Insights · findings from the joined data
What NSW open data shows when you line it up.
We joined Valuer General sales, BOCSAR crime, the Census and SEIFA, rental bonds, hazard maps, school zones, Revenue NSW fines and the ABN register, then asked them plain questions. Here are the answers that held up, each with its method and what it can't tell you.
17findings
1,132suburbs in the standard set
2001–2026sales history
2016–2025crime history
Not financial or property advice.
Ranks, not linesMost numbers here are Spearman correlations (ρ), from −1 to +1. They ask whether suburbs that rank high on one thing tend to rank high on another, which copes with skewed prices better than a straight-line fit.
Partial ρA partial correlation holds other things constant. Distance from Sydney shapes almost everything, so a link that survives "partial on distance" is more interesting than one that doesn't.
Places, not peopleThese are area averages. A finding about suburbs says nothing certain about any household in them, and none of it proves cause and effect.
From the postcode study
More patterns, by postcode
Reported in research notes 07 (NSW postcode correlations) and 13, by postcode. Figures are quoted from those notes.