When a csquares object inherits from class data.frame, you can apply tidyverse
joins to the object (?dplyr::join). The functions implemented here make sure that
the csquares properties are preserved. The functions should be called via the dplyr
generics. So load the dplyr package first, then call the function without the .csquares
suffix (see examples). When x inherits from stars, only left_join is supported.
inner_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
left_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
right_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
full_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
semi_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
anti_join.csquares(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
st_join.csquares(x, y, join, ..., suffix = c(".x", ".y"))A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
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().
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.
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.
geometry predicate function with the same profile as st_intersects; see details
# \donttest{
if (requireNamespace(c("sf", "dplyr"))) {
library(csquares)
library(sf)
library(dplyr)
orca_sf <- orca |> as_csquares(csquares = "csquares") |> st_as_sf()
right_table <- data.frame(csquares = c("1000:1", "1004:1"), foo = "bar")
orca_join <- left_join (orca_sf, right_table, by = "csquares")
orca_join <- right_join(orca_sf, right_table, by = "csquares")
orca_join <- inner_join(orca_sf, right_table, by = "csquares")
orca_join <- anti_join (orca_sf, right_table, by = "csquares")
orca_join <- semi_join (orca_sf, right_table, by = "csquares")
orca_grid <- new_csquares(orca_sf, 5)
orca_grid <- left_join(orca_grid, orca, by = "csquares")
}
# }