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Visualize actor-level network statistics

Source: R/plot_actor_stats.R
plot_actor_stats.Rd

plot_actor_stats creates visualizations of actor-level statistics from summary_actor() output. the function automatically adapts to the data structure (cross-sectional/longitudinal, single/multilayer) and offers two main visualization approaches: distribution across actors or tracking specific actors.

Usage

plot_actor_stats(
  summary_df,
  longitudinal = ifelse("time" %in% colnames(summary_df), TRUE, FALSE),
  multilayer = ifelse("layer" %in% colnames(summary_df), TRUE, FALSE),
  across_actor = TRUE,
  specific_stats = NULL,
  specific_actors = NULL
)

Arguments

summary_df

a data frame from summary_actor() containing actor-level statistics. must include an "actor" column. may include "time" column for longitudinal data and "layer" column for multilayer networks.

longitudinal

logical indicating whether to treat data as longitudinal. if NULL (default), automatically detected based on presence of "time" column. set to FALSE if only one unique time point exists.

multilayer

logical indicating whether to treat data as multilayer. if NULL (default), automatically detected based on presence of "layer" column. set to FALSE if only one unique layer exists.

across_actor

logical. if TRUE (default), visualizes distribution of statistics across all actors. if FALSE, focuses on tracking specific actors. when TRUE with specific_actors provided, shows distribution for only those actors.

specific_stats

character vector of statistic names to plot. if NULL (default), plots all available statistics. must match column names in summary_df.

specific_actors

character vector of actor names to highlight or focus on. if NULL (default) with across_actor = FALSE, includes all actors (with warning if > 25 actors). must match values in the "actor" column.

Value

a ggplot object that can be further customized or saved. the plot type depends on the data structure and parameters:

  • cross-sectional, across actors: density plots with rug plots

  • cross-sectional, specific actors: beeswarm plots

  • longitudinal, across actors: ridge density plots over time

  • longitudinal, specific actors: line plots over time

all plots are faceted by statistic and, when applicable, by layer.

Details

visualization logic:

the function chooses appropriate visualizations based on data structure:

  • distribution plots (across_actor = TRUE): show how statistics are distributed across the actor population

  • actor-specific plots (across_actor = FALSE): track individual actors, with specified actors highlighted in color while others appear in gray

all plots use theme_stat_netify() for consistent styling across netify visualizations.

for multilayer longitudinal data with across_actor = FALSE, consider using specific_stats to avoid overcrowded facets.

Author

cassy dorff, shahryar minhas