Understanding Geom_errorbar in ggplot2

Background and Context

The geom_errorbar function is a popular visualization tool in the ggplot2 package of R, used to create error bars for lines or points on a plot. The question at hand involves creating multiple geom_errorbar for each geom_line in a ggplot.

Why does geom_errorbar require data transformation?

Long vs Narrow Data Format

ggplot2 expects your data to be in a long or narrow data format, which means the data should have only one row per observation and four columns: x-coordinate, variable (which could range from 1 to 4), y-value, and se-value.

The original code provided does not follow this requirement because it contains multiple rows for each observation. To fix this issue, we need to transform the data into a long format using R’s pivot_longer function or a similar approach.

Converting Data to Long Format

Using pivot_longer()

long_data %>%
  pivot_longer(!x,
               names_pattern = "([[:alpha:]]+)([0-9])",
               names_to = c("stat", "variable")) %>%
  pivot_wider(names_from = stat, 
              values_from = value)

In the above code snippet:

• We first create a new column stat which includes the y-value (y1, y2, etc.) and se-value.
• Then we use the pivot_longer function to separate the variable names into a new column called “variable”.
• The names_to argument is used to rename the old columns. We exclude the x-coordinate by using the exclamation mark before x.
• Finally, we use pivot_wider to convert the long format back to a wide format where each variable has its own y-value and se.

Creating Multiple geom_errorbar

Using ggplot()

long_data %>%
  ggplot(aes(x = x,
           y = y,
           colour = variable,
           shape = variable)) +
  geom_point() +
  geom_line() +
  geom_errorbar(aes(ymax = y+se, ymin = y-se), width = 0.17)

In the above code snippet:

• We use geom_errorbar to create error bars for each line.
• The color and shape aesthetics are used to color and shape the lines based on the variable column.

Example Use Case

Using Tidyverse

library(ggplot2)
library(tidyverse)

set.seed(1)

# Generate data
raw_data <- data.frame(x = seq(10),
                         y1 = sample(x=20,size=10), # c(1.1, 2.4, 3.5, 4.1, 5.9, 6.7, 7.1, 8.3, 9.4, 10.0)
                         y2 = sample(x=20,size=10),
                         y3 = sample(x=20,size=10),
                         y4 = sample(x=20,size=10),
                         se1 = runif(n=10,min=0,max=1),
                         se2 = runif(n=10,min=0,max=1),
                         se3 = runif(n=10,min=0,max=1),
                         se4 = runif(n=10,min=0,max=1))

# Convert to a long format
long_data <- raw_data %>%
  pivot_longer(!x,
               names_pattern = "([[:alpha:]]+)([0-9])",
               names_to = c("stat", "variable")) %>%
  pivot_wider(names_from = stat, 
              values_from = value)

# Plot
long_data %>%
  ggplot(aes(x = x,
             y = y,
             colour = variable,
             shape = variable)) +
  geom_point() +
  geom_line() +
  geom_errorbar(aes(ymax = y+se, ymin = y-se), width = 0.17)

# Display plot
print(long_data)

This code creates multiple lines with corresponding error bars using the geom_errorbar function in ggplot2.

In conclusion, creating multiple geom_errorbar for each geom_line in a ggplot involves transforming the data into a long format and then specifying the aesthetics for the geom_errorbar function.

Last modified on 2024-05-18