tidyterra (version 0.7.0)

mutate-joins.SpatVector: Mutating joins for SpatVector objects

Description

Mutating joins add columns from y to x, matching observations based on the keys. There are four mutating joins: the inner join, and the three outer joins.

See dplyr::inner_join() for details.

Usage

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

Value

A SpatVector object.

Arguments

x

A SpatVector created with terra::vect().

y

A data frame or other object coercible to a data frame. If a SpatVector of sf object is provided it would return an error (see terra::intersect() for performing 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.

<a href="https://CRAN.R-project.org/package=terra"><span class="pkg">terra</span></a> equivalent

terra::merge()

Methods

Implementation of the generic dplyr::inner_join() family

SpatVector

The geometry column has a sticky behavior. This means that the result would have always the geometry of x for the records that matches the join conditions.

Note that for right_join() and full_join() it is possible to return empty geometries (since y is expected to be a data frame with no geometries). Although this kind of joining operations may not be common on spatial manipulation, it is possible that the function crashes, since handling of EMPTY geometries differs on terra and sf.

See Also

dplyr::inner_join(), dplyr::left_join(), dplyr::right_join(), dplyr::full_join(), terra::merge()

Other dplyr verbs that operate on pairs Spat*/data.frame: bind_cols.SpatVector, bind_rows.SpatVector, filter-joins.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.Spat, pull.Spat, relocate.Spat, rename.Spat, rowwise.SpatVector(), select.Spat, slice.Spat, summarise.SpatVector()

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)

nrow(inner)
autoplot(inner, aes(fill = letter)) + ggtitle("Inner Join")


# Left join

left <- v %>% left_join(df)
nrow(left)

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

# \donttest{
# Right join
right <- v %>% right_join(df)
nrow(right)

autoplot(right, aes(fill = letter)) + ggtitle("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)
nrow(full)

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

# Check with data from df
ggplot(full, aes(x, y)) +
  geom_point(aes(color = letter))
# }