Residential property price statistics from different countries

core

Files Size Format Created Updated License Source
5 6MB csv zip 1 week ago BIS Selected property prices
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 read more
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Data Files

File Description Size Last changed Download Other formats
nominal-index [csv] 301kB nominal-index [csv] nominal-index [json] (772kB)
nominal-year [csv] 296kB nominal-year [csv] nominal-year [json] (768kB)
real-index [csv] 301kB real-index [csv] real-index [json] (773kB)
real-year [csv] 296kB real-year [csv] real-year [json] (768kB)
house-prices-global_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 651kB house-prices-global_zip [zip]

nominal-index  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
date 1 date (%Y-%m-%d)
country 2 string (default)
price 3 string (default)

nominal-year  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
date 1 date (%Y-%m-%d)
country 2 string (default)
price 3 string (default)

real-index  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
date 1 date (%Y-%m-%d)
country 2 string (default)
price 3 string (default)

real-year  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
date 1 date (%Y-%m-%d)
country 2 string (default)
price 3 string (default)

house-prices-global_zip  

This is a preview version. There might be more data in the original version.

Read me

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). Format: xlsx, csv.
  • long series. Formats: xlsx, csv
  • Commercial property price series. Format: xlsx

Here we use Selected series set, reasons are:

Data format

Output is four files with different metrics:

  • data/nominal_index.csv Nominal Index, 2010 = 100
  • data/nominal_year.csv Nominal Year-on-year changes, in per cent
  • data/real_index.csv Real Index, 2010 = 100
  • data/real_year.csv Real Year-on-year changes, in per cent

Each file structure is like this:

date,country,price
2012-06-30,Philippines,114.5
2012-06-30,Poland,97.36
2012-06-30,Portugal,88.15
2012-06-30,Romania,84.61
2012-06-30,Serbia,96.48
2012-06-30,Russia,89.81
2012-06-30,Sweden,103.47

Detailed Data Description:

Contains data for 59 countries 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.

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/global-house-prices.git

cd global-house-prices
pip install tabulator
python scripts/process.py

License

The data source is National sources, Bank for International Settlements (“BIS”) Residential Property Price database, www.bis.org/statistics/pp.htm.
You can use this data following BIS rules:
https://www.bis.org/terms_conditions.htm#Copyright_and_Permissions
https://www.bis.org/terms_statistics.htm

Import into your tool

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/core/house-prices-global/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources$path[1][1]
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/core/house-prices-global/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('http://datahub.io/core/house-prices-global/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'http://datahub.io/core/house-prices-global/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
(async () => {
  const dataset = await Dataset.load(path)

  // Get the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/core/house-prices-global/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json