Setting Similar Y-Axis Between Two Graphs for a ggplot Code with an Interaction

In this article, we will explore how to set similar y-axis limits between two graphs created using ggplot and cowplot libraries in R. Specifically, we will delve into the challenges of maintaining interaction plots while setting shared y-axis limits.

Introduction

When working with interaction plots, where different variables are plotted against each other, it is common to encounter issues related to y-axis scaling. This can lead to difficulties in visualizing and interpreting the data effectively. In this article, we will discuss how to set similar y-axis limits between two graphs created using ggplot and cowplot libraries in R.

Background

Interaction plots are used to visualize the relationship between two or more variables within a dataset. In our case, we have two interaction plots: one for psychological complaints and another for somatic complaints. We want to combine these plots side-by-side while maintaining similar y-axis limits.

To achieve this, we will use the cowplot library, which provides an efficient way to create complex layouts of ggplot objects. However, when setting shared y-axis limits, things can get tricky.

Understanding Y-Axis Limits

Before diving into the solution, let’s take a closer look at how y-axis limits work in R. The ylim function sets the upper and lower limits for a specific plot or axis. When using ggplot, it is possible to customize the y-axis limits using various functions, including scale_y_continuous() and coord_cartesian().

However, when combining multiple plots with shared y-axis limits using cowplot, things can get complicated. The issue arises because each plot has its own set of y-axis limits, which are not necessarily identical.

Solution

To solve this problem, we need to find a way to create a single, unified y-axis limit that applies to both plots. This can be achieved by using the scale_y_continuous() function in combination with the coord_cartesian() function.

Here is an example of how to set similar y-axis limits between two graphs:

# Load necessary libraries
library(ggplot2)
library(cowplot)

# Create sample data
final_overall <- data.frame(
  surveyyear = c(2002, 2006, 2010, 2014, 2018),
  psycho = c(10, 15, 20, 25, 30),
  somatic = c(5, 10, 15, 20, 25),
  FAS_cat = c("Below Average", "Average", "Above Average")
)

# Create plots for psychological and somatic complaints
plot_psychological <- ggplot(final_overall, aes(x = surveyyear, y = psycho, color = FAS_cat, group = FAS_cat)) +   
  geom_smooth(method = "loess", span = .8, se = FALSE) +   
  labs(x = "Survey Year", y = "Psychological Complaints", title = "Survey Year vs Psychological Complaints per FAS category") +
  scale_color_manual(values = c("Below Average" = "blue", "Average" = "green", "Above Average" = "red"), name = "Family SES categories") +
  scale_x_continuous(breaks = seq(2002, 2022, by = 4), limits = c(2002, 2022)) +
  theme_minimal() +   
  labs(color = "Family SES categories")

plot_somatic <- ggplot(final_overall, aes(x = surveyyear, y = somatic, color = FAS_cat, group = FAS_cat)) +   
  geom_smooth(method = "loess", span = .8, se = FALSE) +   
  labs(x = "Survey Year", y = "Somatic Complaints", title = "Survey Year vs Somatic Complaints per FAS category") +   
  scale_color_manual(values = c("Below Average" = "blue", "Average" = "green", "Above Average" = "red"), name = "Family SES categories") +   
  scale_x_continuous(breaks = seq(2002, 2022, by = 4), limits = c(2002, 2022)) +
  theme_minimal() +   
  labs(color = "Family SES categories")

# Combine plots with shared y-axis limits
combined_plot <- plot_grid(plot_psychological, plot_somatic, nrow = 1, align = "v")

In the example above, we create two separate plots for psychological and somatic complaints using ggplot. We then combine these plots side-by-side using cowplot’s plot_grid() function.

However, to set similar y-axis limits, we need to specify a single range that applies to both plots. This can be achieved by using the scale_y_continuous() function with a custom range specified using the limits argument.

# Set shared y-axis limits
combined_plot <- plot_grid(
  plot_psychological + 
    scale_y_continuous(limits = c(1.75, 2.25)),
  plot_somatic + 
    scale_y_continuous(limits = c(1.75, 2.25))
)

In the example above, we specify a custom range of c(1.75, 2.25) for both plots using the scale_y_continuous() function.

Conclusion

When working with interaction plots created using ggplot and cowplot libraries in R, it can be challenging to maintain shared y-axis limits between multiple plots. However, by using a combination of functions, including scale_y_continuous() and coord_cartesian(), we can achieve a unified y-axis limit that applies to all plots.

By following the solution outlined in this article, you should be able to create complex layouts of interaction plots with shared y-axis limits.

Last modified on 2024-04-28