R Dataset / Package MASS / Skye

How To Create a Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Correlation Coefficient

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-mass-skye.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-20551.csv 214 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the Skye data set which pertains to AFM Compositions of Aphyric Skye Lavas. The Skye data set is found in the MASS R package. You can load the Skye data set in R by issuing the following command at the console data("Skye"). This will load the data into a variable called Skye. If R says the Skye data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Skye R data set. The size of this file is about 214 bytes.

Documentation

AFM Compositions of Aphyric Skye Lavas

Description

The Skye data frame has 23 rows and 3 columns.

Usage

Skye

Format

This data frame contains the following columns:

A

Percentage of sodium and potassium oxides.

F

Percentage of iron oxide.

M

Percentage of magnesium oxide.

Source

R. N. Thompson, J. Esson and A. C. Duncan (1972) Major element chemical variation in the Eocene lavas of the Isle of Skye. J. Petrology, 13, 219–253.

References

J. Aitchison (1986) The Statistical Analysis of Compositional Data. Chapman and Hall, p.360.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

Examples

# ternary() is from the on-line answers.
ternary <- function(X, pch = par("pch"), lcex = 1,
                    add = FALSE, ord = 1:3, ...)
{
  X <- as.matrix(X)
  if(any(X < 0)) stop("X must be non-negative")
  s <- drop(X %*% rep(1, ncol(X)))
  if(any(s<=0)) stop("each row of X must have a positive sum")
  if(max(abs(s-1)) > 1e-6) {
    warning("row(s) of X will be rescaled")
    X <- X / s
  }
  X <- X[, ord]
  s3 <- sqrt(1/3)
  if(!add)
  {
    oldpty <- par("pty")
    on.exit(par(pty=oldpty))
    par(pty="s")
    plot(c(-s3, s3), c(0.5-s3, 0.5+s3), type="n", axes=FALSE,
         xlab="", ylab="")
    polygon(c(0, -s3, s3), c(1, 0, 0), density=0)
    lab <- NULL
    if(!is.null(dn <- dimnames(X))) lab <- dn[[2]]
    if(length(lab) < 3) lab <- as.character(1:3)
    eps <- 0.05 * lcex
    text(c(0, s3+eps*0.7, -s3-eps*0.7),
         c(1+eps, -0.1*eps, -0.1*eps), lab, cex=lcex)
  }
  points((X[,2] - X[,3])*s3, X[,1], ...)
}ternary(Skye/100, ord=c(1,3,2))
--

Dataset imported from https://www.r-project.org.

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