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Data X:
7 13 7 16 11 17 11 11 10 12 9 16 9 13 11 12 8 13 11 17 6 17 8 15 13 16 13 14 10 16 9 17 5 12 5 0 9 11 13 13 14 16 13 11 7 16 11 11 8 13 11 11 12 16 9 15 14 16 9 16 11 13 9 15 6 17 9 11 9 13 11 17 9 11 13 14 11 14 5 18 10 11 8 17 10 13 4 16 9 15 10 15 9 12 8 15 12 13 14 3 12 17 12 13 9 13 9 11 9 14 7 13 10 11 11 17 11 16 10 11 9 17 11 16 11 16 10 16 10 15 7 12 11 17 13 14 11 14 11 16 9 11 9 11 11 10 9 10 10 13 13 15 11 16 13 14 14 15 8 17 10 12 10 10 10 12 9 17 9 13 8 20 9 17 8 18 12 11 10 17 11 14 10 11 10 17 13 12 12 17 10 11 10 16 12 18 5 18 11 16 7 4 11 13 10 15 11 13 11 11 14 13 11 12 14 12 12 11 13 16 13 12 10 10 7 11 11 12 9 14 8 16 9 16 8 13 9 16 12 14 9 15 10 14 12 12 10 15 9 13 10 15 13 16 10 12 6 11 10 11 9 11 13 12 12 18 4 10 11 11 12 8 13 18 8 3 10 15 10 19 7 17 9 10 13 14 13 12 11 13 11 17 12 14 13 19 14 14 12 12 9 9 13 16 10 16 8 15 10 12 10 11 7 17 10 10 9 11 12 18 10 15 9 18 10 15 9 11 11 12 8 10 10 16 9 10 10 16
Names of X columns:
ImagoSOM123 TevredenheidSOM123
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grey
grey
white
blue
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black
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Omit all rows with missing values?
no
no
yes
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R Code
par2 <- 'no' par1 <- 'grey' if(par2=='yes') { z <- na.omit(as.data.frame(t(y))) } else { z <- as.data.frame(t(y)) } bitmap(file='test1.png') (r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=TRUE,col=par1)) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot statistics',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower whisker',1,TRUE) a<-table.element(a,'lower hinge',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper hinge',1,TRUE) a<-table.element(a,'upper whisker',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) for (j in 1:5) { a<-table.element(a,r$stats[j,i]) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot Notches',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower bound',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper bound',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) a<-table.element(a,r$conf[1,i]) a<-table.element(a,r$stats[3,i]) a<-table.element(a,r$conf[2,i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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0 seconds
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Big Analytics Cloud Computing Center
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