Output frequencies for multiple variables

Usage

plot_counts_items(
  data,
  cols,
  category = NULL,
  ordered = NULL,
  ci = FALSE,
  limits = NULL,
  numbers = NULL,
  title = TRUE,
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data: A tibble containing item measures.
cols: Tidyselect item variables (e.g. starts_with...).
category: The value FALSE will force to plot all categories. A character value will focus a selected category. When NULL, in case of boolean values, only the TRUE category is plotted.
ordered: Values can be nominal (0) or ordered ascending (1) descending (-1). By default (NULL), the ordering is automatically detected. An appropriate color scale should be choosen depending on the ordering. For unordered values, colors from VLKR_FILLDISCRETE are used. For ordered values, shades of the VLKR_FILLGRADIENT option are used.
ci: Whether to plot error bars for 95% confidence intervals.
limits: The scale limits, autoscaled by default. Set to c(0,100) to make a 100 % plot.
numbers: The values to print on the bars: "n" (frequency), "p" (percentage) or both.
title: If TRUE (default) shows a plot title derived from the column labels. Disable the title with FALSE or provide a custom title as character value.
labels: If TRUE (default) extracts labels from the attributes, see codebook.
clean: Prepare data by data_clean.
...: Placeholder to allow calling the method with unused parameters from plot_counts.

Value

A ggplot object.

Examples

library(volker)
data <- volker::chatgpt

plot_counts_items(data, starts_with("cg_adoption_"))
#> In the plot, 4 missing case(s) omitted.