ISO 4217 Currency Codes

core

Files Size Format Created Updated License Source
2 53kB csv zip 5 days ago SIX Interbank Clearing Ltd (on behalf of ISO)
List of currencies and their 3 digit codes as defined by ISO 4217. The data provided here is the consolidation of Table A.1 "Current currency & funds code list" and Table A.3 "Historic denominations". Note that the ISO page offers pay-for PDFs but also links to which does provide them in read more
Download

Data Files

File Description Size Last changed Download
codes-all 17kB csv (17kB) , json (63kB)
currency-codes_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 25kB zip (25kB)

codes-all  

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

Field information

Field Name Order Type (Format) Description
Entity 1 string Country or region name
Currency 2 string Name of the currency
AlphabeticCode 3 string 3 digit alphabetic code for the currency
NumericCode 4 number 3 digit numeric code
MinorUnit 5 string
WithdrawalDate 6 string Date currency withdrawn (values can be ranges or months

currency-codes_zip  

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

Read me

List of currencies and their 3 digit codes as defined by ISO 4217. The data provided here is the consolidation of Table A.1 “Current currency & funds code list” and Table A.3 “Historic denominations”.

Note that the ISO page offers pay-for PDFs but also links to http://www.currency-iso.org/en/home/tables.html which does provide them in machine readable form freely.

Contents

Data

The data provided (see data/codes.csv) in this data package provides a consolidated list of currency (and funds) codes by combining these two separate tables:

Install

npm install @datasets/currency-codes

Usage

const codes = require('@datasets/currency-codes');

License

Placing in the Public Domain under the Public Domain Dedication and License. The original site states no restriction on use and the data is small and completely factual.

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/currency-codes/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/currency-codes/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/currency-codes/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/currency-codes/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