Dataset downloaded using the osmdata package representing cycle hire points accross London.

cycle_hire_osm

Format

  • osm_id The OSM ID

  • name The name of the cycle point

  • capacity How many bikes it can take

  • cyclestreets_id The ID linked to cyclestreets' photomap

  • description Additional description of points

  • geometry sfc_POINT

Source

http://www.openstreetmap.org

See also

See the osmdata package: https://cran.r-project.org/package=osmdata

Examples

if (requireNamespace("sf", quietly = TRUE)) { library(sf) data(cycle_hire_osm) # or cycle_hire_osm <- st_read(system.file("shapes/cycle_hire_osm.geojson", package="spData")) plot(cycle_hire_osm) }
#> Reading layer `cycle_hire_osm' from data source `/tmp/RtmpZcdVIy/temp_libpathb72c4795127db/spData/shapes/cycle_hire_osm.geojson' using driver `GeoJSON' #> Simple feature collection with 532 features and 5 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: -0.229123 ymin: 51.45927 xmax: -0.0079843 ymax: 51.54683 #> Geodetic CRS: WGS 84
# Code used to download the data: if (FALSE) { library(osmdata) library(dplyr) library(sf) q = add_osm_feature(opq = opq("London"), key = "network", value = "tfl_cycle_hire") lnd_cycle_hire = osmdata_sf(q) cycle_hire_osm = lnd_cycle_hire$osm_points nrow(cycle_hire_osm) plot(cycle_hire_osm) cycle_hire_osm = dplyr::select(cycle_hire_osm, osm_id, name, capacity, cyclestreets_id, description) %>% mutate(capacity = as.numeric(capacity)) names(cycle_hire_osm) nrow(cycle_hire_osm) }