Mutating joins for SpatVector objects — mutate-joins.SpatVector • tidyterra

Mutating joins add columns from y to x, matching observations based on the keys. The four mutating joins are: inner join, left join, right join and full join.

See dplyr::inner_join() for details.

Usage

# S3 method for class 'SpatVector'
inner_join(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = NULL
)

# S3 method for class 'SpatVector'
left_join(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = NULL
)

# S3 method for class 'SpatVector'
right_join(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = NULL
)

# S3 method for class 'SpatVector'
full_join(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = NULL
)

Arguments

x

A SpatVector created with terra::vect().

y

A data frame or other object coercible to a data frame. If a SpatVector or sf object is provided, this method returns an error. See terra::intersect() for spatial joins.

by

A join specification created with join_by(), or a character vector of variables to join by.

If NULL, the default, *_join() will perform a natural join, using all variables in common across x and y. A message lists the variables so that you can check they're correct; suppress the message by supplying by explicitly.

To join on different variables between x and y, use a join_by() specification. For example, join_by(a == b) will match x$a to y$b.

To join by multiple variables, use a join_by() specification with multiple expressions. For example, join_by(a == b, c == d) will match x$a to y$b and x$c to y$d. If the column names are the same between x and y, you can shorten this by listing only the variable names, like join_by(a, c).

join_by() can also be used to perform inequality, rolling, and overlap joins. See the documentation at ?join_by for details on these types of joins.

For simple equality joins, you can alternatively specify a character vector of variable names to join by. For example, by = c("a", "b") joins x$a to y$a and x$b to y$b. If variable names differ between x and y, use a named character vector like by = c("x_a" = "y_a", "x_b" = "y_b").

To perform a cross-join, generating all combinations of x and y, see cross_join().

copy

If x and y are not from the same data source, and copy is TRUE, then y will be copied into the same src as x. This allows you to join tables across srcs, but it is a potentially expensive operation so you must opt into it.

suffix

If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.

...

Other parameters passed onto methods.

keep

Should the join keys from both x and y be preserved in the output?

If NULL, the default, joins on equality retain only the keys from x, while joins on inequality retain the keys from both inputs.
If TRUE, all keys from both inputs are retained.
If FALSE, only keys from x are retained. For right and full joins, the data in key columns corresponding to rows that only exist in y are merged into the key columns from x. Can't be used when joining on inequality conditions.

Value

A SpatVector object.

terra equivalent

terra::merge()

Methods

Implementation of the generic dplyr::inner_join() family

`SpatVector`

The geometry column has sticky behavior. This means that the result always has the geometry of x for the records that match the join conditions.

For right_join() and full_join(), empty geometries may be returned (since y is expected to be a data frame with no geometries). Although these join operations are not common in spatial workflows, the function may crash because handling of EMPTY geometries differs between terra and sf.

Examples

library(terra)
library(ggplot2)
# Vector
v <- terra::vect(system.file("extdata/cyl.gpkg", package = "tidyterra"))

# A data frame
df <- data.frame(
  cpro = sprintf("%02d", 1:10),
  x = runif(10),
  y = runif(10),
  letter = rep_len(LETTERS[1:3], length.out = 10)
)

# Inner join
inner <- v |> inner_join(df)
#> Joining with `by = join_by(cpro)`

nrow(inner)
#> [1] 2
autoplot(inner, aes(fill = letter)) + labs(title = "Inner Join")


# Left join

left <- v |> left_join(df)
#> Joining with `by = join_by(cpro)`
nrow(left)
#> [1] 9

autoplot(left, aes(fill = letter)) + labs(title = "Left Join")


# \donttest{
# Right join
right <- v |> right_join(df)
#> Joining with `by = join_by(cpro)`
nrow(right)
#> [1] 10

autoplot(right, aes(fill = letter)) + labs(title = "Right Join")


# There are empty geometries, check with data from df
ggplot(right, aes(x, y)) +
  geom_point(aes(color = letter))


# Full join
full <- v |> full_join(df)
#> Joining with `by = join_by(cpro)`
nrow(full)
#> [1] 17

autoplot(full, aes(fill = letter)) + labs(title = "Full Join")


# Check with data from df
ggplot(full, aes(x, y)) +
  geom_point(aes(color = letter))
#> Warning: Removed 7 rows containing missing values or values outside the scale range
#> (`geom_point()`).

# }

Mutating joins for `SpatVector` objects