dplyr joins for PKNCA
Usage
# S3 method for class 'PKNCAresults'
inner_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAresults'
left_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAresults'
right_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAresults'
full_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAconc'
inner_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAconc'
left_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAconc'
right_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAconc'
full_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAdose'
inner_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAdose'
left_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAdose'
right_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
# S3 method for class 'PKNCAdose'
full_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c(".x", ".y"),
...,
keep = FALSE
)
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 join specification created with
join_by()
, or a character vector of variables to join by.If
NULL
, the default,*_join()
will perform a natural join, using all variables in common acrossx
andy
. A message lists the variables so that you can check they're correct; suppress the message by supplyingby
explicitly.To join on different variables between
x
andy
, use ajoin_by()
specification. For example,join_by(a == b)
will matchx$a
toy$b
.To join by multiple variables, use a
join_by()
specification with multiple expressions. For example,join_by(a == b, c == d)
will matchx$a
toy$b
andx$c
toy$d
. If the column names are the same betweenx
andy
, you can shorten this by listing only the variable names, likejoin_by(a, c)
.join_by()
can also be used to perform inequality, rolling, and overlap joins. See the documentation at ?join_by for details on these types of joins.For simple equality joins, you can alternatively specify a character vector of variable names to join by. For example,
by = c("a", "b")
joinsx$a
toy$a
andx$b
toy$b
. If variable names differ betweenx
andy
, use a named character vector likeby = c("x_a" = "y_a", "x_b" = "y_b")
.To perform a cross-join, generating all combinations of
x
andy
, seecross_join()
.- copy
If
x
andy
are not from the same data source, andcopy
isTRUE
, theny
will be copied into the same src asx
. 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
andy
, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.- ...
Other parameters passed onto methods.
- keep
Should the join keys from both
x
andy
be preserved in the output?If
NULL
, the default, joins on equality retain only the keys fromx
, while joins on inequality retain the keys from both inputs.If
TRUE
, all keys from both inputs are retained.If
FALSE
, only keys fromx
are retained. For right and full joins, the data in key columns corresponding to rows that only exist iny
are merged into the key columns fromx
. Can't be used when joining on inequality conditions.
See also
Other dplyr verbs:
filter.PKNCAresults()
,
group_by.PKNCAresults()
,
mutate.PKNCAresults()