cbind(..., deparse.level = 1)
rbind(..., deparse.level = 1)"data.frame" method of cbind these can be further
arguments to data.frame such as stringsAsFactors.)deparse.level = 0 constructs no labels; the default,
deparse.level = 1 or 2 constructs labels from the argument
names, see the ‘Value’ section below.... arguments
column-wise or row-wise. (Exception: if there are no inputs or all
the inputs are NULL, the value is NULL.)The type of a matrix result determined from the highest type of any of
the inputs in the hierarchy raw < logical < integer < double < complex <
character < list .For cbind (rbind) the column (row) names are taken from
the colnames (rownames) of the arguments if these are
matrix-like. Otherwise from the names of the arguments or where those
are not supplied and deparse.level > 0, by deparsing the
expressions given, for deparse.level = 1 only if that gives a
sensible name (a ‘symbol’, see is.symbol).For cbind row names are taken from the first argument with
appropriate names: rownames for a matrix, or names for a vector of
length the number of rows of the result.For rbind column names are taken from the first argument with
appropriate names: colnames for a matrix, or names for a vector of
length the number of columns of the result.
cbind data frame method is just a wrapper for
data.frame(..., check.names = FALSE). This means that
it will split matrix columns in data frame arguments, and convert
character columns to factors unless stringsAsFactors = FALSE is
specified. The rbind data frame method first drops all zero-column and
zero-row arguments. (If that leaves none, it returns the first
argument with columns otherwise a zero-column zero-row data frame.)
It then takes the classes of the columns from the
first data frame, and matches columns by name (rather than by
position). Factors have their levels expanded as necessary (in the
order of the levels of the levelsets of the factors encountered) and
the result is an ordered factor if and only if all the components were
ordered factors. (The last point differs from S-PLUS.) Old-style
categories (integer vectors with levels) are promoted to factors.UseMethod(), but by C-internal dispatching.
Therefore there is no need for, e.g., rbind.default. The dispatch algorithm is described in the source file
(‘.../src/main/bind.c’) as cbind and rbind are S3 generic, with
methods for data frames. The data frame method will be used if at
least one argument is a data frame and the rest are vectors or
matrices. There can be other methods; in particular, there is one for
time series objects. See the section on ‘Dispatch’ for how
the method to be used is selected. In the default method, all the vectors/matrices must be atomic (see
vector) or lists. Expressions are not allowed.
Language objects (such as formulae and calls) and pairlists will be
coerced to lists: other objects (such as names and external pointers)
will be included as elements in a list result. Any classes the inputs
might have are discarded (in particular, factors are replaced by their
internal codes).
If there are several matrix arguments, they must all have the same
number of columns (or rows) and this will be the number of columns (or
rows) of the result. If all the arguments are vectors, the number of
columns (rows) in the result is equal to the length of the longest
vector. Values in shorter arguments are recycled to achieve this
length (with a warning if they are recycled only
fractionally).
When the arguments consist of a mix of matrices and vectors the number of columns (rows) of the result is determined by the number of columns (rows) of the matrix arguments. Any vectors have their values recycled or subsetted to achieve this length.
For cbind (rbind), vectors of zero length (including
NULL) are ignored unless the result would have zero rows
(columns), for S compatibility.
(Zero-extent matrices do not occur in S3 and are not ignored in R.)
c to combine vectors (and lists) as vectors,
data.frame to combine vectors and matrices as a data
frame.
m <- cbind(1, 1:7) # the '1' (= shorter vector) is recycled
m
m <- cbind(m, 8:14)[, c(1, 3, 2)] # insert a column
m
cbind(1:7, diag(3)) # vector is subset -> warning
cbind(0, rbind(1, 1:3))
cbind(I = 0, X = rbind(a = 1, b = 1:3)) # use some names
xx <- data.frame(I = rep(0,2))
cbind(xx, X = rbind(a = 1, b = 1:3)) # named differently
cbind(0, matrix(1, nrow = 0, ncol = 4)) #> Warning (making sense)
dim(cbind(0, matrix(1, nrow = 2, ncol = 0))) #-> 2 x 1
## deparse.level
dd <- 10
rbind(1:4, c = 2, "a++" = 10, dd, deparse.level = 0) # middle 2 rownames
rbind(1:4, c = 2, "a++" = 10, dd, deparse.level = 1) # 3 rownames (default)
rbind(1:4, c = 2, "a++" = 10, dd, deparse.level = 2) # 4 rownames
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