AmarantosPagiavlas03/Project-Optimization-of-Business-Processes
Jan 2025 – Jan 2025
1 Month active
Languages Used
Python
Technical Skills
Data AnalysisData ManipulationData ProcessingData VisualizationPandasPlotly
Amarantos Pagiavlas
PROFILE
Amarantos Pagiavlas
During January 2025, Amarantos Pagiavlas developed enhancements for the AmarantosPagiavlas03/Project-Optimization-of-Business-Processes repository, focusing on improving scheduling and task visualization. He implemented a multi-day shift Gantt view and ensured weekly task schedules display all days, even those without tasks, by introducing placeholders. Using Python, Pandas, and Plotly, he standardized timeline axes and expanded shift representation for more accurate planning. Amarantos also improved user workflows by persisting task input times in forms and increased data resilience by making time parsing robust to errors. His work addressed both user experience and data integrity, demonstrating thoughtful engineering within a short timeframe.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
9Total
Bugs
1
Commits
9
Features
3
Lines of code
335
Activity Months1
Your Network
6 people
Work History
January 2025
9 Commits • 3 Features
Jan 1, 2025January 2025 monthly performance summary for AmarantosPagiavlas03/Project-Optimization-of-Business-Processes: Delivered a more complete, accurate, and user-friendly scheduling system by enhancing multi-day shift visualization, ensuring complete weekly task representations with placeholders, persisting task input times, and hardening time parsing. These changes improve planning accuracy, reduce manual corrections, and strengthen data resilience, enabling better operational visibility and decision-making.
9 Commits • 3 Features
Jan 1, 2025January 2025 monthly performance summary for AmarantosPagiavlas03/Project-Optimization-of-Business-Processes: Delivered a more complete, accurate, and user-friendly scheduling system by enhancing multi-day shift visualization, ensuring complete weekly task representations with placeholders, persisting task input times, and hardening time parsing. These changes improve planning accuracy, reduce manual corrections, and strengthen data resilience, enabling better operational visibility and decision-making.
January 2025
Activity
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Quality Metrics
Correctness81.2%
Maintainability80.0%
Architecture68.8%
Performance64.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData ManipulationData ProcessingData VisualizationPandasPlotlyPythonStreamlit
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