Hi all,
Attached is both a patch file for and a patched version of table.Rd.
The change is to add the following:
\concept{counts}
\concept{frequencies}
\concept{occurrences}
\concept{contingency table}
to enable help.search() to locate table() using the aforementioned
search terms.
This came up again this weekend and going back to the archives, these
seem to cover a significant proportion of the common search terms that
have been mentioned in relevant posts where it was suggested by the
responder to see ?table.
HTH,
Marc Schwartz
--- table.Rd 2005-10-06 07:50:32.000000000 -0500
+++ table-patched.Rd 2005-11-28 14:47:53.000000000 -0600
@@ -7,6 +7,10 @@
\alias{as.table}
\alias{as.table.default}
\alias{is.table}
+\concept{counts}
+\concept{frequencies}
+\concept{occurrences}
+\concept{contingency table}
\description{
\code{table} uses the cross-classifying factors to build a contingency
table of the counts at each combination of factor levels.
\name{table}
\title{Cross Tabulation and Table Creation}
\alias{table}
\alias{summary.table}
\alias{print.summary.table}
\alias{as.data.frame.table}
\alias{as.table}
\alias{as.table.default}
\alias{is.table}
\concept{counts}
\concept{frequencies}
\concept{occurrences}
\concept{contingency table}
\description{
\code{table} uses the cross-classifying factors to build a contingency
table of the counts at each combination of factor levels.
}
\usage{
table(\dots, exclude = c(NA, NaN), dnn = list.names(...),
deparse.level = 1)
as.table(x, \dots)
is.table(x)
as.data.frame.table(x, row.names = NULL, optional = FALSE,
responseName = "Freq")
}
\arguments{
\item{\dots}{objects which can be interpreted as factors (including
character strings), or a list (or data frame) whose components can
be so interpreted. (For \code{as.table}, arguments passed to
specific methods.)}
\item{exclude}{values to use in the exclude argument of \code{\link{factor}}
when interpreting non-factor objects; if specified, levels to remove
from all factors in \code{\dots}.}
\item{dnn}{the names to be given to the dimensions in the result (the
\emph{dimnames names}).}
\item{deparse.level}{controls how the default \code{dnn} is
constructed. See details.}
\item{x}{an arbitrary \R object, or an object inheriting from class
\code{"table"} for the \code{as.data.frame} method.}
\item{row.names}{a character vector giving the row names for the data
frame.}
\item{optional}{a logical controlling whether row names are set.
Currently not used.}
\item{responseName}{The name to be used for the column of
table entries, usually counts.}
}
\value{
\code{table()} returns a \emph{contingency table}, an object of
\code{\link[base]{class}} \code{"table"}, an array of integer values.
There is a \code{summary} method for objects created by \code{table}
or \code{\link{xtabs}}, which gives basic information and performs a
chi-squared test for independence of factors (note that the function
\code{\link{chisq.test}} currently only handles 2-d tables).
\code{as.table} and \code{is.table} coerce to and test for contingency
table, respectively.
The \code{as.data.frame} method for objects inheriting from class
\code{"table"} can be used to convert the array-based representation
of a contingency table to a data frame containing the classifying
factors and the corresponding entries (the latter as component
named by \code{responseName}). This is the inverse of \code{\link{xtabs}}.
}
\details{
If the argument \code{dnn} is not supplied, the internal function
\code{list.names} is called to compute the \sQuote{dimname names}. If the
arguments in \code{\dots} are named, those names are used. For the
remaining arguments, \code{deparse.level = 0} gives an empty name,
\code{deparse.level = 1} uses the supplied argument if it is a symbol,
and \code{deparse.level = 2} will deparse the argument.
Only when \code{exclude} is specified (i.e., not by default), will
\code{table} drop levels of factor arguments potentially.
Note that \code{as.data.frame.table} is also the \code{"table"} method
for \code{\link{as.data.frame}}, but the \code{responseName} argument
can only be given if it is called explicitly.
}
\seealso{Use \code{\link{ftable}} for printing (and more) of
multidimensional tables.
}
\references{
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
\emph{The New S Language}.
Wadsworth \& Brooks/Cole.
}
\examples{
require(stats) # for rpois and xtabs
## Simple frequency distribution
table(rpois(100,5))
attach(warpbreaks)
## Check the design:
table(wool, tension)
detach()
table(state.division, state.region)
# simple two-way contingency table
with(airquality, table(cut(Temp, quantile(Temp)), Month))
a <- letters[1:3]
table(a, sample(a)) # dnn is c("a", "")
table(a, sample(a), deparse.level = 0) # dnn is c("", "")
table(a, sample(a), deparse.level = 2) # dnn is c("a", "sample(a)")
## xtabs() <-> as.data.frame.table() :
UCBAdmissions ## already a contingency table
DF <- as.data.frame(UCBAdmissions)
class(tab <- xtabs(Freq ~ ., DF)) # xtabs & table
## tab *is* "the same" as the original table:
all(tab == UCBAdmissions)
all.equal(dimnames(tab), dimnames(UCBAdmissions))
a <- rep(c(NA, 1/0:3), 10)
table(a)
table(a, exclude=NULL)
b <- factor(rep(c("A","B","C"), 10))
table(b)
table(b, exclude="B")
d <- factor(rep(c("A","B","C"), 10), levels=c("A","B","C","D","E"))
table(d, exclude="B")
## NA counting:
is.na(d) <- 3:4
d <- factor(d, exclude=NULL)
d[1:7]
table(d, exclude = NULL)
}
\keyword{category}
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