table {base}R Documentation

Cross Tabulation and Table Creation

Description

table uses the cross-classifying factors to build a contingency table of the counts at each combination of factor levels.

Usage

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, ...)

Arguments

... objects which can be interpreted as factors (including character strings), or a list (or data frame) whose components can be so interpreted
exclude values to use in the exclude argument of factor when interpreting non-factor objects; if specified, levels to remove from all factors in ....
dnn the names to be given to the dimensions in the result (the dimnames names).
deparse.level controls how the default dnn is constructed. See details.
x an arbitrary R object, or an object inheriting from class "table" for the as.data.frame method.
row.names a character vector giving the row names for the data frame.
optional a logical controlling whether row names are set. Currently not used.

Details

If the argument dnn is not supplied, the internal function list.names is called to compute the ‘dimname names’. If the arguments in ... are named, those names are used. For the remaining arguments, deparse.level = 0 gives an empty name, deparse.level = 1 uses the supplied argument if it is a symbol, and deparse.level = 2 will deparse the argument.

Only when exclude is specified (i.e., not by default), will table drop levels of factor arguments potentially.

Value

table() returns a contingency table, an object of class "table", an array of integer values.
There is a summary method for objects created by table or xtabs, which gives basic information and performs a chi-squared test for independence of factors (note that the function chisq.test in package ctest currently only handles 2-d tables).
as.table and is.table coerce to and test for contingency table, respectively.
The as.data.frame method for objects inheriting from class "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 counts (the latter as component Freq). This is the inverse of xtabs.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

See Also

Use ftable for printing (and more) of multidimensional tables.

Examples

require(stats) # for rpois and xtabs
## Simple frequency distribution
table(rpois(100,5))
data(warpbreaks)
attach(warpbreaks)
## Check the design:
table(wool, tension)
data(state)
table(state.division, state.region)
detach()

data(airquality)
# 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() :
data(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)

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