Skill: Half Violin (R)

Category

Hiplot

When to Use

The half violin plot is a statistical graph used to display the distribution and probability density of data by replacing the left part with the data frequency count graph on the basis of keeping the right part of violin graph.

Required R Packages

• data.table
• dplyr
• ggplot2
• ggpubr
• ggthemes
• jsonlite

Minimal Reproducible Code

# Load packages
library(data.table)
library(dplyr)
library(ggplot2)
library(ggpubr)
library(ggthemes)
library(jsonlite)

# Prepare data
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/half-violin/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# Convert data structure
colnames(data) <- c("Value", "Group")
data[, 2] <- factor(data[, 2], levels = unique(data[, 2]))

# View data
head(data)

# Create visualization
# Half Violin
geom_flat_violin <- function(
  mapping = NULL, data = NULL, stat = "ydensity", position = "dodge", 
  trim = TRUE, scale = "area", show.legend = NA, inherit.aes = TRUE, ...) {
  ggplot2::layer(data = data, mapping = mapping, stat = stat, 
                 geom = geom_flat_violin_proto, position = position,
                 show.legend = show.legend, inherit.aes = inherit.aes,
                 params = list(trim = trim, scale = scale, ...))
}

"%||%" <- function(a, b) {
  if (!is.null(a)) {
    a
  } else {
    b
  }
}

geom_flat_violin_proto <-
  ggproto("geom_flat_violin_proto", Geom,
          setup_data = function(data, params) {
            data$width <- data$width %||%
              params$width %||% (resolution(data$x, FALSE) * 0.9)
            
            data %>%
              dplyr::group_by(.data = ., group) %>%
              dplyr::mutate(.data = ., ymin = min(y), ymax = max(y), xmin = x,
                            xmax = x + width / 2)
          },
# ... (see full tutorial for more)

Key Parameters

• size: Maps 0 to the size aesthetic
• alpha: Maps NA to the alpha aesthetic
• fill: Maps Group to the fill aesthetic
• width: Controls element width
• position: Position adjustment (identity, dodge, stack, fill)
• stat: Statistical transformation to use
• theme: Plot theme; tutorial uses theme_stata()

Tips

• Customize color scales with scale_fill_manual() or scale_color_brewer()
• Adjust text size with theme(text = element_text(size = 14)) for presentations
• See the full tutorial for additional customization options and advanced examples

Full Tutorial

https://openbiox.github.io/Bizard/Hiplot/085-half-violin.html