ggstripchart: Stripcharts
In kassambara/ggpubr: 'ggplot2' Based Publication Ready Plots

ggstripchart

R Documentation

Stripcharts

Description

Create a stripchart, also known as one dimensional scatter plots. These plots are suitable compared to box plots when sample sizes are small.

Usage

ggstripchart(
  data,
  x,
  y,
  combine = FALSE,
  merge = FALSE,
  color = "black",
  fill = "white",
  palette = NULL,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  facet.by = NULL,
  panel.labs = NULL,
  short.panel.labs = TRUE,
  shape = 19,
  size = 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,
  jitter = 0.2,
  position = position_jitter(jitter, seed = 123),
  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".
`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.
`shape`	point shape
`size`	Numeric value (e.g.: size = 1). change the size of points and outlines.
`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.
`jitter`	the amount of jitter.
`position`	position adjustment, either as a string, or the result of a call to a position adjustment function. Used to adjust position for multiple groups.
`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_jitter`, `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 with summary statistics: mean_se
# +++++++++++++++++++++++++++
# Change point shapes by groups: "dose"
ggstripchart(df, x = "dose", y = "len",
   shape = "dose", size = 3,
   add = "mean_se")

# Use mean_sd
# Change error.plot to "crossbar"
ggstripchart(df, x = "dose", y = "len",
   shape = "dose", size = 3,
   add = "mean_sd", add.params = list(width = 0.5),
   error.plot = "crossbar")



# Add summary statistics
# ++++++++++++++++++++++++++

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

# Add violin + mean_sd
ggstripchart(df, x = "dose", y = "len",
 shape = "dose", add = c("violin", "mean_sd"))


# Change colors
# +++++++++++++++++++++++++++
# Change colors by groups: dose
# Use custom color palette
 ggstripchart(df, "dose", "len",  shape = "dose",
   color = "dose", palette = c("#00AFBB", "#E7B800", "#FC4E07"),
   add = "mean_sd")



# Plot with multiple groups
# +++++++++++++++++++++
# Change shape and color by a second group : "supp"
ggstripchart(df, "dose", "len", shape = "supp",
  color = "supp", palette = c("#00AFBB", "#E7B800"))

# Adjust point position
ggstripchart(df, "dose", "len", shape = "supp",
  color = "supp", palette = c("#00AFBB", "#E7B800"),
  position = position_dodge(0.8) )

# You can also use position_jitterdodge()
# but fill aesthetic is required
ggstripchart(df, "dose", "len",  shape = "supp",
   color = "supp", palette = c("#00AFBB", "#E7B800"),
   position = position_jitterdodge() )

# Add boxplot
ggstripchart(df, "dose", "len", shape = "supp",
 color = "supp", palette = c("#00AFBB", "#E7B800"),
 add = "boxplot", add.params = list(color = "black") )

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