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Advanced bar chart visualization module implementing 5 different approaches for creating professional bar charts. Choose from ggplot2 basics, polished presentations, statistical annotations, interactive plots, and publication-ready designs. Each approach optimized for different use cases in clinical research.

Usage

advancedbarplot(
  data,
  x_var,
  y_var,
  fill_var = NULL,
  facet_var = NULL,
  chart_approach = "polished",
  bar_position = "dodge",
  stat_type = "mean",
  error_bars = "se",
  color_palette = "clinical",
  show_values = TRUE,
  value_format = "auto",
  add_statistics = FALSE,
  stat_method = "anova",
  orientation = "vertical",
  plot_title = "",
  x_title = "",
  y_title = "",
  legend_position = "right",
  theme_style = "clean",
  bar_width = 0.8,
  plot_width = 10,
  plot_height = 6,
  sort_bars = "none",
  add_trend_line = FALSE,
  highlight_bars = "",
  transparency = 0.9,
  export_options = TRUE
)

Arguments

data

The data as a data frame.

x_var

Categorical variable for x-axis categories.

y_var

Numeric variable for bar heights.

fill_var

Optional variable for bar fill colors (grouped/stacked bars).

facet_var

Optional variable for creating multiple panels.

chart_approach

Choose the bar chart approach and styling.

bar_position

Position adjustment for grouped bars.

stat_type

Type of statistical summary for y-axis values.

error_bars

Type of error bars to display.

color_palette

Color palette for bar fills including GraphPad Prism palettes.

show_values

Whether to display values on top of bars.

value_format

Format for displayed values.

add_statistics

Whether to perform and display statistical tests.

stat_method

Type of statistical test to perform.

orientation

Orientation of the bars.

plot_title

Main title for the plot.

x_title

Title for x-axis.

y_title

Title for y-axis.

legend_position

Position of the legend.

theme_style

Overall theme style for the plot including GraphPad Prism themes.

bar_width

Width of the bars (0.1 to 1.0).

plot_width

Width of the plot in inches.

plot_height

Height of the plot in inches.

sort_bars

How to sort the bars.

add_trend_line

Whether to add a trend line for numeric x-axis.

highlight_bars

Comma-separated list of categories to highlight.

transparency

Transparency level for bars (alpha value).

export_options

Whether to optimize plot for high-quality export.

Value

A results object containing:

results$instructionsa html
results$approach_descriptiona html
results$main_plotan image
results$statistical_resultsa html
results$summary_statsa html
results$interactive_plota html
results$comparison_gridan image
results$code_examplea html
results$interpretation_guidea html

Examples

# \donttest{
# Example usage - 5 different bar chart approaches:
# 1. Basic ggplot2 approach
# 2. Polished presentation style
# 3. Statistical annotation style
# 4. Interactive plotly style
# 5. Publication-ready style
# }