stat.table creates tabular summaries of the data, using a
limited set of functions. A list of index variables is used
to cross-classify summary statistics. It does NOT work inside
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A factor, or list of factors, used for cross-classification. If the list is named, then the names will be used when printing the table. This feature can be used to give informative labels to the variables.
A function call, or list of function calls. Only a limited set of functions may be called (See Details below). If the list is named, then the names will be used when printing the table.
an optional data frame containing the variables to be tabulated. If this is omitted, the variables will be searched for in the calling environment.
a logical scalar or vector indicating which marginal
tables are to be calculated. If a vector, it should be the same
length as the
an object of class
a scalar giving the minimum column width when printing.
a scalar, or named vector, giving the number of digits to print after the decimal point. If a named vector is used, the names should correspond to one of the permitted functions (See Details below) and all results obtained with that function will be printed with the same precision.
further arguments passed to other print methods.
This function is similar to
tapply, with some enhancements:
multiple summaries of multiple variables may be mixed in the
same table; marginal tables may be calculated; columns and rows may
be given informative labels; pretty printing may be controlled by the
associated print method.
This function is not a replacement for
tapply as it also has
some limitations. The only functions that may be used in the
contents argument are:
count() function, which is the default, simply creates a
contingency table of counts. The other functions are applied to
each cell created by combinations of the
An object of class
stat.table, which is a multi-dimensional
array. A print method is available to create formatted one-way and
The permitted functions in the contents list
are defined inside
stat.table. They have the same interface as
the functions callable from the command line, except for two
differences. If there is an argument
na.rm then its default
value is always
TRUE. A second difference is that the
quantile function can only produce a single quantile in each call.
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data(warpbreaks) # A one-way table stat.table(tension,list(count(),mean(breaks)),data=warpbreaks) # The same table with informative labels stat.table(index=list("Tension level"=tension),list(N=count(), "mean number of breaks"=mean(breaks)),data=warpbreaks) # A two-way table stat.table(index=list(tension,wool),mean(breaks),data=warpbreaks) # The same table with margins over tension, but not wool stat.table(index=list(tension,wool),mean(breaks),data=warpbreaks, margins=c(TRUE, FALSE)) # A table of column percentages stat.table(list(tension,wool), percent(tension), data=warpbreaks) # Cell percentages, with margins stat.table(list(tension,wool),percent(tension,wool), margin=TRUE, data=warpbreaks) # A table with multiple statistics # Note how each statistic has its own default precision a <- stat.table(index=list(wool,tension), contents=list(count(),mean(breaks),percent (wool)), data=warpbreaks) print(a) # Print the percentages rounded to the nearest integer print(a, digits=c(percent=0))