

   FFaaccttoorrss

        factor(x, levels = sort(unique(x), na.last = TRUE), labels,
               exclude = NA, ordered = FALSE)
        ordered(x, levels = sort(unique(x), na.last = TRUE), labels,
               exclude = NA, ordered = TRUE)

        is.factor(x)
        is.ordered(x)
        is.unordered(x)

        as.factor(x, ordered = FALSE)
        as.ordered(x)

   VVaalluuee::

        The function `factor' is used to encode a vector as a
        factor (the names category and enumerated type are also
        used for factors).  If `ordered' is `TRUE', the factor
        levels are assumed ordered.  By default the levels are
        unordered.  For compatibility purposes, there is also a
        function called `ordered' which provides an alternative
        way of creating ordered factors.

        The encoding of the vector happens as follows: if
        `x[i]' equals `levels[j]', then the `i'-th element of
        the result is `j'.  If no match is found for `x[i]' in
        `levels', then the `i'-th element of the result is set
        to `NA'.  Any values listed in `exclude' result in
        `NA's appearing in the factor returned.  If `exclude'
        is set to a zero length vector, then any `NA' values in
        `x' are used for form a new level for the factor.  This
        means that there will be no `NA' values in the result.

        `labels' is a vector of character strings used to label
        the levels of the factor.  The default is to use the
        encoded factor levels.

        `is.factor' returns `TRUE' or `FALSE' depending on
        whether its argument is of type factor or not.  Corre-
        spondingly, `is.ordered' (`is.unordered') returns
        `TRUE' when its argument is ordered (unordered) and
        `FALSE' otherwise.

        `as.factor' coerces its argument to a factor.  It is an
        abbreviated form of `factor'.

        `as.ordered(x)' returns `x' if this is ordered, and
        `ordered(x)' otherwise.

   SSeeee AAllssoo::

        `gl' for construction of ``balanced'' factors; `levels'
        and `nlevels' for accessing the levels,  and `codes' to
        get integer codes.

   EExxaammpplleess::

        ff <- factor(substring("statistics",1:10,1:10), levels=letters)
        ff
        codes(ff)

