Create a Stacked Bar Chart

This function creates a stacked barchart for survey data. It handles raw (unaggregated) data, counting the occurrences of categories, supporting ordered factors, allowing numerical x-axis and stacked variables to be binned into custom groups, and enables renaming of categorical values for display. It can also handle SPSS (.sav) columns automatically.

Usage

create_stackedbar(
  data,
  x_var,
  y_var = NULL,
  stack_var,
  title = NULL,
  subtitle = NULL,
  x_label = NULL,
  y_label = NULL,
  stack_label = NULL,
  stacked_type = c("counts", "percent"),
  tooltip_prefix = "",
  tooltip_suffix = "",
  x_tooltip_suffix = "",
  color_palette = NULL,
  stack_order = NULL,
  x_order = NULL,
  include_na = FALSE,
  na_label_x = "(Missing)",
  na_label_stack = "(Missing)",
  x_breaks = NULL,
  x_bin_labels = NULL,
  x_map_values = NULL,
  stack_breaks = NULL,
  stack_bin_labels = NULL,
  stack_map_values = NULL,
  horizontal = FALSE,
  weight_var = NULL
)

Arguments

data: A data frame containing the raw survey data (one row per respondent).
x_var: String. Name of the column for the X-axis categories.
y_var: Optional string. Name of a pre-computed count column. If NULL (default), the function counts occurrences.
stack_var: String. Name of the column whose values define the stacks.
title: Optional string. Main chart title.
subtitle: Optional string. Chart subtitle.
x_label: Optional string. X-axis label. Defaults to x_var.
y_label: Optional string. Y-axis label. Defaults to "Number of Respondents" or "Percentage of Respondents".
stack_label: Optional string. Title for the stack legend. Defaults to stack_var.
stacked_type: One of "normal" (counts) or "percent" (100% stacked). Default "normal".
tooltip_prefix: Optional string prepended to tooltip values.
tooltip_suffix: Optional string appended to tooltip values.
x_tooltip_suffix: Optional string appended to x-axis values in tooltips.
color_palette: Optional character vector of colors for the stacks.
stack_order: Optional character vector specifying order of stack_var levels.
x_order: Optional character vector specifying order of x_var levels.
include_na: Logical. If TRUE, NA values in both x_var and stack_var are shown as explicit categories. If FALSE (default), rows with NA in either variable are excluded. Default FALSE.
na_label_x: String. Label for NA values in x_var when include_na = TRUE. Default "(Missing)".
na_label_stack: String. Label for NA values in stack_var when include_na = TRUE. Default "(Missing)".
x_breaks: Optional numeric vector of cut points for binning x_var.
x_bin_labels: Optional character vector of labels for x_breaks bins.
x_map_values: Optional named list to remap x_var values for display.
stack_breaks: Optional numeric vector of cut points for binning stack_var.
stack_bin_labels: Optional character vector of labels for stack_breaks bins.
stack_map_values: Optional named list to remap stack_var values for display.
horizontal: Logical. If TRUE, creates horizontal bars. Default FALSE.
weight_var: Optional string. Name of a weight variable to use for weighted aggregation. When provided, counts are replaced with weighted sums using this variable.

Value

An interactive highcharter bar chart plot object.

Details

This function performs the following steps:

Input Validation: Checks if the provided data is a data frame and if x_var and stack_var columns exist.
Data Copy: Creates a mutable copy of the input data to perform transformations without affecting the original.
Handle 'haven_labelled' Columns: If haven package is available, it detects if x_var or stack_var are of class haven_labelled (common for data imported from SPSS/Stata/SAS). If so, it converts them to standard R factors, using their underlying numeric values as levels (e.g., a '1' that was labeled "Male" will become a factor level "1"). This ensures recode can operate correctly.
Apply Value Mapping (x_map_values, stack_map_values): If provided, x_map_values and stack_map_values (named lists, e.g., list("1"="Male")) are used to rename the values in x_var and stack_var respectively. This is useful for converting numeric codes or abbreviations into descriptive labels. If the column is a factor, it's temporarily converted to character to ensure dplyr::recode works reliably on the values.
Handle Binning (x_breaks, x_bin_labels, stack_breaks, stack_bin_labels):
- If x_var (or stack_var) is numeric and corresponding _breaks are provided, the function uses base::cut() to discretize the numeric variable into bins.
- _bin_labels can be supplied to give custom names to these bins (e.g., "18-24" instead of "(17,25]"). If not provided, cut() generates default labels.
- A temporary column (e.g., .x_var_binned) is created to hold the binned values, and this temporary column is then used for plotting.
Data Aggregation and Final Factor Handling:
- The data is transformed using dplyr::mutate to ensure x_var and stack_var (or their binned versions) are treated as factors. If include_na = TRUE, missing values are converted into an explicit "(NA)" factor level.
- If weight_var is provided, weighted sums are calculated for each combination of x_var and stack_var using sum(weight_var, na.rm = TRUE). Otherwise, dplyr::count() is used to count occurrences for each unique combination. This creates the n column required for highcharter.
Apply Custom Ordering (x_order, stack_order): If provided, x_order and stack_order are used to set the display order of the factor levels for the X-axis and stack categories, respectively. This is essential for ordinal scales (e.g., Likert scales) or custom desired sorting. Levels not found in the order vector are appended at the end.
Highcharter Chart Generation: The aggregated plot_data is passed to highcharter::hchart() to create the base stacked column chart.
Chart Customization: Titles, subtitles, axis labels, stacking type (counts vs. percent), data labels, legend titles, tooltips, and custom color palettes are applied based on the function's arguments.
Return Value: The function returns a highcharter plot object, which can be printed directly to display the interactive chart.

Usage

Arguments

Value

Details

Examples