Summarise each group of a SpatVector down to one geometry

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 SpatVector
summarise(.data, ..., .by = NULL, .groups = NULL, .dissolve = TRUE)

# S3 method for SpatVector
summarize(.data, ..., .by = NULL, .groups = NULL, .dissolve = TRUE)

Arguments

.data

A SpatVector.

...

<data-masking> Name-value pairs of summary functions. The name will be the name of the variable in the result.

The value can be:

• A vector of length 1, e.g. min(x), n(), or sum(is.na(y)).

• A data frame, to add multiple columns from a single expression.

Returning values with size 0 or >1 was deprecated as of 1.1.0. Please use reframe() for this instead.

.by

Ignored on this method ( on dplyr).

.groups

See dplyr::summarise()

.dissolve

logical. Should borders between aggregated geometries be dissolved?

Value

A SpatVector.

terra equivalent

terra::aggregate()

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
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 2, 3  (geometries, attributes)
#>  extent      : 2892687, 3341372, 2017622, 2361600  (xmin, xmax, ymin, ymax)
#>  coord. ref. : ETRS89-extended / LAEA Europe (EPSG:3035) 
#>  names       : start_with_s     n  mean
#>  type        :    <logical> <int> <num>
#>  values      :        FALSE     6    28
#>                        TRUE     3 39.67

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
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 2, 3  (geometries, attributes)
#>  extent      : 2892687, 3341372, 2017622, 2361600  (xmin, xmax, ymin, ymax)
#>  coord. ref. : ETRS89-extended / LAEA Europe (EPSG:3035) 
#>  names       : start_with_s     n  mean
#>  type        :    <logical> <int> <num>
#>  values      :        FALSE     6    28
#>                        TRUE     3 39.67

autoplot(no_diss, aes(fill = start_with_s)) +
  ggplot2::ggtitle("Not Dissolved")