Exchange Rates

core

Files Size Format Created Updated License Source
4 4MB csv zip 5 days ago odc-pddl Federal Reserve Bank of St. Louis
Foreign exchange rates from US Federal Reserve in daily, monthly and yearly basis. Data Data is gathered from https://fred.stlouisfed.org. Most of the countries have rates for days, months and years, but some only have for months. Some countries have inverted values. Most are compared to USD, and read more
Download

Data Files

File Description Size Last changed Download
yearly 22kB csv (22kB) , json (49kB)
monthly 408kB csv (408kB) , json (915kB)
daily 6MB csv (6MB) , json (14MB)
exchange-rates_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 3MB zip (3MB)

yearly  

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 format
Country 2 string (default) Name of a country
Value 3 number (default) Foreign Exchange Rate to USD. Only AUD, IEP, NZD, GBP and EUR to USD.

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 format
Country 2 string (default) Name of a country
Value 3 number (default) Foreign Exchange Rate to USD. Only AUD, IEP, NZD, GBP and EUR to USD.

daily  

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 format
Country 2 string (default) Name of a country
Value 3 number (default) Foreign Exchange Rate to USD. Only AUD, IEP, NZD, GBP and EUR to USD.

exchange-rates_zip  

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

Read me

Foreign exchange rates from US Federal Reserve in daily, monthly and yearly basis.

Data

Data is gathered from https://fred.stlouisfed.org. Most of the countries have rates for days, months and years, but some only have for months. Some countries have inverted values. Most are compared to USD, and some are USD compared to them.

Following country currencies have USD/currency ratio:

  • Austalia
  • Euro
  • Ireland
  • New Zealand
  • United Kingdom

The rest of countries have currency/USD ratio.

In this dataset, there are 3 granularities available:

  • daily
  • monthly
  • yearly

The data has following fields:

  • Date - date in ISO format
  • Country - name of a country
  • Value - currency rate

Preparation

Run python script:

scripts/main.py

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 <- 'https://datahub.io/core/exchange-rates/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:
print(json_data$resources$name)

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
  if(json_data$resources$datahub$type[i]=='derived/csv'){
    path_to_file = json_data$resources$path[i]
    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:

import datapackage
import pandas as pd

data_url = 'https://datahub.io/core/exchange-rates/datapackage.json'

# to load Data Package into storage
package = datapackage.Package(data_url)

# to load only tabular data
resources = package.resources
for resource in resources:
    if resource.tabular:
        data = pd.read_csv(resource.descriptor['path'])
        print (data)

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('https://datahub.io/core/exchange-rates/datapackage.json')

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

# print all tabular data(if exists any)
resources = package.resources
for resource in resources:
    if resource.tabular:
        print(resource.read())

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 = 'https://datahub.io/core/exchange-rates/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 list of all resources:
  for (const id in dataset.resources) {
    console.log(dataset.resources[id]._descriptor.name)
  }
  // get all tabular data(if exists any)
  for (const id in dataset.resources) {
    if (dataset.resources[id]._descriptor.format === "csv") {
      const file = dataset.resources[id]
      // Get a raw stream
      const stream = await file.stream()
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data
      stream.pipe(process.stdout)
    }
  }
})()
Datapackage.json