\HeaderA{table}{Cross Tabulation and Table Creation}{table}
\aliasA{as.data.frame.table}{table}{as.data.frame.table}
\aliasA{as.table}{table}{as.table}
\methaliasA{as.table.default}{table}{as.table.default}
\aliasA{is.table}{table}{is.table}
\aliasA{print.summary.table}{table}{print.summary.table}
\aliasA{summary.table}{table}{summary.table}
\keyword{category}{table}
\begin{Description}\relax
\code{table} uses the cross-classifying factors to build a contingency
table of the counts at each combination of factor levels.
\end{Description}
\begin{Usage}
\begin{verbatim}
table(..., exclude = c(NA, NaN), dnn = list.names(...),
      deparse.level = 1)
as.table(x, ...)
is.table(x)

## S3 method for class 'table':
as.data.frame(x, row.names = NULL, optional = FALSE,
              responseName = "Freq", ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{...}] objects which can be interpreted as factors (including
character strings), or a list (or data frame) whose components can
be so interpreted
\item[\code{exclude}] values to use in the exclude argument of \code{\LinkA{factor}{factor}}
when interpreting non-factor objects; if specified, levels to remove
from all factors in \code{...}.
\item[\code{dnn}] the names to be given to the dimensions in the result (the
\emph{dimnames names}).
\item[\code{deparse.level}] controls how the default \code{dnn} is
constructed.  See details.
\item[\code{x}] an arbitrary \R{} object, or an object inheriting from class
\code{"table"} for the \code{as.data.frame} method.
\item[\code{row.names}] a character vector giving the row names for the data
frame.
\item[\code{optional}] a logical controlling whether row names are set.
Currently not used.
\item[\code{responseName}] The name to be used for the column of
table entries, usually counts.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
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{...} 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.
\end{Details}
\begin{Value}
\code{table()} returns a \emph{contingency table}, an object of
\code{\LinkA{class}{class}} \code{"table"}, an array of integer values.

There is a \code{summary} method for objects created by \code{table}
or \code{\LinkA{xtabs}{xtabs}}, which gives basic information and performs a
chi-squared test for independence of factors (note that the function
\code{\LinkA{chisq.test}{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{\LinkA{xtabs}{xtabs}}.
\end{Value}
\begin{References}\relax
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
\emph{The New S Language}.
Wadsworth \& Brooks/Cole.
\end{References}
\begin{SeeAlso}\relax
Use \code{\LinkA{ftable}{ftable}} for printing (and more) of
multidimensional tables.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
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)
\end{ExampleCode}
\end{Examples}

