Top Level Domain Names

core

Files Size Format Created Updated License Source
2 302kB csv zip 1 week ago The Internet Assigned Numbers Authority (IANA)
This Data Package contains the delegation details of top-level domains ##Data The data is available on : http://www.iana.org/domains/root/db ##Preparation The data were copied manually from "The Internet Assigned Numbers Authority (IANA)" site, and then posted to Excel file and saved as CSV read more
Download

Data Files

File Description Size Last changed Download Other formats
top-level-domain-names.csv [csv] 84kB top-level-domain-names.csv [csv] top-level-domain-names.csv [json] (134kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 42kB datapackage_zip [zip]

top-level-domain-names.csv  

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

Field information

Field Name Order Type (Format) Description
Domain 1 string
Type 2 string
Sponsoring Organisation 3 string

datapackage_zip  

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

Read me

This Data Package contains the delegation details of top-level domains

##Data

The data is available on : http://www.iana.org/domains/root/db

##Preparation

The data were copied manually from “The Internet Assigned Numbers Authority (IANA)” site, and then posted to Excel file and saved as CSV file.

##License

These data are made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://www.opendatacommons.org/licenses/pddl/1.0/

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/top-level-domain-names/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/top-level-domain-names/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/top-level-domain-names/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/top-level-domain-names/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/top-level-domain-names/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