CODEWITHSUNDEEP
rggplot2
Maral Dorri
Maral Dorri

Reputation: 478

How to plot error bars for a mean with ggplot2 in R?

I have plotted my data as a scatter bar plot and have a benchmark (Basemodel) and a theoretical value (AASHTO) that I am presenting with different colored points. I use the following code and my graph looks as follows:

library(ggplot2)
ggplot(data = plotshear, aes(x = Shear, y = LLDF)) + geom_jitter(aes(colour = Source))

# plotshear data:

      Source     Shear        LLDF
# 1   Baseline   EXT.Single   0.7627894
# 2   Samples    EXT.Single   0.7130376
# 3   Baseline   EXT.Multi    0.8521338
# 4   Samples    EXT.Multi    0.7975502
# 5   Baseline   INT.Single   0.5706947
# 6   Samples    INT.Single   0.5462812
# 7   Baseline   INT.Multi    0.7291602
# 8   Samples    INT.Multi    0.7331171
# 9   AASHTO     EXT.Multi    0.8250000
# 10  AASHTO     INT.Single   0.7200000
# 11  AASHTO     INT.Multi    0.8840000

I actually need a error bar for a mean looking like this:

current plot

current plot

plot needed

plot needed

Upvotes: 1

Views: 799

Answers (1)

Caitlin
Caitlin

Reputation: 525

Here is a solution that reproduces the "plot needed" figure from your data:

library(ggplot2)

# plotshear data:
plotshear <- data.frame(Source = c(rep(c("Baseline", "Samples"), 4), rep("AASHTO", 3)),
                        Shear = c(rep("EXT.Single", 2), rep("EXT.Multi", 2), rep("INT.Single", 2),
                                  rep("INT.Multi", 3), "INT.Single", "INT.Multi"),
                        LLDF = c(0.7627894, 0.7130376, 0.8521338, 0.7975502, 0.5706947,
                                 0.5462812, 0.7291602, 0.7331171, 0.8250000, 0.7200000, 0.8840000))

#without error bars
ggplot(data = plotshear, aes(x = Shear, y = LLDF)) +
  geom_boxplot() +
  geom_jitter(aes(color = Source)) +
  stat_summary(fun.y=mean, geom="point", shape=23, size=4) +
  stat_summary(fun.y=mean, geom="line", aes(group=1)) 

#with error bars
ggplot(data = plotshear, aes(x = Shear, y = LLDF)) +
  geom_boxplot() +
  geom_jitter(aes(color = Source)) +
  stat_summary(fun.y=mean, geom="point", shape=23, size=4) +
  stat_summary(fun.y=mean, geom="line", aes(group=1)) +
  stat_summary(fun.data = mean_se, geom = "errorbar")

Upvotes: 3

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