\HeaderA{unique}{Extract Unique Elements}{unique}
\methaliasA{unique.array}{unique}{unique.array}
\methaliasA{unique.data.frame}{unique}{unique.data.frame}
\methaliasA{unique.default}{unique}{unique.default}
\methaliasA{unique.matrix}{unique}{unique.matrix}
\keyword{manip}{unique}
\keyword{logic}{unique}
\begin{Description}\relax
\code{unique} returns a vector, data frame or array like \code{x}
but with duplicate  elements removed.
\end{Description}
\begin{Usage}
\begin{verbatim}
unique(x, incomparables = FALSE, ...)

## S3 method for class 'array':
unique(x, incomparables = FALSE, MARGIN = 1, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] an atomic vector or a data frame or an array.
\item[\code{incomparables}] a vector of values that cannot be compared.
Currently, \code{FALSE} is the only possible value, meaning that all
values can be compared.
\item[\code{...}] arguments for particular methods.
\item[\code{MARGIN}] the array margin to be held fixed: a single integer.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This is a generic function with methods for vectors, data frames and
arrays (including matrices).

The array method calculates for each element of the dimension
specified by \code{MARGIN} if the remaining dimensions are identical
to those for an earlier element (in row-major order).  This would most
commonly be used to find unique rows (the default) or columns
(with \code{MARGIN = 2}).
\end{Details}
\begin{Value}
An object of the same type of \code{x}. but if
an element is equal to one with a smaller index, it is removed.
Dimensions of arrays are not dropped.
\end{Value}
\begin{References}\relax
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
\emph{The New S Language}.
Wadsworth \& Brooks/Cole.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{duplicated}{duplicated}} which gives the indices of duplicated
elements.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
unique(c(3:5, 11:8, 8 + 0:5))
length(unique(sample(100, 100, replace=TRUE)))
## approximately 100(1 - 1/e) = 63.21

unique(iris)
\end{ExampleCode}
\end{Examples}

