Baribal

This release focuses on enhancing the package installation experience with improved build configurations and package structure.

Core Improvements
* Fixed package structure for PyPI distribution to ensure consistent installation across all environments
* Enhanced build process in CI/CD pipeline to maintain structural integrity
* Added package installation verification steps in the release process

Previously Released Features
* 🗜️ memory_diet(): Smart DataFrame memory optimization
- Intelligent numeric type downcasting
- Category compression for string columns
- Index optimization
- Optional aggressive mode for maximum memory savings

New Feature
* 🗜️ `memory_diet()`: Smart DataFrame memory optimization
- Intelligent numeric type downcasting
- Category compression for string columns
- Index optimization
- Optional aggressive mode for maximum memory savings
- Preserves data integrity while reducing memory footprint

This release introduces memory optimization capabilities while maintaining all existing functionality from v0.1.0. The new `memory_diet()` function helps users reduce their DataFrame memory usage through intelligent type optimization, making Baribal even more practical for working with large datasets.

🎉 Initial Release

First public release of Baribal with core functionalities:

Features
- 🔍 `glimpse()`: R-style DataFrame preview
- 📊 `tabyl()`: Enhanced cross-tabulations
- 🧹 `clean_names()`: Smart column renaming
- 🔄 `rename_all()`: Pattern-based renaming
- 📊 `missing_summary()`: Missing values analysis

Supported Features
- Works with both pandas and polars DataFrames
- Comprehensive test coverage
- Full documentation