Airport Codes

core

Files Size Format Created Updated License Source
2 35MB csv zip 3 hours ago PDDL-1.0 Our Airports
The airport codes may refer to either IATA airport code, a three-letter code which is used in passenger reservation, ticketing and baggage-handling systems, or the ICAO airport code which is a four letter code used by ATC systems and for airports that do not have an IATA airport code (from read more
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Data Files

File Description Size Last changed Download Other formats
airport-codes [csv] 6MB airport-codes [csv] airport-codes [json] (15MB)
airport-codes_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 7MB airport-codes_zip [zip]

airport-codes  

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

Field information

Field Name Order Type (Format) Description
ident 1 string
type 2 string
name 3 string
elevation_ft 4 integer
continent 5 string
iso_country 6 string
iso_region 7 string
municipality 8 string
gps_code 9 string
iata_code 10 string
local_code 11 string
coordinates 12 string

airport-codes_zip  

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

Read me

The airport codes may refer to either IATA airport code, a three-letter code which is used in passenger reservation, ticketing and baggage-handling systems, or the ICAO airport code which is a four letter code used by ATC systems and for airports that do not have an IATA airport code (from wikipedia).

Airport codes from around the world. Downloaded from public domain source http://ourairports.com/data/ who compiled this data from multiple different sources. This data is updated nightly.

Data

There is one csv file ,“airport-codes” which contains the list of all airport codes, the attributes are identified in datapackage description. Some of the columns contain attributes identifying airport locations, other codes (IATA, local if exist) that are relevant to identification of an airport

Preparation

Download and clean the csv file as is from the url http://ourairports.com/data/

TODO: Add relationship to UNLOCODEs ?

License

The source specifies that the data can be used as is without any warranty. Given size and factual nature of the data and its source from a US company would imagine this was public domain and as such have licensed the Data Package under the Public Domain Dedication and License (PDDL).

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/airport-codes/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/airport-codes/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/airport-codes/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/airport-codes/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/airport-codes/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