2.0.1

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.

2.0.0

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

1.2.0

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

1.1.1

• Bump version for compatibility with new PyPI setup

1.1.0

• Add the Kakwani Index (KI) and Modified Kakwani Index (MKI) from this paper as functions
• Update the vignette to include KI, MKI, and Lorenz curve examples
• Update vignette and README language

1.0.2

Migration to GitHub