Understanding Grouping Bars in a ggplot2 Bar Graph
When working with bar graphs in R using the ggplot2 package, grouping bars by category can be achieved through various methods. In this article, we’ll explore how to group bars in a ggplot2 bar graph and provide practical examples to help you achieve your desired output.
The Problem with Ordering Bars
The user provided a sample dataset and code snippet for creating a bar chart using ggplot2. They wanted to order the bars based on another variable (category) while grouping them by the same category. However, when they used the reorder function from the dplyr package, they received warnings and did not get the desired output.
A Different Approach: Using an Anonymous Function
The provided solution uses an anonymous function to reorder the bars based on the integer codes stored internally for each factor level in R. The code snippet is as follows:
ex1.dta2 <- transform(ex1.dta, domain = reorder(domain, category, FUN = function(x){ min(as.numeric(x)) }))
This approach requires a good understanding of how factors work in R and how to manipulate their internal representations.
Understanding the Factors
Factors are stored internally as integer codes, which can be obtained using the levels function. The code snippet demonstrates how to reorder the bars based on these internal codes:
ex1.dta2 <- transform(ex1.dta, domain = reorder(domain, category, FUN = function(x){ min(as.numeric(levels(x)[as.integer(factor(x))])) }))
In this revised example, we use levels and factor to extract the integer codes stored internally for each factor level.
A More Comprehensive Approach: Grouping Bars
To group bars by categories while maintaining their order, you can use a combination of the group_by function from dplyr, the arrange function, and the scale_x_discrete function with breaks.
Here’s an example:
library(ggplot2)
library(dplyr)
# Load data
ex1.dta <- read.csv("../../Datasets/ex1.txt", sep=",", header = TRUE)
# Group data by category and arrange bars in descending order
ex1.dta2 <- ex1.dta %>%
group_by(category) %>%
arrange(-domain, category)
# Create bar chart with grouped bars
ggplot(ex1.dta2, aes(domain, fill = category)) +
geom_bar(position = "fill") +
scale_y_continuous(name = "Proportion") +
scale_x_discrete(name = "domains", breaks = unique(ex1.dta2$domain), labels = ex1.dta2$category) +
scale_fill_manual(values = c("#841108", "#16a4e9", "#a4a42a", "#eb96ed", "grey"), name = "category") +
theme_bw() +
opts(
axis.text.x = theme_text(angle = -90, hjust = 0),
axis.line = theme_segment(colour = "black"),
panel.grid.major = theme_blank(),
panel.grid.minor = theme_blank(),
panel.border = theme_blank()) +
geom_vline(xintercept = 0)
Using breaks to Group Bars
Another approach is to use the breaks function within scale_x_discrete to group bars together.
ggplot(ex1.dta2, aes(domain, fill = category)) +
geom_bar(position = "fill") +
scale_y_continuous(name = "Proportion") +
scale_x_discrete(name = "domains", breaks = c("ced0.11", "ced1.1", "ced1.5", "ced1.7", "ced1.3", "ced1.6", "ced1.1", "ced0.8", "ced0.6", "ced0.6", "ced1.5", "ced1.5", "ced1.6", "ced0.16", "ced0.15", "ced0.15", "ced0.24", "ced0.8", "ced0.4", "ced0.19", "ced0.5", "ced0.9", "ced0.3"), labels = ex1.dta2$category) +
scale_fill_manual(values = c("#841108", "#16a4e9", "#a4a42a", "#eb96ed", "grey"), name = "category") +
theme_bw() +
opts(
axis.text.x = theme_text(angle = -90, hjust = 0),
axis.line = theme_segment(colour = "black"),
panel.grid.major = theme_blank(),
panel.grid.minor = theme_blank(),
panel.border = theme_blank()) +
geom_vline(xintercept = 0)
In this revised example, the breaks function groups bars by their corresponding category levels.
Last modified on 2025-01-15