Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
426.113 383.703 232.444 70.939 226.731 947.293 611.281 158.047 33.999 37.028 388.3 506.652 392.25 180.818 198.296 217.465 275.562 1030.944 57.47 136.452 556.277 213.361 274.482 220.553 236.71 260.642 2763.544 213.923 169.861 403.064 449.594 406.167 206.893 156.187 257.102 62.156 662.883 251.422 171.328 350.089 221.588 4.813 183.186 190.379 223.166 232.669 356.725 109.215 475.834 315.955 694.87 8.95 278.741 308.16 207.533 192.797 601.162 289.714 293.671 386.688 699.645 85.094 131.812 645.285 197.549 308.174 86.58 242.205 238.502 187.881 140.321 440.31 421.403 218.761 1305.923 137.55 262.517 348.821 150.034 64.016 261.596 259.7 171.26 203.077 249.148 211.655 252.64 438.555 239.89 401.915 216.886 184.641 380.155 653.641 313.906 366.936 236.302 229.641 235.577 103.898 263.906 241.171 216.548 295.281 193.299 204.386 257.567 136.813 240.755 59.609 213.511 380.531 242.344 250.407 183.613 191.835 266.793 246.542 330.563 403.556 208.108 324.04 308.532 199.297 200.156 262.875 287.069 190.157 199.746 265.777 435.956 72.844 756.46 206.771 4202.361 401.422 216.046 39.047 441.437
Sample Range:
(leave blank to include all observations)
From:
To:
Number of bins
(leave empty to use default)
(?)
Colour
data.csv
grey
white
blue
red
black
brown
yellow
Bins are closed on right side
Number of users per operating system
FALSE
TRUE
Scale of data
12
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