Well, from what you say it seems to me that you could also use Pareto
charts together with some aggregation of data. But it depends on what you
want to show to your audience. Below is some code which I slightly adapted
form original author.
Regards
Petr
#----------------------------------------------------------------------------------------------------------------------
# pareto. Produces a Pareto plot of effects.
#
# Parameters:
# effects - vector or matrix of effects to plot.
# names - vector of names to label the effects.
# xlab - String to display as the x axis label.
# ylab - String to display as the y axis label.
# perlab - Label for the cumulative percentage label.
# heading - Vector of names for plot heading.
#
pareto <- function(effects, names=NULL, xlab=NULL, ylab="Magnitude of
Effect", indicate.percent=TRUE, perlab="Cumulative Percentage",
heading=NULL, trunc.perc=.95, long.names=FALSE,...)
{
# set up graphics parameters, note: set las=2 for perpendicular
axis.
oldpar <- par( mar=c(6, 4, 2, 4) + 0.1 , las=3)
on.exit(par(oldpar))
if( ! is.matrix(effects)) effects<-as.matrix( effects )
for( i in 1:ncol(effects) )
{
if( i==2 ) oldpar$ask<-par(ask=TRUE)$ask
# draw bar plot
eff.ord <- rev(order(abs(effects[,i])))
ef <- abs(effects[eff.ord,i])
names<-as.character(names)[eff.ord]
# plot barplot
# get cumulative sum of effects
sumeff <- cumsum(ef)
m<-max(ef)
sm<-sum(ef)
sumeff <- sumeff/sm
vyber<-sumeff>trunc.perc
suma.ef<-sum(ef[vyber])
sumeff<-c(sumeff[!vyber],1)*m
ef<-c(ef[!vyber],suma.ef)
names<-c(as.character(names[!vyber]),"Dalsi")
ylimit<-max(ef) + max(ef)*0.19
ylimit<-c(0,ylimit)
par( mar=c(6, 4, 2, 4) + 0.1 , las=3)
if (long.names) {
x<- barplot(ef, names.arg=names, ylim=ylimit, xlab=xlab,
ylab=ylab, main=heading[i], plot=F, ...)
x<- barplot(ef, ylim=ylimit, xlab=xlab, ylab=ylab,
main=heading[i], ...)
text(x,ylimit[2]/10, names, srt=90, adj=0, cex=.7)} else {
x<-barplot(ef, names.arg=names, ylim=ylimit, xlab=xlab,
ylab=ylab, main=heading[i], ...)
}
if( indicate.percent == TRUE ){
# draws curve.
lines(x, sumeff, lty="solid", lwd=2, col="purple")
# draw 80% line
lines( c(0,max(x)), rep(0.8*m,2) )
# draw axis labling percentage.
at <- c(0:5)* m/5
axis(4, at=at,
labels=c("0","20","40","60","80","100"), pos=max(x)+.6)
# add axis lables
par(las=0)
mtext(perlab, 4, line=2)
}
} # end for each col
}
#Don Wingate
r-help-boun...@r-project.org napsal dne 18.11.2009 16:17:32:
> yes in my data the 1st column is the main category say suppose
"Secretary"
> the second column is the sub category "HR Dept" the 3rd column is the
list
> of duties performed by the Secretary from HR dept and 4th column is time
> required to perform the duty
>
> so there are many such posts and dept with varied duties and times resp.
>
> Regards
>
> Our Thoughts have the Power to Change our Destiny.
> Sunita
>
>
> On Wed, Nov 18, 2009 at 8:42 PM, Petr PIKAL <petr.pi...@precheza.cz>
wrote:
>
> > Hi
> >
> > r-help-boun...@r-project.org napsal dne 18.11.2009 16:01:27:
> >
> > > Yes I tried all the basic ones like box plot, pie chart, etc but the
> > data
> > > representation isnt that clear.
> > >
> >
> > I agree with Tal. But it partly depends on your data. If you have many
> > levels and only few time values in each boxplot would not look well.
Maybe
> > you could check also ?xtabs or ?table and/or R graph gallery
> > http://addictedtor.free.fr/graphiques/ if you find suitable graph.
> >
> > Regards
> > Petr
> >
> >
> >
> > >
> > > Regards
> > >
> > > Our Thoughts have the Power to Change our Destiny.
> > > Sunita
> > >
> > >
> > > On Wed, Nov 18, 2009 at 7:20 PM, Tal Galili <tal.gal...@gmail.com>
> > wrote:
> > >
> > > > I would start with
> > > > ?boxplot
> > > >
> > > >
> > > > ----------------------------------------------
> > > >
> > > >
> > > > My contact information:
> > > > Tal Galili
> > > > E-mail: tal.gal...@gmail.com
> > > > Phone number: 972-52-7275845
> > > > FaceBook: Tal Galili
> > > > My Blogs:
> > > > http://www.talgalili.com (Web and general, Hebrew)
> > > > http://www.biostatistics.co.il (Statistics, Hebrew)
> > > > http://www.r-statistics.com/ (Statistics,R, English)
> > > >
> > > >
> > > >
> > > >
> > > > On Wed, Nov 18, 2009 at 2:47 PM, Sunita Patil
<sunita...@gmail.com>
> > wrote:
> > > >
> > > >> Thanx
> > > >>
> > > >> but I am not able to find a graph that wud suit my data
> > > >>
> > > >> Regards
> > > >>
> > > >> Our Thoughts have the Power to Change our Destiny.
> > > >> Sunita
> > > >>
> > > >>
> > > >> On Sun, Nov 15, 2009 at 8:54 PM, milton ruser
<milton.ru...@gmail.com
> > > >> >wrote:
> > > >>
> > > >> > Google "R graph grallery"
> > > >> > Google "R ggplot2"
> > > >> > Google "R lattice"
> > > >> >
> > > >> > and good luck
> > > >> >
> > > >> > milton
> > > >> > On Sun, Nov 15, 2009 at 7:48 AM, Sunita22 <sunita...@gmail.com>
> > wrote:
> > > >> >
> > > >> >>
> > > >> >> Hello
> > > >> >>
> > > >> >> My data contains following columns:
> > > >> >>
> > > >> >> 1st column: Posts (GM, Secretary, AM, Office Boy)
> > > >> >> 2nd Column: Dept (Finance, HR, ...)
> > > >> >> 3rd column: Tasks (Open the door, Fix an appointment, Fill the
> > > >> register,
> > > >> >> etc.....) depending on the post
> > > >> >> 4th column: Average Time required to do the task
> > > >> >>
> > > >> >> So the sample data would look like
> > > >> >> Posts Dept Task Average
> > time
> > > >> >> Office Boy HR Open the door 00:00:09
> > > >> >> Secretary Finance Fix an appointment 00.00.30
> > > >> >> .... ..... ..... .....
> > > >> >>
> > > >> >> I am trying to represent this data in Graphical format, I
tried
> > graphs
> > > >> >> like
> > > >> >> Mosaic plot, etc. But it does not represent the data
correctly. My
> > aim
> > > >> is
> > > >> >> to
> > > >> >> check the "amount of time and its variability for groups of
tasks"
> > > >> >>
> > > >> >> Thank you in advance
> > > >> >> Regards
> > > >> >> Sunita
> > > >> >>
> > > >> >> --
> > > >> >> View this message in context:
> > > >> >>
> > > >> http://old.nabble.com/Presentation-of-data-in-Graphical-format-
> > > tp26358857p26358857.html
> > > >> >> Sent from the R help mailing list archive at Nabble.com.
> > > >> >>
> > > >> >> ______________________________________________
> > > >> >> R-help@r-project.org mailing list
> > > >> >> https://stat.ethz.ch/mailman/listinfo/r-help
> > > >> >> PLEASE do read the posting guide
> > > >> >> http://www.R-project.org/posting-guide.html<
> > > >> http://www.r-project.org/posting-guide.html>
> > > >>
> > > >> >> and provide commented, minimal, self-contained, reproducible
code.
> > > >> >>
> > > >> >
> > > >> >
> > > >>
> > > >> [[alternative HTML version deleted]]
> > > >>
> > > >>
> > > >> ______________________________________________
> > > >> R-help@r-project.org mailing list
> > > >> https://stat.ethz.ch/mailman/listinfo/r-help
> > > >> PLEASE do read the posting guide
> > > >> http://www.R-project.org/posting-guide.html
> > > >> and provide commented, minimal, self-contained, reproducible
code.
> > > >>
> > > >
> > > >
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > ______________________________________________
> > > R-help@r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> >
> >
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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