Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
560576 548854 531673 525919 511038 498662 555362 564591 541657 527070 509846 514258 516922 507561 492622 490243 469357 477580 528379 533590 517945 506174 501866 516141 528222 532638 536322 536535 523597 536214 586570 596594 580523 564478 557560 575093 580112 574761 563250 551531 537034 544686 600991 604378 586111 563668 548604 551174 555654 547970 540324 530577 520579 518654 572273 581302 563280 547612 538712 540735 561649 558685 545732 536352 527676 530455 581744 598714 583775 571477 563278 564872
Sample Range:
(leave blank to include all observations)
From:
To:
Number of bins
(leave empty to use default)
(?)
Colour
grey
grey
white
blue
red
black
brown
yellow
Bins are closed on right side
FALSE
FALSE
TRUE
Scale of data
Unknown
Unknown
Interval/Ratio
3-point Likert
4-point Likert
5-point Likert
6-point Likert
7-point Likert
8-point Likert
9-point Likert
10-point Likert
11-point Likert
Chart options
Title:
Label x-axis:
R Code
par1 <- as.numeric(par1) if (par3 == 'TRUE') par3 <- TRUE if (par3 == 'FALSE') par3 <- FALSE if (par4 == 'Unknown') par1 <- as.numeric(par1) if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1) if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5) if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5) if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5) if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5) if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5) if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5) if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5) if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5) bitmap(file='test1.png') if(is.numeric(x[1])) { if (is.na(par1)) { myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3) } else { if (par1 < 0) par1 <- 3 if (par1 > 50) par1 <- 50 myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3) } } else { plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency') } dev.off() if(is.numeric(x[1])) { myhist n <- length(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/histogram.htm','Frequency Table (Histogram)',''),6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Bins',header=TRUE) a<-table.element(a,'Midpoint',header=TRUE) a<-table.element(a,'Abs. Frequency',header=TRUE) a<-table.element(a,'Rel. Frequency',header=TRUE) a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE) a<-table.element(a,'Density',header=TRUE) a<-table.row.end(a) crf <- 0 if (par3 == FALSE) mybracket <- '[' else mybracket <- ']' mynumrows <- (length(myhist$breaks)-1) for (i in 1:mynumrows) { a<-table.row.start(a) if (i == 1) dum <- paste('[',myhist$breaks[i],sep='') else dum <- paste(mybracket,myhist$breaks[i],sep='') dum <- paste(dum,myhist$breaks[i+1],sep=',') if (i==mynumrows) dum <- paste(dum,']',sep='') else dum <- paste(dum,mybracket,sep='') a<-table.element(a,dum,header=TRUE) a<-table.element(a,myhist$mids[i]) a<-table.element(a,myhist$counts[i]) rf <- myhist$counts[i]/n crf <- crf + rf a<-table.element(a,round(rf,6)) a<-table.element(a,round(crf,6)) a<-table.element(a,round(myhist$density[i],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') } else { mytab reltab <- mytab / sum(mytab) n <- length(mytab) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Category',header=TRUE) a<-table.element(a,'Abs. Frequency',header=TRUE) a<-table.element(a,'Rel. Frequency',header=TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,labels(mytab)$x[i],header=TRUE) a<-table.element(a,mytab[i]) a<-table.element(a,round(reltab[i],4)) 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