Box / Violin / Bar / Beeswarm plot

BoxPlot draws box plots or bar plots (mean ± error bars) with extensive customisation options. Supports jittered or beeswarm points, paired observations with connecting lines, trend lines, statistical test annotations (pairwise or omnibus), background stripes, reference lines, point highlighting, and custom summary statistic overlays.

This is the public API — it delegates to BoxViolinPlot with base = "box" or base = "bar", which in turn dispatches to BoxViolinPlotAtomic for each split_by level.

ViolinPlot draws violin plots with extensive customisation options. Supports jittered or beeswarm points, box plot overlays, trend lines, statistical test annotations, background stripes, reference lines, point highlighting, and custom summary statistic overlays.

This is the public API — it delegates to BoxViolinPlot with base = "violin", which dispatches to BoxViolinPlotAtomic for each split_by level.

BeeswarmPlot draws beeswarm plots — points arranged by the beeswarm algorithm to avoid overlap while displaying the distribution density. This is a convenience wrapper that delegates to BoxViolinPlot with base = "none" and add_beeswarm = TRUE.

Requires the ggbeeswarm package. To get a beeswarm plot WITH a box plot, use BeeswarmPlot(..., add_box = TRUE). To get a violin plot with beeswarm points, use ViolinPlot(..., add_beeswarm = TRUE).

Usage

BoxPlot(
  data,
  x,
  x_sep = "_",
  y = NULL,
  base = c("box", "bar"),
  in_form = c("long", "wide"),
  split_by = NULL,
  split_by_sep = "_",
  symnum_args = NULL,
  sort_x = NULL,
  flip = FALSE,
  keep_empty = FALSE,
  keep_na = FALSE,
  group_by = NULL,
  group_by_sep = "_",
  group_name = NULL,
  paired_by = NULL,
  x_text_angle = ifelse(isTRUE(flip), 0, 45),
  step_increase = 0.1,
  fill_mode = ifelse(!is.null(group_by), "dodge", "x"),
  palreverse = FALSE,
  position_dodge_preserve = "total",
  theme = "theme_this",
  theme_args = list(),
  palette = "Paired",
  palcolor = NULL,
  alpha = 1,
  aspect.ratio = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  add_point = FALSE,
  pt_color = if (isTRUE(add_beeswarm)) NULL else "grey30",
  pt_size = NULL,
  pt_alpha = 1,
  jitter_width = NULL,
  jitter_height = 0,
  stack = FALSE,
  y_max = NULL,
  y_min = NULL,
  y_brackets = NULL,
  add_beeswarm = FALSE,
  beeswarm_method = "swarm",
  beeswarm_cex = 1,
  beeswarm_priority = "ascending",
  beeswarm_dodge = 0.9,
  add_trend = FALSE,
  trend_color = NULL,
  trend_linewidth = 1,
  trend_ptsize = 2,
  add_stat = NULL,
  stat_name = NULL,
  stat_color = "black",
  stat_size = 1,
  stat_stroke = 1,
  stat_shape = 25,
  add_errorbar = "SEM",
  errorbar_color = "grey20",
  errorbar_width = 0.4,
  errorbar_linewidth = 0.6,
  add_bg = FALSE,
  bg_palette = "stripe",
  bg_palcolor = NULL,
  bg_alpha = 0.2,
  add_line = NULL,
  line_color = "red2",
  line_width = 0.6,
  line_type = 2,
  highlight = NULL,
  highlight_color = "red2",
  highlight_size = 1,
  highlight_alpha = 1,
  comparisons = NULL,
  ref_group = NULL,
  pairwise_method = "wilcox.test",
  multiplegroup_comparisons = FALSE,
  multiple_method = "kruskal.test",
  sig_label = "p.format",
  sig_labelsize = 3.5,
  hide_ns = FALSE,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_ncol = NULL,
  facet_nrow = NULL,
  facet_byrow = TRUE,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = axes,
  guides = NULL,
  ...
)

ViolinPlot(
  data,
  x,
  x_sep = "_",
  y = NULL,
  in_form = c("long", "wide"),
  split_by = NULL,
  split_by_sep = "_",
  symnum_args = NULL,
  sort_x = NULL,
  flip = FALSE,
  keep_empty = FALSE,
  keep_na = FALSE,
  group_by = NULL,
  group_by_sep = "_",
  group_name = NULL,
  paired_by = NULL,
  x_text_angle = ifelse(isTRUE(flip), 0, 45),
  step_increase = 0.1,
  fill_mode = ifelse(!is.null(group_by), "dodge", "x"),
  palreverse = FALSE,
  position_dodge_preserve = "total",
  theme = "theme_this",
  theme_args = list(),
  palette = "Paired",
  palcolor = NULL,
  alpha = 1,
  aspect.ratio = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  add_point = FALSE,
  pt_color = if (isTRUE(add_beeswarm)) NULL else "grey30",
  pt_size = NULL,
  pt_alpha = 1,
  jitter_width = NULL,
  jitter_height = 0,
  stack = FALSE,
  y_max = NULL,
  y_min = NULL,
  y_brackets = NULL,
  add_beeswarm = FALSE,
  beeswarm_method = "swarm",
  beeswarm_cex = 1,
  beeswarm_priority = "ascending",
  beeswarm_dodge = 0.9,
  add_box = FALSE,
  box_color = "black",
  box_width = 0.1,
  box_ptsize = 2.5,
  add_trend = FALSE,
  trend_color = NULL,
  trend_linewidth = 1,
  trend_ptsize = 2,
  add_stat = NULL,
  stat_name = NULL,
  stat_color = "black",
  stat_size = 1,
  stat_stroke = 1,
  stat_shape = 25,
  add_bg = FALSE,
  bg_palette = "stripe",
  bg_palcolor = NULL,
  bg_alpha = 0.2,
  add_line = NULL,
  line_color = "red2",
  line_width = 0.6,
  line_type = 2,
  highlight = NULL,
  highlight_color = "red2",
  highlight_size = 1,
  highlight_alpha = 1,
  comparisons = NULL,
  ref_group = NULL,
  pairwise_method = "wilcox.test",
  multiplegroup_comparisons = FALSE,
  multiple_method = "kruskal.test",
  sig_label = "p.format",
  sig_labelsize = 3.5,
  hide_ns = FALSE,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_ncol = NULL,
  facet_nrow = NULL,
  facet_byrow = TRUE,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = axes,
  guides = NULL,
  ...
)

BeeswarmPlot(
  data,
  x,
  x_sep = "_",
  y = NULL,
  in_form = c("long", "wide"),
  split_by = NULL,
  split_by_sep = "_",
  symnum_args = NULL,
  sort_x = NULL,
  flip = FALSE,
  keep_empty = FALSE,
  keep_na = FALSE,
  group_by = NULL,
  group_by_sep = "_",
  group_name = NULL,
  paired_by = NULL,
  x_text_angle = ifelse(isTRUE(flip), 0, 45),
  step_increase = 0.1,
  fill_mode = ifelse(!is.null(group_by), "dodge", "x"),
  palreverse = FALSE,
  theme = "theme_this",
  theme_args = list(),
  palette = "Paired",
  palcolor = NULL,
  alpha = 1,
  aspect.ratio = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  pt_color = NULL,
  pt_size = NULL,
  pt_alpha = 1,
  position_dodge_preserve = "total",
  jitter_width = NULL,
  jitter_height = 0,
  stack = FALSE,
  y_max = NULL,
  y_min = NULL,
  y_brackets = NULL,
  add_violin = FALSE,
  beeswarm_method = "swarm",
  beeswarm_cex = 1,
  beeswarm_priority = "ascending",
  beeswarm_dodge = 0.9,
  add_box = FALSE,
  box_color = "black",
  box_width = 0.1,
  box_ptsize = 2.5,
  add_trend = FALSE,
  trend_color = NULL,
  trend_linewidth = 1,
  trend_ptsize = 2,
  add_stat = NULL,
  stat_name = NULL,
  stat_color = "black",
  stat_size = 1,
  stat_stroke = 1,
  stat_shape = 25,
  add_bg = FALSE,
  bg_palette = "stripe",
  bg_palcolor = NULL,
  bg_alpha = 0.2,
  add_line = NULL,
  line_color = "red2",
  line_width = 0.6,
  line_type = 2,
  highlight = NULL,
  highlight_color = "red2",
  highlight_size = 1,
  highlight_alpha = 1,
  comparisons = NULL,
  ref_group = NULL,
  pairwise_method = "wilcox.test",
  multiplegroup_comparisons = FALSE,
  multiple_method = "kruskal.test",
  sig_label = "p.format",
  sig_labelsize = 3.5,
  hide_ns = FALSE,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_ncol = NULL,
  facet_nrow = NULL,
  facet_byrow = TRUE,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = axes,
  guides = NULL,
  ...
)

Arguments

data

A data frame.

x

A character string specifying the column name of the data frame to plot for the x-axis.

x_sep

A character string to join multiple x columns. Default "_".

y

A character string specifying the column name of the data frame to plot for the y-axis.

base

A character string: "box" (default) or "bar". Bar plots show group means with optional error bars.

in_form

A character string: "long" (default) or "wide". In wide form, x columns are pivoted to long format.

split_by

The column(s) to split the data by for separate sub-plots.

split_by_sep

Separator for concatenated split_by columns.

symnum_args

A list of arguments passed to symnum for symbolic p-value coding.

sort_x

An R expression string (e.g., "mean(y)") to order x-axis categories. Default NULL keeps the original order. When keep_empty_x is TRUE, empty levels are placed last.

flip

Logical; if TRUE, swap the x and y axes.

keep_empty

One of FALSE, TRUE and "level". It can also take a named list to specify different behavior for different columns. Without a named list, the behavior applies to the categorical/character columns used on the plot, for example, the x, group_by, fill_by, etc.

FALSE (default): Drop empty factor levels from the data before plotting.
TRUE: Keep empty factor levels and show them as a separate category in the plot.
"level": Keep empty factor levels, but do not show them in the plot. But they will be assigned colors from the palette to maintain consistency across multiple plots. Alias: levels

keep_na

A logical value or a character to replace the NA values in the data. It can also take a named list to specify different behavior for different columns. If TRUE or NA, NA values will be replaced with NA. If FALSE, NA values will be removed from the data before plotting. If a character string is provided, NA values will be replaced with the provided string. If a named vector/list is provided, the names should be the column names to apply the behavior to, and the values should be one of TRUE, FALSE, or a character string. Without a named vector/list, the behavior applies to categorical/character columns used on the plot, for example, the x, group_by, fill_by, etc.

group_by

Columns to group the data for plotting For those plotting functions that do not support multiple groups, They will be concatenated into one column, using group_by_sep as the separator

group_by_sep

The separator for multiple group_by columns. See group_by

group_name

A character string for the dodge legend title.

paired_by

A character string naming a column that identifies paired observations. Forces add_point = TRUE and connects paired observations with lines.

x_text_angle

A numeric value specifying the angle of the x-axis text.

step_increase

Fractional step increase for stacking significance brackets when multiple comparisons exist.

fill_mode

A character string controlling fill colour mapping: "dodge" (fill by group_by, discrete), "x" (fill by x-axis categories, discrete), "mean" or "median" (fill by pre-computed statistic, continuous gradient).

palreverse

A logical value indicating whether to reverse the palette. Default is FALSE.

position_dodge_preserve

Passed to position_dodge(): "total" preserves the overall group width; "single" preserves individual element width.

theme

A character string or a theme class (i.e. ggplot2::theme_classic) specifying the theme to use. Default is "theme_this".

theme_args

A list of arguments to pass to the theme function.

palette

A character string specifying the palette to use. A named list or vector can be used to specify the palettes for different split_by values.

palcolor

A character string specifying the color to use in the palette. A named list can be used to specify the colors for different split_by values. If some values are missing, the values from the palette will be used (palcolor will be NULL for those values).

alpha

A numeric value specifying the transparency of the plot.

aspect.ratio

A numeric value specifying the aspect ratio of the plot.

legend.position

A character string specifying the position of the legend. if waiver(), for single groups, the legend will be "none", otherwise "right".

legend.direction

A character string specifying the direction of the legend.

add_point

Logical; add jittered or beeswarm points to the plot.

pt_color

Colour of the points. When add_beeswarm = TRUE and pt_color is NULL, points are coloured by the fill variable.

pt_size

Numeric size of the points. Default computed from data size: min(3000 / nrow(data), 0.6).

pt_alpha

Numeric transparency of the points.

jitter_width

Numeric width of the jitter. Defaults to 0.5, but set to 0 when paired_by is provided.

jitter_height

Numeric height of the jitter. Default 0.

stack

Logical; stack facetted panels in a compact layout with shared strip labels.

y_max, y_min

Numeric y-axis limits, or quantile notation strings (e.g., "q95" for the 95th percentile, "q5" for the 5th percentile).

y_brackets

Numeric y-axis position for significance brackets (or p-value labels for multiple comparisons). If NULL, the brackets are placed above the maximum y-value.

add_beeswarm

Logical; use ggbeeswarm::geom_beeswarm() for non-overlapping point layout instead of jitter. Requires the ggbeeswarm package.

beeswarm_method

Beeswarm layout method: "swarm", "compactswarm", "hex", "square", or "center".

beeswarm_cex

Numeric scaling for point spacing. Larger values spread points more.

beeswarm_priority

Point layout priority: "ascending", "descending", "density", or "random".

beeswarm_dodge

Numeric dodge width for beeswarm points when group_by is provided. Default 0.9.

add_trend

Logical; add trend lines connecting group medians.

trend_color

Colour of the trend line. When NULL and group_by is present, lines are coloured per group.

trend_linewidth

Width of the trend line.

trend_ptsize

Size of the trend line points.

add_stat

A summary function (e.g., mean, median) to display as a point with a shape legend entry.

stat_name

Legend title for the stat summary shape.

stat_color

Colour of the stat summary point.

stat_size

Size of the stat summary point.

stat_stroke

Stroke width of the stat summary point.

stat_shape

Shape (an integer) for the stat summary point. Uses scale_shape_identity() so the shape is rendered directly.

add_errorbar

Type of error bars for bar plots. See Details.

errorbar_color, errorbar_width, errorbar_linewidth

Error bar appearance controls.

add_bg

Logical; add alternating background stripes.

bg_palette

Palette for the background stripes.

bg_palcolor

Custom colours for the background stripes.

bg_alpha

Alpha transparency for the background stripes.

add_line

A numeric y-intercept for a horizontal reference line.

line_color

Colour of the reference line.

line_width

Width of the reference line.

line_type

Linetype of the reference line.

highlight

A specification of points to highlight: TRUE (all), a numeric index vector, a logical expression string, or a character vector of row names.

highlight_color

Colour of highlighted points.

highlight_size

Size of highlighted points.

highlight_alpha

Alpha of highlighted points.

comparisons

A logical value (TRUE for all pairs) or a list of two-element vectors specifying pairwise comparisons. Only available when fill_mode = "dodge" (i.e., group_by is present).

ref_group

A character string specifying the reference group for comparisons.

pairwise_method

Method for pairwise tests. Default "wilcox.test".

multiplegroup_comparisons

Logical; perform an omnibus test (e.g., Kruskal-Wallis) across all groups.

multiple_method

Method for the omnibus test. Default "kruskal.test".

sig_label

Label format for significance annotations. For pairwise comparisons: "p.format", "p.signif", or a glue template (e.g., "p = {p}"). For multiple-group tests: "p.format" or "p.signif".

sig_labelsize

Size of the significance label text.

hide_ns

Logical; hide non-significant comparison labels.

facet_by

A character string specifying the column name of the data frame to facet the plot. Otherwise, the data will be split by split_by and generate multiple plots and combine them into one using patchwork::wrap_plots

facet_scales

Whether to scale the axes of facets. Default is "fixed" Other options are "free", "free_x", "free_y". See ggplot2::facet_wrap

facet_ncol

A numeric value specifying the number of columns in the facet. When facet_by is a single column and facet_wrap is used.

facet_nrow

A numeric value specifying the number of rows in the facet. When facet_by is a single column and facet_wrap is used.

facet_byrow

A logical value indicating whether to fill the plots by row. Default is TRUE.

title

A character string specifying the title of the plot. A function can be used to generate the title based on the default title. This is useful when split_by is used and the title needs to be dynamic.

subtitle

A character string specifying the subtitle of the plot.

xlab

A character string specifying the x-axis label.

ylab

A character string specifying the y-axis label.

seed

A numeric seed for reproducibility.

combine

Logical; when TRUE (default), returns a combined patchwork object. When FALSE, returns a named list of ggplot objects.

ncol, nrow

Integer number of columns / rows for the combined layout.

byrow

Logical; fill the combined layout by row (default TRUE).

axes, axis_titles

Character strings for axis handling in the combined layout.

guides

Character string for legend collection across panels.

...

Additional arguments.

add_box

Logical; overlay a box plot on the primary geometry. Mutually exclusive with base = "box" and base = "bar".

box_color

Colour of the overlaid box plot outline and fill.

box_width

Width of the overlaid box plot.

box_ptsize

Size of the median point in the overlaid box plot.

add_violin

Logical; whether to add a violin plot behind the beeswarm points. Not supported — the function will stop with an error directing you to use ViolinPlot(..., add_beeswarm = TRUE) instead.

Value

A ggplot object, a patchwork object, or a named list of ggplot objects (when combine = FALSE), each with height and width attributes in inches.

Bar plots (`base = "bar"`)

When base = "bar", bars display group means with optional error bars. add_errorbar controls the error bar type:

"SEM" (default) — standard error of the mean.
"SD" — standard deviation.
"CI" or "CI95" — 95\
"none" — no error bars.

Error bars are computed via a custom stat_summary(fun.data = ...) that handles per-group mean, SD, and sample size.

Examples

# \donttest{
set.seed(8525)
data <- data.frame(
    x = rep(LETTERS[1:8], each = 40),
    y = c(rnorm(160), rnorm(160, mean = 1)),
    group1 = sample(c("g1", "g2"), 320, replace = TRUE),
    group2 = sample(c("h1", "h2", "h3", "h4"), 320, replace = TRUE)
)

# Basic box plot
BoxPlot(data, x = "x", y = "y")


# With beeswarm points
BoxPlot(data, x = "x", y = "y", add_beeswarm = TRUE, pt_color = "grey30")


# Stacked + flipped + faceted
BoxPlot(data,
    x = "x", y = "y",
    stack = TRUE, flip = TRUE, facet_by = "group1",
    add_bg = TRUE, bg_palette = "Paired")


# Stacked + flipped + split_by with per-split colours
BoxPlot(data,
    x = "x", y = "y",
    stack = TRUE, flip = TRUE, split_by = "group1",
    add_bg = TRUE, bg_palette = "Paired",
    palcolor = list(g1 = c("red", "blue"), g2 = c("blue", "red")))


# sort_x — order by mean(y)
data <- data.frame(
  x = factor(rep(LETTERS[1:5], each = 40),
     levels = c(LETTERS[1:2], "unused", LETTERS[3:5])),
  y = c(rnorm(40, mean = 5), rnorm(40, mean = 4), rnorm(40, mean = 3),
     rnorm(40, mean = 2), rnorm(40, mean = 1))
)
BoxPlot(data, x = "x", y = "y", sort_x = "mean(y)", keep_empty = TRUE)

BoxPlot(data, x = "x", y = "y", sort_x = "mean(-y)", keep_empty = TRUE)


# Wide-form data
data_wide <- data.frame(A = rnorm(100), B = rnorm(100), C = rnorm(100))
BoxPlot(data_wide, x = c("A", "B", "C"), in_form = "wide")


# Paired observations with connecting lines and paired test
paired_data <- data.frame(
    subject = rep(paste0("s", 1:10), each = 2),
    visit = rep(c("pre", "post"), times = 10),
    value = rnorm(20))
BoxPlot(paired_data,
    x = "visit", y = "value", comparisons = TRUE,
    paired_by = "subject", add_point = TRUE)


# Paired + grouped
paired_group_data <- data.frame(
    subject = rep(paste0("s", 1:6), each = 2),
    x = rep(c("A", "B"), each = 6),
    group = rep(c("before", "after"), times = 6),
    value = rnorm(12))
BoxPlot(paired_group_data,
    x = "x", y = "value",
    paired_by = "subject", group_by = "group",
    comparisons = TRUE, pt_size = 3, pt_color = "red")
#> Warning: Forcing 'add_point' = TRUE when 'paired_by' is provided.
#> Warning: [Box/Violin/BeeswarmPlot] Some pairwise comparisons may fail due to insufficient data points or variability. Adjusting data to ensure valid comparisons.


# keep_na and keep_empty examples
data <- data.frame(
    x = factor(rep(c(LETTERS[1:3], NA, LETTERS[5:8]), each = 40),
       levels = c(LETTERS[1:8])),
    y = c(rnorm(160), rnorm(160, mean = 1)),
    group1 = sample(c("g1", "g2"), 320, replace = TRUE),
    group2 = factor(sample(c("h1", NA, "h3", "h4"), 320, replace = TRUE),
       levels = c("h1", "h2", "h3", "h4")))

BoxPlot(data, x = "x", y = "y")

BoxPlot(data, x = "x", y = "y", keep_na = TRUE, keep_empty = TRUE)

BoxPlot(data, x = "x", y = "y", keep_na = TRUE, keep_empty = TRUE,
        facet_by = "group2")

BoxPlot(data, x = "x", y = "y", keep_na = TRUE, keep_empty = 'level')

BoxPlot(data, x = "x", y = "y", group_by = "group2")

BoxPlot(data, x = "x", y = "y", group_by = "group2",
        keep_na = TRUE, keep_empty = TRUE)

BoxPlot(data, x = "x", y = "y", group_by = "group2",
        keep_na = TRUE, keep_empty = 'level')


# Per-column keep_na / keep_empty
BoxPlot(data, x = "x", y = "y", group_by = "group2",
        keep_na = list(x = TRUE, group2 = FALSE),
        keep_empty = list(x = FALSE, group2 = TRUE))


# Bar plot (base = "bar")
data$y <- abs(data$y)
BoxPlot(data, x = "x", y = "y", base = "bar")

BoxPlot(data, x = "x", y = "y", base = "bar", add_errorbar = "SD")

BoxPlot(data, x = "x", y = "y", base = "bar", add_errorbar = "CI95")

BoxPlot(data, x = "x", y = "y", base = "bar", add_errorbar = "none")

BoxPlot(data, x = "x", y = "y", base = "bar", group_by = "group1")

BoxPlot(data, x = "x", y = "y", base = "bar", add_point = TRUE)

BoxPlot(data, x = "x", y = "y", base = "bar",
        fill_mode = "mean", palette = "Blues")

# }
# \donttest{
ViolinPlot(data, x = "x", y = "y")

ViolinPlot(data, x = "x", y = "y", add_beeswarm = TRUE, pt_color = "grey30")

ViolinPlot(data, x = "x", y = "y", add_box = TRUE)

ViolinPlot(data, x = "x", y = "y", add_point = TRUE)

ViolinPlot(data, x = "x", y = "y", add_trend = TRUE)

ViolinPlot(data, x = "x", y = "y", add_stat = mean)

ViolinPlot(data, x = "x", y = "y", add_bg = TRUE)

ViolinPlot(data, x = "x", y = "y", add_line = 0)


# Grouped
ViolinPlot(data, x = "x", y = "y", group_by = "group1")


# Grouped + faceted + box overlay
ViolinPlot(data,
    x = "x", y = "y", group_by = "group1",
    facet_by = "group2", add_box = TRUE)
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.
#> Warning: Groups with fewer than two datapoints have been dropped.
#> ℹ Set `drop = FALSE` to consider such groups for position adjustment purposes.


# Highlight
ViolinPlot(data,
    x = "x", y = "y", add_point = TRUE,
    highlight = 'group1 == "g1"', alpha = 0.8,
    highlight_size = 1.5, pt_size = 1, add_box = TRUE)


# Pairwise comparisons with formatted labels
if (requireNamespace("ggpubr", quietly = TRUE)) {
  # https://github.com/kassambara/ggpubr/issues/751
  library(ggpubr)
  ViolinPlot(data,
    x = "x", y = "y", group_by = "group1",
    comparisons = TRUE, sig_label = "p = {p}")
}
#> Loading required package: ggplot2


# Explicit comparison list + hide non-significant
ViolinPlot(data,
    x = "x", y = "y", sig_label = "p.format", hide_ns = TRUE,
    facet_by = "group2", comparisons = list(c("D", "E")))


# Continuous fill (mean) + omnibus test
ViolinPlot(data,
    x = "x", y = "y", fill_mode = "mean",
    facet_by = "group2", palette = "Blues",
    multiplegroup_comparisons = TRUE)
#> Warning: The following aesthetics were dropped during statistical transformation: fill.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation: fill.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation: fill.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?


# Per-split palettes
ViolinPlot(data,
    x = "x", y = "y", fill_mode = "mean",
    split_by = "group1", palette = c(g1 = "Blues", g2 = "Reds"))


# Stacked faceting
ViolinPlot(data,
    x = "x", y = "y", stack = TRUE,
    facet_by = "group2", add_box = TRUE, add_bg = TRUE,
    bg_palette = "Paired")

# }
# \donttest{
# Basic beeswarm
BeeswarmPlot(data, x = "x", y = "y")


# Control point size
BeeswarmPlot(data, x = "x", y = "y", pt_size = 1)


# Beeswarm with box overlay
BeeswarmPlot(data, x = "x", y = "y", add_box = TRUE, pt_color = "grey30")


# Grouped
BeeswarmPlot(data, x = "x", y = "y", group_by = "group1")


# Grouped without dodging
BeeswarmPlot(data, x = "x", y = "y", group_by = "group1",
             beeswarm_dodge = NULL)


# Hex layout with wider spacing
BeeswarmPlot(data,
    x = "x", y = "y", beeswarm_method = "hex",
    beeswarm_cex = 2)
#> Warning: In `position_beeswarm`, method `hex` discretizes the data axis (a.k.a the
#> continuous or non-grouped axis).
#> This may result in changes to the position of the points along that axis,
#> proportional to the value of `cex`.
#> To prevent this behavior, set `preserve.data.axis=TRUE`.
#> This warning is displayed once per session.

# }

Usage

Arguments

Value

Bar plots (base = "bar")

Examples

Bar plots (`base = "bar"`)