Appelpy

🚀 Now due for proper versioning to reflect evolution of features, this release has enhanced regression diagnostics.

**Main additions:**
- `BadApples` class in `diagnostics` module takes a model object and calculates measures of influence, leverage and outliers. It includes a method for leverage vs residuals squared plot.
- Heteroskedasticity test in the `diagnostics` module: supports Breusch-Pagan and White tests.
- Models support having an index for X that is beyond the typical RangeIndex.

🚀 New module (`discrete_model`) with class for logistic regression `Logit`.

Features for Logit include: standardized estimation (via Long's method); odds ratios; model selection stats; prediction.

🚀 New module (utils) with classes to encode columns of data:
- `DummyEncoder`: create dummy columns from categorical columns. Deals with NaN data in three different ways.
- `InteractionEncoder`: create interaction effects between two columns. Deals with many scenarios for interactions between Boolean, categorical and continuous variables.

🚀 Main features:
- OLS and WLS models (results, predict, model selection, etc.)
- Initial regression diagnostics and EDA functionality