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You may also take a look at the source code.
The network in this dataset can be loaded directly from graph-tool with:import graph_tool.all as gt g = gt.collection.ns["us_air_traffic"]
Yearly snapshots of flights among all commercial airports in the United States from 1990 to today. Metadata include passengers, distance, carrier, airport located city, state, and month of the flight.1
| 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 | 65.4 MiB | 84.7 MiB | 55.3 MiB | 69.9 MiB |