
Marcos Moya contributed to the arvindkrishna87/STAT390_LegalAid_Fall2025 repository by developing analytics features focused on chatbot interactions within legal aid call data. He implemented data analysis workflows in Python and Jupyter Notebook, leveraging Pandas and Seaborn for data wrangling and visualization to extract insights on call outcomes, termination reasons, and durations. Marcos also enhanced repository maintainability through documentation updates, asset reorganization, and removal of redundant files, streamlining onboarding for new contributors. His work emphasized reproducibility and clarity, resulting in a well-structured analytics project with presentation-ready artifacts. The contributions demonstrated solid technical depth in data engineering and project hygiene.

October 2025 performance snapshot for the STAT390_LegalAid_Fall2025 analytics project. Focused on delivering actionable chatbot analytics capabilities and improving repository hygiene to support scalable analytics work.
October 2025 performance snapshot for the STAT390_LegalAid_Fall2025 analytics project. Focused on delivering actionable chatbot analytics capabilities and improving repository hygiene to support scalable analytics work.
Month 2025-09: Focused on repository hygiene and knowledge transfer through non-functional housekeeping and documentation updates for arvindkrishna87/STAT390_LegalAid_Fall2025. No major bug fixes this period; groundwork laid for maintainability and onboarding.
Month 2025-09: Focused on repository hygiene and knowledge transfer through non-functional housekeeping and documentation updates for arvindkrishna87/STAT390_LegalAid_Fall2025. No major bug fixes this period; groundwork laid for maintainability and onboarding.
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