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)
summary(feed)
return(feed)
})#> tidygtfs object
#> files agency, routes, stop_times, trips, shapes, dead_runs, layover, blocks, calendar, calendar_dates, feed_info, stops
#> agency Transportes Colectivos do Barreiro
#> service from 2026-05-06 to 2026-12-31
#> uses stop_times (no frequencies)
#> # routes 76
#> # trips 3239
#> # stop_ids 279
#> # stop_names 162
#> # shapes 76
#> tidygtfs object
#> files agency, routes, stop_times, trips, fare_attributes, fare_rules, shapes, vehicles, calendar, calendar_dates, feed_info, stops
#> agency Fertagus
#> service from 2026-04-13 to 2026-10-13
#> 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, dead_runs, layover, blocks, vehicles, ., calendar, calendar_dates, feed_info, stops
#> agencies Transportes Colectivos do Barreiro, Fertagus
#> service from 2026-04-13 to 2026-12-31
#> uses stop_times (no frequencies)
#> # routes 79
#> # trips 3499
#> # stop_ids 293
#> # stop_names 176
#> # shapes 82
summary(gtfs_united$transfers)
#> from_stop_id to_stop_id transfer_type min_transfer_time
#> Length :1150 Length :1150 Min. :2 Min. :120.0
#> N.unique : 277 N.unique : 277 1st Qu.:2 1st Qu.:120.0
#> N.blank : 0 N.blank : 0 Median :2 Median :247.0
#> Min.nchar: 6 Min.nchar: 6 Mean :2 Mean :245.0
#> Max.nchar: 7 Max.nchar: 7 3rd Qu.:2 3rd Qu.:349.8
#> Max. :2 Max. :416.0It can be displayed using mapview.
Aggregated routes
shape_agency = gtfs_united$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")