fjoin_right_anti: Right anti-join

In fjoin: Data Frame Joins Leveraging 'data.table'

Right anti-join

Description

The anti-join of y in a join of x and y, i.e. the rows of y that do not join.

Usage

fjoin_right_anti(
  x = NULL,
  y = NULL,
  on,
  match.na = FALSE,
  mult.x = "all",
  mult.y = "all",
  select = NULL,
  do = !(is.null(x) && is.null(y)),
  show = !do
)

Arguments

x, y	data.frame-like objects (plain, data.table, tibble, sf, list, etc.) or else both omitted for a mock join statement with no data. See Details.
on	A character vector of join predicates, e.g. c("id", "col_x == col_y", "date > date", "cost <= budget"), or else NA for a natural join (an equality join on all same-named columns).
match.na	Whether to allow equality matches between NAs or NaNs. Default FALSE.
mult.x, mult.y	When a row of x (y) has multiple matching rows in y (x), which to accept: "all" (the default), "first", or "last". May be used in combination.
select	Character vector of columns to be selected from y. NULL (the default) selects all columns. Join columns are always selected.
do	Whether to execute the join. If FALSE, show is set to TRUE and the data.table code for the join is printed to the console instead. Default is TRUE unless x and y are both omitted/NULL, in which case a mock join statement is produced. See Details.
show	Whether to print the data.table code for the join to the console. Default is the opposite of do. If x and y are both omitted/NULL, mock join code is displayed.

Details

Details are as for e.g. fjoin_inner except for arguments controlling the order and prefixing of output columns, which do not apply. Output class is determined by y.

Value

A data.frame, data.table, (grouped) tibble, sf, or sf-tibble, or else NULL if do is FALSE. See Details.

See Also

See the package-level documentation fjoin for related functions.

Examples

# ---------------------------------------------------------------------------
# Semi- and anti-joins: basic usage
# ---------------------------------------------------------------------------

# data frames
x <- data.table::fread(data.table = FALSE, input = "
country   pop_m
Australia  27.2
Brazil    212.0
Chad        3.0
")

y <- data.table::fread(data.table = FALSE, input = "
country forest_pc
Brazil       59.1
Chad          3.2
Denmark      15.8
")

# full join with `indicate = TRUE` for comparison
fjoin_full(x, y, on = "country", indicate = TRUE)

fjoin_semi(x, y, on = "country")
fjoin_anti(x, y, on = "country")
fjoin_right_semi(x, y, on = "country")
fjoin_right_anti(x, y, on = "country")

# ---------------------------------------------------------------------------
# `mult.x` and `mult.y` support
# ---------------------------------------------------------------------------

# data frames
events <- data.table::fread(data.table = FALSE, input = "
event_id event_ts
       1       10
       2       20
       3       40
")

reactions <- data.table::fread(data.table = FALSE, input = "
reaction_id reaction_ts
          1          30
          2          50
          3          60
")
# ---------------------------------------------------------------------------

# for each event, the next reaction, provided there was no intervening event (1:1)
fjoin_full(
  events,
  reactions,
  on = c("event_ts < reaction_ts"),
  mult.x = "first",
  mult.y = "last",
  indicate = TRUE
)

fjoin_semi(
  events,
  reactions,
  on = c("event_ts < reaction_ts"),
  mult.x = "first",
  mult.y = "last"
)

fjoin_anti(
  events,
  reactions,
  on = c("event_ts < reaction_ts"),
  mult.x = "first",
  mult.y = "last"
)

# ---------------------------------------------------------------------------
# Natural join
# ---------------------------------------------------------------------------
fjoin_semi(x, y, on = NA)

fjoin_anti(x, y, on = NA)

# ---------------------------------------------------------------------------
# Mock join
# ---------------------------------------------------------------------------
fjoin_semi(on="id")

fjoin_semi(on=c("id", "date"))

fjoin_semi(on=c("id"), mult.y = "last")

fjoin documentation built on Dec. 11, 2025, 5:07 p.m.