Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
21 10 22 15 17 14 21 14 19 8 23 19 21 17 22 18 11 10 20 15 18 16 16 12 18 13 13 10 17 14 20 15 20 20 15 9 18 12 15 13 19 16 19 12 19 14 20 15 20 19 16 16 18 16 17 14 18 14 13 14 20 13 21 18 17 15 19 15 20 15 15 13 15 14 19 15 18 14 22 19 20 16 18 16 14 12 15 10 17 11 16 13 17 14 15 11 17 11 18 16 16 9 18 16 22 19 16 13 16 15 20 14 18 15 16 11 16 14 20 15 21 17 18 16 15 13 18 15 18 14 20 15 18 14 16 12 19 12 20 15 22 17 18 13 8 5 13 7 13 10 18 15 12 9 16 9 21 15 20 14 18 11 22 18 23 20 23 20 21 16 16 15 14 14 18 13 22 18 20 14 18 12 12 9 17 19 15 13 18 12 18 14 15 6 16 14 15 11 16 11 19 14 19 12 23 19 20 13 18 14 21 17 19 12 18 16 19 15 17 15 21 15 19 16 24 15 12 12 15 13 18 14 19 17 22 14 19 14 16 14 19 15 18 11 18 11 19 16 21 12 19 12 22 19 23 18 17 16 18 16 19 13 15 11 14 10 18 14 17 14 19 14 16 16 14 10 20 16 16 7 18 16 16 15 21 17 16 11 14 11 16 10 19 13 19 14 19 13 18 13 16 12 14 10 19 15 11 6 18 15 18 15 16 11 20 14 18 14 20 16 16 12 18 15 19 20 19 12 15 9 17 13 21 15 24 19 16 11 13 11 21 17 16 15 17 14 17 15 18 11 18 12 23 15 20 16 20 16
Names of X columns:
Information_Quality Perceived_Ease_of_Use
Sample Range:
(leave blank to include all observations)
From:
To:
Color
grey
grey
white
blue
red
black
brown
yellow
Omit all rows with missing values?
no
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