ggviolin: Violin plot
In kassambara/ggpubr: 'ggplot2' Based Publication Ready Plots

ggviolin

R Documentation

Violin plot

Description

Create a violin plot with error bars. Violin plots are similar to box plots, except that they also show the kernel probability density of the data at different values.

Usage

ggviolin(
  data,
  x,
  y,
  combine = FALSE,
  merge = FALSE,
  color = "black",
  fill = "white",
  palette = NULL,
  alpha = 1,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  facet.by = NULL,
  panel.labs = NULL,
  short.panel.labs = TRUE,
  linetype = "solid",
  trim = FALSE,
  size = NULL,
  width = 1,
  draw_quantiles = NULL,
  select = NULL,
  remove = NULL,
  order = NULL,
  add = "mean_se",
  add.params = list(),
  error.plot = "pointrange",
  label = NULL,
  font.label = list(size = 11, color = "black"),
  label.select = NULL,
  repel = FALSE,
  label.rectangle = FALSE,
  position = position_dodge(0.8),
  ggtheme = theme_pubr(),
  ...
)

Arguments

`data`	a data frame
`x`	character string containing the name of x variable.
`y`	character vector containing one or more variables to plot
`combine`	logical value. Default is FALSE. Used only when y is a vector containing multiple variables to plot. If TRUE, create a multi-panel plot by combining the plot of y variables.
`merge`	logical or character value. Default is FALSE. Used only when y is a vector containing multiple variables to plot. If TRUE, merge multiple y variables in the same plotting area. Allowed values include also "asis" (TRUE) and "flip". If merge = "flip", then y variables are used as x tick labels and the x variable is used as grouping variable.
`color`	outline color.
`fill`	fill color.
`palette`	the color palette to be used for coloring or filling by groups. Allowed values include "grey" for grey color palettes; brewer palettes e.g. "RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and scientific journal palettes from ggsci R package, e.g.: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty".
`alpha`	color transparency. Values should be between 0 and 1.
`title`	plot main title.
`xlab`	character vector specifying x axis labels. Use xlab = FALSE to hide xlab.
`ylab`	character vector specifying y axis labels. Use ylab = FALSE to hide ylab.
`facet.by`	character vector, of length 1 or 2, specifying grouping variables for faceting the plot into multiple panels. Should be in the data.
`panel.labs`	a list of one or two character vectors to modify facet panel labels. For example, panel.labs = list(sex = c("Male", "Female")) specifies the labels for the "sex" variable. For two grouping variables, you can use for example panel.labs = list(sex = c("Male", "Female"), rx = c("Obs", "Lev", "Lev2") ).
`short.panel.labs`	logical value. Default is TRUE. If TRUE, create short labels for panels by omitting variable names; in other words panels will be labelled only by variable grouping levels.
`linetype`	line types.
`trim`	If `TRUE` (default), trim the tails of the violins to the range of the data. If `FALSE`, don't trim the tails.
`size`	Numeric value (e.g.: size = 1). change the size of points and outlines.
`width`	violin width.
`draw_quantiles`	If `not(NULL)` (default), draw horizontal lines at the given quantiles of the density estimate.
`select`	character vector specifying which items to display.
`remove`	character vector specifying which items to remove from the plot.
`order`	character vector specifying the order of items.
`add`	character vector for adding another plot element (e.g.: dot plot or error bars). Allowed values are one or the combination of: "none", "dotplot", "jitter", "boxplot", "point", "mean", "mean_se", "mean_sd", "mean_ci", "mean_range", "median", "median_iqr", "median_hilow", "median_q1q3", "median_mad", "median_range"; see ?desc_statby for more details.
`add.params`	parameters (color, shape, size, fill, linetype) for the argument 'add'; e.g.: add.params = list(color = "red").
`error.plot`	plot type used to visualize error. Allowed values are one of c("pointrange", "linerange", "crossbar", "errorbar", "upper_errorbar", "lower_errorbar", "upper_pointrange", "lower_pointrange", "upper_linerange", "lower_linerange"). Default value is "pointrange" or "errorbar". Used only when add != "none" and add contains one "mean_" or "med_" where "*" = sd, se, ....
`label`	the name of the column containing point labels. Can be also a character vector with length = nrow(data).
`font.label`	a list which can contain the combination of the following elements: the size (e.g.: 14), the style (e.g.: "plain", "bold", "italic", "bold.italic") and the color (e.g.: "red") of labels. For example font.label = list(size = 14, face = "bold", color ="red"). To specify only the size and the style, use font.label = list(size = 14, face = "plain").
`label.select`	can be of two formats: a character vector specifying some labels to show. a list containing one or the combination of the following components: `top.up` and `top.down`: to display the labels of the top up/down points. For example, `label.select = list(top.up = 10, top.down = 4)`. `criteria`: to filter, for example, by x and y variabes values, use this: label.select = list(criteria = "`y` > 2 & `y` < 5 & `x` %in% c('A', 'B')").
`repel`	a logical value, whether to use ggrepel to avoid overplotting text labels or not.
`label.rectangle`	logical value. If TRUE, add rectangle underneath the text, making it easier to read.
`position`	Position adjustment, either as a string naming the adjustment (e.g. `"jitter"` to use `position_jitter`), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
`ggtheme`	function, ggplot2 theme name. Default value is theme_pubr(). Allowed values include ggplot2 official themes: theme_gray(), theme_bw(), theme_minimal(), theme_classic(), theme_void(), ....
`...`	other arguments to be passed to `geom_violin`, `ggpar` and `facet`.

Details

The plot can be easily customized using the function ggpar(). Read ?ggpar for changing:

main title and axis labels: main, xlab, ylab
axis limits: xlim, ylim (e.g.: ylim = c(0, 30))
axis scales: xscale, yscale (e.g.: yscale = "log2")
color palettes: palette = "Dark2" or palette = c("gray", "blue", "red")
legend title, labels and position: legend = "right"
plot orientation : orientation = c("vertical", "horizontal", "reverse")

Examples

# Load data
data("ToothGrowth")
df <- ToothGrowth

# Basic plot
# +++++++++++++++++++++++++++
ggviolin(df, x = "dose", y = "len")
# Change the plot orientation: horizontal
ggviolin(df, "dose", "len", orientation = "horiz")

# Add summary statistics
# ++++++++++++++++++++++++++
# Draw quantiles
ggviolin(df, "dose", "len", add = "none",
   draw_quantiles = 0.5)

# Add box plot
ggviolin(df, x = "dose", y = "len",
 add = "boxplot")

ggviolin(df, x = "dose", y = "len",
 add = "dotplot")

# Add jitter points and
# change point shape by groups ("dose")
ggviolin(df, x = "dose", y = "len",
add = "jitter", shape = "dose")


# Add mean_sd + jittered points
ggviolin(df, x = "dose", y = "len",
 add = c("jitter", "mean_sd"))

# Change error.plot to "crossbar"
ggviolin(df, x = "dose", y = "len",
 add = "mean_sd", error.plot = "crossbar")


# Change colors
# +++++++++++++++++++++++++++
# Change outline and fill colors
ggviolin(df, "dose", "len",
   color = "black", fill = "gray")

# Change outline colors by groups: dose
# Use custom color palette and add boxplot
ggviolin(df, "dose", "len",  color = "dose",
   palette = c("#00AFBB", "#E7B800", "#FC4E07"),
   add = "boxplot")

# Change fill color by groups: dose
# add boxplot with white fill color
ggviolin(df, "dose", "len", fill = "dose",
   palette = c("#00AFBB", "#E7B800", "#FC4E07"),
   add = "boxplot", add.params = list(fill = "white"))


# Plot with multiple groups
# +++++++++++++++++++++
# fill or color box plot by a second group : "supp"
ggviolin(df, "dose", "len", color = "supp",
 palette = c("#00AFBB", "#E7B800"), add = "boxplot")

kassambara/ggpubr documentation built on Feb. 15, 2023, 4:09 a.m.