Adding x and y Axis Label to ggplot-grid Built with cowplot in R

ggplot2 is one of the most widely used libraries for creating elegant data visualizations in R. Often, you will want to arrange multiple plots together to create a grid layout for comparison or presentation purposes. cowplot is a popular extension that simplifies the arrangement of multiple ggplot objects into a grid. However, one challenge when using a cowplot is adding common axis labels to the entire grid of plots using R Programming Language.

In this article, we will walk through how to add common x-axis and y-axis labels to a grid of ggplots built using cowplot.

What is a cowplot?

cowplot is an add-on for ggplot2 that makes it easier to create grids of plots and add annotations like titles, labels, and captions. While ggplot2 has its tools for arranging plots (like facet_grid()), cowplot is designed for more control and customization in multi-plot layouts.

Prerequisites

Before you begin, ensure you have the required packages installed:

library(ggplot2)
library(cowplot)

Step 1: Create Individual Plots Using ggplot2

We’ll use the mtcars dataset to create two different plots as examples.

# Creating the first plot: mpg vs wt
plot1 <- ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(color = "blue") +
  ggtitle("Miles per Gallon vs Weight") +
  theme_minimal()

# Creating the second plot: hp vs wt
plot2 <- ggplot(mtcars, aes(x = wt, y = hp)) +
  geom_point(color = "red") +
  ggtitle("Horsepower vs Weight") +
  theme_minimal()

At this point, we have two separate ggplot objects, plot1 and plot2.

Step 2: Combine the Plots Using plot_grid from cowplot

To combine the plots into a single grid, use the plot_grid() function from cowplot.

# Combine the plots into a grid
combined_plot <- plot_grid(plot1, plot2, labels = c("A", "B"), ncol = 2)
combined_plot

Output:

The labels argument adds labels to each plot, and ncol = 2 arranges the plots in two columns.

Step 3: Adding X and Y Axis Labels to the Entire Grid

Adding common X and Y-axis labels requires the draw_label() and ggdraw() functions from cowplot. Here's how you do it:

# Adding axis labels using ggdraw and draw_label
final_plot <- ggdraw(combined_plot) +
  draw_label("Weight (1000 lbs)", x = 0.5, y = 0, vjust = -1, angle = 0, size = 14) +
  draw_label("Value", x = 0, y = 0.5, vjust = 1.5, angle = 90, size = 14)

final_plot

Output:

• ggdraw(combined_plot): Wraps the combined plot to allow additional elements to be added.
• draw_label("Weight (1000 lbs)", ...): Adds the X-axis label with:
  • x = 0.5: Centers the label horizontally.
  • y = 0: Positions it at the bottom.
  • vjust = -1: Adjusts vertical justification to avoid overlapping.
  • angle = 0: Keeps the label horizontal.
  • size = 14: Sets the font size.
• draw_label("Value", ...): Adds the Y-axis label with:
  • x = 0: Places it on the left.
  • y = 0.5: Centers the label vertically.
  • vjust = 1.5: Adjusts vertical positioning.
  • angle = 90: Rotates the label to be vertical.

Using plot_grid Options to Adjust Layout

If you need a more complex layout, plot_grid() can handle multiple rows or different column widths:

# Combining three plots in a grid layout
plot3 <- ggplot(mtcars, aes(x = wt, y = qsec)) +
  geom_point(color = "green") +
  ggtitle("Quarter Mile Time vs Weight") +
  theme_minimal()

combined_plot <- plot_grid(plot1, plot2, plot3, ncol = 1, align = "v", labels = c("A", "B", "C"))

# Adding axis labels
final_plot <- ggdraw(combined_plot) +
  draw_label("Weight (1000 lbs)", x = 0.5, y = 0, vjust = -1.2, angle = 0, size = 16, fontface = "bold",
               color = "darkblue") +
  draw_label("Value", x = 0, y = 0.5, vjust = 1.2, angle = 90, size = 16, fontface = "bold", color = "darkred")

final_plot

Output:

This example arranges three plots vertically (ncol = 1) and aligns them, showcasing how flexible plot_grid() is in handling multiple layouts.

Conclusion

• cowplot provides a seamless way to combine ggplot objects into a grid and add common axis labels.
• You can use draw_label() and ggdraw() functions to add custom X and Y-axis labels to your plot grid.
• This approach offers flexibility in customization, enabling you to adjust label position, size, color, and alignment.

With these techniques, you can create professional multi-plot layouts with clearly defined axis labels, enhancing the overall readability and interpretation of your data visualizations.