factor is used to encode a vector as a factor (the
terms ‘category’ and ‘enumerated type’ are also used for
factors). If argument ordered is TRUE, the factor
levels are assumed to be ordered. For compatibility with S there is
also a function ordered. is.factor, is.ordered, as.factor and as.ordered
are the membership and coercion functions for these classes.
factor(x = character(), levels, labels = levels, exclude = NA, ordered = is.ordered(x), nmax = NA)
ordered(x, ...)
is.factor(x)
is.ordered(x)
as.factor(x)
as.ordered(x)
addNA(x, ifany = FALSE)x might have taken. The default is the unique set of
values taken by as.character(x), sorted into
increasing order of x. Note that this set can be
specified as smaller than sort(unique(x)).levels after removing those in
exclude), or a character string of length 1.x, and
will be coerced if necessary.ordered(.)): any of the above, apart from
ordered itself.NA level if it is used, i.e.
if any(is.na(x))."levels" attribute. Be careful only to compare factors with
the same set of levels (in the same order). In particular,
as.numeric applied to a factor is meaningless, and may
happen by implicit coercion. To transform a factor f to
approximately its original numeric values,
as.numeric(levels(f))[f] is recommended and slightly more
efficient than as.numeric(as.character(f)). The levels of a factor are by default sorted, but the sort order
may well depend on the locale at the time of creation, and should
not be assumed to be ASCII. There are some anomalies associated with factors that have
NA as a level. It is suggested to use them sparingly, e.g.,
only for tabulation purposes."factor" and "ordered" methods for the
group generic Ops which
provide methods for the Comparison operators,
and for the min, max, and
range generics in Summary
of "ordered". (The rest of the groups and the
Math group generate an error as they
are not meaningful for factors.) Only == and != can be used for factors: a factor can
only be compared to another factor with an identical set of levels
(not necessarily in the same ordering) or to a character vector.
Ordered factors are compared in the same way, but the general dispatch
mechanism precludes comparing ordered and unordered factors. All the comparison operators are available for ordered factors.
Collation is done by the levels of the operands: if both operands are
ordered factors they must have the same level set.x is not restricted; it only must have
an as.character method and be sortable (by
sort.list).Ordered factors differ from factors only in their class, but methods and the model-fitting functions treat the two classes quite differently.
The encoding of the vector happens as follows. First all the values
in exclude are removed from levels. 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
(which will happen for excluded values) then the i-th element
of the result is set to NA.
Normally the ‘levels’ used as an attribute of the result are
the reduced set of levels after removing those in exclude, but
this can be altered by supplying labels. This should either
be a set of new labels for the levels, or a character string, in
which case the levels are that character string with a sequence
number appended.
factor(x, exclude = NULL) applied to a factor is a no-operation
unless there are unused levels: in that case, a factor with the
reduced level set is returned. If exclude is used it should
also be a factor with the same level set as x or a set of codes
for the levels to be excluded.
The codes of a factor may contain NA. For a numeric
x, set exclude = NULL to make NA an extra
level (prints as
If NA is a level, the way to set a code to be missing (as
opposed to the code of the missing level) is to
use is.na on the left-hand-side of an assignment (as in
is.na(f)[i] <- TRUE; indexing inside is.na does not work).
Under those circumstances missing values are currently printed as
NA.
is.factor is generic: you can write methods to handle
specific classes of objects, see InternalMethods.
Where levels is not supplied, unique is called.
Since factors typically have quite a small number of levels, for large
vectors x it is helpful to supply nmax as an upper bound
on the number of unique values.
[.factor for subsetting of factors. gl for construction of balanced factors and
C for factors with specified contrasts.
levels and nlevels for accessing the
levels, and unclass to get integer codes.
(ff <- factor(substring("statistics", 1:10, 1:10), levels = letters))
as.integer(ff) # the internal codes
(f. <- factor(ff)) # drops the levels that do not occur
ff[, drop = TRUE] # the same, more transparently
factor(letters[1:20], labels = "letter")
class(ordered(4:1)) # "ordered", inheriting from "factor"
z <- factor(LETTERS[3:1], ordered = TRUE)
## and "relational" methods work:
stopifnot(sort(z)[c(1,3)] == range(z), min(z) < max(z))
## suppose you want "NA" as a level, and to allow missing values.
(x <- factor(c(1, 2, NA), exclude = NULL))
is.na(x)[2] <- TRUE
x # [1] 1 <NA> <NA>
is.na(x)
# [1] FALSE TRUE FALSE
## Using addNA()
Month <- airquality$Month
table(addNA(Month))
table(addNA(Month, ifany = TRUE))
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