us_air_traffic — U.S. air traffic

Description

Network of domestic air traffic in the United States from January 1990 to early 2020, from the T-100 Domestic Market table of the Bureau of Transportation Statistics (BTS), which records the monthly traffic reported by U.S. air carriers. Nodes are airports and a directed edge $i \to j$ is a record of the table: the traffic carried by one carrier from origin airport $i$ to destination airport $j$ in a given month, for a given service class. Each pair of airports is therefore connected by many parallel edges, one per carrier, month and service class (about 6.4 million edges in total).

The network has the following properties:

airport_code: the three-letter code of the airport.
airport_id, airport_seq_id, city_market_id: the BTS identifiers of the airport, of the airport at a given point in time, and of the city market served by the airport.
city_name, state_abr, state_fips, state_nm, wac: the city, the state abbreviation, FIPS code and name, and the BTS world area code of the airport.
passengers, freight, mail: the number of passengers, and the amount of freight and mail (in pounds) transported.
distance: the distance between the airports, in miles, and distance_group, the corresponding 500-mile distance interval.
unique_carrier, airline_id, unique_carrier_name, unique_carrier_entity, carrier, carrier_name: codes and names identifying the carrier.
region: the carrier's operating region (e.g. D for domestic).
carrier_group, carrier_group_new: the carrier group codes (based on the carrier's revenue).
year, quarter, month: the period of the record.
class: the service class: F (scheduled passenger/cargo service), G (scheduled all-cargo service), L (non-scheduled civilian passenger/cargo service) or P (non-scheduled all-cargo service).

Tags

Transportation Airport Unweighted Metadata Temporal

Citation

Bureau of Transportation Statistics. "T-100 Domestic Market". https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=310 (2017) www.transtats.bts.gov

Upstream URL 404

https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=310

Networks

Tip: hover over a column header for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
us_air_traffic	2,278	6,390,340	2805.24	23318.93	225.51	41.03	0.03	0.92	6	1.00	Directed	Unipartite	airport_code airport_id airport_seq_id city_market_id origin city_name state_abr state_fips state_nm wac	passengers freight mail distance unique_carrier airline_id unique_carrier_name unique_carrier_entity region carrier carrier_name carrier_group carrier_group_new year quarter month distance_group class	64.1 MiB	84.7 MiB	75.6 MiB	69.9 MiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.