10y UK Government Bond Yields (long-term interest rate)

core

Files Size Format Created Updated License Source
3 18kB csv zip 1 week ago public_domain_dedication_and_license Bank of England
10 year nominal yields on UK government bonds from the bank of England. The 10 year government bond yield is considered a standard indicator of long-term interest rates. This is a direct extract from the Bank of [England IUAAMNPY series: "Annual average yield from British Government Securities, 10 read more
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Data Files

File Description Size Last changed Download Other formats
quarterly [csv] 3kB quarterly [csv] quarterly [json] (5kB)
annual [csv] 623B annual [csv] annual [json] (1kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 5kB datapackage_zip [zip]

quarterly  

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)
Rate 2 number (percentage) Quarterly average yield from British Government Securities, 10 year Nominal Par Yield

annual  

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

Field information

Field Name Order Type (Format) Description
Year 1 date (%Y-%m-%d)
Rate 2 number (percentage) Annual average yield from British Government Securities, 10 year Nominal Par Yield

datapackage_zip  

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

Read me

10 year nominal yields on UK government bonds from the bank of England. The 10 year government bond yield is considered a standard indicator of long-term interest rates. This is a direct extract from the Bank of England IUAAMNPY series: “Annual average yield from British Government Securities, 10 year Nominal Par Yield”.

Data

Data from Bank of England (series IUAAMNPY “Annual average yield from British Government Securities, 10 year Nominal Par Yield”) with some minor processing (see scripts).

Full information about the BoE Yields data may be found on the BoE website at: http://www.bankofengland.co.uk/statistics/Pages/iadb/notesiadb/Yields.aspx

There are several relevant series:

Preparation

Do the following:

. scripts/download.sh
. scripts/extract.sh

Data will be in annual.csv.

License

The Bank of England Terms of Use appear only to allow non-commercial use:

Statistical Interactive Database (IADB) Terms and Conditions

The content of the database is for general information only, and is provided to users free of charge. Commercial use for financial gain is not permitted without the express permission of the Bank of England. The Bank of England reserves the right to terminate or restrict user access if it determines that a user is acting in a manner contrary to the interests of other users of the database e.g. excessive usage. [retrieved 2013-04-07]

However, the amounts of data provided in this dataset is so minimal as likely to fall below any threshold for Database Rights.

As such the maintainers feel warranted in putting the dataset out under the Public Domain Dedication and License but that they can, obviously, only license (or dedicate) material they control (or in which there are no rights).

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/bond-yields-uk-10y/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources[[1]]$path
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/bond-yields-uk-10y/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/bond-yields-uk-10y/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/bond-yields-uk-10y/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/bond-yields-uk-10y/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