Add Summary Statistics onto a ggplot.

Source: R/add_summary.R

add summary statistics onto a ggplot.

add_summary(
  p,
  fun = "mean_se",
  error.plot = "pointrange",
  color = "black",
  fill = "white",
  group = 1,
  width = NULL,
  shape = 19,
  size = 1,
  linetype = 1,
  show.legend = NA,
  ci = 0.95,
  data = NULL,
  position = position_dodge(0.8)
)

mean_se_(x, error.limit = "both")

mean_sd(x, error.limit = "both")

mean_ci(x, ci = 0.95, error.limit = "both")

mean_range(x, error.limit = "both")

median_iqr(x, error.limit = "both")

median_hilow_(x, ci = 0.95, error.limit = "both")

median_q1q3(x, error.limit = "both")

median_mad(x, error.limit = "both")

median_range(x, error.limit = "both")

Arguments

p

a ggplot on which you want to add summary statistics.

fun

a function that is given the complete data and should return a data frame with variables ymin, y, and ymax. 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".

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".

color

point or outline color.

fill

fill color. Used only whne error.plot = "crossbar".

group

grouping variable. Allowed values are 1 (for one group) or a character vector specifying the name of the grouping variable. Used only for adding statistical summary per group.

width

numeric value between 0 and 1 specifying bar or box width. Example width = 0.8. Used only when error.plot is one of c("crossbar", "errorbar").

shape

point shape. Allowed values can be displayed using the function show_point_shapes().

size

numeric value in [0-1] specifying point and line size.

linetype

line type.

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.

ci

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

data

a data.frame to be displayed. If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot.

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.

x

a numeric vector.

error.limit

allowed values are one of ("both", "lower", "upper", "none") specifying whether to plot the lower and/or the upper limits of error interval.

Functions

  • add_summary(): add summary statistics onto a ggplot.

  • mean_se_(): returns the mean and the error limits defined by the standard error. We used the name mean_se_() to avoid masking mean_se().

  • mean_sd(): returns the mean and the error limits defined by the standard deviation.

  • mean_ci(): returns the mean and the error limits defined by the confidence interval.

  • mean_range(): returns the mean and the error limits defined by the range = max - min.

  • median_iqr(): returns the median and the error limits defined by the interquartile range.

  • median_hilow_(): computes the sample median and a selected pair of outer quantiles having equal tail areas. This function is a reformatted version of Hmisc::smedian.hilow(). The confidence limits are computed as follow: lower.limits = (1-ci)/2 percentiles; upper.limits = (1+ci)/2 percentiles. By default (ci = 0.95), the 2.5th and the 97.5th percentiles are used as the lower and the upper confidence limits, respectively. If you want to use the 25th and the 75th percentiles as the confidence limits, then specify ci = 0.5 or use the function median_q1q3().

  • median_q1q3(): computes the sample median and, the 25th and 75th percentiles. Wrapper around the function median_hilow_() using ci = 0.5.

  • median_mad(): returns the median and the error limits defined by the median absolute deviation.

  • median_range(): returns the median and the error limits defined by the range = max - min.

Examples


# Basic violin plot
p <- ggviolin(ToothGrowth, x = "dose", y = "len", add = "none")
p


# Add mean_sd
add_summary(p, "mean_sd")