\HeaderA{agriculture}{European Union Agricultural Workforces}{agriculture}
\keyword{datasets}{agriculture}
\begin{Description}\relax
Gross National Product (GNP) per capita and percentage of the
population working in agriculture for each country belonging to the
European Union in 1993.
\end{Description}
\begin{Usage}
\begin{verbatim}data(agriculture)\end{verbatim}
\end{Usage}
\begin{Format}\relax
A data frame with 12 observations on 2 variables:
\Tabular{rlll}{
[ , 1] & \code{x} & numeric & per capita GNP \\{}
[ , 2] & \code{y} & numeric & percentage in agriculture
}
The row names of the data frame indicate the countries.
\end{Format}
\begin{Details}\relax
The data seem to show two clusters, the \dQuote{more agricultural} one
consisting of Greece, Portugal, Spain, and Ireland.
\end{Details}
\begin{Source}\relax
Eurostat (European Statistical Agency, 1994):
\emph{Cijfers en feiten: Een statistisch portret van de Europese Unie}.
\end{Source}
\begin{References}\relax
Anja Struyf, Mia Hubert \& Peter J. Rousseeuw (1996):
Clustering in an Object-Oriented Environment.
\emph{Journal of Statistical Software}, \bold{1}.
\url{http://www.stat.ucla.edu/journals/jss/}
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{agnes}{agnes}}, \code{\LinkA{daisy}{daisy}}, \code{\LinkA{diana}{diana}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(agriculture)

## Compute the dissimilarities using Euclidean metric and without
## standardization
daisy(agriculture, metric = "euclidean", stand = FALSE)

## 2nd plot is similar to Figure 3 in Struyf et al (1996)
plot(pam(agriculture, 2))

## Plot similar to Figure 7 in Struyf et al (1996)
## Not run: plot(agnes(agriculture), ask = TRUE)


## Plot similar to Figure 8 in Struyf et al (1996)
## Not run: plot(diana(agriculture), ask = TRUE)

\end{ExampleCode}
\end{Examples}

