Data & methodology

Where the data comes from

The starter price figures are compiled from GlobalPropertyGuide, Numbeo, and general public web research. These are reputable aggregators of housing and cost-of-living data, but coverage, collection dates and methodology differ between them — so we treat the combined figures as directional, not authoritative. Per-source attribution and a per-metric "last updated" date are on the roadmap; until then, this page is the provenance record.

What the columns mean

Each location has three figures — the median purchase price of a 1-bedroom, 2-bedroom, and 3-bedroom home, expressed in US dollars. "Median" means the middle of the local market, so it's less skewed by a handful of very cheap or very expensive listings than an average would be.

• 1-bed / 2-bed / 3-bed price — median home-purchase price for that size, in USD.
• vs median — how a city compares to the whole dataset. Across all 400 cities, the median is $182,500 (1-bed), $252,000 (2-bed) and $358,000 (3-bed). A green number means cheaper than that global median; red means pricier.
• Country figures — on the country comparison, each country's number is the median of its cities in the dataset.

USD normalization

All prices are stored and shown in US dollars so cities in different countries are directly comparable. Because currencies move, the dollar figure for a non-US city is a snapshot, not a live conversion. We show full precision in tables ($540,250) and abbreviate in tight UI ($540k).

Caveats — read before you rely on this

• Directional, not a valuation. These medians are for comparing markets at a glance. They are not an appraisal of any specific home.
• Coverage varies. Some countries have many cities in the dataset; others have one. A single-city country reflects only that market.
• Provenance is still being attached. Until full source and date metadata is published per metric, treat figures as a well-informed starting point.
• No cost-of-income context yet. A low price in one country may still be expensive relative to local incomes — that context is coming (see below).

What's coming next

Home prices are the first layer. TrendingCities will expand each city profile with the signals that actually decide where people live:

• Cost of living and local income (so prices are read against earnings)
• Rent alongside purchase prices
• Climate, safety, and job-market signals
• Real city photography
• Per-metric source labels and "last updated" dates throughout

Have a better dataset or a correction? This is v1 and built to be improved.