Top Suburbs by Hungarian Population — NSW
NSW suburbs with the highest number of Hungarian ancestry residents, ranked by count from Census 2021.
Top Suburbs by Hungarian Population
NSW suburbs with the highest number of Hungarian ancestry residents, ranked by count from Census 2021. — NSW
This list works best when you want to understand where a particular ancestry group has the largest visible footprint in NSW.
High counts usually reflect scale and concentration. They do not automatically mean better affordability, schools, safety, or investment quality.
Use the ranking to find candidate suburbs, then confirm price levels, incomes, schools, transport, and other local tradeoffs on the suburb pages.
This ranking is backed by demographic counts. It is good for finding clusters, not for deciding suburb quality alone.
Use top rows as research leads, then test affordability, services, and evidence depth before shortlisting.
Rankings are strongest when they hand you a shortlist quickly. Compare the top two first, then open suburb detail if the head-to-head result still feels narrow.
- 10#1BurrawangNSW
- 8#2DalwoodNSW
- 8#3Kains FlatNSW
- 8#4MunyablaNSW
- 7#5Clear CreekNSW
- 7#6LowtherNSW
- 6#7ComboyneNSW
- 6#8Taylors ArmNSW
- 5#9Black RangeNSW
- 5#10FaulklandNSW
- 5#11HargravesNSW
- 5#12KillawarraNSW
- 5#13Lade ValeNSW
- 5#14Lower MacdonaldNSW
- 5#15OgunbilNSW
- 5#16Upper Crystal CreekNSW
- 4#17BurrumbuttockNSW
- 4#18Hartley ValeNSW
- 4#19NashuaNSW
- 4#20RossglenNSW
- 4#21Upper Rollands PlainsNSW
- 3#22BarrengarryNSW
- 3#23CootralantraNSW
- 3#24CounteganyNSW
- 3#25CurrabubulaNSW
- 3#26Devils HoleNSW
- 3#27Frogs HollowNSW
- 3#28Giants CreekNSW
- 3#29Good ForestNSW
- 3#30MonakNSW
- 3#31ReidsdaleNSW
- 3#32Rushes CreekNSW
- 3#33Upper ColoNSW
| # ▲ | SUBURB | STATE | COUNT | % OF POP | POP |
|---|---|---|---|---|---|
| 1 | Burrawang | NSW | 10 | 431 | 2.3% |
| 2 | Dalwood | NSW | 8 | 218 | 3.7% |
| 3 | Kains Flat | NSW | 8 | 219 | 3.7% |
| 4 | Munyabla | NSW | 8 | 72 | 11.1% |
| 5 | Clear Creek | NSW | 7 | 115 | 6.1% |
| 6 | Lowther | NSW | 7 | 69 | 10.1% |
| 7 | Comboyne | NSW | 6 | 416 | 1.4% |
| 8 | Taylors Arm | NSW | 6 | 133 | 4.5% |
| 9 | Black Range | NSW | 5 | 230 | 2.2% |
| 10 | Faulkland | NSW | 5 | 106 | 4.7% |
| 11 | Hargraves | NSW | 5 | 300 | 1.7% |
| 12 | Killawarra | NSW | 5 | 178 | 2.8% |
| 13 | Lade Vale | NSW | 5 | 158 | 3.2% |
| 14 | Lower Macdonald | NSW | 5 | 244 | 2.0% |
| 15 | Ogunbil | NSW | 5 | 152 | 3.3% |
| 16 | Upper Crystal Creek | NSW | 5 | 212 | 2.4% |
| 17 | Burrumbuttock | NSW | 4 | 421 | 1.0% |
| 18 | Hartley Vale | NSW | 4 | 84 | 4.8% |
| 19 | Nashua | NSW | 4 | 267 | 1.5% |
| 20 | Rossglen | NSW | 4 | 50 | 8.0% |
| 21 | Upper Rollands Plains | NSW | 4 | 150 | 2.7% |
| 22 | Barrengarry | NSW | 3 | 214 | 1.4% |
| 23 | Cootralantra | NSW | 3 | 107 | 2.8% |
| 24 | Countegany | NSW | 3 | 38 | 7.9% |
| 25 | Currabubula | NSW | 3 | 339 | 0.9% |
| 26 | Devils Hole | NSW | 3 | 10 | 30.0% |
| 27 | Frogs Hollow | NSW | 3 | 117 | 2.6% |
| 28 | Giants Creek | NSW | 3 | 149 | 2.0% |
| 29 | Good Forest | NSW | 3 | 38 | 7.9% |
| 30 | Monak | NSW | 3 | 60 | 5.0% |
| 31 | Reidsdale | NSW | 3 | 121 | 2.5% |
| 32 | Rushes Creek | NSW | 3 | 98 | 3.1% |
| 33 | Upper Colo | NSW | 3 | 48 | 6.3% |
Top Suburbs by Hungarian Population FAQ
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What does this Hungarian ranking show?
This ranking shows NSW suburbs with the highest Hungarian resident counts, based on Census 2021 demographic data.
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Should I choose a suburb just because it ranks highly here?
No. Demographic rankings explain local context, not investment quality by themselves. Use them with price, rent, income, schools, transport, and detail-page evidence before shortlisting.
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Why does QuickProperty show count and percentage of population?
The count shows the size of the local group, while the percentage helps avoid overreading large suburbs that rank highly only because they have more residents overall.
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What is the next step after this demographic ranking?
Open the suburb detail pages for the strongest candidates, save realistic matches to your shortlist, and compare them against affordability and local evidence before making a decision.