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Generate Publication-Ready Comparative Boxplots

Source: R/visualization.r
viz_thermal_boxplot.Rd

Creates a high-quality box-and-whisker plot to visualize the distribution of thermal metrics across groups. This function is ideal for displaying median values, quartiles, and range, while optionally overlaying individual data points to reveal the underlying sample distribution.

Usage

viz_thermal_boxplot(
  data,
  y_var,
  x_var,
  fill_var = NULL,
  add_points = TRUE,
  point_size = 1.5,
  point_alpha = 0.6,
  palette = "npg"
)

Arguments

data

Data frame. The merged dataset (e.g., output from aggregate_replicates).

y_var

String. The name of the numeric column to plot (e.g., "Max", "Mean").

x_var

String. The name of the categorical column for the X-axis groupings.

fill_var

String. The name of the variable used for fill colors. Default is NULL, which uses x_var.

add_points

Logical. If TRUE (default), overlays individual data points using geom_jitter. Highly recommended to show sample size and distribution density.

point_size

Numeric. The size of the individual jitter points. Default is 1.5.

point_alpha

Numeric. The transparency of the jitter points (0 to 1). Default is 0.6.

palette

String or Vector.

  • If a string: Pre-defined scientific palettes ("npg", "jco").

  • If a character vector: A custom list of hex codes.

Value

A ggplot object. Can be further customized with standard ggplot2 functions (e.g., + ylim(20, 40)).

Details

This function includes several automated optimizations for scientific reporting:

  • Smart Outlier Handling: If add_points is TRUE, the function automatically hides the standard boxplot outliers (outlier.shape = NA) to avoid plotting the same data point twice (once as an outlier, once as a jittered point).

  • Palette Expansion: Like the barplot function, it automatically interpolates colors if the number of experimental groups exceeds the palette's limit.

  • Layout: Uses theme_classic() for a clean, academic look.

Examples

if (FALSE) { # \dontrun{
# Standard boxplot with individual points
p <- viz_thermal_boxplot(df_bio, y_var = "Mean", x_var = "Treatment")
} # }