Media Types

core

Files Size Format Created Updated License Source
2 1MB csv zip 1 month ago IANA
This dataset lists all the Media Types (MIME types), Media Subtypes, and their file extensions. Source The details of the Media Types and Media Subtypes are taken from the official registry of Media Types maintained by IANA. The extension details are taken the website of the Apache Software read more
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Data Files

File Description Size Last changed Download Other formats
media-types [csv] 401kB media-types [csv] media-types [json] (512kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 73kB datapackage_zip [zip]

media-types  

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

Field information

Field Name Order Type (Format) Description
Media Type 1 string
Type 2 string
Subtype 3 string
Template 4 string
Extensions 5 string

datapackage_zip  

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

Read me

This dataset lists all the Media Types (MIME types), Media Subtypes, and their file extensions.

Source

The details of the Media Types and Media Subtypes are taken from the official registry of Media Types maintained by IANA. The extension details are taken the website of the Apache Software Foundation.

Preparation

The Type, Subtype, and Template name were copied from IANA’s websites into a Google Sheets document. The link to the Template was generated in a fourth column in the same sheet by concatenating the Template name with a reference to the Template folder on IANA’s website.

The extensions were copied from Apache’s website into a separate sheet in the same Google Sheets document. The data was cleaned to place the extensions on their own in a single column without the Type and Subtype.

The extensions were finally added to the original sheet using VLOOKUP.

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/media-types/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/media-types/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/media-types/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/media-types/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/media-types/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