Washington Metropolitan Area Transit Authority API.

metro

The goal of metro is to return data frames from the Washington Metropolitan Area Transit Authority API. Nested lists have been converted to tidy data frames when possible.

Installation

The release version of metro (0.9.1) can be installed from CRAN:

install.packages("metro")

Or install the development version from GitHub:

# install.packages("devtools")
devtools::install_github("k5cents/metro")

Key

Usage of the WMATA API requires a developer API key. Such a key can be obtained by creating a developer account and subscribing to the free default tier.

The WMATA also provides a demo key to try out the various features of the API. This key should never be used in production, it is rate limited and subject to change at any time.

Sys.setenv(WMATA_KEY = "e13626d03d8e4c03ac07f95541b3091b")

Example

library(metro)
packageVersion("metro")
#> [1] '0.9.3'

Functions return data frames for easy analysis.

next_train(StationCodes = "A01")
#> # A tibble: 6 × 9
#>     Car Destination DestinationCode DestinationName Group Line  LocationCode LocationName   Min
#>   <int> <chr>       <chr>           <chr>           <int> <chr> <chr>        <chr>        <int>
#> 1     6 Shady Grove <NA>            Shady Grove         2 RD    A01          Metro Center     0
#> 2     8 Glenmont    B11             Glenmont            1 RD    A01          Metro Center     2
#> 3     8 Glenmont    B11             Glenmont            1 RD    A01          Metro Center     5
#> 4     6 Shady Grove <NA>            Shady Grove         2 RD    A01          Metro Center     8
#> 5     8 Glenmont    B11             Glenmont            1 RD    A01          Metro Center    11
#> 6     6 Shady Grove <NA>            Shady Grove         2 RD    A01          Metro Center    14

Coordinates

Use coordinates to find station entrances or bus stops near a location. The geodist::geodist() function is used to calculate distance from the supplied coordinates.

# Washington Monument coordinates
rail_entrance(Lat = 38.890, Lon = -77.035, Radius = 750)[, -(3:4)]
#> # A tibble: 6 × 5
#>   Name                                        StationCode   Lat   Lon Distance
#>   <chr>                                       <chr>       <dbl> <dbl>    <dbl>
#> 1 12TH ST NW & JEFERSON DR SW                 D02          38.9 -77.0     582.
#> 2 12TH ST SW & INDEPENDENCE AVE SW (ELEVATOR) D02          38.9 -77.0     612.
#> 3 12TH ST SW & INDEPENDENCE AVE SW            D02          38.9 -77.0     626.
#> 4 12TH ST NW & PENNSYLVANIA AVE NW            D01          38.9 -77.0     672.
#> 5 13TH ST NW & PENNSYLVANIA AVE NW (BUILDING) D01          38.9 -77.0     685.
#> 6 12TH ST NW & PENNSYLVANIA AVE NW (ELEVATOR) D01          38.9 -77.0     714.

Dates and Times

Date columns with class POSIXt have been shifted from Eastern time to the UTC time zone (+5 hours).

bus_position(RouteId = "33")[, 1:8]
#> # A tibble: 8 × 8
#>   VehicleID   Lat   Lon Distance Deviation DateTime            TripID   RouteID
#>   <chr>     <dbl> <dbl>    <dbl>     <dbl> <dttm>              <chr>    <chr>  
#> 1 7139       38.9 -77.0       NA         2 2024-03-11 15:24:28 45406020 33     
#> 2 4595       38.9 -77.1       NA        -2 2024-03-11 15:24:48 3269020  33     
#> 3 7119       38.9 -77.0       NA        -1 2024-03-11 15:24:30 9921020  33     
#> 4 4783       38.9 -77.1       NA        -4 2024-03-11 15:24:45 33498020 33     
#> 5 4787       38.9 -77.1       NA         9 2024-03-11 15:24:48 6634020  33     
#> 6 7108       38.9 -77.0       NA        -2 2024-03-11 15:24:46 3492020  33     
#> 7 4600       39.0 -77.1       NA         4 2024-03-11 15:24:28 33552020 33     
#> 8 4588       38.9 -77.0       NA         1 2024-03-11 15:24:27 20757020 33

Time values are left in Eastern time and are represented using the class hms, which counts the seconds since midnight. If the last train on a Saturday leaves at 1:21 AM (past midnight), this would be represented as 25:21.

tail(rail_times(StationCode = "E10"))
#> # A tibble: 6 × 7
#>   StationCode StationName DestinationStation Weekday OpeningTime FirstTime LastTime
#>   <chr>       <chr>       <chr>              <chr>   <time>      <time>    <time>  
#> 1 E10         Greenbelt   F11                Tue     04:50       05:00     23:30   
#> 2 E10         Greenbelt   F11                Wed     04:50       05:00     23:30   
#> 3 E10         Greenbelt   F11                Thu     04:50       05:00     23:30   
#> 4 E10         Greenbelt   F11                Fri     04:50       05:00     26:30   
#> 5 E10         Greenbelt   F11                Sat     06:50       07:00     26:30   
#> 6 E10         Greenbelt   F11                Sun     06:50       07:00     23:30

Data

Some data frames are includes as objects if their functions typically return the same thing every time.

metro_lines # rail_lines() for live
#> # A tibble: 6 × 5
#>   LineCode DisplayName StartStationCode EndStationCode InternalDestination
#>   <chr>    <chr>       <chr>            <chr>          <list>             
#> 1 BL       Blue        J03              G05            <chr [0]>          
#> 2 GR       Green       F11              E10            <chr [0]>          
#> 3 OR       Orange      K08              D13            <chr [0]>          
#> 4 RD       Red         A15              B11            <chr [2]>          
#> 5 SV       Silver      N06              G05            <chr [0]>          
#> 6 YL       Yellow      C15              E06            <chr [1]>