Learn from the best! Meet the four finalists headed to the FINALS of the Power BI Dataviz World Championships! Register now
Hi,
I have a table in PowerQuery that is built in a following way:
| Name | Primary Cost Center | Secondary Cost Center | Primary FTE | Secondary FTE |
| Employee 1 | CC1 | CC2 | 0.5 | 0.5 |
| Employee 2 | CC1 | 1 |
I would like to have a query showing data in layout like this:
| CC1 | 1.5 |
| CC2 | 0.5 |
Do you have any tips how to do it in a smart way? Do I need to transform the table?
Solved! Go to Solution.
@matal4 try the following
1) Duplicate the tables and call it lets say table2
2) rename primary cost center & primary fte cols to cost center and fte in orig table
3) delete secondary cost center & secondary fte cols from orig table
4) group by fte by cost center in orig table
5) rename secondary cost center & secondary fte cols to cost center and fte in table2
6) delete primary cost center & primary fte cols from table2
7) group by fte by cost center in table2
😎 union these tables which have been grouped by cost center
@matal4 try the following
1) Duplicate the tables and call it lets say table2
2) rename primary cost center & primary fte cols to cost center and fte in orig table
3) delete secondary cost center & secondary fte cols from orig table
4) group by fte by cost center in orig table
5) rename secondary cost center & secondary fte cols to cost center and fte in table2
6) delete primary cost center & primary fte cols from table2
7) group by fte by cost center in table2
😎 union these tables which have been grouped by cost center
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 |
|---|---|
| 57 | |
| 38 | |
| 34 | |
| 18 | |
| 16 |
| User | Count |
|---|---|
| 68 | |
| 67 | |
| 42 | |
| 30 | |
| 26 |