Thanks, now I got the bars (although without notch) but I lost the main plot: ``` xyplot(Value ~ Concentration, group = Substance, data = df, pch = 16, cex = 1.2, type = "b", xlab=expression(bold(paste("Concentration (", mu, "M)"))), ylab=expression(bold("Infection rate")), col=COLS, scales = list(x = list(log = 10, at=c(unique(df$Concentration)) ) ), key = list(space="top", columns=4, col = "black", points=list(pch=c(16, 16, 16, 16), col=COLS ), text=list(c("A", "B", "C", "D") ) ), panel = function (x,y) { panel.segments(x0 = log10(df$Concentration), x1 = log10(df$Concentration), y0 = df$Value - dfsd$Value, y1 = df$Value + dfsd$Value, col = COLS) }
) ``` I will check xYplot out, I think it is the tool for the job. On Mon, Oct 11, 2021 at 3:56 PM Deepayan Sarkar <deepayan.sar...@gmail.com> wrote: > > On Mon, Oct 11, 2021 at 5:41 PM Luigi Marongiu <marongiu.lu...@gmail.com> > wrote: > > > > Hello, > > I am trying to plot data using lattice. The basic plot works: > > ``` > > Substance = rep(c("A", "B", "C", "D"),4) > > Concentration = rep(1:4,4), > > Value = c(62.80666667, 116.26333333, 92.26000000, 9.87333333, > > 14.82333333, > > 92.37333333, 98.95666667, 1.48333333, 0.64666667, > > 50.66000000, > > 25.75333333, 0.69000000, 0.21666667, 7.40666667, 6.92000000, > > 0.06333333) > > df = data.frame(Substance, Concentration, Value, stringsAsFactors = FALSE) > > Value = c(15.2974126, 16.3196089, 57.4294280, 9.1943370, 20.5567321, > > 14.0874424, > > 38.3626672, 0.3780653, 0.4738495, 37.9124874, 16.2473916, > > 0.7218726, > > 0.2498666, 8.4537585, 10.8058456, 0.1096966) > > dfsd = data.frame(Substance, Concentration, Value, stringsAsFactors = FALSE) > > > > library(lattice) > > COLS = c("gold", "forestgreen", "darkslategray3", "purple") > > xyplot(Value ~ Concentration, > > group = Substance, data = df, > > pch = 16, cex = 1.2, type = "b", > > xlab=expression(bold(paste("Concentration (", mu, "M)"))), > > ylab=expression(bold("Infection rate")), > > col=COLS, > > scales = list(x = list(log = 10, at=c(unique(df$Concentration)) > > ) > > ), > > key = list(space="top", columns=4, col = "black", > > points=list(pch=c(16, 16, 16, 16), > > col=COLS, > > text=list(c("6-PN", "8-PN", "IX", "XN") > > ) > > ) > > ) > > > > ) > > ``` > > but how do I add the error bars? > > I tried with > > ``` > > xyplot(Value ~ Concentration, > > group = Substance, data = df, > > pch = 16, cex = 1.2, type = "b", > > xlab=expression(bold(paste("Concentration (", mu, "M)"))), > > ylab=expression(bold("Infection rate")), > > col=COLS, > > scales = list(x = list(log = 10, at=c(unique(df$Concentration)) > > ) > > ), > > key = list(space="top", columns=4, col = "black", > > points=list(pch=c(16, 16, 16, 16), > > col=COLS, > > text=list(c("6-PN", "8-PN", "IX", "XN") > > ) > > ) > > ), > > panel = function (x,y,) { > > panel.segments(x0 = df$Concentration, x1 = df$Concentration, > > y0 = df$Value - dfsd$Value, > > y1 = df$Value + dfsd$Value, > > col = COLS) > > } > > > > ) > > ``` > > but the bars are plotted outside the graph. > > You need to apply the log-transformation yourself, e.g., > > panel.segments(x0 = log10(df$Concentration), x1 = > log10(df$Concentration), > > But this is not really a scalable approach. You should check if > Hmisc::xYplot suits your needs: > > https://search.r-project.org/CRAN/refmans/Hmisc/html/xYplot.html > > Best, > -Deepayan > > > What is the correct syntax? can I use raw data instead of making the > > mean and std dev separately? > > Thanks > > > > -- > > Best regards, > > Luigi > > > > ______________________________________________ > > 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. -- Best regards, Luigi ______________________________________________ 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.