cbind {base}  R Documentation 
Take a sequence of vector, matrix or dataframe arguments and combine by columns or rows, respectively. These are generic functions with methods for other R classes.
cbind(..., deparse.level = 1) rbind(..., deparse.level = 1) ## S3 method for class 'data.frame' rbind(..., deparse.level = 1, make.row.names = TRUE, stringsAsFactors = default.stringsAsFactors(), factor.exclude = TRUE)
... 
(generalized) vectors or matrices. These can be given as named
arguments. Other R objects may be coerced as appropriate, or S4
methods may be used: see sections ‘Details’ and
‘Value’. (For the 
deparse.level 
integer controlling the construction of labels in
the case of nonmatrixlike arguments (for the default method): 
make.row.names 
(only for data frame method:) logical
indicating if unique and valid 
stringsAsFactors 
logical, passed to 
factor.exclude 
if the data frames contain factors, the default

The functions 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. If some of the arguments are of an
S4 class, i.e., isS4(.)
is true, S4 methods are sought
also, and the hidden cbind
/ rbind
functions
from package methods maybe called, which in turn build on
cbind2
or rbind2
, respectively. In that
case, deparse.level
is obeyed, similarly to the default method.
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.
(Zeroextent matrices do not occur in S3 and are not ignored in R.)
Matrices are restricted to less than 2^31 rows and columns even on 64bit systems. So input vectors have the same length restriction: as from R 3.2.0 input matrices with more elements (but meeting the row and column restrictions) are allowed.
For the default method, a matrix combining the ...
arguments
columnwise or rowwise. (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
matrixlike. 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.
The 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 zerocolumn and
zerorow arguments. (If that leaves none, it returns the first
argument with columns otherwise a zerocolumn zerorow 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 level sets 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 SPLUS.) Oldstyle
categories (integer vectors with levels) are promoted to factors.
Note that for result column j
, factor(., exclude = X(j))
is applied, where
X(j) := if(isTRUE(factor.exclude)) { if(!NA.lev[j]) NA # else NULL } else factor.exclude
where NA.lev[j]
is true iff any contributing data frame has had a
factor
in column j
with an explicit NA
level.
The method dispatching is not done via
UseMethod()
, but by Cinternal 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
For each argument we get the list of possible class memberships from the class attribute.
We inspect each class in turn to see if there is an applicable method.
If we find a method, we use it. Otherwise, if there was an S4 object among the arguments, we try S4 dispatch; otherwise, we use the default code.
(Before R 4.0.0, an applicable method found was used only if identical to any method determined for prior arguments.)
If you want to combine other objects with data frames, it may be necessary to coerce them to data frames first. (Note that this algorithm can result in calling the data frame method if all the arguments are either data frames or vectors, and this will result in the coercion of character vectors to factors.)
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
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 ## cheap row names: b0 < gl(3,4, labels=letters[1:3]) bf < setNames(b0, paste0("o", seq_along(b0))) df < data.frame(a = 1, B = b0, f = gl(4,3)) df. < data.frame(a = 1, B = bf, f = gl(4,3)) new < data.frame(a = 8, B ="B", f = "1") (df1 < rbind(df , new)) (df.1 < rbind(df., new)) stopifnot(identical(df1, rbind(df, new, make.row.names=FALSE)), identical(df1, rbind(df., new, make.row.names=FALSE)))