Introduction
Public transit analysis takes advantage of the standardized GTFS
format. However, its provision by operator makes it difficult for
network aggregated analysis, considering connectivity and multimodality.
GTFShift::unify() proposes a simple solution to this
problem, generating an aggregated GTFS file given several instances of
these.
This article uses GTFS feeds from the library GTFS database for Portugal as an example. Refer to the vignette(“download”) for more details.
# Get GTFS from library GTFS database for Portugal
data = read.csv(system.file("extdata", "gtfs_sources_pt.csv", package = "GTFShift"))
gtfs_list = lapply(c("barreiro", "fertagus"), function(ID) {
feed = GTFShift::load_feed(data$URL[data$ID == ID], create_transfers=FALSE)
# If some GTFS does not have calendar.txt, but another yes, so we must create it to enable unification
if (! ("calendar" %in% names(feed))) feed$calendar = GTFShift::create_calendar(feed)
summary(feed)
return(feed)
})
#> tidygtfs object
#> files agency, routes, stop_times, trips, shapes, calendar, calendar_dates, feed_info, stops
#> agency Transportes Colectivos do Barreiro
#> service from 2025-05-01 to 2025-12-31
#> uses stop_times (no frequencies)
#> # routes 20
#> # trips 2284
#> # stop_ids 278
#> # stop_names 161
#> # shapes 75
#> tidygtfs object
#> files agency, routes, stop_times, trips, fare_attributes, fare_rules, shapes, vehicles, calendar, calendar_dates, feed_info, stops
#> agency Fertagus
#> service from 2025-06-03 to 2025-12-03
#> uses stop_times (no frequencies)
#> # routes 3
#> # trips 260
#> # stop_ids 14
#> # stop_names 14
#> # shapes 6Unify GTFS
The unification is performed through GTFShift::unify(),
producing a single GTFS instance, saved as a ZIP file. Option
create_transfers enables the generation of
transfers.txt, aggregating close stops, even if from
different GTFS.
# Perform unification
gtfs_united = GTFShift::unify(gtfs_list[[1]], gtfs_list[[2]], create_transfers = TRUE)
summary(gtfs_united)
#> tidygtfs object
#> files agency, routes, stop_times, trips, fare_attributes, fare_rules, shapes, transfers, ., calendar, calendar_dates, feed_info, stops
#> agencies Transportes Colectivos do Barreiro, Fertagus
#> service from 2025-05-01 to 2025-12-31
#> uses stop_times (no frequencies)
#> # routes 23
#> # trips 2544
#> # stop_ids 292
#> # stop_names 175
#> # shapes 81
summary(gtfs_united$transfers)
#> from_stop_id to_stop_id transfer_type min_transfer_time
#> Length:1126 Length:1126 Min. :2 Min. :120.0
#> Class :character Class :character 1st Qu.:2 1st Qu.:120.0
#> Mode :character Mode :character Median :2 Median :255.0
#> Mean :2 Mean :246.9
#> 3rd Qu.:2 3rd Qu.:351.8
#> Max. :2 Max. :416.0It can be displayed using mapview.
Aggregated routes
shape_agency = gtfs_united$trips |>
left_join(gtfs_united$routes, by = "route_id") |>
left_join(gtfs_united$agency, by = "agency_id") |>
select(shape_id, agency_id, agency_name) |>
distinct()
shapes_sf = tidytransit::shapes_as_sf(gtfs_united$shapes) |>
left_join(shape_agency, by = "shape_id") |>
filter(!is.na(agency_id))
mapview::mapview(shapes_sf, zcol = "agency_name", legend = TRUE, layer.name="Agency")Aggregated stops
stop_agency = gtfs_united$stop_times |>
left_join(gtfs_united$trips, by = "trip_id") |>
left_join(gtfs_united$routes, by = "route_id") |>
left_join(gtfs_united$agency, by = "agency_id") |>
select(stop_id, agency_id, agency_name) |>
distinct()
stops_sf = tidytransit::stops_as_sf(gtfs_united$stops) |>
left_join(stop_agency, by = "stop_id") |>
filter(!is.na(agency_id))
mapview::mapview(stops_sf, zcol = "agency_name", legend = TRUE, layer.name="Agency")