NOTE: deprecated, functionality moved to: https://github.com/r-transit/tidytransit

You can still use this but its not under development for now.

Description

bustt is a package for working with time in transit schedule data. In particular, it is focused on questions like:

• What are the headway of train lines at 59-Street Columbus Circle on Saturdays?
• What are the typical headway characteristics of the A Train on weekdays?

Installation

Install from CRAN: install.packages("bustt")

For development, you can install this package from GitHub using the devtools package:

if (!require(devtools)) {
    install.packages('devtools')
}
devtools::install_github('r-gtfs/bustt')

Note that the development version is currently less reliable than the CRAN version.

Example Usage

library(dplyr)
library(trread)
library(bustt)

NYC <- import_gtfs("http://web.mta.info/developers/data/nyct/subway/google_transit.zip")
#> [1] "agency.txt"         "calendar_dates.txt" "calendar.txt"      
#> [4] "routes.txt"         "shapes.txt"         "stop_times.txt"    
#> [7] "stops.txt"          "transfers.txt"      "trips.txt"

Route Headways

List the routes with the shortest median headways.

route_frequency_summary <- route_frequency(NYC) %>%
  arrange(median_headways)

head(route_frequency_summary)
#> # A tibble: 6 x 5
#>   route_id median_headways mean_headways st_dev_headways stop_count
#>   <chr>              <int>         <int>           <dbl>      <int>
#> 1 GS                     4             4           0.01           4
#> 2 L                      4             4           0.13          48
#> 3 1                      5             5           0.14          76
#> 4 7                      5             5           0.290         44
#> 5 6                      6             7           2.84          76
#> 6 E                      6            23          53.0           48

Stop Headways

List the stops with the shortest headways in the system.

stop_frequency_summary <- stop_frequency(NYC, by_route=FALSE) %>%
  inner_join(NYC$stops_df) %>%
    select(stop_name, headway) %>%
      arrange(headway)

head(stop_frequency_summary)
#> # A tibble: 6 x 4
#> # Groups:   direction_id, stop_id [6]
#>   direction_id stop_id stop_name             headway
#>          <int> <chr>   <chr>                   <dbl>
#> 1            0 902N    Times Sq - 42 St         3.60
#> 2            1 901S    Grand Central - 42 St    3.60
#> 3            1 902S    Times Sq - 42 St         3.60
#> 4            0 901N    Grand Central - 42 St    3.61
#> 5            0 702N    Mets - Willets Point     3.72
#> 6            0 707N    Junction Blvd            3.72