How to Superimpose Bar Plots in R

Superimposing bar plots are an effective way to visualize and compare datasets in a single figure. In R, bar plots are typically created using base R graphics or the ggplot2 package, both of which offer powerful options for overlaying bars. This article will explain how to superimpose bar plots, covering both theoretical concepts and practical examples using R Programming Language.

Bar Plots in R

Bar plots display categorical data with rectangular bars where the height of the bar represents the data values. Bar plots can be:

• Grouped: Side-by-side bars for comparison of categories.
• Stacked: Bars are stacked on top of one another.
• Superimposed: Overlapping bars with varying transparency.

What is Superimposing?

Superimposing refers to placing multiple plots on top of one another for direct comparison. In bar plots, this is typically done by controlling the opacity (transparency) of the bars to avoid obscuring data. This can be particularly useful for comparing multiple datasets across the same categories.

Method 1: Create Superimposing Bar Plots Using Base R Graphics

Base R offers the barplot() function for generating bar plots. However, overlaying bar plots with base R is somewhat limited compared to ggplot2.

# Sample Data
x <- c("A", "B", "C", "D", "E")
y1 <- c(5, 10, 15, 20, 25)
y2 <- c(10, 5, 20, 15, 10)

# Create a basic bar plot
barplot(y1, names.arg = x, col = "blue", ylim = c(0, 30), beside = TRUE)

# Superimpose another bar plot with transparency
barplot(y2, col = rgb(1, 0, 0, 0.5), add = TRUE)

Output:

• barplot(y1,...): Creates the first bar plot for y1.
• barplot(y2,...): Superimposes the second bar plot on top of y1. The argument add = TRUE is used to overlay the second plot.
• rgb(1, 0, 0, 0.5): Controls the color and transparency of the second bar plot. Here, the bars are red with 50% transparency.

Method 2: Create Superimposing Bar Plots Using ggplot2

ggplot2 offers more flexibility and control over the appearance of superimposed bar plots through the use of layers. The alpha argument controls transparency, and multiple geom_bar() layers can be added to the same plot.

install.packages("ggplot2")
library(ggplot2)
# Create a dataframe
df <- data.frame(
  Category = rep(c("A", "B", "C", "D", "E"), times = 2),
  Value = c(5, 10, 15, 20, 25, 10, 5, 20, 15, 10),
  Group = rep(c("Group 1", "Group 2"), each = 5)
)
# Superimpose bar plots with transparency using ggplot2
ggplot(df, aes(x = Category, y = Value, fill = Group)) +
  geom_bar(stat = "identity", position = "identity", alpha = 0.5) +
  labs(title = "Superimposed Bar Plots", x = "Category", y = "Value") +
  scale_fill_manual(values = c("blue", "red"))

Output:

• ggplot(df, aes(...)): Initializes the ggplot object with the dataframe df and aesthetics for x, y, and fill mapped to Group.
• geom_bar(stat = "identity", position = "identity", alpha = 0.5): Creates bar plots for both groups. The position = "identity" argument makes the bars overlap, while alpha = 0.5 sets the transparency to 50%.
• scale_fill_manual(): Manually assigns colors to the bars (blue for Group 1 and red for Group 2).
• labs(): Adds labels to the title, x-axis, and y-axis.

Superimposing Grouped Bar Plots

In some cases, you may want to group bars rather than stack them. Here’s how you can do this:

# Grouped bar plot with transparency
ggplot(df, aes(x = Category, y = Value, fill = Group)) +
  geom_bar(stat = "identity", position = position_dodge(width = 0.8), alpha = 0.5) +
  labs(title = "Grouped Superimposed Bar Plots", x = "Category", y = "Value") +
  scale_fill_manual(values = c("blue", "red"))

Output:

• position_dodge(width = 0.8): This positions the bars side by side (grouped) with some overlap.
• alpha = 0.5: Ensures the bars remain semi-transparent.

Conclusion

Superimposing bar plots allows for more direct visual comparison between datasets by overlapping bars. This method can be implemented using both base R graphics and ggplot2. However, ggplot2 provides more flexibility with regard to aesthetics, transparency control, and layering of plots.