datamat 0.2.4

* DataMat
/Matrix Operations on Data Arrays./ A pandas-friendly toolkit that wraps rich matrix algebra primitives in DataFrame/Series-aware containers (~DataMat~, ~DataVec~).

** Features
- Drop-in replacements for many ~numpy~ matrix operations that preserve pandas metadata.
- Helpers for aligning MultiIndex structures and constructing dummy variables from categorical sources.
- A ~DataVec~/~DataMat~ API that mirrors pandas while adding linear-algebra conveniences (projection, leverage, SVD, etc.).

** Repository Layout
#+begin_example
src/datamat/        Core source code (DataMat, DataVec, utilities)
docs/               Historical literate notebooks and design notes
tests/              Unit tests
scripts/            Development tooling (e.g., pre-push hook)
#+end_example

** Getting Started
1. Install Python 3.11 (e.g., via pyenv) and Poetry (https://python-poetry.org/docs/).
2. Create and initialise the virtual environment:
   #+begin_src bash
   poetry env use 3.11
   poetry install --with dev
   # optional extras, e.g. lsms, can be added via `poetry add`
   #+end_src
3. Run the quality gates and test suite:
   #+begin_src bash
   poetry run ruff check .
   poetry run black --check .
   poetry run mypy src tests
   poetry run pytest
   # or simply
   make check
   #+end_src

** Development Workflow
- Contribution guidelines: [[file:CONTRIBUTING.org][CONTRIBUTING.org]]
- Agent-specific policies: [[file:AGENTS.org][AGENTS.org]]
- Pre-push automation: =ln -s ../../scripts/pre-push.sh .git/hooks/pre-push=

** Documentation
The historical literate source from the original Metrics Miscellany project lives in =docs/metrics_miscellany.org=. It remains the best place to reference derivations and design notes. Current development happens directly in the Python modules under =src/datamat/=; augment the Org materials when adding new capabilities.

** Online Docs
Rendered documentation generated by MkDocs is available at [[https://ligon.github.io/DataMat/]].

** Optional Dependencies
- Robust Stata ingestion relies on =lsms.tools.from_dta=. Install the =lsms= package if you plan to call =datamat.read_stata=.

** License
The project continues under the original license; see =LICENSE.txt=.