Cleaning Up Your Boxplots: Removing Tails and Keeping Median Lines with ggridges
The ggridges package in R is a powerful tool for visualizing distributions across categories using ridgeline plots. However, sometimes the default plot can be visually cluttered, especially with overlapping tails. In this article, we'll learn how to remove the tails from your ridgeline plots while preserving the important median lines, creating a cleaner and more impactful visualization.
Let's consider a simple example using the iris dataset:
library(ggplot2)
library(ggridges)
ggplot(iris, aes(x = Sepal.Length, y = Species, fill = Species)) +
geom_density_ridges(alpha = 0.6) +
theme_ridges()
This code generates a basic ridgeline plot, showcasing the distribution of Sepal Length across different Iris species. While informative, the overlapping tails can make it challenging to distinguish individual distributions.
Removing Tails and Keeping Median Lines
To address this, we can leverage the scale and quantile_lines parameters within geom_density_ridges():
ggplot(iris, aes(x = Sepal.Length, y = Species, fill = Species)) +
geom_density_ridges(alpha = 0.6, scale = 0.8, quantile_lines = TRUE) +
theme_ridges()
Here's how this code works:
scale = 0.8: This parameter controls the width of the density curves. Reducing the scale to 0.8 effectively removes the tails of the distributions, creating a clearer visual separation.quantile_lines = TRUE: This parameter adds horizontal lines representing the quantiles of each distribution. By default, it displays the 50th percentile (median).
Tailoring Your Visualization
You can customize the appearance of the median lines further:
quantile_lines.color: Sets the color of the median lines.quantile_lines.linetype: Adjusts the line type, e.g., dashed, dotted, etc.quantile_lines.size: Changes the thickness of the lines.quantile_lines.alpha: Controls the transparency of the lines.
For example, to display the median lines with a dashed, red line:
ggplot(iris, aes(x = Sepal.Length, y = Species, fill = Species)) +
geom_density_ridges(alpha = 0.6, scale = 0.8, quantile_lines = TRUE, quantile_lines.color = "red", quantile_lines.linetype = "dashed") +
theme_ridges()
Advantages of This Approach
- Improved Visual Clarity: Removing tails and focusing on the median lines allows for clearer comparison between distributions.
- Highlighting Key Trends: The median lines effectively represent the central tendency of each group, making it easier to spot differences in central location.
- Customization: You have full control over the appearance of the median lines to match your specific visualization needs.
Remember, visualization is about communicating data effectively. Experiment with different parameters to create the most informative and visually appealing ridgeline plot for your data.
Additional Resources
ggridgesdocumentation: https://ggridges.tidyverse.org/- "Data Visualization with R" by Garrett Grolemund: https://r4ds.had.co.nz/
This article provided you with a practical solution for customizing your ridgeline plots with ggridges. By removing tails and showcasing median lines, you can create visualizations that are both visually appealing and informative.
