Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more
Hi
I have GDP data per country, and would like to calculate the weight each country within a Geographic Group has, and then multiply the wieghts to corresponding scores per country, ultimately get a weighted average score per Geographic Group. How do I calculate the weights in a table (table view)? I thought about using
Thanks!
Solved! Go to Solution.
Hi @wsspglobal ,
You may create column or measure like DAX below to get weighted rate.
Measure: Weighted rate= DIVIDE(SUM(Table1[GDP]),CALCULATE(SUM(Table1[GDP]),ALL(Table1))) Column: Weighted rate= DIVIDE(CALCULATE(COUNT(Table1[GDP]),FILTER(ALLSELECTED(Table1),Table1[Country]=EARLIER(Table1[Country])&&Table1[Geographic Group]=EARLIER(Table1[Geographic Group]))),SUM(Table1[GDP]))
Best Regards,
Amy
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @wsspglobal ,
Does that make sense? If so, kindly mark my answer as a solution to help others having the similar issue and close the case. If not, let me know and I'll try to help you further.
Best regards
Amy
Hi @wsspglobal ,
You may create column or measure like DAX below to get weighted rate.
Measure: Weighted rate= DIVIDE(SUM(Table1[GDP]),CALCULATE(SUM(Table1[GDP]),ALL(Table1))) Column: Weighted rate= DIVIDE(CALCULATE(COUNT(Table1[GDP]),FILTER(ALLSELECTED(Table1),Table1[Country]=EARLIER(Table1[Country])&&Table1[Geographic Group]=EARLIER(Table1[Geographic Group]))),SUM(Table1[GDP]))
Best Regards,
Amy
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!
Check out the November 2025 Power BI update to learn about new features.
| User | Count |
|---|---|
| 66 | |
| 45 | |
| 42 | |
| 28 | |
| 18 |
| User | Count |
|---|---|
| 200 | |
| 125 | |
| 102 | |
| 69 | |
| 53 |