We compile statistics and geographic data from public sources, municipal map services and automated scripts that collect the underlying data.
2. Processing and indexes
The data is normalised and combined into an index.
3. Updates and transparency
We update our data and methods continuously to make sure the information is current and relevant. You can read more about each measure further down the page.
Data sources by module
Quick facts
Price ranges, services, green spaces and commuting are based on a compilation of official statistics, map data and calculated indexes from our scripts.
Types of housing
The split between houses, tenant-owned apartments (bostadsrätter) and rental apartments is based on official statistics, normalised for each area.
Automatically calculated indexes
Price level
The price index is based on socio-economic signals (income, education, employment) combined with location measures such as green space, public transport, parking and travel times. We calibrate it against current prices and rents in the city and use a Monte Carlo simulation to estimate a typical monthly cost range per square metre (P10/P50/P90).
Green space and nature nearby
The index is based on municipal GIS layers, nature and forest areas from open map data, and access to parks within a reasonable walking distance.
Commuting and public transport
We calculate travel times to important destinations and add how frequent public transport is, with timetables for both weekdays and weekends.
Student life
This indicator combines age structure, type of housing, student housing and travel options to campus.
Family friendliness
Here we combine the share of families with children, the age distribution and household types into a level you can compare between areas.
Parking
Availability and cost are estimated from parking zones, resident permits, car parks and street parking nearby.
Weighted indexes
The collected data is combined into comparable indexes that are updated when new data is available.
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