xtabs {stats}R Documentation

Cross Tabulation


Create a contingency table from cross-classifying factors, usually contained in a data frame, using a formula interface.


xtabs(formula = ~., data = parent.frame(), subset, na.action,
      exclude = c(NA, NaN), drop.unused.levels = FALSE)


formula a formula object with the cross-classifying variables, separated by +, on the right hand side. Interactions are not allowed. On the left hand side, one may optionally give a vector or a matrix of counts; in the latter case, the columns are interpreted as corresponding to the levels of a variable. This is useful if the data has already been tabulated, see the examples below.
data a data frame, list or environment containing the variables to be cross-tabulated.
subset an optional vector specifying a subset of observations to be used.
na.action a function which indicates what should happen when the data contain NAs.
exclude a vector of values to be excluded when forming the set of levels of the classifying factors.
drop.unused.levels a logical indicating whether to drop unused levels in the classifying factors. If this is FALSE and there are unused levels, the table will contain zero marginals, and a subsequent chi-squared test for independence of the factors will not work.


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 currently only handles 2-d tables).

If a left hand side is given in formula, its entries are simply summed over the cells corresponding to the right hand side; this also works if the lhs does not give counts.


A contingency table in array representation of class c("xtabs", "table"), with a "call" attribute storing the matched call.

See Also

table for “traditional” cross-tabulation, and as.data.frame.table which is the inverse operation of xtabs (see the DF example below).


## 'esoph' has the frequencies of cases and controls for all levels of
## the variables 'agegp', 'alcgp', and 'tobgp'.
xtabs(cbind(ncases, ncontrols) ~ ., data = esoph)
## Output is not really helpful ... flat tables are better:
ftable(xtabs(cbind(ncases, ncontrols) ~ ., data = esoph))
## In particular if we have fewer factors ...
ftable(xtabs(cbind(ncases, ncontrols) ~ agegp, data = esoph))

## This is already a contingency table in array form.
DF <- as.data.frame(UCBAdmissions)
## Now 'DF' is a data frame with a grid of the factors and the counts
## in variable 'Freq'.
## Nice for taking margins ...
xtabs(Freq ~ Gender + Admit, DF)
## And for testing independence ...
summary(xtabs(Freq ~ ., DF))

## Create a nice display for the warp break data.
warpbreaks$replicate <- rep(1:9, len = 54)
ftable(xtabs(breaks ~ wool + tension + replicate, data = warpbreaks))

[Package stats version 2.2.1 Index]