| merge {base} | 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"), ...)
x, y |
data frames, or objects to be coerced to one. |
by, by.x, by.y |
specifications of the common columns. See Details. |
all |
logical; all = L is shorthand for all.x = L and
all.y = L. |
all.x |
logical; if TRUE, then extra rows will be added to
the output, one for each row in x that 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 x and
y are included in the output. |
all.y |
logical; analogous to all.x above. |
sort |
logical. Should the results be sorted on the by
columns? |
suffixes |
character(2) specifying the suffixes to be used for
making non-by names() unique. |
... |
arguments to be passed to or from methods. |
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. Columns can be specified by name, number
or by a logical vector: the name "row.names" or the number
0 specifies the row names. 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.
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 remaining columns in the data frames have any common names,
these have suffixes (".x" and ".y" by default)
appended to make the names of the result unique.
Prior to R 2.4.0 the complexity was proportional to the product of
the numbers of rows of x and y. As from R 2.4.0 it is
proportional to the length of the answer, which can be much less if
there are few matches (for example, only 1–1 matches).
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.
## 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)