Count the observations in each SpatVector group

count() lets you quickly count the unique values of one or more variables: df |> count(a, b) is roughly equivalent to df |> group_by(a, b) |> summarise(n = n()). count() is paired with tally(), a lower-level helper that is equivalent to df |> summarise(n = n()). Supply wt to perform weighted counts, switching the summary from n = n() to n = sum(wt).

add_count() is equivalent to count() but use mutate() instead of summarise() so that it adds a new column with group-wise counts.

Usage

# S3 method for class 'SpatVector'
count(
  x,
  ...,
  wt = NULL,
  sort = FALSE,
  name = NULL,
  .drop = deprecated(),
  .dissolve = TRUE
)

# S3 method for class 'SpatVector'
tally(x, wt = NULL, sort = FALSE, name = NULL)

# S3 method for class 'SpatVector'
add_count(x, ..., wt = NULL, sort = FALSE, name = NULL, .drop = deprecated())

Arguments

x

A SpatVector.

...

<data-masking> Variables to group by.

wt

<data-masking> Frequency weights. Can be NULL or a variable:

• If NULL (the default), counts the number of rows in each group.

• If a variable, computes sum(wt) for each group.

sort

If TRUE, will show the largest groups at the top.

name

The name of the new column in the output.

If omitted, it will default to n. If there's already a column called n, it will use nn. If there's a column called n and nn, it'll use nnn, and so on, adding ns until it gets a new name.

.drop

Argument not longer supported; empty groups are always removed (see dplyr::count(), .drop = TRUE argument).

.dissolve

logical. Should borders between aggregated geometries be dissolved?

Value

A SpatVector object with an additional attribute.

terra equivalent

terra::aggregate()

Methods

Implementation of the generic dplyr::count() methods for SpatVector objects.

tally() will always return a disaggregated geometry while count() can handle this. See also summarise.SpatVector().

See also

dplyr::count(), dplyr::tally()

Other dplyr verbs that operate on group of rows: group-by.SpatVector, rowwise.SpatVector(), summarise.SpatVector()

Other dplyr methods: arrange.SpatVector(), bind_cols.SpatVector, bind_rows.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, summarise.SpatVector()

Examples

# \donttest{

library(terra)
f <- system.file("ex/lux.shp", package = "terra")
p <- vect(f)

p |> count(NAME_1, sort = TRUE)
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 3, 2  (geometries, attributes)
#>  extent      : 5.74414, 6.528252, 49.44781, 50.18162  (xmin, xmax, ymin, ymax)
#>  coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#>  names       :       NAME_1     n
#>  type        :        <chr> <int>
#>  values      :     Diekirch     5
#>                  Luxembourg     4
#>                Grevenmacher     3

p |> count(pop = ifelse(POP < 20000, "A", "B"))
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 2, 2  (geometries, attributes)
#>  extent      : 5.74414, 6.528252, 49.44781, 50.18162  (xmin, xmax, ymin, ymax)
#>  coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#>  names       :   pop     n
#>  type        : <chr> <int>
#>  values      :     A     5
#>                    B     7

# tally() is a lower-level function that assumes you've done the grouping
p |> tally()
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 1, 1  (geometries, attributes)
#>  extent      : 5.74414, 6.528252, 49.44781, 50.18162  (xmin, xmax, ymin, ymax)
#>  coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#>  names       :     n
#>  type        : <int>
#>  values      :    12

p |>
  group_by(NAME_1) |>
  tally()
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 3, 2  (geometries, attributes)
#>  extent      : 5.74414, 6.528252, 49.44781, 50.18162  (xmin, xmax, ymin, ymax)
#>  coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#>  names       :       NAME_1     n
#>  type        :        <chr> <int>
#>  values      :     Diekirch     5
#>                Grevenmacher     3
#>                  Luxembourg     4

# Dissolve geometries by default

library(ggplot2)
p |>
  count(NAME_1) |>
  ggplot() +
  geom_spatvector(aes(fill = n))


# Opt out
p |>
  count(NAME_1, .dissolve = FALSE, sort = TRUE) |>
  ggplot() +
  geom_spatvector(aes(fill = n))

# }