Create barplots — barplotter • ggAU

Enables the creation of barplots in a convenient and customizable manner, and calculates the associated Fisher's test p-value on the count data.

Usage

barplotter(
  data,
  x_val,
  y_val,
  order = NA,
  scale_labs = ggplot2::waiver(),
  pct = T,
  style = "light",
  colors = NA,
  y_lab = ggplot2::waiver(),
  x_lab = ggplot2::waiver(),
  title = "",
  labcol = "black",
  display_n = T,
  legend_lab = NA,
  labels = NA,
  filter_col = NA,
  filter_val = NA
)

Arguments

data: The data.frame to be used for the visualization.
x_val: string, the name of the column to plot on the x axis.
y_val: string, the name of the column to plot on the y axis.
order: vector, the order in which the bars should appear. It should include all unique values in x_val in the desired order. If unspecified, the bars follow the order of the dataframe.
scale_labs: vector, names to display on the x axis ticks. By default, it shows the names as they appear in x_val.
pct: boolean, if TRUE, percentages are displayed on the bars, if FALSE, the absolute numbers are shown.
style: string, palette style to be used for scale_fill_au. Default is light. Style is only applied if colors remains NA.
colors: vector containing the colors to be used for the fill aesthetic. Default is NA. If unspecified, the function uses au_colors().
y_lab: string, the y axis label. Default is percent. If pct = FALSE, the default is number.
x_lab: string, the x axis label. Default is the string passed into x_val.
title: string, the title of the plot to be displayed on top. Deafult is "".
labcol: string, the color of the annotation numbers displayed inside the bars. The default is black.
display_n: boolean, if TRUE, the plot displays the sample size appended to the title. Default is TRUE.
legend_lab: string, the legend title. Default is the string passed into y_val.
labels: vector, the legend annotations. Default is the unique values in y_val.
filter_col: string, the name of the column to filter data by. Default is NA.
filter_val: string or list, the entries to keep in filter_col. Default is NA.

Value

A ggplot object.

Examples

iris = dplyr::mutate(iris, Petal_mean = ifelse(Petal.Length > mean(Petal.Length),
"above_mean", "below_mean"))

barplotter(data = iris, x_val = "Species", y_val = "Petal_mean", labcol = "white")