# ftable

0th

Percentile

##### Flat Contingency Tables

Create flat contingency tables.

Keywords
category
##### Usage
ftable(x, ...)## S3 method for class 'default':
ftable(\dots, exclude = c(NA, NaN), row.vars = NULL,
col.vars = NULL)
##### Arguments
x, ...
Robjects which can be interpreted as factors (including character strings), or a list (or data frame) whose components can be so interpreted, or a contingency table object of class "table" or "ftable".
exclude
values to use in the exclude argument of factor when interpreting non-factor objects.
row.vars
a vector of integers giving the numbers of the variables, or a character vector giving the names of the variables to be used for the rows of the flat contingency table.
col.vars
a vector of integers giving the numbers of the variables, or a character vector giving the names of the variables to be used for the columns of the flat contingency table.
##### Details

ftable creates flat contingency tables. Similar to the usual contingency tables, these contain the counts of each combination of the levels of the variables (factors) involved. This information is then re-arranged as a matrix whose rows and columns correspond to unique combinations of the levels of the row and column variables (as specified by row.vars and col.vars, respectively). The combinations are created by looping over the variables in reverse order (so that the levels of the left-most variable vary the slowest). Displaying a contingency table in this flat matrix form (via print.ftable, the print method for objects of class "ftable") is often preferable to showing it as a higher-dimensional array.

ftable is a generic function. Its default method, ftable.default, first creates a contingency table in array form from all arguments except row.vars and col.vars. If the first argument is of class "table", it represents a contingency table and is used as is; if it is a flat table of class "ftable", the information it contains is converted to the usual array representation using as.ftable. Otherwise, the arguments should be Robjects which can be interpreted as factors (including character strings), or a list (or data frame) whose components can be so interpreted, which are cross-tabulated using table. Then, the arguments row.vars and col.vars are used to collapse the contingency table into flat form. If neither of these two is given, the last variable is used for the columns. If both are given and their union is a proper subset of all variables involved, the other variables are summed out.

When the arguments are Rexpressions interpreted as factors, additional arguments will be passed to table to control how the variable names are displayed; see the last example below.

Function ftable.formula provides a formula method for creating flat contingency tables.

There are methods for as.table, as.matrix and as.data.frame.

##### Value

• ftable returns an object of class "ftable", which is a matrix with counts of each combination of the levels of variables with information on the names and levels of the (row and columns) variables stored as attributes "row.vars" and "col.vars".

ftable.formula for the formula interface (which allows a data = . argument); read.ftable for information on reading, writing and coercing flat contingency tables; table for ordinary cross-tabulation; xtabs for formula-based cross-tabulation.
library(stats) ## Start with a contingency table. ftable(Titanic, row.vars = 1:3) ftable(Titanic, row.vars = 1:2, col.vars = "Survived") ftable(Titanic, row.vars = 2:1, col.vars = "Survived") . <- integer() (f04 <- ftable(Titanic, col.vars= .)) (f10 <- ftable(Titanic, col.vars= 1, row.vars= .)) (f01 <- ftable(Titanic, col.vars= ., row.vars= 1)) (f00 <- ftable(Titanic, col.vars= ., row.vars= .)) stopifnot( dim(f04) == c(32,1), dim(f10) == c(1,4), dim(f01) == c(4,1), dim(f00) == c(1,1)) ## Start with a data frame. x <- ftable(mtcars[c("cyl", "vs", "am", "gear")]) x ftable(x, row.vars = c(2, 4)) ## Start with expressions, use table()'s "dnn" to change labels ftable(mtcars$cyl, mtcars$vs, mtcars$am, mtcars$gear, row.vars = c(2, 4), dnn = c("Cylinders", "V/S", "Transmission", "Gears"))