Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
14 15 19 13 17 14 17 13 15 12 20 17 15 12 19 13 15 13 15 16 19 12 NA 12 20 13 18 16 15 15 14 12 20 NA NA NA 16 15 16 12 16 15 10 11 19 13 19 13 16 14 15 14 18 14 17 15 19 16 17 16 NA 16 19 13 20 13 5 14 19 13 16 14 15 12 16 17 18 14 16 15 15 13 17 14 NA 15 20 19 19 14 7 13 13 12 16 NA 16 14 NA 15 18 15 18 12 16 14 17 11 19 12 16 10 19 NA 13 14 16 14 13 15 12 15 17 13 17 15 17 16 16 12 16 17 14 15 16 NA 13 12 16 16 14 15 20 15 12 12 13 13 18 10 14 14 19 11 18 12 14 14 18 12 19 14 15 12 14 13 17 13 19 14 13 12 19 15 18 13 20 13 15 11 15 12 15 16 20 11 15 13 19 12 18 17 18 14 15 15 20 8 17 13 12 13 18 15 19 14 20 13 NA 14 17 12 15 19 16 15 18 14 18 14 14 15 15 13 12 15 17 14 14 11 18 17 17 13 17 9 20 12 16 13 14 17 15 14 18 13 20 16 17 14 17 14 17 14 17 10 15 12 17 13 18 14 17 18 20 14 15 14 16 13 15 13 18 16 11 NA 15 13 18 14 20 8 19 13 14 13 16 16 15 14 17 13 18 14 20 12 17 16 18 18 15 16 16 15 11 18 15 15 18 14 17 14 16 15 12 9 19 17 18 11 15 15 17 NA 19 15 18 13 19 NA 16 15 16 15 16 14 14 13
Names of X columns:
ITHsum EPsum
Sample Range:
(leave blank to include all observations)
From:
To:
Color
12
grey
white
blue
red
black
brown
yellow
Omit all rows with missing values?
-0.5
no
yes
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation