This help topic is for R version 2.9.0. For the current version of R, try https://stat.ethz.ch/R-manual/R-patched/library/base/html/table.html
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 = if (useNA == "no") c(NA, NaN), useNA = c("no", 
    "ifany", "always"), dnn = list.names(...), deparse.level = 1) 

as.table(x, ...)
is.table(x)

## S3 method for class 'table'
as.data.frame(x, row.names = NULL, ...,
              responseName = "Freq")

Arguments

...

one of more objects which can be interpreted as factors (including character strings), or a list (or data frame) whose components can be so interpreted. (For as.table and as.data.frame, arguments passed to specific methods.)

exclude

levels to remove from all factors in .... If set to NULL, it implies useNA="always".

useNA

whether to include extra NA levels in the table.

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.

responseName

The name to be used for the column of table entries, usually counts.

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 and non-NULL (i.e., not by default), will table potentially drop levels of factor arguments.

Both exclude and useNA operate on an "all or none" basis. If you want to control the dimensions of a multiway table separately, modify each argument using factor or addNA

The summary method for class "table" (used 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 currently only handles 2-d tables).

Value

table() returns a contingency table, an object of class "table", an array of integer values. Note that unlike S the result is always an array, a 1D array if one factor is given.

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 entries (the latter as component named by responseName). 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

tabulate is the underlying function and allows finer control.

Use ftable for printing (and more) of multidimensional tables. margin.table, prop.table, addmargins.

Examples

require(stats) # for rpois and xtabs
## Simple frequency distribution
table(rpois(100,5))
## Check the design:
with(warpbreaks, table(wool, tension))
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")
print(table(b,d), zero.print = ".")

## NA counting:
is.na(d) <- 3:4
d. <- addNA(d)
d.[1:7]
table(d.) # ", exclude = NULL" is not needed
## i.e., if you want to count the NA's of 'd', use
table(d, useNA="ifany")

## Two-way tables with NA counts. The 3rd variant is absurd, but shows
## something that cannot be done using exclude or useNA. 
with(airquality,
   table(OzHi=Ozone > 80, Month, useNA="ifany"))
with(airquality,
   table(OzHi=Ozone > 80, Month, useNA="always"))
with(airquality,
   table(OzHi=Ozone > 80, addNA(Month)))

[Package base version 2.9.0 ]