Don't miss your chance to take the Fabric Data Engineer (DP-600) exam for FREE! Find out how by attending the DP-600 session on April 23rd (pacific time), live or on-demand.
Learn moreNext up in the FabCon + SQLCon recap series: The roadmap for Microsoft SQL and Maximizing Developer experiences in Fabric. All sessions are available on-demand after the live show. Register now
I have to write Dax to make a calculated table which should collect all distinct years from date table and create something like this:
2018 2017
2018 2018
2019 2018
2019 2019
2020 2019
2020 2020
2021 2020
2021 2021
Please help, thanks
I want to have a calculated table
Solved! Go to Solution.
Well this was a fun question to answer because I had to think of a strategy to get 2 rows per unique year in the date table.
Anyway, I found a solution for you. I have a date table (DateTable2) from 1/1/2018 till 31/12/2022. THen I create the following calculated table for it:
CalcTable =
VAR _DateTableWIthYears = ADDCOLUMNS(DateTable2, "Year", YEAR([Date]))
VAR _rankedTable = ADDCOLUMNS(_DateTableWIthYears,
"RankWithinYear", RANKX(FILTER(_DateTableWIthYears, [Year] = EARLIER([Year])), [Date]))
VAR _filterTopTwoPerYear = FILTER(_rankedTable, [RankWithinYear] <3)
VAR _addPrevYear = ADDCOLUMNS(_filterTopTwoPerYear, "SecondColumn",
IF([RankWithinYear] = 1, [Year], [Year] -1))
RETURN
SELECTCOLUMNS(_addPrevYear, "Year1", [Year], "Year2", [SecondColumn])This is not optimized but I wrote it like you could easily follow the logic behind it. It results in the following table:
Let me know if this works for you! 🙂
Kind regards
Djerro123
-------------------------------
If this answered your question, please mark it as the Solution. This also helps others to find what they are looking for.
Keep those thumbs up coming! 🙂
Proud to be a Super User!
Hi @JarroVGIT ,
Thanks for the answer.
Even I figured out a way to acheive this.
DateCYPY =
SELECTCOLUMNS (
ADDCOLUMNS (
GENERATEALL (
VALUES ( 'Date'[Year] ),
DATATABLE ( "type", STRING, { { "m" }, { "m-1" } } )
),
"visibleY", IF ( [type] = "m", VALUE ( 'Date'[Year] ), 'Date'[Year] - 1 )
),
"SelectedYear", 'Date'[Year],
"VisibleYear", [visibleY]
)
Well this was a fun question to answer because I had to think of a strategy to get 2 rows per unique year in the date table.
Anyway, I found a solution for you. I have a date table (DateTable2) from 1/1/2018 till 31/12/2022. THen I create the following calculated table for it:
CalcTable =
VAR _DateTableWIthYears = ADDCOLUMNS(DateTable2, "Year", YEAR([Date]))
VAR _rankedTable = ADDCOLUMNS(_DateTableWIthYears,
"RankWithinYear", RANKX(FILTER(_DateTableWIthYears, [Year] = EARLIER([Year])), [Date]))
VAR _filterTopTwoPerYear = FILTER(_rankedTable, [RankWithinYear] <3)
VAR _addPrevYear = ADDCOLUMNS(_filterTopTwoPerYear, "SecondColumn",
IF([RankWithinYear] = 1, [Year], [Year] -1))
RETURN
SELECTCOLUMNS(_addPrevYear, "Year1", [Year], "Year2", [SecondColumn])This is not optimized but I wrote it like you could easily follow the logic behind it. It results in the following table:
Let me know if this works for you! 🙂
Kind regards
Djerro123
-------------------------------
If this answered your question, please mark it as the Solution. This also helps others to find what they are looking for.
Keep those thumbs up coming! 🙂
Proud to be a Super User!
Hi @JarroVGIT ,
Thanks for the answer.
Even I figured out a way to acheive this.
DateCYPY =
SELECTCOLUMNS (
ADDCOLUMNS (
GENERATEALL (
VALUES ( 'Date'[Year] ),
DATATABLE ( "type", STRING, { { "m" }, { "m-1" } } )
),
"visibleY", IF ( [type] = "m", VALUE ( 'Date'[Year] ), 'Date'[Year] - 1 )
),
"SelectedYear", 'Date'[Year],
"VisibleYear", [visibleY]
)
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 9 | |
| 6 | |
| 3 | |
| 2 | |
| 2 |
| User | Count |
|---|---|
| 21 | |
| 14 | |
| 9 | |
| 5 | |
| 5 |