cbind
Building a Matrix from Columns or Rows
Description
Returns a matrix that is pieced together from the specified vectors
and/or matrices. The functions cbind and rbind are generic.
In particular, there are cbind methods for data frames and time series,
and rbind method for data frames.
Usage
cbind(..., deparse.level = 1)
## S3 method for class 'ts':
cbind(..., deparse.level = 1)
rbind(..., deparse.level = 1)
Arguments
| ... |
vectors and/or matrices. Missing values (NAs) are allowed.
For cbind.ts method, this argument can be one or more time series
objects or objects can be coerced to time series. All these time series
must have same frequency.
|
| deparse.level |
the value determining the construction of labels (column labels
for cbind or row labels for rbind).
This argument applies only to unnamed vector (non-matrix) arguments,
and only the following values are acceptable:
- If 0, the corresponding row or column has no label.
- If 1 (the default), the deparsed form is used only if
the argument is a simple name. Any other expression results in
no label.
- If 2, the label is the deparsed form of the argument.
For cbind.ts method, this argument is not used yet, but must
be default value 1.
|
Details
The default methods for cbind and rbind are built
into the generic functions. That is, there are no cbind.default or
rbind.default functions.
If any of the input data objects have classes, the appropriate S3 or S4
method is called. This method is found as follows: First, for each
argument with class XX it searches for an S3 method
"cbind.XX" (or "rbind.XX" when executing rbind).
If an S3 object has multiple classes, these are searched in order. If
an argument is an S4 object, the class and all of its superclasses are
searched. If this search produces the same S3 method for all arguments
with classes, it is called. If this search finds more than one S3
method, this is a conflict, and no S3 methods are called. In this case,
if any of the arguments are S4 objects, it calls methods:::cbind
(or methods:::rbind), which will repeatedly call
methods::cbind2 (or methods::rbind2) to process the
arguments two at a time. If neither an S3 or S4 method is found, the
arguments are processed as if they had no classes.
If several arguments are matrices, they must contain the same number
of rows (cbind) or columns (rbind).
In addition, all arguments that have names attributes must have
the same length, which also must match the number of rows/columns
of any matrix arguments.
Vector arguments are treated as row vectors by rbind and column
vectors by cbind. If all arguments are vectors, the result contains
as many rows or columns as the length of the longest vector. Shorter
vectors are repeated.
The
dimnames attribute of the returned matrix is constructed
as follows:
- For any matrix argument, its dimnames attribute is carried
over.
- For any vector argument with a names attribute,
the names attribute becomes the row (column) component
of dimnames for cbind (rbind). (Any vector
argument can be given in name=value form, where the name
specifies its corresponding dimnames entry.)
- If cbind is given more than one named vector or matrix,
the rownames of the result are the names of the first named vector
or matrix with rownames in the argument list
(and similarly for the column names the result of rbind).
cbind.ts is an invisible method, it uses the same way as ts.union
to combine one or more time series, and return the value as a time series(not data frames).
See ts.union for more details.
Value
returns a matrix composed of adjoining columns (cbind) or rows
(rbind). This matrix can have a dimnames attribute.
For cbind.ts method, returns a union time series.
Warning
When you write a function, you could build a matrix by using a statement
such as x <- cbind(x, tmp.vec) inside of a for loop.
Better yet, create a matrix that is the
final size before you enter the
for loop:
x <- matrix(nrow=n, ncol=p)
Then use replacement inside the
for loop:
This latter strategy uses much less memory than the method using
cbind. (Use the
cbind method only when you do not
know the eventual size of the matrix.)
See Also
Examples
# add column of ones
df <- data.frame(a = c(1:5), b = (1:5)^2)
cbind(1, df)
# add 2 new rows
rbind(df, c(2, 3), c(5, 6))
# 3 column matrix with column dimnames
cbind(Index = c(1:3), Age = c(30, 45, 34), Salary = c(500, 600, 550))
# 4 combining two named vectors
mil1 <- c(c=3,d=4,e=5)
mil2 <- c(f=6,g=7,h=8)
# column names will be mil1, mil2, rownames will be c, d, e
cbind(mil1, mil2)
# column names will be mil2, mil1, rownames will be f, g, h
cbind(mil2, mil1)
# combine time series.
# "mdeaths", "fdeaths" and "ldeaths" are data sets from R
cbind(mdeaths, fdeaths, ldeaths)
cbind(cbind(mdeaths, fdeaths), ldeaths)
# The dim names of above two examples are different.