Produce or manipulate a flat contingency table using formula notation.
# S3 method for formula
ftable(formula, data = NULL, subset, na.action, …)a formula object with both left and right hand sides specifying the column and row variables of the flat table.
a data frame, list or environment (or similar: see
    model.frame) containing the variables
    to be cross-tabulated, or a contingency table (see below).
an optional vector specifying a subset of observations
    to be used.
    Ignored if data is a contingency table.
a function which indicates what should happen when
    the data contain NAs.
    Ignored if data is a contingency table.
further arguments to the default ftable method may also
    be passed as arguments, see ftable.default.
A flat contingency table which contains the counts of each combination of the levels of the variables, collapsed into a matrix for suitably displaying the counts.
This is a method of the generic function ftable.
The left and right hand side of formula specify the column and
  row variables, respectively, of the flat contingency table to be
  created.  Only the + operator is allowed for combining the
  variables.  A . may be used once in the formula to indicate
  inclusion of all the remaining variables.
If data is an object of class "table" or an array with
  more than 2 dimensions, it is taken as a contingency table, and hence
  all entries should be nonnegative.  Otherwise, if it is not a flat
  contingency table (i.e., an object of class "ftable"), it
  should be a data frame or matrix, list or environment containing the
  variables to be cross-tabulated.  In this case, na.action is
  applied to the data to handle missing values, and, after possibly
  selecting a subset of the data as specified by the subset
  argument, a contingency table is computed from the variables.
The contingency table is then collapsed to a flat table, according to
  the row and column variables specified by formula.
# NOT RUN {
Titanic
x <- ftable(Survived ~ ., data = Titanic)
x
ftable(Sex ~ Class + Age, data = x)
# }
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