Description Usage Arguments Join types Grouping
These are generic functions that dispatch to individual tbl methods - see the
method documentation for details of individual data sources. x and
y should usually be from the same data source, but if copy is
TRUE, y will automatically be copied to the same source as
x - this may be an expensive operation.
1 2 3 4 5 6 7 8 9 10 11 | inner_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
left_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
right_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
full_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
semi_join(x, y, by = NULL, copy = FALSE, ...)
anti_join(x, y, by = NULL, copy = FALSE, ...)
|
x, y |
tbls to join |
by |
a character vector of variables to join by. If To join by different variables on x and y use a named vector.
For example, |
copy |
If |
suffix |
If there are non-joined duplicate variables in |
... |
other parameters passed onto methods |
Currently dplyr supports four join types:
inner_joinreturn all rows from x where there are matching
values in y, and all columns from x and y. If there are multiple matches
between x and y, all combination of the matches are returned.
left_joinreturn all rows from x, and all columns from x
and y. Rows in x with no match in y will have NA values in the new
columns. If there are multiple matches between x and y, all combinations
of the matches are returned.
right_joinreturn all rows from y, and all columns from x
and y. Rows in y with no match in x will have NA values in the new
columns. If there are multiple matches between x and y, all combinations
of the matches are returned.
semi_joinreturn all rows from x where there are matching
values in y, keeping just columns from x.
A semi join differs from an inner join because an inner join will return
one row of x for each matching row of y, where a semi
join will never duplicate rows of x.
anti_joinreturn all rows from x where there are not
matching values in y, keeping just columns from x.
full_joinreturn all rows and all columns from both x and y.
Where there are not matching values, returns NA for the one missing.
Groups are ignored for the purpose of joining, but the result preserves
the grouping of x.
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