Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowTry your skills in the Power BI Dataviz World Championship! Round one ends June 26. Join now
Hello,
I have two tables with différent type of code, each table has a code, an amount column and a date table.
I want to create a third table wich is a summary of the previous one.
With 5 columns :
- Month
- Countrows of the first table
- Sum of the amount from the first table
- Countrows of the second table
- Sum of the amount from the second table
I created a pbix file in order to give you some view over my datas.
Best regard,
ScrappyS
Solved! Go to Solution.
Add this code to a calulated table:
Table =
NATURALINNERJOIN(
SUMMARIZE(ADDCOLUMNS('Table 1' , "Month_" , MONTH('Table 1'[Month])) , [Month_] , "Countrows T1" , COUNTROWS('Table 1') , "SUM CA T1" , SUM('Table 1'[CA]))
,
SUMMARIZE(ADDCOLUMNS('Table 2' , "Month_" , MONTH('Table 2'[Month])) , [Month_] , "Countrows T2" , COUNTROWS('Table 1') , "SUM CA T2" , SUM('Table 1'[CA]))
)
Br,
J
@Anonymous , you can append merge and group by
https://radacad.com/append-vs-merge-in-power-bi-and-power-query
https://www.poweredsolutions.co/2019/07/30/grouping-rows-with-power-bi-power-query/
Add this code to a calulated table:
Table =
NATURALINNERJOIN(
SUMMARIZE(ADDCOLUMNS('Table 1' , "Month_" , MONTH('Table 1'[Month])) , [Month_] , "Countrows T1" , COUNTROWS('Table 1') , "SUM CA T1" , SUM('Table 1'[CA]))
,
SUMMARIZE(ADDCOLUMNS('Table 2' , "Month_" , MONTH('Table 2'[Month])) , [Month_] , "Countrows T2" , COUNTROWS('Table 1') , "SUM CA T2" , SUM('Table 1'[CA]))
)
Br,
J
Thanks a lot @tex628 , it's work like a charm !
I have just another question : how can i add to my summary table a column wich is the difference between 'table 1'[Sum CA] and 'table 2'[Sum CA] ?
('table 1'[Sum CA] - 'table 2'[Sum CA])
Best regards,
ScrappyS
| User | Count |
|---|---|
| 24 | |
| 22 | |
| 22 | |
| 21 | |
| 13 |
| User | Count |
|---|---|
| 66 | |
| 56 | |
| 45 | |
| 45 | |
| 30 |