Merge two data frames by common columns or row names, or do other versions of database join operations.
merge(x, y, ...) ## S3 method for class 'default': 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"), 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 = Lis shorthand for
all.x = Land
all.y = L, where
- logical; if
TRUE, then extra rows will be added to the output, one for each row in
xthat has no matching row in
y. These rows will have
NAs in those columns that are usually filled with values from
y. The default is
FALSE, so that only rows with data from both
yare included in the output.
- logical; analogous to
- logical. Should the result be sorted on the
- a character vector of length 2 specifying the suffixes to be used for making unique the names of columns in the result which not used for merging (appearing in
- 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
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.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
Columns to merge on can be specified by name, number or by a logical vector: the name
"row.names" or the number
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
If the columns in the data frames not used in merging have any common names, these have
".y" by default) appended to try to make the names of the result unique. If this is not possible, an error is thrown.
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.
## use character columns of names to get sensible sort order authors <- data.frame( surname = I(c("Tukey", "Venables", "Tierney", "Ripley", "McNeil")), nationality = c("US", "Australia", "US", "UK", "Australia"), deceased = c("yes", rep("no", 4))) 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")) (m1 <- merge(authors, books, by.x = "surname", by.y = "name")) (m2 <- merge(books, authors, by.x = "name", by.y = "surname")) stopifnot(as.character(m1[, 1]) == as.character(m2[, 1]), all.equal(m1[, -1], m2[, -1][ names(m1)[-1] ]), dim(merge(m1, m2, by = integer(0))) == c(36, 10)) ## "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 = c("k1","k2"), incomparables = NA) merge(x, y, by = "k1") # NA's match, so 6 rows merge(x, y, by = "k2", incomparables = NA) # 2 rows
Documentation reproduced from R 3.0.2. License: GPL-2.