How to Put Plots Without Any Space Using plot_grid in R?

Combining multiple plots into a single visual can be incredibly useful for data comparison and storytelling. In R, the cowplot package provides the plot_grid() function, which makes it easy to arrange multiple ggplot2 plots into a grid layout. Sometimes, you might want these plots to appear without any gaps between them to create a clean and seamless look. This article will show you how to achieve this using plot_grid.

Introduction to the Cowplot Package

The cowplot package is an extension that makes combining multiple plots into a single layout easyggplot2. It offers more control over plot arrangement, margins, and labels.

install.packages("cowplot")
library(cowplot)

Now we will discuss how to Put Plots Without Any Space Using plot_grid in R Programming Language.

Step 1: Creating Basic Plots with ggplot2

First, we need to create some sample plots using ggplot2. Let's create a sample dataset:

install.packages("ggplot2")
library(ggplot2)

# Sample dataset
set.seed(123)
data <- data.frame(
  category = rep(LETTERS[1:3], each = 10),
  value1 = rnorm(30, mean = 5, sd = 1),
  value2 = rnorm(30, mean = 10, sd = 2)
)
# Plot 1: A boxplot
plot1 <- ggplot(data, aes(x = category, y = value1, fill = category)) +
  geom_boxplot() +
  theme_minimal()

# Plot 2: A scatter plot
plot2 <- ggplot(data, aes(x = category, y = value2, color = category)) +
  geom_point(size = 3) +
  theme_minimal()

Step 2: Using plot_grid to Combine Plots

The plot_grid() function allows us to arrange multiple plots in a single layout. By default, some space is present between plots:

# Combining plots with default spacing
combined_plot <- plot_grid(plot1, plot2, ncol = 1)
print(combined_plot)

Output:

Step 3: Removing Space Between Plots

To remove the space between the plots, we can adjust the rel_heights or rel_widths parameter and set align to 'v' (vertical) or 'h' (horizontal). This aligns the plots and removes unnecessary spacing.

# Removing vertical space between two plots
combined_plot_no_space <- plot_grid(plot1, plot2, ncol = 1, 
                                    align = "v", rel_heights = c(1, 1), axis = "lr")
print(combined_plot_no_space)

# Removing horizontal space between two plots
combined_plot_no_space_horizontal <- plot_grid(plot1, plot2, nrow = 1, 
                                      align = "h", rel_widths = c(1, 1), axis = "tb")
print(combined_plot_no_space_horizontal)

Output:

The axis parameter ("lr" for left-right and "tb" for top-bottom) ensures alignment across the shared axis.

Practical Examples with Visualizations

Let's create three different examples using various combinations of plots to illustrate how to remove space effectively. Combining a Line Plot and Bar Plot Vertically Without Space

# Line Plot
line_plot <- ggplot(data, aes(x = category, y = value1, group = 1)) +
  geom_line(color = "blue", size = 1) +
  theme_minimal()

# Bar Plot
bar_plot <- ggplot(data, aes(x = category, y = value2, fill = category)) +
  geom_bar(stat = "identity", color = "black") +
  theme_minimal()

# Combine vertically without space
combined_example1 <- plot_grid(line_plot, bar_plot, ncol = 1, align = "v", rel_heights = c(1, 1), axis = "lr")
print(combined_example1)

Output:

Example 2: Combining a Histogram and Density Plot Horizontally Without Space

In this example we will Combining a Histogram and Density Plot Horizontally Without Space.

# Histogram
histogram_plot <- ggplot(data, aes(x = value1, fill = category)) +
  geom_histogram(binwidth = 0.5, alpha = 0.7) +
  theme_minimal()

# Density Plot
density_plot <- ggplot(data, aes(x = value1, fill = category)) +
  geom_density(alpha = 0.7) +
  theme_minimal()

# Combine horizontally without space
combined_example2 <- plot_grid(histogram_plot, density_plot, nrow = 1, align = "h", 
                               rel_widths = c(1, 1), axis = "tb")
print(combined_example2)

Output:

Conclusion

Using plot_grid from the cowplot package makes it easy to combine multiple plots into a single visualization while removing any unwanted space. This is particularly useful when you want to create clean, side-by-side comparisons or when you want your plots to appear as a cohesive unit. By setting align, rel_heights, and rel_widths appropriately, you can achieve various configurations that fit your data visualization needs. By following these examples, you should be able to combine and align your plots seamlessly, creating a more polished and professional look for your R visualizations.