Hi Ana, This is a very common question about ggplot. A quick search turns up lots of hits that answer your question. Here are a couple https://community.rstudio.com/t/trouble-scaling-y-axis-to-percentages-from-counts/42999 https://stackoverflow.com/questions/3695497/show-instead-of-counts-in-charts-of-categorical-variables
>From reading those discussions, the following should work (untested) ggplot(a, aes(x = HBA1C, fill=pheno)) + geom_histogram(aes(y = stat(density)), binwidth = 0.5) + scale_y_continuous(labels = scales::percent_format()) HTH, Eric On Fri, May 22, 2020 at 7:18 AM Jim Lemon <drjimle...@gmail.com> wrote: > > Hi Ana, > Just noticed a typo from a hasty cut-paste. Two lines should read: > > casehist<-table(cut(aafd$HBAIC[aafd$pheno=="case"],breaks=0:15)) > controlhist<-table(cut(aafd$HBAIC[aafd$pheno=="control"],breaks=0:15)) > > Jim > > On Fri, May 22, 2020 at 2:08 PM Jim Lemon <drjimle...@gmail.com> wrote: > > > > Hi Ana, > > My apologies for the pedestrian graphics, but it may help. > > > > # a bit of fake data > > aafd<-data.frame(FID=paste0("fam",1000:2739), > > IID=paste0("G",1000,2739),FLASER=rep(1,1740), > > PLASER=c(rep(1,892),rep(2,848)), > > DIABDUR=sample(10:50,1740,TRUE), > > HBAIC=rnorm(1740,mean=7.45,sd=2),ESRD=rep(1,1740), > > pheno=c(rep("control",892),rep("case",848))) > > par(mfrow=c(2,1)) > > casepct<-table(cut(aafd$HBAIC[aafd$pheno=="case"],breaks=0:15)) > > controlpct<-table(cut(aafd$HBAIC[aafd$pheno=="control"],breaks=0:15)) > > par(mar=c(0,4,1,2)) > > barpos=barplot(100*casehist,names.arg=names(casepct),col="orange", > > space=0,ylab="Percentage",xaxt="n",ylim=c(0,25)) > > text(mean(barpos),23, > > "Cases: n=848, nulls=26, median=7.3, mean=7.45, sd=1.96") > > box() > > par(mar=c(3,4,0,2)) > > barplot(100*controlhist,names.arg=names(controlpct), > > space=0,ylab="Percentage",col="orange",ylim=c(0,25)) > > text(mean(barpos),23, > > "Controls: n=892, nulls=7, median=7.3, mean=7.45, sd=1.12") > > box() > > > > Jim > > > > On Fri, May 22, 2020 at 9:08 AM Ana Marija <sokovic.anamar...@gmail.com> > > wrote: > > > > > > the result would basically look something like this on in attach or > > > the overlay of those two plots > > > > > > > > > On Thu, May 21, 2020 at 5:23 PM Ana Marija <sokovic.anamar...@gmail.com> > > > wrote: > > > > > > > > Hello, > > > > > > > > I have a data frame like this: > > > > > head(a) > > > > FID IID FLASER PLASER DIABDUR HBA1C ESRD pheno > > > > 1 fam1000-03 G1000 1 1 38 10.2 1 control > > > > 2 fam1001-03 G1001 1 1 15 7.3 1 control > > > > 3 fam1003-03 G1003 1 2 17 7.0 1 case > > > > 4 fam1005-03 G1005 1 1 36 7.7 1 control > > > > 5 fam1009-03 G1009 1 1 23 7.6 1 control > > > > 6 fam1052-03 G1052 1 1 32 7.3 1 control > > > > > > > > > dim(a) > > > > [1] 1698 8 > > > > > > > > I am doing histogram plot via: > > > > ggplot(a, aes(x=HBA1C, fill=pheno)) + geom_histogram(binwidth=.5, > > > > position="dodge") > > > > > > > > there is 848 who have "case" in pheno column and 892 who have > > > > "control" in pheno column. > > > > > > > > I would like to have on y-axis shown percentage of individuals which > > > > have either "case" or "control" in pheno instead of count. > > > > > > > > Please advise, > > > > Ana > > > ______________________________________________ > > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > > 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. > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.