Metadata-Version: 2.4
Name: swiss_cheese
Version: 0.1.1
Classifier: Programming Language :: Rust
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Dist: pandas>=2.3
Requires-Dist: numpy>=2.4
Requires-Dist: scipy>=1.16
Requires-Dist: pytest>=7.0 ; extra == 'dev'
Provides-Extra: dev
Summary: Missing Value generation library for research purposes.
Requires-Python: >=3.10
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM

# swiss-cheese
Making missing values for research purposes.
Focuses on tabular data.

# Missing Completely At Random (MCAR)

  Sets $\alpha$ percentage of values to missing completely at random.
  Ensures that every element has at least one feature.

# Missing Not At Random (MNAR)
  
  Sets $\alpha$ percentage of values missing by sampling from a normal distribution and matching to the nearest data value.

