Hi Bob, Hi John, Hi readers, many thanks for your reply.
I did barplot(colSums(dataset %>% select(FirstVar:LastVar))) and it worked fine. How would I do it with ggplot2? Kind regards Georg Von: "Fox, John" <j...@mcmaster.ca> An: "g.maub...@weinwolf.de" <g.maub...@weinwolf.de>, Kopie: "r-help@r-project.org" <r-help@r-project.org> Datum: 05.10.2016 15:01 Betreff: RE: [R] How to plot a bunch of dichotomous code variables in one plot using ggplot2 Dear Georg, How about barplot(colSums(ds)) ? Best, John ----------------------------- John Fox, Professor McMaster University Hamilton, Ontario Canada L8S 4M4 Web: socserv.mcmaster.ca/jfox > -----Original Message----- > From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of > g.maub...@weinwolf.de > Sent: October 5, 2016 8:47 AM > To: r-help@r-project.org > Subject: [R] How to plot a bunch of dichotomous code variables in one plot > using ggplot2 > > Hi All, > > I have a bunch of dichotomous code variables which shall be plotted in one > graph using one of their values, this is "1" in this case. > > The dataset looks like this: > > -- cut -- > var1 <- c(1,0,1,0,0,1,1,1,0,1) > var2 <- c(0,1,1,1,1,0,0,0,0,0) > var3 <- c(1,1,1,1,1,1,1,1,0,1) > > ds <- data.frame(var1, var2, var3) > -- cut -- > > I would like to have a bar plot like this > > > > * > * > * > * > * * > * * > * * * > * * * > * * * > * * * > ------------------------- > var1 var2 var3 > > If this possible in R? If so, how can I achieve this? > > Kind regards > > Georg > > ______________________________________________ > 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.
