Compute skill ranking per profession over time periods — compute_skill_ranking

Aggregates skill counts by profession and time period, then ranks skills within each profession-period combination (descending by count). The time unit controls the granularity of aggregation.

Usage

compute_skill_ranking_series(
  competenze,
  time_unit = "year",
  cutoff_date = NULL
)

Arguments

competenze: A data.table with columns escoskill_level_3 (skill label), nome_3 (profession name), and gdate (date, either Date or IDate class).
time_unit: Character, time unit for lubridate::floor_date(). Default: "year". Other options: "quarter", "month", etc.
cutoff_date: Date or character in "YYYY-MM-DD" format. Observations on or after this date are excluded. Default: NULL (no filtering).

Value

A data.table with columns professione (from nome_3), mese (floored date), skill (from escoskill_level_3), N (count), and rango (rank within profession-period, 1 = most frequent).

Details

This reproduces the temporal ranking logic where skills are ranked by frequency within each profession at each time step.