Airport Codes

core

Files Size Format Created Updated License Source
2 36MB csv zip 5 months ago 18 hours ago Open Data Commons Public Domain Dedication and License v1.0 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
Download

Data Files

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

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

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

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

Data-cli or just data is the program to get and post your data with the datahub.
Use data with the datahub.io almost like you use git with the github. Here are installation instructions.

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

# Get resources

curl -L https://datahub.io/core/airport-codes/r/0.csv

curl -L https://datahub.io/core/airport-codes/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/airport-codes/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/airport-codes/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/airport-codes/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/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 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)
    }
  }
})()
Datapackage.json