filter-joins: Filtering joins

Description Usage Arguments Value Methods See Also Examples

Description

Filtering joins filter rows from x based on the presence or absence of matches in y:

Usage

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semi_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'data.frame'
semi_join(x, y, by = NULL, copy = FALSE, ..., na_matches = c("na", "never"))

anti_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'data.frame'
anti_join(x, y, by = NULL, copy = FALSE, ..., na_matches = c("na", "never"))

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.

by

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 by different variables on x and y, use a named vector. For example, by = c("a" = "b") will match x$a to y$b.

To join by multiple variables, use a vector with length > 1. For example, by = c("a", "b") will match x$a to y$a and x$b to y$b. Use a named vector to match different variables in x and y. For example, by = c("a" = "b", "c" = "d") will match x$a to y$b and x$c to y$d.

To perform a cross-join, generating all combinations of x and y, use by = character().

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.

...

Other parameters passed onto methods.

na_matches

Should NA and NaN values match one another?

The default, "na", treats two NA or NaN values as equal, like %in%, match(), merge().

Use "never" to always treat two NA or NaN values as different, like joins for database sources, similarly to merge(incomparables = FALSE).

Value

An object of the same type as x. The output has the following properties:

Methods

These function are generics, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.

Methods available in currently loaded packages:

See Also

Other joins: mutate-joins, nest_join()

Examples

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# "Filtering" joins keep cases from the LHS
band_members %>% semi_join(band_instruments)
band_members %>% anti_join(band_instruments)

# To suppress the message about joining variables, supply `by`
band_members %>% semi_join(band_instruments, by = "name")
# This is good practice in production code

Example output

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Joining, by = "name"
# A tibble: 2 x 2
  name  band   
  <chr> <chr>  
1 John  Beatles
2 Paul  Beatles
Joining, by = "name"
# A tibble: 1 x 2
  name  band  
  <chr> <chr> 
1 Mick  Stones
# A tibble: 2 x 2
  name  band   
  <chr> <chr>  
1 John  Beatles
2 Paul  Beatles

dplyr documentation built on June 19, 2021, 1:07 a.m.