scf (version 1.0.5)

scf_plot_hex: Hexbin Plot of Two Continuous SCF Variables

Description

Visualizes the bivariate relationship between two continuous SCF variables using hexagonal bins.

Usage

scf_plot_hex(design, x, y, bins = 50, title = NULL, xlab = NULL, ylab = NULL)

Value

A ggplot2 object displaying a Rubin-pooled hexbin plot.

Arguments

design

A scf_mi_survey object created by scf_load().

x

A one-sided formula for the x-axis variable (e.g., ~income).

y

A one-sided formula for the y-axis variable (e.g., ~networth).

bins

Integer. Number of hexagonal bins along the x-axis. Default is 50.

title

Optional character string for the plot title.

xlab

Optional x-axis label. Defaults to the variable name.

ylab

Optional y-axis label. Defaults to the variable name.

Implementation

The function stacks all implicates into one data frame, retains replicate weights, and uses ggplot2::geom_hex() to produce a density-style scatterplot. The color intensity of each hexagon reflects the Rubin-pooled weighted count of households in that cell. Missing values are excluded.

This plot is especially useful for visualizing joint distributions with large samples and skewed marginals, such as net worth vs. income.

Aesthetic Guidance

This plot uses a log-scale fill and viridis palette to highlight variation in density. To adjust the visual style globally, use scf_theme() or set it explicitly with ggplot2::theme_set(scf_theme()). For mobile-friendly or publication-ready appearance, export the plot at 5.5 x 5.5 inches, 300 dpi.

Dependencies

Requires the ggplot2 package. The fill scale uses scale_fill_viridis_c() from ggplot2. Requires the hexbin package. The function will stop with an error if it is not installed.

See Also

scf_corr(), scf_plot_smooth(), scf_theme()

Examples

# Do not implement these lines in real analysis:
# Use functions `scf_download()` and `scf_load()`
td <- tempfile("plot_hex_")
dir.create(td)

src <- system.file("extdata", "scf2022_mock_raw.rds", package = "scf")
file.copy(src, file.path(td, "scf2022.rds"), overwrite = TRUE)
scf2022 <- scf_load(2022, data_directory = td)

# Example for real analysis: Plot hexbin of income vs. net worth
scf_plot_hex(scf2022, ~income, ~networth)

# Do not implement these lines in real analysis: Cleanup for package check
unlink(td, recursive = TRUE, force = TRUE)