10 year US Government Bond Yields (long-term interest rate)

core

Files Size Format Created Updated License Source
2 66kB csv zip 1 day ago PDDL-1.0 Federal Reserve (Release H.15)
10 year nominal yields on US government bonds from the Federal Reserve. The 10 year government bond yield is considered a standard indicator of long-term interest rates. Data Data comes from the [Release H.15 from the Federal Reserve - Selected Interest Rates Daily][fed] specifically the [10 year read more
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Data Files

File Description Size Last changed Download Other formats
monthly [csv] Annual Market yield on U.S. Treasury securities at 10-year constant maturity, quoted on investment basis. (Monthly granuarlity) 13kB monthly [csv] monthly [json] (28kB)
bond-yields-us-10y_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 13kB bond-yields-us-10y_zip [zip]

monthly  

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) Date in ISO 8601
Rate 2 number (percent) Percent per year

bond-yields-us-10y_zip  

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

Read me

10 year nominal yields on US government bonds from the Federal Reserve. The 10 year government bond yield is considered a standard indicator of long-term interest rates.

Data

Data comes from the Release H.15 from the Federal Reserve - Selected Interest Rates Daily specifically the 10 year US Treasury (monthly, csv).

Preparation

Run the shell script:

. scripts/process.sh

Note we keep a copy of the raw data from the Federal Reserve (pre-tidying) in archive.

License

Licensed under the Public Domain Dedication and License (assuming either no rights or public domain license in source data).

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-us-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$resources$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/bond-yields-us-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-us-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-us-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-us-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