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
I have a table that contains a customer_id column which a few thousand entries. I have another table that lists a customer_id column of "bad" ID's that I want to filter OUT OF the first table. The end result would be the first table minus any rows of the "bad" customer_id listed in the second table. Help?
Solved! Go to Solution.
There are likely several ways to do this. I would approach it by adding a calculated column to your first table which tests whether the customer_id is within the second table's list:
Good IDs = IF(Table1[customer_id] in VALUES(Table2[bad_ids]), True, False)
You can edit the True and False outputs to be anything you'd like, and slice by "True" to see only those customers without bad IDs.
I actually got it to work using a version of:
FILTER ( Table1, NOT Table1[Id] IN DISTINCT ( Table2[Id] ) )
It's amazing how much you can learn at Power BI when you are dealing with a crappy data source! 🙂 Thanks All!
I actually got it to work using a version of:
FILTER ( Table1, NOT Table1[Id] IN DISTINCT ( Table2[Id] ) )
It's amazing how much you can learn at Power BI when you are dealing with a crappy data source! 🙂 Thanks All!
There are likely several ways to do this. I would approach it by adding a calculated column to your first table which tests whether the customer_id is within the second table's list:
Good IDs = IF(Table1[customer_id] in VALUES(Table2[bad_ids]), True, False)
You can edit the True and False outputs to be anything you'd like, and slice by "True" to see only those customers without bad IDs.
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 21 | |
| 10 | |
| 9 | |
| 4 | |
| 4 |
| User | Count |
|---|---|
| 34 | |
| 31 | |
| 19 | |
| 13 | |
| 10 |