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  \item{x}{x coordinates, rounded and sorted.}
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  \item{x}{x coordinates, rounded and sorted.}
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  \item{y}{y coordinates, rounded (and sorted within \code{x}).}
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  \item{y}{y coordinates, rounded (and sorted within \code{x}).}
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  \item{number}{multiplicities (positive integers); i.e.,
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  \item{number}{multiplicities (positive integers); i.e.,
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    \code{number[i]} is the multiplicity of \code{(x[i], y[i])}.}
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    \code{number[i]} is the multiplicity of \code{(x[i], y[i])}.}
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}
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}
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\note{
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  Missing values in the coordinates are counted towards the multiplicities. The
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  sum of the multiplicities will equal the number of coordinates.
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}
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\seealso{\code{\link{sunflowerplot}} which typically uses
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\seealso{\code{\link{sunflowerplot}} which typically uses
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  \code{xyTable()}; \code{\link{signif}}.
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  \code{xyTable()}; \code{\link{signif}}.
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}
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}
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\examples{
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\examples{
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xyTable(iris[, 3:4], digits = 6)
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xyTable(iris[, 3:4], digits = 6)
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## If missing coordinates exist, they are also counted
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iris2 <- iris[1:10, 3:4]
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iris2[4, 2] <- NA
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iris2[c(3, 5), ] <- NA
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xyTable(iris2)
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## Discretized uncorrelated Gaussian:
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## Discretized uncorrelated Gaussian:
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\dontshow{set.seed(1)}
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\dontshow{set.seed(1)}
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xy <- data.frame(x = round(sort(stats::rnorm(100))), y = stats::rnorm(100))
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xy <- data.frame(x = round(sort(stats::rnorm(100))), y = stats::rnorm(100))
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xyTable(xy, digits = 1)
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xyTable(xy, digits = 1)
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}
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}