 | unrelated1 |
| a8 | unrelated2 |
| a8 | unrelated2 |
| a8 | unrelated2 |
| a8 | unrelated2 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a12 | unrelated0 |
and you want explicit measure to return the top5 count of t2[id] that are not in top3 count of t1[id]
They can be achieved as following
Count =
CALCULATE (
COUNT ( t2[ID] ),
CALCULATETABLE (
t2,
EXCEPT (
VALUES ( t2[C_name] ),
SUMMARIZE (
TOPN (
3,
GROUPBY ( t1, t1[C_name], "@X", COUNTX ( CURRENTGROUP (), t1[ID] ) ),
[@X]
),
t1[C_name]
)
)
)
)
t2CountRanking = RANKX(ALL(t2[C_name]),[Count],,DESC,Dense)
and then by applying following visual level filter
This measure actually replicates the following DAX query
Table =
VAR _base =
CALCULATETABLE (
t2,
EXCEPT (
VALUES ( t2[C_name] ),
SUMMARIZE (
TOPN (
3,
GROUPBY ( t1, t1[C_name], "@X", COUNTX ( CURRENTGROUP (), t1[ID] ) ),
[@X]
),
t1[C_name]
)
)
)
VAR _count =
ADDCOLUMNS (
_base,
"Count", CALCULATE ( COUNT ( t2[ID] ), ALLEXCEPT ( t2, t2[C_name] ) )
)
VAR _rank =
FILTER (
ADDCOLUMNS ( _count, "rank", RANKX ( _count, [Count],, DESC, DENSE ) ),
[rank] <= 5
)
RETURN
_rank
The pbix is attached
https://1drv.ms/u/s!AkrysYUHaNRvhcVzAbrcNKeeaU62Dw?e=cmTuJT
@Brighton10 if you have two source table as following
| t1 |
|----|---------|
| ID | C_name |
|----|---------|
| a1 | tim |
| a1 | sarah |
| a2 | sarah |
| a2 | Alaine |
| a2 | max |
| a3 | alex |
| a4 | mike |
| a5 | mike |
| a5 | michael |
| a5 | Timmy |
| a5 | Alaine |
| a6 | Alaine |
| t2 |
|-----|------------|
| ID | C_name |
|-----|------------|
| a1 | Timmy |
| a1 | sarah |
| a2 | Timmy |
| a2 | Alaine |
| a2 | max |
| a2 | max |
| a3 | Timmy |
| a4 | mike |
| a5 | mike |
| a5 | Alaine |
| a5 | Timmy |
| a5 | Alaine |
| a6 | Alaine |
| a7 | unrelated1 |
| a7 | unrelated1 |
| a8 | unrelated2 |
| a8 | unrelated2 |
| a8 | unrelated2 |
| a8 | unrelated2 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a9 | unrelated3 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a10 | unrelated4 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a11 | unrelated5 |
| a12 | unrelated0 |
and you want explicit measure to return the top5 count of t2[id] that are not in top3 count of t1[id]
They can be achieved as following
Count =
CALCULATE (
COUNT ( t2[ID] ),
CALCULATETABLE (
t2,
EXCEPT (
VALUES ( t2[C_name] ),
SUMMARIZE (
TOPN (
3,
GROUPBY ( t1, t1[C_name], "@X", COUNTX ( CURRENTGROUP (), t1[ID] ) ),
[@X]
),
t1[C_name]
)
)
)
)
t2CountRanking = RANKX(ALL(t2[C_name]),[Count],,DESC,Dense)
and then by applying following visual level filter
This measure actually replicates the following DAX query
Table =
VAR _base =
CALCULATETABLE (
t2,
EXCEPT (
VALUES ( t2[C_name] ),
SUMMARIZE (
TOPN (
3,
GROUPBY ( t1, t1[C_name], "@X", COUNTX ( CURRENTGROUP (), t1[ID] ) ),
[@X]
),
t1[C_name]
)
)
)
VAR _count =
ADDCOLUMNS (
_base,
"Count", CALCULATE ( COUNT ( t2[ID] ), ALLEXCEPT ( t2, t2[C_name] ) )
)
VAR _rank =
FILTER (
ADDCOLUMNS ( _count, "rank", RANKX ( _count, [Count],, DESC, DENSE ) ),
[rank] <= 5
)
RETURN
_rank
The pbix is attached
https://1drv.ms/u/s!AkrysYUHaNRvhcVzAbrcNKeeaU62Dw?e=cmTuJT
@Brighton10 , Table1's ID count based on TOP 3 of table 2
calculate(Count(Table1[ID]),filter(Table1, Table1[ID] in TOPN(3, allselected(Table2[ID]),calculate(Count(Table2[ID])),DESC)) )
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