comparison_plot {GTAPViz} | R Documentation |
Create Comparative Bar Charts from HAR and SL4 Data
Description
Generates comparative bar charts using GTAP data. Supports panel facets, split-by grouping, and fully customizable styling and export options.
Input Data
Usage
comparison_plot(
data,
filter_var = NULL,
x_axis_from,
split_by = "Variable",
panel_var = "Experiment",
variable_col = "Variable",
unit_col = "Unit",
desc_col = "Description",
invert_axis = FALSE,
separate_figure = FALSE,
var_name_by_description = FALSE,
add_var_info = FALSE,
output_path = NULL,
export_picture = TRUE,
export_as_pdf = FALSE,
export_config = NULL,
plot_style_config = NULL
)
Arguments
data |
A data frame or list of data frames containing GTAP results. |
filter_var |
NULL, a vector, a data frame, or a named list specifying filtering conditions.
For example: |
x_axis_from |
Character. Column name used for the x-axis. |
split_by |
Character or vector.
|
panel_var |
Character. Column for panel facets. Default is |
variable_col |
Character. Column name for variable codes. Default is |
unit_col |
Character. Column name for units. Default is |
desc_col |
Character. Column name for variable descriptions. Default is Plot Behavior |
invert_axis |
Logical. If |
separate_figure |
Logical. If Variable Display |
var_name_by_description |
Logical. If |
add_var_info |
Logical. If Export Settings |
output_path |
Character. Directory to save plots. If |
export_picture |
Logical. If |
export_as_pdf |
Logical or
|
export_config |
List. Export options including dimensions, DPI, and background.
See Styling |
plot_style_config |
List. Custom plot appearance settings.
See |
Details
Please refer to the full plot
Value
A ggplot object or a named list of ggplot objects depending on the separate_figure
setting.
If export_picture
or export_as_pdf
is enabled, the plots are also saved to output_path
.
Author(s)
Pattawee Puangchit
See Also
get_all_config
, detail_plot
, stack_plot
,
create_title_format
Examples
# Load data
input_path <- system.file("extdata/in", package = "GTAPViz")
sl4.plot.data <- readRDS(file.path(input_path, "sl4.plot.data.rds"))
reg_data <- sl4.plot.data[["REG"]]
# Generate plot
plotA <- comparison_plot(
data = reg_data,
filter_var = list(Region = "Oceania", Variable = "qgdp"),
x_axis_from = "Region",
split_by = "Variable",
panel_var = "Experiment",
variable_col = "Variable",
unit_col = "Unit",
desc_col = "Description",
invert_axis = FALSE,
separate_figure = FALSE,
var_name_by_description = FALSE,
add_var_info = FALSE,
output_path = NULL,
export_picture = FALSE,
export_as_pdf = FALSE,
export_config = create_export_config(width = 20, height = 12),
plot_style_config = create_plot_style(
color_tone = "purdue",
add_unit_to_title = TRUE,
title_format = create_title_format(
type = "prefix",
text = "Impact on"
),
panel_rows = 2
)
)