# Admin Analytics

University administrative cost benchmarking project using public data (IRS 990, IPEDS, BLS CPI-U). **First iteration is scoped to the University of Delaware only.** Peer/AAU/multi-institution comparisons are planned for a later iteration.

## Project status

Currently in planning. Phase 1 (Data Acquisition) is planned but not yet built. See `phase1_plan.md` for the full implementation plan and `administrative_analytics_scope_v0.1.md` for project scope.

## Architecture

- **Language:** Python
- **Database:** DuckDB for Phase 1 (single-file, zero-config). Migrate to PostgreSQL in Phase 3 when the dashboard needs concurrent access.
- **Package manager:** uv
- **CLI framework:** typer or click (TBD)
- **Testing:** pytest

## Data sources

| Source | Format | What we extract |
|--------|--------|-----------------|
| IRS 990 bulk XML | XML (versioned schemas) | Filing financials, Part VII compensation, Schedule J detailed compensation |
| IPEDS | CSV bulk downloads | Institution directory (HD), finance by function (F1A/F2), staffing (S/SAL), enrollment (EF) |
| BLS CPI-U | Flat file or API | Consumer Price Index for inflation-adjusted compensation analysis |
| Admin office web pages (stretch) | HTML scraping | Staff directory headcounts |

## Key concepts

- **University of Delaware** is the sole target institution for the first iteration. UD's IPEDS UNITID is the anchor for all IPEDS queries.
- **UD is a public university** and does not file an IRS 990. However, the **University of Delaware Foundation** (a separate nonprofit) does file a 990 — this is the source for executive compensation (Schedule J) and philanthropic data.
- **UNITID** is the canonical institution identifier (from IPEDS). All cross-source linking flows through UNITID.
- **EIN** links to IRS 990 filings. For the first iteration, only UD Foundation EIN(s) are needed. A broader UNITID-to-EIN crosswalk will be built when expanding to peer institutions.
- IRS 990 XML schemas change across tax years. Use the Master Concordance File or IRSx library to handle XPath variations.
- IPEDS variable names change across years. Always parse the accompanying data dictionary; never hardcode variable names.

## Planned project structure

```
src/admin_analytics/
  config.py
  cli.py
  db/           # DuckDB schema and connection
  irs990/       # 990 download, XML parsing, Schedule J extraction, university filtering
  ipeds/        # IPEDS download, dictionary parsing, finance/HR/enrollment loading
  bls/          # CPI-U fetcher and loader
  scraper/      # Stretch: admin office headcount scraper
data/raw/       # Downloaded files (gitignored)
tests/
  fixtures/     # Sample XML/CSV files for tests
```

## Build & run

Not yet implemented. When built, the CLI will support:
```
admin-analytics ingest ipeds --year-range 2005-2024
admin-analytics ingest irs990 --year-range 2005-2024
admin-analytics ingest cpi
admin-analytics ingest all
```

## Conventions

- Raw data tables are prefixed with `raw_` (e.g., `raw_institution`, `raw_990_schedule_j`)
- Downloaded files go in `data/raw/` and are gitignored
- IPEDS variables are mapped to canonical column names at ingest time; raw CSVs stay on disk for reprocessing
- First iteration filters all data to UD/UD Foundation only. Design parsers to accept institution filters so they can scale to multi-institution in a later iteration
- 990 downloads are filtered by EIN from index files to avoid downloading the full archive (hundreds of GB)