| 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 = 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")
... |
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 |
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. |
responseName |
The name to be used for the column of table entries, usually counts. |
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.
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 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 entries (the latter as component
named by responseName). This is the inverse of xtabs.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
Use ftable for printing (and more) of
multidimensional tables. margin.table,
prop.table, addmargins.
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 <- factor(d, exclude=NULL)
d[1:7]
table(d, exclude = NULL)