DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Data Mining Data Mining Data Mining with Rattle Introduction Data Transform Explore A Model Building Framework Unsupervised Modelling Two Class Models Multi Class Models Regression Models Text Mining Evaluation and Deployment Moving into R Troubleshooting R for the Data Miner R Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Cluster Analysis Conditional Trees Hierarchical Clustering K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products AlphaMiner Borgelt Data Mining Suite KNime R Rattle Weka Closed Products C4.5 Clementine Equbits Foresight GhostMiner InductionEngine ODM Enterprise Miner Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Box and Whisker Plot: With Means

The simple box plot is extended to include the mean of each column. The means are calculated using scipy, and plotted as a + (pch=3).

[width=0.7]rplot-boxplot-means

rows <- 100
cols <- 17
pdf("graphics/rplot-boxplot-means.pdf")
  dataset <- matrix(rnorm(rows*cols), nrow=rows, ncol=cols)
  means <- mean(as.data.frame(dataset))
  boxplot(as.data.frame(dataset), notch=TRUE, at=1:17,
          xlim=c(0, cols+1), ylim=c(-4,4), xaxt='n')
  axis(side=1, at=1:17, labels=letters[1:17])
  points(1:17, means, pch=3)
dev.off()

http://rattle.togaware.com/code/rplot-boxplot-means.R

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