Make error-bands only around selected lines in ggplot

tidyverse
1

Hi everyone,
I would like to plot error bands around the orange and the yellowish plot lines whereas no error bands should be plotted for the blue and the black dots (see Fig).

How do I achive this? both the color of the "geom_smooth" and the "geom_fill" cannot be independently manipulated. I posted an example below in which I disabled the drawing of the error band (i.e. se=F in the geom_smooth command)
Thanks a lot for your help
Michael

Rplot
Rplot750×532 57.6 KB

data<-structure(list(CT_percent_dw = c(3.055555556, 3.409090909, 3.360215054,
3.315789474, 3.602362205, 3.086642599, 2.559726962, 2.232824427,
3.409090909, 2.978723404, 3.284883721, 3.016605166, 3.192041522,
2.952961672, 0.666666667, 1.810344828, 1.304347826, 1.781609195,
1.132075472, 1.349480969, 1.711956522, 0.517857143, 0.616438356,
0.510416667, 0.510638298, 0.610671937, 0.571428571, 0.802816901,
0.645104895, 0.718867925, 0.418478261, 0.696428571, 0.372093023,
0.742474916, 0.579150579, 0.615789474, 0.424914676, 0.349315068,
0.45112782, 0.416666667, 0.43772242, 2.819343066, 2.575757576,
2.984429066, 2.87109375, 2.142857143, 2.408759124, 1.8, 2.191901408,
2.293814433, 2.17472119, 2.405660377, 1.972318339, 3.036971831,
2.409747292, 2.572992701, 0.719557196, 0.622340426, 0.528169014,
0.625, 0.619791667, 0.436643836, 0.557761733, 0.430795848, 0.720430108,
0.446488294, 0.513422819, 0.469072165, 0.670648464, 0.559782609,
0.623239437, 0.776978417, 0.528169014, 0.711864407, 0.591796875,
0.734899329, 0.774368231, 0.525, 0.561776062, 0.734899329, 0.711956522,
0.963898917, 0.525, 0.439929329, 0.331578947, 0.366666667, 0.527777778,
0.796232877, 0.570588235, 0.262081784, 0.45959596, 0.448943662,
0.375, 0.505434783, 0.380681818), Pgpctsum = c(13.10100945, 14.03673316,
14.49033379, 14.20816207, 14.82049752, 14.31834663, 15.88320471,
16.26222056, 15.99855401, 16.7586737, 14.25929587, 15.36294444,
20.4937829, 16.90591139, 15.15631183, 22.7635716, 20.21575313,
21.22385497, 19.61140996, 23.80658212, 23.76776508, 18.21564315,
18.75050239, 18.66763459, 16.00376874, 14.83957532, 16.30774913,
19.49650719, 20.49798949, 18.15922748, 22.44657632, 21.26352884,
22.0857716, 17.86958824, 22.34934497, 20.0878363, 16.45076702,
18.61461888, 20.22716516, 21.77610898, 21.61290398, 15.47781773,
17.72589645, 13.24205241, 18.32590611, 16.14200976, 16.80843022,
16.82300431, 21.87117205, 18.1808839, 20.08058227, 23.5485354,
18.1125673, 17.30384798, 16.16080714, 17.21315326, 18.650118,
20.9817806, 18.07990634, 15.44913819, 18.02141379, 17.66843885,
17.37556129, 14.98621478, 23.52376447, 29.35898523, 23.13026266,
26.52283678, 28.29012736, 25.71698236, 15.2704095, 16.05241869,
17.23668338, 14.14301824, 13.91135314, 16.39329887, 20.18792759,
21.02312301, 24.68641607, 18.11268841, 15.88482023, 18.86816297,
23.52210358, 18.04458379, 24.7702106, 21.463626, 26.25516317,
24.04047496, 21.12506343, 22.69767598, 18.16931978, 20.33538331,
19.20997483, 20.1073092, 28.82528598), Category = c("CW", "CW",
"CW", "CW", "CW", "BeW", "BeW", "BeW", "BeW", "BeW", "BeW", "CD",
"CD", "CD", "CD", "CD", "BeD", "BeD", "BeD", "BeD", "BeD", "CW",
"CW", "CW", "CW", "CW", "BeW", "BeW", "BeW", "BeW", "BeW", "CD",
"CD", "CD", "CD", "CD", "BeD", "BeD", "BeD", "BeD", "BeD", "CW",
"CW", "CW", "CW", "CW", "CW", "CW", "BeW", "BeW", "BeW", "BeW",
"BeW", "BeW", "BeW", "BeW", "CW", "CW", "CW", "CW", "CW", "CW",
"CW", "BeW", "BeW", "BeW", "BeW", "BeW", "BeW", "BeW", "CW",
"CW", "CW", "CW", "CW", "CW", "BeW", "BeW", "BeW", "BeW", "BeW",
"BeW", "BeW", "CD", "CD", "CD", "CD", "CD", "CD", "BeD", "BeD",
"BeD", "BeD", "BeD", "BeD")), class = "data.frame", row.names = c(NA,
-95L))

ggplot(data, aes(x=log(CT_percent_dw),y=Pgpctsum, color=Category, linetype=Category)) +
geom_point(aes(fill=Category,color=Category),alpha=1, size=5, shape=21) +
geom_smooth(method="lm", alpha=0.4, linewidth=1.2,se=F, aes(fill=Category))+# group=1 necessary for drawing line
scale_fill_manual(values=c("#3182bd","#f46d43","#d3c88f","black"),labels=c("CW"="No stress","CD"="Drought (Dr)","BeW"="Defoliation (Def)","BeD"="Dr-Def"))+
scale_color_manual(values=c("#3182bd","#f46d43","#d3c88f","black"),labels=c("CW"="No stress","CD"="Drought (Dr)","BeW"="Defoliation (Def)","BeD"="Dr-Def"))+
scale_linetype_manual(values=c("blank","solid","solid","blank"),labels=c("CW"="No stress","CD"="Drought (Dr)","BeW"="Defoliation (Def)","BeD"="Dr-Def"))+
labs(title = "", y = "Phenolic glycosides [%dw]", x="log(Condensed tannins [%dw])")+
guides(fill=guide_legend(title="Stress treatment"))+
guides(color=guide_legend(title="Stress treatment"))+
guides(linetype=guide_legend(title="Stress treatment"))+
#Legend labels
theme(legend.position="right")+
#define theme
theme_classic() +
theme(axis.text=element_text(face="bold",size=16),
axis.title = element_text(color="black",face="bold",size=18),
axis.line = element_line(colour = 'black', size = 1),
axis.ticks = element_line(colour = "black", size = 1),
legend.text=element_text(size=16),
legend.title=element_text(size=18, face="bold"),
panel.grid.major.y = element_line(colour = "grey85",size = .5),
plot.title = element_text(color="black", size=21, face="bold"))+
#Increase legend symbol size
guides(shape = guide_legend(override.aes = list(size=3.5)))

2

you can change the data on which the geom_smooth operates, for example

 geom_smooth(data =data |> filter(Category %in% c("CD","BeW")),
method="lm", alpha=0.4, linewidth=1.2,se=TRUE, aes(fill=Category)
1 Like
3

Thanks a ton for your fast reply. I was unaware of the "filter" option in ggplot. An eye opener!
Michael

4

sorry; filter is not a ggplot2 function; its from dplyr which is part of the tidyverse alongside ggplot2
so you would need either library(tidyverse) or library(dplyr) to make such an approach work.
you could also subset data with base R

data[data[,3] %in% c("CD","BeW"),]

i just prefer the dplyr filter syntax.

5

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