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Data X:
13 22 16 24 17 26 15 21 16 26 16 25 18 21 16 24 17 27 17 28 17 23 15 25 16 24 14 24 16 24 17 25 16 25 15 25 17 25 16 24 15 26 16 26 15 25 17 26 14 23 16 24 15 24 16 25 16 25 13 24 15 28 17 27 15 25 13 23 17 23 15 24 14 24 14 22 18 25 15 25 17 28 13 22 16 28 15 25 15 24 16 24 15 23 13 25 17 26 18 25 18 27 11 26 14 23 13 25 15 21 17 22 16 24 15 25 17 27 16 24 16 26 16 21 15 27 12 22 17 23 14 24 14 25 16 24 15 23 15 28 14 23 13 24 18 26 15 22 16 25 14 25 15 24 17 24 16 26 10 21 16 25 17 25 17 26 20 25 17 26 18 27 15 25 17 23 14 20 15 24 17 26 16 25 17 25 15 24 16 26 18 25 18 28 16 27 17 26 15 26 13 26 15 21 17 28 16 26 16 21 15 25 16 25 16 24 14 24 15 24 12 23 19 23 16 24 16 24 17 25 16 28 14 23 15 24 14 23 16 24 15 25 17 24 15 23 16 23 16 25 15 21 15 22 11 19 16 24 18 25 13 21 11 22 16 23 18 27 15 26 19 29 17 28 13 24 14 25 16 25 13 22 17 25 14 26 19 26 14 24 16 25 12 19 16 25 16 23 15 25 12 25 15 26 17 27 14 24 15 22 18 25 15 24 18 23 15 27 15 24 16 24 13 21 16 25 14 25 16 23
Names of X columns:
TVDCSUM SKSUM
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grey
grey
white
blue
red
black
brown
yellow
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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Big Analytics Cloud Computing Center
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