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 nowJuly 7 - July 17 | Round 2 of the Power BI Dataviz World Championships. Don't miss your chance! Learn more
Hello, I have a dataset with separate columns for Country, State, City, and Postal code information as follows:
When I include all these fields under 'location', many countries don't show up (e.g. Japan, United Kingdom, and other countries where my data don't have postal code or state data). When I omit State and postal code information and only include country and city fields, most data points are plotted in the correct location, including those countries with missing state info, but so many of my US data don't get plotted correctly-- e.g. a city in state X gets mapped to state Y, etc. I am not sure how to get around this issue. Is there a way I can include the state field, and for those entries where I have missing state info, force power BI to just consider the city level info? (get the data to show up just as they did when i included only country and city fields? Thanks for your help.
Solved! Go to Solution.
@jscivias I have often found that concatenating this kind of information into a single field and then setting the data category to Place helps resolve a lot of map plotting issues.
@jscivias I have often found that concatenating this kind of information into a single field and then setting the data category to Place helps resolve a lot of map plotting issues.
@Greg_Deckler thanks for the concatenation suggestion, it did solve a bulk of data points that were randomly mis plotted all over the place on the map!
Join us in Barcelona for FabCon and SQLCon, the Fabric, Power BI, SQL, and AI community event. Save €200 with code FABCMTY200.
Join Data Days 2026: 60 days of free live/on-demand sessions, challenges, study groups, and certification opportunities.
| User | Count |
|---|---|
| 29 | |
| 27 | |
| 24 | |
| 24 | |
| 18 |
| User | Count |
|---|---|
| 54 | |
| 50 | |
| 41 | |
| 33 | |
| 25 |