A collection of analytical investigations, predictive modeling, and data engineering projects, ranging from geospatial analysis to deep learning architectures.
Projects are organized by technical domain to make navigation easier:
- geo-eleitoral-sp: Geographical analysis of the educational profile distribution of São Paulo voters (2022) using TSE public data.
- lyrics-sentiment-analysis: Quantitative and sentiment analysis of song lyrics from Spotify Top Brasil.
The tech stack is selected based on each project's needs, with analytical accuracy as a core principle:
- Languages: Python 3.8+
- Data Analysis: Pandas, GeoPandas, NumPy
- Visualization: Matplotlib, Seaborn, Plotly
- AI & NLP: PyTorch, NLTK, TextBlob
- Make sure your virtual environment is active.
- Each subdirectory has its own
requirements.txtfile for reproducibility. - Large datasets (such as the 5GB TSE file) are not versioned; check each project's
README.mdfor download instructions.
This repository and all subprojects are licensed under the MIT License.
Author: Mauro Santos
GitHub: @Maurog-rgba