Compute skill co-occurrence networks for multiple professions

Iterates over a set of professions and calls the internal .cooc_single() for each one, binding the results into a single data.table with a professione identifier column.

Usage

cooc_all_professions(
  skills,
  professions = NULL,
  group_col = "preferredLabel",
  top_n = 30L,
  min_weight = 10L
)

Arguments

skills

A data.table with at least columns general_id, escoskill_level_3, and the column named by group_col.

professions

Optional character vector of profession names to process. When NULL (the default), all unique values of group_col are used.

group_col

Character name of the column used to identify professions. Defaults to "preferredLabel".

top_n

Integer maximum number of edges per profession (before largest-component filtering). Defaults to 30L.

min_weight

Integer minimum co-occurrence count. Defaults to 10L.

Value

A data.table with columns professione, from, to, weight. Professions producing no valid edges are silently dropped.

Examples

if (FALSE) { # \dontrun{
skills <- data.table::data.table(
  general_id = c(1, 1, 1, 2, 2, 3, 3, 3),
  escoskill_level_3 = c("A", "B", "C", "A", "B", "A", "B", "C"),
  preferredLabel = rep("Analyst", 8)
)
cooc_all_professions(skills)
} # }