This function generates a dataframe similar to the
planes dataset from nycflights13
for any US airports and time frame. Please
note that, even with a strong internet connection, this function
may take several minutes to download relevant data.
Source
FAA Aircraft registry, https://www.faa.gov/licenses_certificates/aircraft_certification/aircraft_registry/releasable_aircraft_download
Arguments
- year
A numeric giving the year of interest. This argument is currently not vectorized, as dataset sizes for single years are significantly large. Information for the most recent year is usually available by February or March in the following year.
- dir
An optional character string giving the directory to save datasets in. By default, datasets will not be saved to file.
- flights_data
Optional---either a filepath as a character string or a dataframe outputted by
get_flightsthat will be used to subset the output to only include relevant carriers/planes. If not supplied, all carriers/planes will be returned.
Value
A data frame with ~3500 rows and 9 variables:
- tailnum
Tail number
- year
Year manufactured
- type
Type of plane
- manufacturer, model
Manufacturer and model
- engines, seats
Number of engines and seats
- speed
Average cruising speed in mph
- engine
Type of engine
See also
get_flights for flight data,
get_weather for weather data,
get_airlines for airlines data,
get_airports for airports data,
or anyflights for a wrapper function.
Use the as_flights_package function to convert this dataset
to a data-only package.
Examples
# grab airplanes data for 2018
if (FALSE) get_planes(2018)
# if you'd like to only return the planes that appear
# in \code{flights}, query your flights dataset first,
# and then supply it as a \code{flights_data} argument
if (FALSE) get_planes(2018,
flights_data = get_flights("PDX", 2018, 6))