ggplot2 barplot with dual Y-axis and error bars

Question

I am trying to generate a barplot with dual Y-axis and error bars. I have successfully generated a plot with error bars for one variable but I don't know how to add error bars for another one. My code looks like this. Thanks.

library(ggplot2)


#Data generation
Year <- c(2014, 2015, 2016)
Response <- c(1000, 1100, 1200)
Rate <- c(0.75, 0.42, 0.80)
sd1<- c(75, 100, 180)
sd2<- c(75, 100, 180)

df <- data.frame(Year, Response, Rate,sd1,sd2)
df



# The errorbars overlapped, so use position_dodge to move them horizontally
pd <- position_dodge(0.7) # move them .05 to the left and right


png("test.png", units="in", family="Times",  width=2, height=2.5, res=300) #pointsize is font size| increase image size to see the key
ggplot(df)  + 
  geom_bar(aes(x=Year, y=Response),stat="identity", fill="tan1", colour="black")+
  geom_errorbar(aes(x=Year, y=Response, ymin=Response-sd1, ymax=Response+sd1),
                width=.2,  # Width of the error bars
                position=pd)+
 geom_line(aes(x=Year, y=Rate*max(df$Response)),stat="identity",color = 'red', size = 2)+
 geom_point(aes(x=Year, y=Rate*max(df$Response)),stat="identity",color = 'black',size = 3)+
 scale_y_continuous(name = "Left Y axis", expand=c(0,0),limits = c(0, 1500),breaks = seq(0, 1500, by=500),sec.axis = sec_axis(~./max(df$Response),name = "Right Y axis"))+
  theme(
    axis.title.y = element_text(color = "black"),
    axis.title.y.right = element_text(color = "blue"))+
  theme(
    axis.text=element_text(size=6, color = "black",family="Times"),
    axis.title=element_text(size=7,face="bold", color = "black"),
    plot.title = element_text(color="black", size=5, face="bold.italic",hjust = 0.5,margin=margin(b = 5, unit = "pt")))+
  theme(axis.text.x = element_text(angle = 360, hjust = 0.5, vjust = 1.2,color = "black" ))+
  theme(axis.line = element_line(size = 0.2, color = "black"),axis.ticks = element_line(colour = "black", size = 0.2))+
  theme(axis.ticks.length = unit(0.04, "cm"))+
  theme(plot.margin=unit(c(1,0.1,0.1,0.4),"mm"))+
  theme(axis.title.y = element_text(margin = margin(t = 0, r = 4, b = 0, l = 0)))+
  theme(axis.title.x = element_text(margin = margin(t = 0, r = 4, b = 2, l = 0)))+
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    panel.background = element_blank())+
  ggtitle("SRG3")+
  theme(legend.position="top")+
  theme(  legend.text=element_text(size=4),
          #legend.justification=c(2.5,1),
          legend.key = element_rect(size = 1.5),
          legend.key.size = unit(0.3, 'lines'),
          legend.position=c(0.79, .8),  #width and height
          legend.direction = "horizontal",
          legend.title=element_blank())

dev.off()

and my plot is as follows:

Answer 1

A suggestion for future questions: your example is far from being a minimal reproducible example. All the visuals an the annotations are not related to your problem but render the code overly complex which makes it harder for others to work with it.

The following would be sufficient:

ggplot(df) + 
geom_bar(aes(x = Year, y = Response), 
             stat = "identity", fill = "tan1", 
             colour = "black") +
geom_errorbar(aes(x = Year, ymin = Response - sd1, ymax = Response + sd1),
              width = .2,
              position = pd) +
geom_line(aes(x = Year, y = Rate * max(df$Response)), 
          color = 'red', size = 2) +
geom_point(aes(x = Year, y = Rate * max(df$Response)), 
           color = 'black', size = 3)

(Notice that I've removed stat = "identity" in all geom_s because this is set by default. Furthermore, y is not a valid aestetic for geom_errorbar() so I omitted that, too.)

Assuming that the additional variable you would like to plot error bars for is Rate * max(df$Response)) and that the relevant standard deviation is sd2, you may simply append

 + geom_errorbar(aes(x = Year, ymin = Rate * max(df$Response) - sd2, 
                     ymax = Rate * max(df$Response) + sd2), 
                 colour = "green",
                 width = .2)

to the code chunk above. This yields the output below.