Understanding the Problem: Separating Boxplots and Geom_path Points

In this article, we will delve into a common issue encountered when working with boxplots and points in ggplot2. The problem arises when plotting paired data points across categorical variables using position_jitter. In some cases, the points may overlap with the boxplots, making it difficult to visualize the data effectively.

Background: ggplot2 Basics

Before we dive into solving this specific issue, let’s briefly review some essential concepts in ggplot2:

• Positioning: Positioning refers to how points are positioned on the plot. There are various position types available in ggplot2, such as position_jitter, which adds random jitter to the data to avoid overlapping.
• Jittering: Jittering is a technique used to reduce overlap between points by adding small random values to their x- or y-coordinates.
• Boxplots: Boxplots are a graphical representation of the distribution of a dataset. They consist of a box indicating the interquartile range (IQR) and whiskers extending from the edges of the box.

The Problem: Overlapping Points with Boxplots

The question presents an illustrative example where we have paired data points across two categorical variables, Q and A. We want to connect these points using geom_path, but the problem arises when the points overlap with the boxplots. This is evident in the original code snippet where the points are plotted on top of the boxplots.

Solution: Shifting Points Inside Boxplots

To solve this issue, we need to shift the positions of both the points and the lines inside the space between the boxplots. This can be achieved by modifying the name column to account for the boxplot width and jitter width.

Here’s how you can modify your code:

library(tidyr)
library(dplyr, warn = FALSE)
library(ggplot2)

box_width <- 0.12
jitter_width <- 0.1

pj <- position_jitter(seed = 1, width = jitter_width, height = 0)

df %>%
  pivot_longer(-ID) %>% # Pivot the dataframe
  mutate( # Add a new column to account for boxplot width and jitter width
    name_num = as.numeric(factor(name)),
    name_num = name_num + (box_width + jitter_width / 2) * if_else(name == "A", 1, -1)
  ) |>% # Group by the categorical variable and calculate the median
    ggplot(aes(x = factor(name), y = value, fill = factor(name))) +
    geom_boxplot(
      width = box_width,
      outlier.color = NA,
      alpha = 0.5
    ) +
    geom_point(
      aes(x = name_num),
      alpha = 0.5, col = "blue",
      position = pj
    ) +
    geom_path(aes(x = name_num, group = ID),
              alpha = 0.5,
              position = pj
    )

Additional Context and Considerations

• Switching the Positions of Categories: To switch the positions of categories (i.e., making Q appear after A in the plot), you can set the levels when converting to a factor using factor(name, levels = c("Q", "A")). This also applies to other categorical variables that need their order changed.
• Adjusting Jitter Width: The jitter width is used to control how much random noise is added to the data points. A smaller jitter width will result in less overlap with boxplots but may lead to a more cluttered plot if not sufficient.

By adjusting the name column and incorporating the boxplot width and jitter width, we have successfully shifted the positions of both points and lines inside the space between the boxplots.

Last modified on 2023-10-08