Useful metadata about airports.
Format
A data frame with columns:
- faa
FAA airport code.
- name
Usual name of the airport.
- lat, lon
Location of airport.
- alt
Altitude, in feet.
- tz
Timezone offset from GMT.
- dst
Daylight savings time zone. A = Standard US DST: starts on the second Sunday of March, ends on the first Sunday of November. U = unknown. N = no dst.
- tzone
IANA time zone, as determined by GeoNames webservice.
Source
https://github.com/jpatokal/openflights/blob/master/data/airports.dat, last updated 2019-05-13
Examples
airports
#> # A tibble: 1,251 × 8
#> faa name lat lon alt tz dst tzone
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 AAF Apalachicola Regional Airport 29.7 -85.0 20 -5 A Amer…
#> 2 AAP Andrau Airpark 29.7 -95.6 79 -6 A Amer…
#> 3 ABE Lehigh Valley International Airpo… 40.7 -75.4 393 -5 A Amer…
#> 4 ABI Abilene Regional Airport 32.4 -99.7 1791 -6 A Amer…
#> 5 ABL Ambler Airport 67.1 -158. 334 -9 A Amer…
#> 6 ABQ Albuquerque International Sunport 35.0 -107. 5355 -7 A Amer…
#> 7 ABR Aberdeen Regional Airport 45.4 -98.4 1302 -6 A Amer…
#> 8 ABY Southwest Georgia Regional Airport 31.5 -84.2 197 -5 A Amer…
#> 9 ACK Nantucket Memorial Airport 41.3 -70.1 47 -5 A Amer…
#> 10 ACT Waco Regional Airport 31.6 -97.2 516 -6 A Amer…
#> # ℹ 1,241 more rows
library(dplyr, warn.conflicts = FALSE)
airports |>
rename(dest = faa) |>
semi_join(flights)
#> Joining with `by = join_by(dest)`
#> # A tibble: 125 × 8
#> dest name lat lon alt tz dst tzone
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 ABQ Albuquerque International Sunport 35.0 -107. 5355 -7 A Amer…
#> 2 ABR Aberdeen Regional Airport 45.4 -98.4 1302 -6 A Amer…
#> 3 ALB Albany International Airport 42.7 -73.8 285 -5 A Amer…
#> 4 ANC Ted Stevens Anchorage Internation… 61.2 -150. 152 -9 A Amer…
#> 5 APN Alpena County Regional Airport 45.1 -83.6 690 -5 A Amer…
#> 6 ASE Aspen-Pitkin Co/Sardy Field 39.2 -107. 7820 -7 A Amer…
#> 7 ATL Hartsfield Jackson Atlanta Intern… 33.6 -84.4 1026 -5 A Amer…
#> 8 ATW Appleton International Airport 44.3 -88.5 918 -6 A Amer…
#> 9 AUS Austin Bergstrom International Ai… 30.2 -97.7 542 -6 A Amer…
#> 10 AZO Kalamazoo Battle Creek Internatio… 42.2 -85.6 874 -5 A Amer…
#> # ℹ 115 more rows
flights |>
anti_join(airports |> rename(dest = faa))
#> Joining with `by = join_by(dest)`
#> # A tibble: 80 × 19
#> year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time
#> <dbl> <dbl> <dbl> <int> <int> <dbl> <int> <int>
#> 1 2013 1 5 818 745 33 1519 1502
#> 2 2013 1 12 738 745 -7 1500 1502
#> 3 2013 1 19 827 745 42 1525 1502
#> 4 2013 1 26 745 745 0 1448 1502
#> 5 2013 12 21 944 900 44 1717 1611
#> 6 2013 12 28 931 900 31 1641 1611
#> 7 2013 2 2 753 745 8 1456 1502
#> 8 2013 2 9 742 745 -3 1428 1502
#> 9 2013 2 16 740 745 -5 1518 1502
#> 10 2013 2 23 738 745 -7 1447 1502
#> # ℹ 70 more rows
#> # ℹ 11 more variables: arr_delay <dbl>, carrier <chr>, flight <dbl>,
#> # tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>,
#> # hour <dbl>, minute <dbl>, time_hour <dttm>
airports |>
rename(origin = faa) |>
semi_join(flights)
#> Joining with `by = join_by(origin)`
#> # A tibble: 1 × 8
#> origin name lat lon alt tz dst tzone
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 MSP Minneapolis-St Paul International/… 44.9 -93.2 841 -6 A Amer…