Music behavior analytics project comparing listening patterns across cities, weekdays, artists, and genres.
- English documentation: README_EN.md
- Documentación en español: README_ES.md
- Notebook EN: notebooks/project_EN.ipynb
- Notebook ES: notebooks/project_ES.ipynb
pip install -r requirements.txt
jupyter notebook notebooks/project_EN.ipynb- Behavioral analytics using music-streaming event data
- Data cleaning and schema normalization
- Missing-value handling and duplicate removal
- Category normalization for genre aliases
- City and weekday segmentation
- Hypothesis-driven interpretation
Springfield shows consistently higher listening activity than Shelbyville across the observed weekdays. The behavioral difference is strongest in volume and weekday timing, while broad genre preferences remain relatively similar.