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

Multiple Boxplots

The default boxplot function in fact will plot multiple boxplots.

By comparing a number of variables we can see that some have quite a bit more spread than others, and their medians have different relative positions within the box.

We include the code here to generate a PDF version of the plot primarily to demonstrate how we can increase the width of the plot for a more pleasing presentation.

We could have presented the plot horizontally by setting the horizontal option to TRUE.

pdf("graphics/rplot-wine-boxplot-multi.pdf", width=9)
load("wine.Rdata")
boxplot(wine[,c(3,4,7,8,10,13)])
dev.off()

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

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