Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
7.101883333 6.39505 3.874066667 1.182316667 3.77885 15.78821667 10.18801667 2.634116667 0.56665 0.617133333 6.471666667 8.4442 6.5375 3.013633333 3.304933333 3.624416667 4.5927 17.1824 0.957833333 2.2742 9.271283333 3.556016667 4.5747 3.675883333 3.945166667 4.344033333 46.05906667 3.565383333 2.831016667 6.717733333 7.493233333 6.76945 3.448216667 2.603116667 4.285033333 1.035933333 11.04805 4.190366667 2.855466667 5.834816667 3.693133333 0.080216667 3.0531 3.172983333 3.719433333 3.877816667 5.945416667 1.82025 7.930566667 5.265916667 11.58116667 0.149166667 4.645683333 5.136 3.458883333 3.213283333 10.01936667 4.828566667 4.894516667 6.4448 11.66075 1.418233333 2.196866667 10.75475 3.292483333 5.136233333 1.443 4.03675 3.975033333 3.13135 2.338683333 7.3385 7.023383333 3.646016667 21.76538333 2.2925 4.375283333 5.813683333 2.500566667 1.066933333 4.359933333 4.328333333 2.854333333 3.384616667 4.152466667 3.527583333 4.210666667 7.30925 3.998166667 6.698583333 3.614766667 3.07735 6.335916667 10.89401667 5.231766667 6.1156 3.938366667 3.82735 3.926283333 1.731633333 4.398433333 4.019516667 3.609133333 4.92135 3.22165 3.406433333 4.292783333 2.280216667 4.012583333 0.993483333 3.558516667 6.342183333 4.039066667 4.17345 3.060216667 3.19725 4.44655 4.109033333 5.509383333 6.725933333 3.468466667 5.400666667 5.1422 3.321616667 3.335933333 4.38125 4.784483333 3.169283333 3.3291 4.429616667 7.265933333 1.214066667 12.60766667 3.446183333 70.03935 6.690366667 3.600766667 0.650783333 7.357283333
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
Interval/Ratio
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation