Assesspy

Changes

- Adds a new function [`med_ratio_met`](https://github.com/ccao-data/assesspy/blob/16f6c671bac14215a806d7316a53e9a14241d8dc/assesspy/metrics.py#L339-L349) to test whether median sales ratios meet the relevant [IAAO standard](https://www.iaao.org/wp-content/uploads/Standard_on_Ratio_Studies.pdf). See #31.
- Simplifies unit tests using `tox`. See 28 and 29.
- Adds caching for docs generation on CI. See 30.

> [!IMPORTANT]
> This release contains a major bugfix for the `prb()` function. Previous versions of this function (back to AssessPy 1.0.0) returned incorrect PRB values due to an omitted intercept in the PRB formula. Please update your version of AssessPy to >= 2.0.1.

Changes

- Fixed missing intercept in the `prb()` formula, see 27.
- Fixed incorrect sampling in `_ci` functions introduced by 24. See 27.
- Fixed mis-specified CI `alpha` tests. See 27.
- Added additional unit tests based on IAAO data. See 26.

> [!WARNING]
> This is a breaking refactor. It significantly changes the API of some functions and deprecates others.

Breaking changes

- All metrics (COD, PRD, etc.) now have the same inputs (`estimate`, `sale_price`) and return the same output (a single `float`). Previously, some metrics had one input (COD) or different outputs (PRD)
- The sub-functions of `detect_chasing` and `is_outlier` are no longer exported to the user. Instead they can be selected via an argument in their respective functions
- `detect_chasing` is renamed to `is_sales_chased` for consistency with `is_outlier`
- Sample datasets are renamed to reflect their respective sources

Other changes

- Removed as much `numpy` as possible for compatibility with Spark/Athena
- Added static types to almost everything, which should make this package easier to maintain in the long run
- Replaced all unit tests with a fixtures matrix and parameters
- Updated a lot of the documentation structure
- Updated the example ratio study notebook

- Switch entire package from legacy setup (setup.py, cfg, etc.) to modern setup (pyproject.toml, ruff)

- Bump version for compatibility with new PyPI setup

- Add the Kakwani Index (KI) and Modified Kakwani Index (MKI) from [this paper](https://researchexchange.iaao.org/jptaa/vol17/iss2/2/) as functions
- Update the vignette to include KI, MKI, and Lorenz curve examples
- Update vignette and README language