Learn R Programming

ggpubr (version 0.4.0)

ggerrorplot: Visualizing Error

Description

Visualizing error.

Usage

ggerrorplot(
  data,
  x,
  y,
  desc_stat = "mean_se",
  numeric.x.axis = FALSE,
  combine = FALSE,
  merge = FALSE,
  color = "black",
  fill = "white",
  palette = NULL,
  size = NULL,
  width = NULL,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  facet.by = NULL,
  panel.labs = NULL,
  short.panel.labs = TRUE,
  select = NULL,
  remove = NULL,
  order = NULL,
  add = "none",
  add.params = list(),
  error.plot = "pointrange",
  ci = 0.95,
  position = position_dodge(),
  ggtheme = theme_pubr(),
  ...
)

Arguments

data

a data frame

x, y

x and y variables for drawing.

desc_stat

descriptive statistics to be used for visualizing errors. Default value is "mean_se". Allowed values are one of , "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.

numeric.x.axis

logical. If TRUE, x axis will be treated as numeric. Default is FALSE.

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, fill

outline and fill colors.

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".

size

Numeric value (e.g.: size = 1). change the size of points and outlines.

width

numeric value between 0 and 1 specifying box width.

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.

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. Considered only when x axis is a factor variable.

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, ....

ci

the percent range of the confidence interval (default is 0.95).

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

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 be passed to ggpar().

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")

See Also

ggpar, ggline

Examples

Run this code

# Data: ToothGrowth data set we'll be used.
df<- ToothGrowth
head(df, 10)

# Plot mean_se
ggerrorplot(df, x = "dose", y = "len")


# Change desc_stat to mean_sd
# (other values include: mean_sd, mean_ci, median_iqr, ....)
# Add labels
ggerrorplot(df, x = "dose", y = "len",
 desc_stat = "mean_sd")

# Change error.plot to "errorbar" and add mean point
# Visualize the mean of each group
ggerrorplot(df, x = "dose", y = "len",
 add = "mean", error.plot = "errorbar")

# Horizontal plot
ggerrorplot(df, x = "dose", y = "len",
 add = "mean", error.plot = "errorbar",
 orientation = "horizontal")


# Change error.plot to "crossbar"
ggerrorplot(df, x = "dose", y = "len",
 error.plot = "crossbar", width = 0.5)


# Add jitter points and errors (mean_se)
ggerrorplot(df, x = "dose", y = "len",
 add = "jitter")

# Add dot and errors (mean_se)
ggerrorplot(df, x = "dose", y = "len",
 add = "dotplot")

# Multiple groups with error bars and jitter point
ggerrorplot(df, x = "dose", y = "len",
 color = "supp", palette = "Paired",
 error.plot = "pointrange",
 position = position_dodge(0.5))


Run the code above in your browser using DataLab