anyflights: 'nycflights13'-Like Data for Specified Years and Airports

Description

The anyflights package supplies a set of functions to generate nycflights13-like datasets and data packages for specified years and airports.

Author(s)

Maintainer: Simon P. Couch simonpatrickcouch@gmail.com

Other contributors:

• Hadley Wickham hadley@rstudio.com [contributor]

• Jay Lee jaylee@reed.edu [contributor]

• Dennis Irorere denironyx@gmail.com [contributor]

See Also

Useful links:

• https://github.com/simonpcouch/anyflights

• https://simonpcouch.github.io/anyflights/

• Report bugs at https://github.com/simonpcouch/anyflights/issues

Query nycflights13-Like Air Travel Data

Description

This function generates a list of dataframes similar to those found in the nycflights13 data package for any US airports and time frames. Please note that, even with a strong internet connection, this function may take several minutes to download relevant data.

Usage

anyflights(station, year, month = 1:12, dir = NULL)

Arguments

Details

The anyflights() function is a wrapper around the following functions:

• get_airlines: Grab data to translate between two letter carrier codes and names

• get_airports: Grab data on airport names and locations

• get_flights: Grab data on all flights that departed given US airports in a given year and month

• get_planes: Grab construction information about each plane

• get_weather: Grab hourly meterological data for a given airport in a given year and month

The recommended approach to download data for many stations (airports) is to supply a vector of stations to the station argument rather than iterating over many calls to anyflights(). The faa column in dataframes outputted by get_airports() provides the FAA LID codes for all supported airports. See ?get_flights for more details on implementation.

Value

A list of dataframes (and, optionally, a directory of datasets) similar to those found in the nycflights13 data package.

See Also

get_flights for flight data, get_weather for weather data, get_airlines for airlines data, get_airports for airports data, or get_planes for planes data.

Use the as_flights_package function to convert the output of this function to a data-only package.

Examples

# grab data on all flights departing from 
# Portland International Airport in June 2019 and 
# other useful metadata without saving to file
## Not run: anyflights("PDX", 2018, 6)

# ...or, grab that same data and opt to save the 
# file as well! (tempdir() can usually be specified 
# as a character string giving the path to a folder)
## Not run: anyflights("PDX", 2018, 6, tempdir())

Generate a Data Package from 'anyflights' Data

Description

Generate a data-only package, including documentation, from data outputted by the 'anyflights()' function. Please do not submit the outputted package to CRAN or similar repositories as original packages.

Usage

as_flights_package(data, name = make.names(deparse(substitute(data))))

Arguments

Value

A directory containing a data-only package built around the supplied data.

Query nycflights13-Like Airlines Data

Description

This function generates a dataframe similar to the airlines 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.

Usage

get_airlines(dir = NULL, flights_data = NULL)

Arguments

Value

A data frame with <2k rows and 2 variables:

carrier

Two or three length letter or number abbreviation. In cases whgere the the Unique Carrier Code has been use more than once, a suffix is added. ex. ML, ML (1). This list matches the 'Reporting_Airline' field in the BTS documentation for the flights data set

name

Full name

Source

https://www.bts.gov/

See Also

get_flights for flight data, get_weather for weather data, get_airports for airports data, get_planes for planes data, or anyflights for a wrapper function.

Use the as_flights_package function to convert this dataset to a data-only package.

Examples

# run with defaults
## Not run: get_airlines()

# if you'd like to only return the airline 
# abbreviations only for airlines that appear in 
# \code{flights}, query your flights dataset first, 
# and then supply it as a flights_data argument
## Not run: get_airlines(flights_data = get_flights("PDX", 2018, 6))

Query nycflights13-Like Airports Data

Description

This function generates a dataframe similar to the airports 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.

Usage

get_airports(dir = NULL)

Arguments

Value

A data frame with ~1350 rows and 8 variables:

faa

FAA airport code

name

Usual name of the airport

lat, lon

Location of airport

alt

Altitude, in feet

tz

Timezone offset from GMT/UTC

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://openflights.org/data.html'

See Also

get_flights for flight data, get_weather for weather data, get_airlines for airlines data, get_planes for planes data, or anyflights for a wrapper function.

Use the as_flights_package function to convert this dataset to a data-only package.

Examples

# grab airports data
## Not run: get_airports()

Query nycflights13-Like Flights Data

Description

This function generates a dataframe similar to the flights dataset from nycflights13 for any US airport and time frame. Please note that, even with a strong internet connection, this function may take several minutes to download relevant data.

Usage

get_flights(station, year, month = 1:12, dir = NULL, ...)

Arguments

Details

This function currently downloads data for all stations for each month supplied, and then filters out data for relevant stations. Thus, the recommended approach to download data for many airports is to supply a vector of airport codes to the station argument rather than iterating over many calls to get_flights().

Value

A data frame with ~1k-500k rows and 19 variables:

year, month, day

Date of departure

dep_time, arr_time

Actual departure and arrival times, UTC.

sched_dep_time, sched_arr_time

Scheduled departure and arrival times, UTC.

dep_delay, arr_delay

Departure and arrival delays, in minutes. Negative times represent early departures/arrivals.

hour, minute

Time of scheduled departure broken into hour and minutes.

carrier

Two letter carrier abbreviation. See get_airlines to get full name

tailnum

Plane tail number

flight

Flight number

origin, dest

Origin and destination. See get_airports for additional metadata.

air_time

Amount of time spent in the air, in minutes

distance

Distance between airports, in miles

time_hour

Scheduled date and hour of the flight as a POSIXct date. Along with origin, can be used to join flights data to weather data.

Note

If you are repeatedly getting a timeout error when downloading flights, this could be because your download is taking longer than the default timeout R option. You can change the timeout value for your R session by running the code options(timeout = timeout_value_in_seconds) in your console.

Source

RITA, Bureau of transportation statistics, https://www.bts.gov

See Also

get_weather for weather data, get_airlines for airlines data, get_airports for airports data, get_planes for planes data, or anyflights for a wrapper function.

Use the as_flights_package function to convert this dataset to a data-only package.

Examples

# flights out of Portland International in June 2018
## Not run: get_flights("PDX", 2018, 6)

# ...or the original nycflights13 flights dataset
## Not run: get_flights(c("JFK", "LGA", "EWR"), 2013)

# use the dir argument to indicate the folder to 
# save the data in \code{dir} as "flights.rda"
## Not run: get_flights("PDX", 2018, 6, dir = tempdir())

Query nycflights13-Like Planes Data

Description

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.

Usage

get_planes(year, dir = NULL, flights_data = NULL)

Arguments

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

Source

FAA Aircraft registry, https://www.faa.gov/licenses_certificates/aircraft_certification/aircraft_registry/releasable_aircraft_download

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
## Not run: 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
## Not run: get_planes(2018, 
                 flights_data = get_flights("PDX", 2018, 6))
## End(Not run)

Query nycflights13-Like Weather Data

Description

This function generates a dataframe similar to the weather 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.

Usage

get_weather(station, year, month = 1:12, dir = NULL)

Arguments

Value

A data frame with ~1k-25k rows and 15 variables:

origin

Weather station. Named origin to facilitate merging with flights data

year, month, day, hour

Time of recording, UTC

temp, dewp

Temperature and dewpoint in F

humid

Relative humidity

wind_dir, wind_speed, wind_gust

Wind direction (in degrees), speed and gust speed (in mph)

precip

Precipitation, in inches

pressure

Sea level pressure in millibars

visib

Visibility in miles

time_hour

Date and hour of the recording as a POSIXct date, UTC

Source

ASOS download from Iowa Environmental Mesonet, https://mesonet.agron.iastate.edu/request/download.phtml

See Also

get_flights for flight data, get_airlines for airlines data, get_airports for airports data, get_planes for planes data, or anyflights for a wrapper function.

Use the as_flights_package function to convert this dataset to a data-only package.

Examples

# query weather at Portland International in June 2018
## Not run: get_weather("PDX", 2018, 6)

# ...or the original nycflights13 weather dataset
## Not run: get_weather(c("JFK", "LGA", "EWR"), 2013)

# use the dir argument to indicate the folder to 
# save the data in as "weather.rda"
## Not run: get_weather("PDX", 2018, 6, dir = tempdir())