ggpubr (version 0.1.6)

stat_mean: Draw group mean points

Description

Draw the mean point of each group.

Usage

stat_mean(mapping = NULL, data = NULL, geom = "point",
  position = "identity", na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE, ...)

Arguments

mapping

Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.

geom

The geometric object to use display the data

position

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

na.rm

If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

...

other arguments to pass to geom_point.

See Also

stat_conf_ellipse, stat_chull and ggscatter

Examples

# NOT RUN {
# Load data
data("mtcars")
df <- mtcars
df$cyl <- as.factor(df$cyl)

# Scatter plot with ellipses and group mean points
ggscatter(df, x = "wt", y = "mpg",
   color = "cyl", shape = "cyl", ellipse = TRUE)+
 stat_mean(aes(color = cyl, shape = cyl), size = 4)

# }