| table {base} | R Documentation |
table uses the cross-classifying factors to build a contingency
table of the counts at each combination of factor levels.
table(..., exclude = c(NA, NaN), dnn, deparse.level = 1)
as.table(x, ...)
is.table(x)
as.data.frame.table(x, row.names = NULL, optional = FALSE, ...)
... |
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 |
dnn |
the names to be given to the dimensions in the result ('the dimname names'). |
deparse.level |
controls how the default |
x |
an arbitrary R object. |
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. |
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.
There is a summary method for contingency table 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.
as.data.frame.table is a method for the generic function
as.data.frame 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.
## Simple frequency distribution
table(rpois(100,5))
data(warpbreaks)
attach(warpbreaks)
## Check the design:
table(wool, tension)
data(state)
table(state.division, state.region)
data(airquality)
attach(airquality)
# simple two-way contingency table
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))