List of all countries with their 2 digit codes (ISO 3166-2)

core

Files Size Format Created Updated License Source
2 29kB csv zip 6 days ago ODC-PDDL ISO
ISO 3166-1-alpha-2 English country names and code elements. This list states the country names (official short names in English) in alphabetical order as given in ISO 3166-1 and the corresponding ISO 3166-1-alpha-2 code elements. [ISO 3166-1]: read more
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Data Files

File Description Size Last changed Download
data 4kB csv (4kB) , json (9kB)
country-list_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 9kB zip (9kB)

data  

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

Field information

Field Name Order Type (Format) Description
Name 1 string Country Name
Code 2 string ISO 2-digit code from ISO 3166-alpha-2

country-list_zip  

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

Read me

ISO 3166-1-alpha-2 English country names and code elements. This list states the country names (official short names in English) in alphabetical order as given in ISO 3166-1 and the corresponding ISO 3166-1-alpha-2 code elements.

This list is updated whenever a change to the official code list in ISO 3166-1 is effected by the ISO 3166/MA.

It lists 250 official short names and code elements as of Dec 2012.

License

This material is licensed by its maintainers under the Public Domain Dedication and License.

Nevertheless, it should be noted that this material is ultimately sourced from ISO and their rights and licensing policy is somewhat unclear. As this is a short, simple database of facts there is a strong argument that no rights can subsist in this collection. However, ISO state on their site:

ISO makes the list of alpha-2 country codes available for internal use and non-commercial purposes free of charge.

This carries the implication (though not spelled out) that other uses are not permitted and that, therefore, there may be rights preventing further general use and reuse.

Import into your tool

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

install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")

json_file <- 'https://datahub.io/core/country-list/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)
  }
}

Note: You might need to run the script with root permissions if you are running on Linux machine

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/country-list/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/country-list/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/country-list/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