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

Source: R/joins_filtering.R
filter_joins.Rd

  • semi_join() return all rows from x with a match in y.

  • anti_join() return all rows from x without a match in y.

Usage

anti_join(x, y, by = NULL, copy = FALSE, ..., na_matches = c("na", "never"))

semi_join(x, y, by = NULL, copy = FALSE, ..., na_matches = c("na", "never"))

Arguments

x, y

The data.frames to join.

by

A character vector of variables to join by. If NULL, the default, *_join() will do a natural join, using all variables with common names across the two tables. A message lists the variables so that you can check they're right (to suppress the message, simply explicitly list the variables that you want to join).

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.

copy

Ignored. Included for compatibility with dplyr, where it allows y to come from a different data source.

...

Ignored. Included for compatibility with dplyr.

na_matches

Should NA and NaN values match one another?

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

Use "never" to always treat two NA or NaN values as different, so that a row of x with a missing value in any of its keys never has a match in y.

Examples

table1 <- data.frame(
  pupil = rep(1:3, each = 2),
  test = rep(c("A", "B"), 3),
  score = c(60, 70, 65, 80, 85, 70),
  stringsAsFactors = FALSE
)
table2 <- table1[c(1, 3, 4), ]

table1 %>% anti_join(table2, by = c("pupil", "test"))
#>   pupil test score
#> 1     1    B    70
#> 2     3    A    85
#> 3     3    B    70
table1 %>% semi_join(table2, by = c("pupil", "test"))
#>   pupil test score
#> 1     1    A    60
#> 2     2    A    65
#> 3     2    B    80

sensors <- data.frame(site = c("north", NA, "south"), reading = c(4.2, 3.9, 5.1))
sites <- data.frame(site = c("north", NA))
semi_join(sensors, sites, by = "site")
#>    site reading
#> 1 north     4.2
#> 2  <NA>     3.9
semi_join(sensors, sites, by = "site", na_matches = "never")
#>    site reading
#> 1 north     4.2