# NOT RUN {
# default tibble output
x = get_stats19(2009)
class(x)
x = get_stats19(2017, silent = TRUE)
# data.frame output
x = get_stats19(2009, silent = TRUE, output_format = "data.frame")
class(x)
# multiple years
get_stats19(c(2017, 2018), silent = TRUE)
# sf output
x_sf = get_stats19(2017, silent = TRUE, output_format = "sf")
# sf output with lonlat coordinates
x_sf = get_stats19(2017, silent = TRUE, output_format = "sf", lonlat = TRUE)
sf::st_crs(x_sf)
# multiple years
get_stats19(c(2017, 2018), silent = TRUE, output_format = "sf")
if (requireNamespace("spatstat", quietly = TRUE)) {
# ppp output
x_ppp = get_stats19(2017, silent = TRUE, output_format = "ppp")
spatstat::plot.ppp(x_ppp, use.marks = FALSE)
# Multiple years
get_stats19(c(2017, 2018), silent = TRUE, output_format = "ppp")
# We can use the window parameter of format_ppp function to filter only the
# events occurred in a specific area. For example we can create a new bbox
# of 5km around the city center of Leeds
leeds_window = spatstat::owin(
xrange = c(425046.1, 435046.1),
yrange = c(428577.2, 438577.2)
)
leeds_ppp = get_stats19(2017, silent = TRUE, output_format = "ppp", window = leeds_window)
spatstat::plot.ppp(leeds_ppp, use.marks = FALSE, clipwin = leeds_window)
# or even more fancy examples where we subset all the events occurred in a
# pre-defined polygon area
# The following example requires osmdata package
# greater_london_sf_polygon = osmdata::getbb(
# "Greater London, UK",
# format_out = "sf_polygon"
# )
# spatstat works only with planar coordinates
# greater_london_sf_polygon = sf::st_transform(greater_london_sf_polygon, 27700)
# then we extract the coordinates and create the window object.
# greater_london_polygon = sf::st_coordinates(greater_london_sf_polygon)[, c(1, 2)]
# greater_london_window = spatstat::owin(poly = greater_london_polygon)
# greater_london_ppp = get_stats19(2017, output_format = "ppp", window = greater_london_window)
# spatstat::plot.ppp(greater_london_ppp, use.marks = FALSE, clipwin = greater_london_window)
}
# }
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