merge {base}

R Documentation

Merge Two Data Frames

Description

Merge two data frames by common columns or row names, or do other versions of database join operations.

Usage

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"), incomparables = NULL, ...)

Arguments

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.
incomparables	values which cannot be matched. See match.
...	arguments to be passed to or from methods.

Details

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. For the precise meaning of ‘match’, see match.

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.

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.

Value

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.

See Also

data.frame, by, cbind

Examples

## 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

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