metrosp 1.2.1

Datasets

• Refroze the bundled snapshot with the latest upstream refresh, adding July 2026 observations where published. The monthly line and station datasets now cover the new month, and station_daily includes observations through July 31, 2026.

metrosp 1.2.0

Datasets

• Extended METRO coverage back to January 2016 for passengers_entrance, passengers_transported, and station_averages.
• Added January–September 2017 to passengers_entrance, passengers_transported, and station_averages. METRO published those months only as PDFs without a text layer; they were transcribed from the rendered pages and reconciled against the totals printed beside them.
• July 2017 remains absent from passengers_entrance for Lines 1, 2, 3, 5, and 15, and for the network total. The file METRO published under that name repeats the transported table, so no entrance figures exist for that month. Line 4 comes from the Dataverse and is unaffected.
• June 2017 has no network total (line_number = 99) in passengers_transported. The report reprinted May’s network column; the per-line values for June are unaffected.
• Refroze the shipped snapshot through June 2026 (Lines 4 and 5 end earlier, in March and April 2026, since the Dataverse source lags METRO).

Bug fixes

• Corrected mdu, msa, mdo, and max for Lines 4 and 5 in passengers_entrance, across the whole series. The Dataverse source is station-level, and the averages and daily peak were taken over station-days rather than over line-day totals, so each was divided by the number of stations reporting that month. Values rise by roughly 5 to 17 times depending on the line and the year. total is unchanged. Anyone comparing Line 4 or 5 averages against an earlier release should expect a break.
• Fixed metric labels resolving to NA for 2016–2019 in passengers_entrance and passengers_transported. The lookup keyed a named vector on accented Portuguese text, which stops matching outside a UTF-8 locale, so a build could drop every label without erroring. Station names and line numbers in station_averages were affected the same way. The pipeline now refuses to run outside a UTF-8 locale.

Pipeline

No exported value changes. The snapshot was refrozen for two structural differences: metric_abb in passengers_entrance and passengers_transported no longer carries a stray names attribute, and station_averages drops one all-NA row (Jardim Colonial, January 2022).

• Replaced the per-year, per-line row-offset tables in the station-average and passenger readers with block detection over the file’s own text. The readers locate each line’s table by its LINHA … / DEMANDA … header and take the line roster from that header, so a source that adds a title row or drops a line no longer needs a hand-edited offset. One reader now serves 2016 and 2020 onward, and another serves the 2017–2019 monthly files.
• Removed .import_stn_avg_2016(), get_skip_offset(), read_csv_stations_average(), and clean_stations_average(), all superseded by the shared readers.
• Fixed the 2016 line-level reader placing Line 5 in Line 15’s column. The committed CSVs were already correct, so no exported value changes; the fix is what keeps a future re-import of the 2016 files correct.
• Collapsed three copies of the line-name lookup into dim_line$line_name_full, and derived metro_lines from dim_line instead of restating it.
• Renamed the pipeline’s functions onto one vocabulary (psg_line, stn_avg, stn_daily, suffixed by era) and dropped the . prefix.
• Required dplyr 1.2.0, for filter_out() and replace_values().
• data-publish.yaml now writes each batch to a dated data-YYYY-MM release tag as well as the rolling data-latest tag, so a batch stays retrievable after data-latest moves on.

Documentation

• Documented that passengers_transported reports thousands of passengers, while the other demand datasets count individual passengers.
• Documented a defect in the Line 1 station averages for February–June 2016. The values run short and are misallocated across stations, so those five months should be excluded from station-level baselines.
• Corrected the end of Line 5 coverage in passengers_transported to August 2018, the month of the ViaMobilidade handover.
• Added the frozen-snapshot vintage and the data-latest release to the package landing page and both vignettes.
• Regenerated the time-coverage figures and their alt text against the new snapshot.

metrosp 1.1.1

Datasets

• passengers_entrance, passengers_transported, and station_daily rebuilt through April 2026.

Vignettes

• Added time-coverage-by-line charts and tables to the data dictionary for all four core datasets (previously only passengers_entrance had one).
• Rewrote the “Core datasets” sections of the data dictionary to follow a single consistent structure (columns table, glimpse, time coverage).
• Reordered the interchange-stations table by reference line and station name, and fixed assorted typos and wording issues.

metrosp 1.1.0

Datasets

• 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.
• Fixed a duplicate row in stations (Vila Mariana, Line 1) caused by the GeoSampa import not deduplicating after the name/join cleanup step. Added a regression test asserting stations has no duplicate rows.
• Fixed a row-skip bug in the passenger-by-line CSV parser (passengers_entrance, passengers_transported): a hardcoded per-year header offset was one row short of where the source’s “Jan” row actually landed, which shifted every month’s figures up one slot (February’s numbers were recorded as January’s, and so on) and mistook the annual total row for December. The offset is now detected dynamically per file instead of hardcoded, since the header length has drifted release to release.
• Fixed a targets caching gap where the METRO CSV download target returned a constant directory path, so a fresh download never invalidated the downstream parsers (entrance_current, transported_current, averages_current, daily_current) – they kept serving stale cached data even right after a real re-download. The target is now content-hashed against the downloaded files themselves.

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.

metrosp 1.0.0

• Initial CRAN submission.