See join for a description of the general purpose of the
functions.
Usage
## S3 method for class 'tbl_df'
inner_join(x, y, by = NULL, copy = FALSE,
suffix = c(".x", ".y"), ...)
## S3 method for class 'tbl_df'
left_join(x, y, by = NULL, copy = FALSE, suffix = c(".x",
".y"), ...)
## S3 method for class 'tbl_df'
right_join(x, y, by = NULL, copy = FALSE,
suffix = c(".x", ".y"), ...)
## S3 method for class 'tbl_df'
full_join(x, y, by = NULL, copy = FALSE, suffix = c(".x",
".y"), ...)
## S3 method for class 'tbl_df'
semi_join(x, y, by = NULL, copy = FALSE, ...)
## S3 method for class 'tbl_df'
anti_join(x, y, by = NULL, copy = FALSE, ...)
Arguments
x
tbls to join
y
tbls 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
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 diambiguate them.
...
included for compatibility with the generic; otherwise ignored.
Examples
if (require("Lahman")) {
batting_df <- tbl_df(Batting)
person_df <- tbl_df(Master)
uperson_df <- tbl_df(Master[!duplicated(Master$playerID), ])
# Inner join: match batting and person data
inner_join(batting_df, person_df)
inner_join(batting_df, uperson_df)
# Left join: match, but preserve batting data
left_join(batting_df, uperson_df)
# Anti join: find batters without person data
anti_join(batting_df, person_df)
# or people who didn't bat
anti_join(person_df, batting_df)
}