sf (version 1.0-7)

st_join: spatial join, spatial filter


spatial join, spatial filter


st_join(x, y, join, ...)

# S3 method for sf st_join( x, y, join = st_intersects, ..., suffix = c(".x", ".y"), left = TRUE, largest = FALSE )

st_filter(x, y, ...)

# S3 method for sf st_filter(x, y, ..., .predicate = st_intersects)



object of class sf


object of class sf


geometry predicate function with the same profile as st_intersects; see details


for st_join: arguments passed on to the join function or to st_intersection when largest is TRUE; for st_filter arguments passed on to the .predicate function, e.g. prepared, or a pattern for st_relate


length 2 character vector; see merge


logical; if TRUE return the left join, otherwise an inner join; see details. see also left_join


logical; if TRUE, return x features augmented with the fields of y that have the largest overlap with each of the features of x; see https://github.com/r-spatial/sf/issues/578


geometry predicate function with the same profile as st_intersects; see details


an object of class sf, joined based on geometry


alternative values for argument join are:

A left join returns all records of the x object with y fields for non-matched records filled with NA values; an inner join returns only records that spatially match.

To replicate the results of st_within(x, y) you will need to use st_join(x, y, join = "st_within", left = FALSE).


Run this code
a = st_sf(a = 1:3,
 geom = st_sfc(st_point(c(1,1)), st_point(c(2,2)), st_point(c(3,3))))
b = st_sf(a = 11:14,
 geom = st_sfc(st_point(c(10,10)), st_point(c(2,2)), st_point(c(2,2)), st_point(c(3,3))))
st_join(a, b)
st_join(a, b, left = FALSE)
# two ways to aggregate y's attribute values outcome over x's geometries:
st_join(a, b) %>% aggregate(list(.$a.x), mean)
st_join(a, b) %>% group_by(a.x) %>% summarise(mean(a.y))
# example of largest = TRUE:
nc <- st_transform(st_read(system.file("shape/nc.shp", package="sf")), 2264)                
gr = st_sf(
    label = apply(expand.grid(1:10, LETTERS[10:1])[,2:1], 1, paste0, collapse = " "),
    geom = st_make_grid(st_as_sfc(st_bbox(nc))))
gr$col = sf.colors(10, categorical = TRUE, alpha = .3)
# cut, to check, NA's work out:
gr = gr[-(1:30),]
nc_j <- st_join(nc, gr, largest = TRUE)
# the two datasets:
opar = par(mfrow = c(2,1), mar = rep(0,4))
plot(st_geometry(gr), add = TRUE, col = gr$col)
text(st_coordinates(st_centroid(gr)), labels = gr$label)
# the joined dataset:
plot(st_geometry(nc_j), border = 'black', col = nc_j$col)
text(st_coordinates(st_centroid(nc_j)), labels = nc_j$label, cex = .8)
plot(st_geometry(gr), border = 'green', add = TRUE)
# }

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