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Get aggregated frequency per hour for each bus stop

Source: R/get_stop_frequency_hourly.R
get_stop_frequency_hourly.Rd

For each stop, returns the number of departures aggregated per hour.

Usage

get_stop_frequency_hourly(
  gtfs,
  date = GTFShift::calendar_nextBusinessWednesday()
)

Arguments

gtfs

tidygtfs. GTFS feed.

date

Date (Default GTFShift::calendar_nextBusinessWednesday()). Reference date to consider when analyzing the GTFS file.

Value

sf data.frame. Hourly stop frequencies, with the following columns:

stop_id

The stop_id attribute from stops.txt file.

hour

The hour for which the frequency applies (24 hour format).

frequency

The number of services provided at the stop for the corresponding 60 minutes period.

geometry

The stop coordinates.

Details

This method analyses the GTFS feed for a representative day, generating for each stop the number of services aggregated per hour. For a detailed example, see the vignette("analyse").

See also

GTFShift::calendar_nextBusinessWednesday()

Examples

# Subset GTFS for one route only, for demo purposes
gtfs <- GTFShift::load_feed(system.file("extdata/samples",
  "gtfs_tcb_sample.zip", package = "GTFShift")
)
gtfs <- GTFShift::filter_by_route_name(gtfs, c("1", "2", "3", "4"))

# Get frequency
frequency_analysis <- GTFShift::get_stop_frequency_hourly(
  gtfs,
  date = gtfs$calendar$start_date[1]
)
#> Analysing GTFS for 2026-06-10...
#> > Filtering by reference date 2026-06-10...
#> > Found 6 routes operating 5 trips on 56 stops...
#> > Identified 1 service patterns matching date: DF / Projeto A _26-1783608301691
#> > Calculating stop frequencies for hours 0 to 23...
#> Finished GTFS analysis!

head(frequency_analysis)
#> Simple feature collection with 6 features and 3 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -9.081225 ymin: 38.65708 xmax: -9.078934 ymax: 38.65942
#> Geodetic CRS:  WGS 84
#> # A tibble: 6 × 4
#>   stop_id  hour frequency             geometry
#>   <chr>   <int>     <int>          <POINT [°]>
#> 1 000002      6         1 (-9.078934 38.65708)
#> 2 000002     10         1 (-9.078934 38.65708)
#> 3 000002     23         1 (-9.078934 38.65708)
#> 4 000003      6         1 (-9.081225 38.65942)
#> 5 000003     11         1 (-9.081225 38.65942)
#> 6 000003     23         1 (-9.081225 38.65942)