You can use the following basic syntax to add error bars to a bar plot in R:

ggplot(df) +
    geom_bar(aes(x=x, y=y), stat='identity') +
    geom_errorbar(aes(x=x, ymin=y-sd, ymax=y+sd), width=0.4)

The following examples show how to use this function in practice.

Example 1: Add Error Bars Using Summary Data

Suppose we have the following data frame in R that shows the summary statistics for five categories:

#create data frame
df <- data.frame(category=c('A', 'B', 'C', 'D', 'E'),
                 value=c(12, 17, 30, 22, 19),
                 sd=c(4, 5, 7, 4, 2))

#view data frame
df

  category value sd
1        A    12  4
2        B    17  5
3        C    30  7
4        D    22  4
5        E    19  2

We can use the following code to create a bar plot with error bars to visualize this data:

library(ggplot2)

#create bar plot with error bars
ggplot(df) +
    geom_bar(aes(x=category, y=value), stat='identity', fill='steelblue') +
    geom_errorbar(aes(x=category, ymin=value-sd, ymax=value+sd), width=0.4)

Feel free to use the following arguments to modify the appearance of the error bars:

• width: The width of the error bars
• size: The thickness of the error bars
• color: The color of the error bars

For example:

library(ggplot2)#create bar plot with custom error bars 
ggplot(df) +
    geom_bar(aes(x=category, y=value), stat='identity', fill='steelblue') +
    geom_errorbar(aes(x=category, ymin=value-sd, ymax=value+sd),
                  width=0.3, size=2.3, color='red')

Example 2: Add Error Bars Using Raw Data

Suppose we have the following data frame that shows the raw data for five different categories:

#make this example reproducible
set.seed(0)

#create data frame
df <- data.frame(category=rep(c('A', 'B', 'C', 'D', 'E'), each=10),
                 value=runif(50, 10, 20))

#view first six rows of data frame
head(df)

  category    value
1        A 18.96697
2        A 12.65509
3        A 13.72124
4        A 15.72853
5        A 19.08208
6        A 12.01682

library(dplyr)
library(ggplot2)
#summarize mean and sd for each category
df_summary <- df %>%
  group_by(category) %>%
  summarize(mean=mean(value),
            sd=sd(value))

#view summary data
df_summary

# A tibble: 5 x 3
  category  mean    sd
       
1 A         16.4  2.80
2 B         14.9  2.99
3 C         14.6  3.25
4 D         15.2  2.48
5 E         15.8  2.41 

#create bar plot with error bars
ggplot(df_summary) +
    geom_bar(aes(x=category, y=mean), stat='identity', fill='steelblue') +
    geom_errorbar(aes(x=category, ymin=mean-sd, ymax=mean+sd), width=0.3, color='red')

The following tutorials explain how to create other common data visualizations in R: