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Monthly traffic on the busiest domestic airline routes in Australia, including passengers, flights and seats by origin–destination pair. Data cover revenue (paying) passengers on regular public transport (RPT) services from 2016 onward.

Usage

au_dom_routes

Format

Data frame with columns:

origin_airport

Three-letter IATA code of the origin airport (e.g. "SYD" for Sydney).

dest_airport

Three-letter IATA code of the destination airport (e.g. "MEL" for Melbourne).

origin_city

Name of the origin city (e.g. "Sydney").

dest_city

Name of the destination city (e.g. "Melbourne").

year

Calendar year, e.g. 2016.

month

Calendar month 1–12 (1 = January, 12 = December).

n_passengers

Number of revenue (paying) passengers carried on the route in that month, both directions combined.

n_flights

Number of aircraft trips (flights) operated on the route in that month.

n_seats

Total number of seats offered on flights on the route in that month (capacity).

Source

Bureau of Infrastructure and Transport Research Economics (BITRE), Domestic aviation statistics – Top routes. Data downloaded from https://www.bitre.gov.au/publications/ongoing/domestic_airline_activity-time_series.

Examples

au_dom_routes
#> # A tibble: 8,595 × 9
#>    origin_airport dest_airport origin_city dest_city  year month n_passengers
#>    <chr>          <chr>        <chr>       <chr>     <dbl> <dbl>        <dbl>
#>  1 ABX            SYD          Albury      Sydney     2016     1        16007
#>  2 ABX            SYD          Albury      Sydney     2016     2        16461
#>  3 ABX            SYD          Albury      Sydney     2016     3        19486
#>  4 ABX            SYD          Albury      Sydney     2016     4        19155
#>  5 ABX            SYD          Albury      Sydney     2016     5        19278
#>  6 ABX            SYD          Albury      Sydney     2016     6        17766
#>  7 ABX            SYD          Albury      Sydney     2016     7        19599
#>  8 ABX            SYD          Albury      Sydney     2016     8        20126
#>  9 ABX            SYD          Albury      Sydney     2016     9        20218
#> 10 ABX            SYD          Albury      Sydney     2016    10        19717
#> # ℹ 8,585 more rows
#> # ℹ 2 more variables: n_flights <dbl>, n_seats <dbl>