Pie charts for categorical data with statistical details included in the plot as a subtitle.
ggpiestats( data, main, condition = NULL, counts = NULL, ratio = NULL, paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(direction = "both"), label.repel = FALSE, conf.level = 0.95, nboot = 100L, k = 2L, proportion.test = TRUE, perc.k = 0, bf.message = TRUE, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, ggtheme = ggplot2::theme_bw(), ggstatsplot.layer = TRUE, package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, output = "plot", x = NULL, y = NULL, ... )
data  A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted. 

counts  A string naming a variable in data containing counts, or 
ratio  A vector of proportions: the expected proportions for the
proportion test (should sum to 1). Default is 
paired  Logical indicating whether data came from a withinsubjects or
repeated measures design study (Default: 
results.subtitle  Decides whether the results of statistical tests are
to be displayed as a subtitle (Default: 
label  Character decides what information needs to be displayed
on the label in each pie slice. Possible options are 
label.args  Additional aesthetic arguments that will be passed to

label.repel  Whether labels should be repelled using 
conf.level  Scalar between 0 and 1. If unspecified, the defaults return

nboot  Number of bootstrap samples for computing confidence interval
for the effect size (Default: 
k  Number of digits after decimal point (should be an integer)
(Default: 
proportion.test  Decides whether proportion test for 
perc.k  Numeric that decides number of decimal places for percentage
labels (Default: 
bf.message  Logical that decides whether to display Bayes Factor in
favor of the null hypothesis. This argument is relevant only for
parametric test (Default: 
sampling.plan  Character describing the sampling plan. Possible options
are 
fixed.margin  For the independent multinomial sampling plan, which
margin is fixed ( 
prior.concentration  Specifies the prior concentration parameter, set
to 
title  The text for the plot title. 
subtitle  The text for the plot subtitle. Will work only if

caption  The text for the plot caption. 
legend.title  Title text for the legend. 
ggtheme  A function, 
ggstatsplot.layer  Logical that decides whether 
package  Name of package from which the palette is desired as string or symbol. 
palette  Name of palette as string or symbol. 
ggplot.component  A 
output  Character that describes what is to be returned: can be

x, main  The variable to use as the rows in the contingency table. 
y, condition  The variable to use as the columns in the contingency
table. Default is 
...  Currently ignored. 
Unlike a number of statistical softwares, ggstatsplot
doesn't
provide the option for Yates' correction for the Pearson's chisquared
statistic. This is due to compelling amount of MonteCarlo simulation
research which suggests that the Yates' correction is overly conservative,
even in small sample sizes. As such it is recommended that it should not
ever be applied in practice (Camilli & Hopkins, 1978, 1979; Feinberg, 1980;
Larntz, 1978; Thompson, 1988).
For more about how the effect size measures and their confidence intervals
are computed, see ?rcompanion::cohenG
, ?rcompanion::cramerV
, and
?rcompanion::cramerVFit
.
https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggpiestats.html
# for reproducibility set.seed(123) # one sample goodness of fit proportion test ggstatsplot::ggpiestats(ggplot2::msleep, vore)# association test (or contingency table analysis) ggstatsplot::ggpiestats( data = mtcars, x = vs, y = cyl, legend.title = "Engine" )#> Warning: Chisquared approximation may be incorrect#> Warning: Chisquared approximation may be incorrect