Media Types

core

Files Size Format Created Updated License Source
2 98kB csv zip 7 months ago 3 months ago Open Data Commons Public Domain Dedication and Licence 1.0 IANA
This dataset lists all the Media Types (MIME types), Media Subtypes, and their file extensions. Data 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
Download

Data Files

File Description Size Last changed Download
media-types 401kB csv (401kB) , json (512kB)
media-types_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 74kB zip (74kB)

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

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

data get https://datahub.io/core/media-types
data info core/media-types
tree core/media-types
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/media-types/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/media-types/r/0.csv

curl -L https://datahub.io/core/media-types/r/1.zip

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/media-types/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

Install the Frictionless Data data package library and the pandas itself:

pip install datapackage
pip install pandas

Now you can use the datapackage in the Pandas:

import datapackage
import pandas as pd

data_url = 'https://datahub.io/core/media-types/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/media-types/datapackage.json')

# print list of all resources:
print(package.resource_names)

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':
        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/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 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)
    }
  }
})()

Read me

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

Data

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/

Datapackage.json