Added calendar_spo: a São Paulo holiday and business-day calendar (2012–2030) covering national, state, and municipal holidays, for use in demand seasonality and business-day adjustments.
Removed the forecasts and forecast_accuracy exports. These were exported in 1.0.0 by mistake: metrosp is an observed-demand data package and forecasting belongs downstream, so they should never have shipped.
Removed the metro_lines export. Its line-name columns (line_name, line_name_pt) are already denormalized onto every passenger/station dataset, and the full line list (including planned and CPTM lines) is available in lines. It remains an internal join dimension in the ETL pipeline.
station_daily$line_number / station_daily$year are now integer (previously double), matching the other datasets. Values are unchanged.
Data quality
Station names are now canonicalized consistently across the demand datasets (station_averages, station_daily) and the geometry datasets (stations), so a station joins cleanly across sources.
Fixed footnote-digit and sponsor-name contamination in station names (e.g. stray trailing digits and parenthesized line numbers).
Trailing unpublished NA rows are now trimmed per line during assembly; interior NAs (e.g. station outages) are preserved. All datasets rebuilt.
Refreshed the 2017–2019 source CSV.
Data pipeline
The data-raw/ ETL now runs as a targets pipeline (targets::tar_make()), replacing the flag-driven run_pipeline.R orchestrator. Pipeline functions live in data-raw/R/; the legacy scripts remain and produce identical output. See CLAUDE.md for the workflow.
Gated refreshes (download, historical re-import, Dataverse) are controlled by environment-variable flags via tarchetypes::tar_force() and skip cleanly when the flags are off.
