merge | R Documentation |
Merge two data frames by common columns or row names, or do other versions of database join operations.
merge(x, y, ...) ## Default S3 method: merge(x, y, ...) ## S3 method for class 'data.frame' merge(x, y, by = intersect(names(x), names(y)), by.x = by, by.y = by, all = FALSE, all.x = all, all.y = all, sort = TRUE, suffixes = c(".x",".y"), no.dups = TRUE, incomparables = NULL, ...)
x, y |
data frames, or objects to be coerced to one. |
by, by.x, by.y |
specifications of the columns used for merging. See ‘Details’. |
all |
logical; |
all.x |
logical; if |
all.y |
logical; analogous to |
sort |
logical. Should the result be sorted on the |
suffixes |
a character vector of length 2 specifying the suffixes
to be used for making unique the names of columns in the result
which are not used for merging (appearing in |
no.dups |
logical indicating that |
incomparables |
values which cannot be matched. See
|
... |
arguments to be passed to or from methods. |
merge
is a generic function whose principal method is for data
frames: the default method coerces its arguments to data frames and
calls the "data.frame"
method.
By default the data frames are merged on the columns with names they
both have, but separate specifications of the columns can be given by
by.x
and by.y
. The rows in the two data frames that
match on the specified columns are extracted, and joined together. If
there is more than one match, all possible matches contribute one row
each. For the precise meaning of ‘match’, see
match
.
Columns to merge on can be specified by name, number or by a logical
vector: the name "row.names"
or the number 0
specifies
the row names. If specified by name it must correspond uniquely to a
named column in the input.
If by
or both by.x
and by.y
are of length 0 (a
length zero vector or NULL
), the result, r
, is the
Cartesian product of x
and y
, i.e.,
dim(r) = c(nrow(x)*nrow(y), ncol(x) + ncol(y))
.
If all.x
is true, all the non matching cases of x
are
appended to the result as well, with NA
filled in the
corresponding columns of y
; analogously for all.y
.
If the columns in the data frames not used in merging have any common
names, these have suffixes
(".x"
and ".y"
by
default) appended to try to make the names of the result unique. If
this is not possible, an error is thrown.
If a by.x
column name matches one of y
, and if
no.dups
is true (as by default), the y version gets suffixed as
well, avoiding duplicate column names in the result.
The complexity of the algorithm used is proportional to the length of the answer.
In SQL database terminology, the default value of all = FALSE
gives a natural join, a special case of an inner
join. Specifying all.x = TRUE
gives a left (outer)
join, all.y = TRUE
a right (outer) join, and both
(all = TRUE
) a (full) outer join. DBMSes do not match
NULL
records, equivalent to incomparables = NA
in R.
A data frame. The rows are by default lexicographically sorted on the
common columns, but for sort = FALSE
are in an unspecified order.
The columns are the common columns followed by the
remaining columns in x
and then those in y
. If the
matching involved row names, an extra character column called
Row.names
is added at the left, and in all cases the result has
‘automatic’ row names.
This is intended to work with data frames with vector-like columns: some aspects work with data frames containing matrices, but not all.
Currently long vectors are not accepted for inputs, which are thus restricted to less than 2^31 rows. That restriction also applies to the result for 32-bit platforms.
data.frame
,
by
,
cbind
.
dendrogram
for a class which has a merge
method.
authors <- data.frame( ## I(*) : use character columns of names to get sensible sort order surname = I(c("Tukey", "Venables", "Tierney", "Ripley", "McNeil")), nationality = c("US", "Australia", "US", "UK", "Australia"), deceased = c("yes", rep("no", 4))) authorN <- within(authors, { name <- surname; rm(surname) }) books <- data.frame( name = I(c("Tukey", "Venables", "Tierney", "Ripley", "Ripley", "McNeil", "R Core")), title = c("Exploratory Data Analysis", "Modern Applied Statistics ...", "LISP-STAT", "Spatial Statistics", "Stochastic Simulation", "Interactive Data Analysis", "An Introduction to R"), other.author = c(NA, "Ripley", NA, NA, NA, NA, "Venables & Smith")) (m0 <- merge(authorN, books)) (m1 <- merge(authors, books, by.x = "surname", by.y = "name")) m2 <- merge(books, authors, by.x = "name", by.y = "surname") stopifnot(exprs = { identical(m0, m2[, names(m0)]) as.character(m1[, 1]) == as.character(m2[, 1]) all.equal(m1[, -1], m2[, -1][ names(m1)[-1] ]) identical(dim(merge(m1, m2, by = NULL)), c(nrow(m1)*nrow(m2), ncol(m1)+ncol(m2))) }) ## "R core" is missing from authors and appears only here : merge(authors, books, by.x = "surname", by.y = "name", all = TRUE) ## example of using 'incomparables' x <- data.frame(k1 = c(NA,NA,3,4,5), k2 = c(1,NA,NA,4,5), data = 1:5) y <- data.frame(k1 = c(NA,2,NA,4,5), k2 = c(NA,NA,3,4,5), data = 1:5) merge(x, y, by = c("k1","k2")) # NA's match merge(x, y, by = "k1") # NA's match, so 6 rows merge(x, y, by = "k2", incomparables = NA) # 2 rows
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