Media Types

core

Files Size Format Created Updated License Source
2 2MB csv zip 2 months 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] 202kB media-types [csv] media-types [json] (202kB)
media-types_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 73kB media-types_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

media-types_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

In order to use Data Package in R follow instructions below:

install.packages("devtools")
library(devtools)
install_github("hadley/readr")
install_github("ropenscilabs/jsonvalidate")
install_github("ropenscilabs/datapkg")

#Load client
library(datapkg)

#Get Data Package
datapackage <- datapkg_read("https://pkgstore.datahub.io/core/media-types/latest")

#Package info
print(datapackage)

#Open actual data in RStudio Viewer
View(datapackage$data$"media-types")
View(datapackage$data$"media-types_zip")

Tested with Python 3.5.2

To generate Pandas data frames based on JSON Table Schema descriptors we have to install jsontableschema-pandas plugin. To load resources from a data package as Pandas data frames use datapackage.push_datapackage function. Storage works as a container for Pandas data frames.

In order to work with Data Packages in Pandas you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-pandas

To get Data Package run following code:

import datapackage

data_url = "https://pkgstore.datahub.io/core/media-types/latest/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# to see datasets in this package
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

In order to work with Data Packages in Python you need to install our packages:

$ pip install datapackage

To get Data Package into your Python environment, run following code:

import datapackage

dp = datapackage.DataPackage('https://pkgstore.datahub.io/core/media-types/latest/datapackage.json')

# see metadata
print(dp.descriptor)

# get list of csv files
csvList = [dp.resources[x].descriptor['name'] for x in range(0,len(dp.resources))]
print(csvList) # ["resource name", ...]

# access csv file by the index starting 0
print(dp.resources[0].data)

To use this dataset in JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use code snippet below:

  const {Dataset} = require('data.js')

  const path = 'https://pkgstore.datahub.io/core/media-types/latest/datapackage.json'

  const dataset = Dataset.load(path)

  // get a data file in this dataset
  const file = dataset.resources[0]
  const data = file.stream()

In order to work with Data Packages in SQL you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-sql
$ pip install sqlalchemy

To import Data Package to your SQLite Database, run following code:

import datapackage
from sqlalchemy import create_engine

data_url = 'https://pkgstore.datahub.io/core/media-types/latest/datapackage.json'
engine = create_engine('sqlite:///:memory:')

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'sql', engine=engine)

# to see datasets in this package
storage.buckets

# to execute sql command (assuming data is in "data" folder, name of resource is data and file name is data.csv)
storage._Storage__connection.execute('select * from data__data___data limit 1;').fetchall()

# description of the table columns
storage.describe('data__data___data')
Datapackage.json