Dataset downloaded using the osmdata package representing cycle hire points accross London.
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
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
#> `/home/runner/work/_temp/Library/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) { # \dontrun{
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)
} # }