API Access
Access dataset files directly from scripts, code, or AI agents.
Browse dataset files
API Access
Access dataset files directly from scripts, code, or AI agents.
Each file has a stable URL (r-link) that you can use directly in scripts, apps, or AI agents. These URLs are permanent and safe to hardcode.
Start with these files — they give you everything you need to understand and access the dataset.
- 1. Fetch datapackage.json to inspect schema and resources
- 2. Download data resources listed in datapackage.json
- 3. Read README.md for full context
Data Files
Explore with AInominal-index
| Field | Type | Format | Description |
|---|---|---|---|
| date | date | default | Last day of the reference quarter in ISO 8601 format (YYYY-MM-DD). For example, 2023-09-30 represents Q3 2023. |
| country_code | string | ISO 3166-1 alpha-2 country code or BIS regional aggregate code (e.g. XM = Euro area, XW = World, 4T = Emerging market economies, 5R = Advanced economies). | |
| country | string | Full name of the country or regional aggregate. | |
| price | number | Nominal residential property price index value (base year 2010 = 100). Empty for periods where no data is available. |
Download
Download CSVAbout
- Nominal residential property price index for selected countries and regions at quarterly frequency, base year 2010 = 100.
- Last updated
- 19 May 2026
- Total rows
- ...
- Format
- CSV
- File size
- 292 kB
nominal-year
| Field | Type | Format | Description |
|---|---|---|---|
| date | date | default | Last day of the reference quarter in ISO 8601 format (YYYY-MM-DD). For example, 2023-09-30 represents Q3 2023. |
| country_code | string | ISO 3166-1 alpha-2 country code or BIS regional aggregate code (e.g. XM = Euro area, XW = World, 4T = Emerging market economies, 5R = Advanced economies). | |
| country | string | Full name of the country or regional aggregate. | |
| price | number | Nominal residential property price year-on-year change, in per cent. Empty for periods where no data is available. |
Download
Download CSVAbout
- Nominal residential property price year-on-year percentage changes for selected countries and regions at quarterly frequency.
- Last updated
- 19 May 2026
- Total rows
- ...
- Format
- CSV
- File size
- 274 kB
real-index
| Field | Type | Format | Description |
|---|---|---|---|
| date | date | default | Last day of the reference quarter in ISO 8601 format (YYYY-MM-DD). For example, 2023-09-30 represents Q3 2023. |
| country_code | string | ISO 3166-1 alpha-2 country code or BIS regional aggregate code (e.g. XM = Euro area, XW = World, 4T = Emerging market economies, 5R = Advanced economies). | |
| country | string | Full name of the country or regional aggregate. | |
| price | number | Real residential property price index value (base year 2010 = 100), deflated by the consumer price index. Empty for periods where no data is available. |
Download
Download CSVAbout
- Real residential property price index for selected countries and regions at quarterly frequency, base year 2010 = 100. Deflated by the consumer price index.
- Last updated
- 19 May 2026
- Total rows
- ...
- Format
- CSV
- File size
- 291 kB
real-year
| Field | Type | Format | Description |
|---|---|---|---|
| date | date | default | Last day of the reference quarter in ISO 8601 format (YYYY-MM-DD). For example, 2023-09-30 represents Q3 2023. |
| country_code | string | ISO 3166-1 alpha-2 country code or BIS regional aggregate code (e.g. XM = Euro area, XW = World, 4T = Emerging market economies, 5R = Advanced economies). | |
| country | string | Full name of the country or regional aggregate. | |
| price | number | Real residential property price year-on-year change, in per cent, deflated by the consumer price index. Empty for periods where no data is available. |
Download
Download CSVAbout
- Real residential property price year-on-year percentage changes for selected countries and regions at quarterly frequency. Deflated by the consumer price index.
- Last updated
- 19 May 2026
- Total rows
- ...
- Format
- CSV
- File size
- 272 kB
About this dataset
Residential property price statistics from different countries. Contains property price indicators (real series are the nominal price series deflated by the consumer price index), both in levels and in growth rates. Can be used for property market analysis.
Data
This data comes from Bank For International Settlements BIS. There are several series of data on the BIS site:
- detailed data set. Format: xlsx
- [source of this repo] selected series (nominal and real), available via the BIS SDMX REST API
- long series. Formats: xlsx, csv
- Commercial property price series. Format: xlsx
Here we use Selected series set, reasons are:
- 'Selected series' dataset covers most of the countries
- available via the BIS SDMX API: https://stats.bis.org/api/v2/data/dataflow/BIS/WS_SPP/1.0
- facilitates access for users and enhance comparability.
Data format
Output is four files with different metrics:
data/nominal_index.csvNominal Index, 2010 = 100data/nominal_year.csvNominal Year-on-year changes, in per centdata/real_index.csvReal Index, 2010 = 100data/real_year.csvReal Year-on-year changes, in per cent
Each file structure is like this:
date,country_code,country,price
2012-06-30,PH,Philippines,114.5
2012-06-30,PL,Poland,97.36
2012-06-30,PT,Portugal,88.15
2012-06-30,RO,Romania,84.61
2012-06-30,RS,Serbia,96.48
2012-06-30,RU,Russia,89.81
2012-06-30,SE,Sweden,103.47
Detailed Data Description:
Contains data for 60+ countries and regions at a quarterly frequency (real series are the nominal price series deflated by the consumer price index), both in levels and in growth rates (ie four series per country). These indicators have been selected from the detailed data set to facilitate access for users and enhance comparability. The BIS has made the selection based on the Handbook on Residential Property Prices and the experience and metadata of central banks. An analysis based on these selected indicators is also released on a quarterly basis, with a particular focus on longer-term developments in the May release.
Data quirks
- Dates are the last day of each quarter (e.g.
2023-09-30for Q3 2023). country_codeuses ISO 3166-1 alpha-2 codes for individual countries plus BIS aggregate codes:XM(Euro area),XW(World),4T(Emerging market economies),5R(Advanced economies).- Early rows (roughly pre-1970 for most countries) have an empty
pricefield because source data does not extend that far back; the BIS source file contains columns for all quarters from 1927 onward.
Preparation
You will need python and pip installed to run the data downloading and processing script.
# if you don't have "git" you can download and unzip the datapackage directly from this page.
git clone https://github.com/datasets/house-prices-global.git
python scripts/process.py
Automation
Up-to-date (auto-updates every month) house-prices-global dataset could be found on the datahub.io: https://datahub.io/core/house-prices-global
License
The data source is National sources, Bank for International Settlements ("BIS") Residential Property Price database, https://www.bis.org/statistics/dataportal/pp.htm.
You can use this data following BIS rules (attribution to BIS as source is required):
https://www.bis.org/terms_conditions.htm#Copyright_and_Permissions
https://www.bis.org/terms_statistics.htm