GGPlot Error Bars Best Reference - Datanovia (2023)

• Loading required R package
• Data preparation
• Key R functions and error plot types
• Basic error bars
• Grouped error bars
• Conclusion

Related Book

GGPlot2 Essentials for Great Data Visualization in R

Loading required R package

Load the ggplot2 package and set the default theme to theme_classic() with the legend at the top of the plot:

library(ggplot2)theme_set( theme_classic() + theme(legend.position = "top") )

Data preparation

• Prepare the data: ToothGrowth data set.

df <- ToothGrowthdf$dose <- as.factor(df$dose)head(df, 3)

## len supp dose## 1 4.2 VC 0.5## 2 11.5 VC 0.5## 3 7.3 VC 0.5

• Compute summary statistics for the variable len organized into groups by the variable dose:

library(dplyr)df.summary <- df %>% group_by(dose) %>% summarise( sd = sd(len, na.rm = TRUE), len = mean(len) )df.summary

## # A tibble: 3 x 3## dose sd len## <fct> <dbl> <dbl>## 1 0.5 4.50 10.6## 2 1 4.42 19.7## 3 2 3.77 26.1

Key R functions and error plot types

Key functions to create error plots using the summary statistics data:

• geom_crossbar() for hollow bar with middle indicated by horizontal line
• geom_errorbar() for error bars
• geom_errorbarh() for horizontal error bars
• geom_linerange() for drawing an interval represented by a vertical line
• geom_pointrange() for creating an interval represented by a vertical line, with a point in the middle.

Start by initializing ggplot with the summary statistics data:

• Specify x and y as usually
• Specify ymin = len-sd and ymax = len+sd to add lower and upper error bars. If you want only to add upper error bars but not the lower ones, use ymin = len (instead of len-sd) and ymax = len+sd.

# Initialize ggplot with dataf <- ggplot( df.summary, aes(x = dose, y = len, ymin = len-sd, ymax = len+sd) )

Possible error plots:

Basic error bars

Create simple error plots:

# Vertical line with point in the middlef + geom_pointrange()# Standard error barsf + geom_errorbar(width = 0.2) + geom_point(size = 1.5)

Create horizontal error bars. Put dose on y axis and len on x-axis. Specify xmin and xmax.

# Horizontal error bars with mean points# Change the color by groupsggplot(df.summary, aes(x = len, y = dose, xmin = len-sd, xmax = len+sd)) + geom_point() + geom_errorbarh(height=.2)

• Add jitter points (representing individual points), dot plots and violin plots. For this, you should initialize ggplot with original data (df) and specify the df.summary data in the error plot function, here geom_pointrange().

# Combine with jitter pointsggplot(df, aes(dose, len)) + geom_jitter(position = position_jitter(0.2), color = "darkgray") + geom_pointrange(aes(ymin = len-sd, ymax = len+sd),data = df.summary)# Combine with violin plotsggplot(df, aes(dose, len)) + geom_violin(color = "darkgray", trim = FALSE) + geom_pointrange(aes(ymin = len-sd, ymax = len+sd), data = df.summary)

• Create basic bar/line plots of mean +/- error. So we need only the df.summary data. :
  1. Add lower and upper error bars for the line plot: ymin = len-sd and ymax = len+sd.
  2. Add only upper error bars for the bar plot: ymin = len (instead of len-sd) and ymax = len+sd.

Note that, for line plot, you should always specify group = 1 in the aes(), when you have one group of line.

# (1) Line plotggplot(df.summary, aes(dose, len)) + geom_line(aes(group = 1)) + geom_errorbar( aes(ymin = len-sd, ymax = len+sd),width = 0.2) + geom_point(size = 2)# (2) Bar plotggplot(df.summary, aes(dose, len)) + geom_col(fill = "lightgray", color = "black") + geom_errorbar(aes(ymin = len, ymax = len+sd), width = 0.2) 

For line plot, you might want to treat x-axis as numeric:

df.sum2 <- df.summarydf.sum2$dose <- as.numeric(df.sum2$dose)ggplot(df.sum2, aes(dose, len)) + geom_line() + geom_errorbar( aes(ymin = len-sd, ymax = len+sd),width = 0.2) + geom_point(size = 2)

• Bar plots and line plots + jitter points. We need the original df data for the jitter points and the df.summary data for the other geom layers.
  1. For the line plot: First, add jitter points, then add lines + error bars + mean points on top of the jitter points.
  2. For the bar plot: First, add the bar plot, then add jitter points + error bars on top of the bars.

# (1) Create a line plot of means + # individual jitter points + error bars ggplot(df, aes(dose, len)) + geom_jitter( position = position_jitter(0.2), color = "darkgray") + geom_line(aes(group = 1), data = df.summary) + geom_errorbar( aes(ymin = len-sd, ymax = len+sd), data = df.summary, width = 0.2) + geom_point(data = df.summary, size = 2)# (2) Bar plots of means + individual jitter points + errorsggplot(df, aes(dose, len)) + geom_col(data = df.summary, fill = NA, color = "black") + geom_jitter( position = position_jitter(0.2), color = "black") + geom_errorbar( aes(ymin = len-sd, ymax = len+sd), data = df.summary, width = 0.2) 

Grouped error bars

Case of one continuous variable (len) and two grouping variables (dose, supp).

• Compute the summary statistics of len grouped by dose and supp:

library(dplyr)df.summary2 <- df %>% group_by(dose, supp) %>% summarise( sd = sd(len), len = mean(len) )df.summary2

## # A tibble: 6 x 4## # Groups: dose [?]## dose supp sd len## <fct> <fct> <dbl> <dbl>## 1 0.5 OJ 4.46 13.2 ## 2 0.5 VC 2.75 7.98## 3 1 OJ 3.91 22.7 ## 4 1 VC 2.52 16.8 ## 5 2 OJ 2.66 26.1 ## 6 2 VC 4.80 26.1

• Create error plots for multiple groups:
  1. pointrange colored by groups (supp)
  2. standard error bars + mean points colored by groups (supp)

# (1) Pointrange: Vertical line with point in the middleggplot(df.summary2, aes(dose, len)) + geom_pointrange( aes(ymin = len-sd, ymax = len+sd, color = supp), position = position_dodge(0.3) )+ scale_color_manual(values = c("#00AFBB", "#E7B800"))# (2) Standard error barsggplot(df.summary2, aes(dose, len)) + geom_errorbar( aes(ymin = len-sd, ymax = len+sd, color = supp), position = position_dodge(0.3), width = 0.2 )+ geom_point(aes(color = supp), position = position_dodge(0.3)) + scale_color_manual(values = c("#00AFBB", "#E7B800")) 

• Create simple line/bar plots for multiple groups.
  1. Line plots: change linetype by groups (supp)
  2. Bar plots: change fill color by groups (supp)

# (1) Line plot + error barsggplot(df.summary2, aes(dose, len)) + geom_line(aes(linetype = supp, group = supp))+ geom_point()+ geom_errorbar( aes(ymin = len-sd, ymax = len+sd, group = supp), width = 0.2 )# (2) Bar plots + upper error bars.ggplot(df.summary2, aes(dose, len)) + geom_col(aes(fill = supp), position = position_dodge(0.8), width = 0.7)+ geom_errorbar( aes(ymin = len, ymax = len+sd, group = supp), width = 0.2, position = position_dodge(0.8) )+ scale_fill_manual(values = c("grey80", "grey30"))

• Add jitter points:

# Line plots with jittered pointsggplot(df, aes(dose, len, color = supp)) + geom_jitter(position = position_jitter(0.2)) + geom_line(aes(group = supp),data = df.summary2) + geom_errorbar(aes(ymin = len-sd, ymax = len+sd), data = df.summary2, width = 0.2)+ scale_color_manual(values = c("#00AFBB", "#E7B800")) + theme(legend.position = "top")# Bar plots + jittered points + error barsggplot(df, aes(dose, len, color = supp)) + geom_col(data = df.summary2, position = position_dodge(0.8), width = 0.7, fill = "white") + geom_jitter( position = position_jitterdodge(jitter.width = 0.2, dodge.width = 0.8) ) + geom_errorbar( aes(ymin = len-sd, ymax = len+sd), data = df.summary2, width = 0.2, position = position_dodge(0.8) )+ scale_color_manual(values = c("#00AFBB", "#E7B800")) + theme(legend.position = "top")

Conclusion

This article describes how to add error bars to plots created using the ggplot2 R package.