search for: geom_hlin

Hi I have a long data set on which I want to do Bland-Altman style plots for each rhythm type Using ggplot2, when I use geom_hline with facet_grid I get an extra set of empty panels. I can't get it to do it with the "Diamonds" data supplied with the package so here is a (much abbreviated) example: > lvexs cvd_basestudy ecd_rhythm fixed_time variable_time 1 CBP05J02 AF 30.9000 29.422...

...39;ve run into a minor problem with ggplot2. In particular, I get an error message when trying to plot a horizonal line through zero. Here is what I do: plt.df <- subset(xfm.df, select=c(stage, subj, tX)) plt <- ggplot(pp.df, aes(x=stage, y=tX, group=subj)) + geom_line() plt plt <- plt + geom_hline(intercept=0) plt The first plot yields a most lovely graph. Addition of the geom_hline yields ... "Error in eval(expr, envir, enclos) : object "subj" not found" The data.frame that I'm plotting looks like this ... > str(plt.df) 'data.frame': 468 obs. of 3...

...ine is not drawn. If I set my intercept to 15 then it'll work but I dont want to hardcode it because the Y axis parameters could be different for another variable. I would like to alway set my hline along the zero as default. Thanks p <- ggplot(mtcars, aes(x = wt, y=mpg)) + geom_point() p + geom_hline(intercept=0) Felipe D. Carrillo Fishery Biologist US Fish & Wildlife Service California, USA ____________________________________________________________________________________ Looking for last minute shopping deals?

Hi, I am newbie user of ggplot and would like some assistance in implementing time series plots. I'd like to know how the tsdiag plot can be made in ggplot? Thanks Harsh Singhal Decisions Systems, Mu Sigma Inc.

...t;, "B"), Detail = c( "b", "c", "1", "2"), resp = runif(4, min = 0.5, max = 1)) ggplot(dataset, aes(x = Detail, y = resp)) + facet_grid(.~Main, scales = "free_x")+ geom_point(aes( size=6,shape = c(16,16,15,15) ),colour="blue")+geom_hline(aes(yintercept=0.25),colour='blue', size=2) with this code all the point are blue (like the line below) But if i try the following code, where my goal is to have the point on the left blue and the one on the right red, a problem appears: dataset <- data.frame(Main = c("A&quo...

Hello, I'm using geom_hline to add a minimum line to my plot (representing the best solution found so far by a search algorithm). I'd like to annotate this line with it's numerical value to save trying to read it off the graph, but I can't see a clear way to do this - any ideas? (Alternatively, if this is...

Dear R Users: I have the individual mortality rate and 95% CI of 100 hospitals, how to do the plot with the individual hospital in the Yaxis, and the mortality rate and 95% CI in the Xais and a overall mean as a reference line? Thanks and regards, Xin [[alternative HTML version deleted]]

...size = 3) + geom_point(aes(x = Date, y = bg, shape = missed_meds), alpha = 0) + #Invisible point layer for shape mapping scale_y_continuous(name = "Blood glucose (mg/dL)", breaks = seq(100, 230, by = 20) ) + geom_hline(yintercept = 130) + scale_shape_manual(name = "Conditions", labels = c("Missed meds", "Missed exercise"), values = c(20, 4), ## size = 3 )...

Dear R-users, I want to plot residuals vs fitted for multiple groups with ggplot2. I try this code, but unsuccessful. library("plyr") models<-dlply(dat1,"d",function(df) mod<-lm(y~x,data=df) ggplot(models,aes(.fitted,.resid), color=factor(d))+ geom_hline(yintercept=0,col="white",size=2)+ geom_point()+ geom_smooth(se=F) -- --- Catalin-Constantin ROIBU Forestry engineer, PhD Forestry Faculty of Suceava Str. Universitatii no. 13, Suceava, 720229, Romania office phone +4 0230 52 29 78, ext. 531 mobile phone +4 0745 53 18 01...

...df, aes(x = x, y = y)) p + geom_point(aes(colour="Observations", shape="Observations")) + stat_summary(aes(colour = "Means", shape ="Means"), fun.y = mean, fun.ymin = min, fun.ymax = max, geom = "point") + geom_hline(aes(yintercept = mean(y), linetype = "Overall Mean"), show_guide = TRUE) I tried to map the linetype in geom_point (and stat_summary) to NULL and I tried to set it to "blank" but neither worked. Is it furthermore possible to combine the two legends? My preferred plot would ha...

...;vp", "a", "b", "c") p <- c(2, 2,1, 3,5) pm<- c(3,4,2,5,4) pn <- c(1,1,1,2,3) x<-data.frame(cbind(n,p,pm,pn)) library(ggplot2) qplot(x=n, y=p, data=x, ymin=pn, ymax=pm, xlab='', ylab='', main='Order Label as: va vp a b c') + geom_hline(yintercept = 2) + geom_linerange() + coord_flip() Thanks! [[alternative HTML version deleted]]

...F=as.vector(acfth),Lag=as.numeric(names(acfth))) ci <- 0.95 climy <- qnorm((1 + ci)/2) / sqrt(artest$n.used) ###Computing significativity levels q2 <- qplot(Lag, IACF, data = base, yend = 0, xend = Lag, geom="bar",stat="identity",fill=I("Darkblue"))+theme_bw()+geom_hline(yintercept=c(-climy,climy),colour="red",linetype="dashed")+opts(title=expression(paste("Inverse autocorrelogram of ",y[t])),plot.title = theme_text(size = 25))+geom_hline(yintercept=0) q2 Hope this can help somebody JB Lepetit -- View this message in context:...

...R 2.14 with ggplot2 0.9 and am finding bugs. > ggplot2 "GPL-2" "2.14.0" This example is taken from pg 101 in the ggplot book. > plot <- qplot(date, psavert, data = economics, geom = "line") + > ylab("Personal savings rate") + geom_hline(xintercept = 0, colour = > "grey50")' > plot + scale_x_date(major = "10 years") Error in continuous_scale(aesthetics, "date", identity, breaks = breaks, : unused argument(s) (major = "10 years")> plot + scale_x_date(limits = as.Date(c("2...

...order * facet_wrap: now works when a layer doesn't contain every level of the faceting variables * geom_abline should now work in a wider variety of situations * geom_smooth now gives correct asymmetric standard errors with generalised linear models (thanks to Thierry Onkelinx) * geom_vline and geom_hline now correctly transform their intercepts if the scale is transformed * geom_vline and geom_hline: now use xintercept and yintercept instead of intercept * legend.position and legend.justification work again * position_dodge now works for any number of elements with smaller widths, not just 2! * sc...

...order * facet_wrap: now works when a layer doesn't contain every level of the faceting variables * geom_abline should now work in a wider variety of situations * geom_smooth now gives correct asymmetric standard errors with generalised linear models (thanks to Thierry Onkelinx) * geom_vline and geom_hline now correctly transform their intercepts if the scale is transformed * geom_vline and geom_hline: now use xintercept and yintercept instead of intercept * legend.position and legend.justification work again * position_dodge now works for any number of elements with smaller widths, not just 2! * sc...

...es (as defined by the coordinate system) to figure out how many pieces each segment should be broken in to (thanks to prompting from Jean-Olivier Irisson) * fix ordering bug in facet_wrap (thanks to bug report by Frank Davenport) * geom_errorh correctly responds to height parameter outside of aes * geom_hline and geom_vline will not impact legend when used for fixed intercepts * geom_hline/geom_vline: intercept values not set quite correctly which caused a problem in conjunction with transformed scales (reported by Seth Finnegan) * geom_line: can now stack lines again with position = "stack"...

...es (as defined by the coordinate system) to figure out how many pieces each segment should be broken in to (thanks to prompting from Jean-Olivier Irisson) * fix ordering bug in facet_wrap (thanks to bug report by Frank Davenport) * geom_errorh correctly responds to height parameter outside of aes * geom_hline and geom_vline will not impact legend when used for fixed intercepts * geom_hline/geom_vline: intercept values not set quite correctly which caused a problem in conjunction with transformed scales (reported by Seth Finnegan) * geom_line: can now stack lines again with position = "stack"...

...all would be like this: ggplot(data = b2, aes(x = Date, y = bg)) + geom_line() + geom_point(aes(shape = medStat), size = 3)+ geom_point(aes(shape = exercise),size = 3)+ scale_y_continuous(name = "Blood glucose (mg/dL)", breaks = seq(100, 230, by = 20) ) + geom_hline(yintercept = 130) + scale_shape_manual(name = "Conditions", labels = c("Missed meds", "Missed exercise"), values = c(20, 4) ) Note that this method then gets very close without the scale_s...

...ot p <- ggplot(data = MyData, aes(x=Year, y=Chloride , col=Detections)) + geom_point(aes(shape=Detections)) + #sets the detect vs. non-detect colors scale_colour_manual(values=c("black","red")) + #sets the y scale and log base 10 scale_y_log10() + ##adds line geom_hline(aes(yintercept=250),linetype="dashed")+ #location of the legend theme(legend.position=c("right")) + #sets the line color, type and size geom_line(colour="black", linetype="dotted", size=0.5) + ylab("Chloride (mg/L)") ## does the graph...

...a = b2, aes(x = Date, y = bg)) + > ? geom_line() + > ? geom_point(aes(shape = medStat), size = 3)+ > ? geom_point(aes(shape = exercise),size = 3)+ > ? scale_y_continuous(name = "Blood glucose (mg/dL)", > ???????????????????? breaks = seq(100, 230, by = 20) > ? ) + > ? geom_hline(yintercept = 130) + > ? scale_shape_manual(name = "Conditions", > ???????????????????? labels = c("Missed meds", > ??????????????????????????????? "Missed exercise"), > ???????????????????? values = c(20, 4) > ? ) > > > Note that this method...