cross_join function

Cross join

Cross joins match each row in x to every row in y, resulting in a data frame with nrow(x) * nrow(y) rows.

Since cross joins result in all possible matches between x and y, they technically serve as the basis for all mutating joins , which can generally be thought of as cross joins followed by a filter. In practice, a more specialized procedure is used for better performance.

cross_join(x, y, ..., copy = FALSE, suffix = c(".x", ".y"))

Arguments

• 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.
• ...: Other parameters passed onto methods.
• 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.

Returns

An object of the same type as x (including the same groups). The output has the following properties:

• There are nrow(x) * nrow(y) rows returned.
• Output columns include all columns from both x and y. Column name collisions are resolved using suffix.
• The order of the rows and columns of x is preserved as much as possible.

Methods

This function is a generic , which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.

The following methods are currently available in loaded packages: dplyr:::methods_rd("cross_join") .

Examples

s match each row in `x` to every row in `y`.
# Data within the columns is not used in the matching process.
cross_join(band_instruments, band_members)

# Control the suffix added to variables duplicated in
# `x` and `y` with `suffix`.
cross_join(band_instruments, band_members, suffix = c("", "_y"))

See Also

Other joins: filter-joins, mutate-joins, nest_join()