summarise.SpatVector {tidyterra} | R Documentation |
Summarise each group of a SpatVector
down to one geometry
Description
summarise()
creates a new SpatVector
. It returns one geometry for each
combination of grouping variables; if there are no grouping variables, the
output will have a single geometry summarising all observations in the input
and combining all the geometries of the SpatVector
. It will contain one
column for each grouping variable and one column for each of
the summary statistics that you have specified.
summarise.SpatVector()
and summarize.SpatVector()
are synonyms
Usage
## S3 method for class 'SpatVector'
summarise(.data, ..., .by = NULL, .groups = NULL, .dissolve = TRUE)
## S3 method for class 'SpatVector'
summarize(.data, ..., .by = NULL, .groups = NULL, .dissolve = TRUE)
Arguments
.data |
A |
... |
< The value can be:
Returning values with size 0 or >1 was
deprecated as of 1.1.0. Please use |
.by |
Ignored on this method ( on dplyr). |
.groups |
|
.dissolve |
logical. Should borders between aggregated geometries be dissolved? |
Value
A SpatVector
.
terra equivalent
Methods
Implementation of the generic dplyr::summarise()
function.
SpatVector
Similarly to the implementation on sf this function can be used to
dissolve geometries (with .dissolve = TRUE
) or create MULTI
versions of
geometries (with .dissolve = FALSE
). See Examples.
See Also
dplyr::summarise()
, terra::aggregate()
Other single table verbs:
arrange.SpatVector()
,
filter.Spat
,
mutate.Spat
,
rename.Spat
,
select.Spat
,
slice.Spat
Other dplyr verbs that operate on group of rows:
count.SpatVector()
,
group-by.SpatVector
,
rowwise.SpatVector()
Other dplyr methods:
arrange.SpatVector()
,
bind_cols.SpatVector
,
bind_rows.SpatVector
,
count.SpatVector()
,
distinct.SpatVector()
,
filter-joins.SpatVector
,
filter.Spat
,
glimpse.Spat
,
group-by.SpatVector
,
mutate-joins.SpatVector
,
mutate.Spat
,
pull.Spat
,
relocate.Spat
,
rename.Spat
,
rowwise.SpatVector()
,
select.Spat
,
slice.Spat
Examples
library(terra)
library(ggplot2)
v <- vect(system.file("extdata/cyl.gpkg", package = "tidyterra"))
# Grouped
gr_v <- v %>%
mutate(start_with_s = substr(name, 1, 1) == "S") %>%
group_by(start_with_s)
# Dissolving
diss <- gr_v %>%
summarise(n = dplyr::n(), mean = mean(as.double(cpro)))
diss
autoplot(diss, aes(fill = start_with_s)) + ggplot2::ggtitle("Dissolved")
# Not dissolving
no_diss <- gr_v %>%
summarise(n = dplyr::n(), mean = mean(as.double(cpro)), .dissolve = FALSE)
# Same statistic
no_diss
autoplot(no_diss, aes(fill = start_with_s)) +
ggplot2::ggtitle("Not Dissolved")