Chameleon-company/MOP-Code
Aug 2025 – Aug 2025
1 Month active
Languages Used
HTMLJavaScriptJupyter NotebookPython
Technical Skills
Data AnalysisData CleaningData VisualizationFoliumGeospatial AnalysisMatplotlib
Hanwen Dun
PROFILE
Hanwen Dun
During August 2025, Dunh developed a geospatial-ready hydrant coverage analysis for Melbourne in the Chameleon-company/MOP-Code repository. The project involved end-to-end data import, cleaning, and preparation using Python, Pandas, and Folium, enabling geospatial visualization to support urban planning and fire safety analytics. Dunh established a reusable workflow for processing hydrant datasets, laying the groundwork for rapid visualization and future analytical features. The work focused on enabling data-driven decision making by ensuring the data was clean, well-structured, and ready for mapping. No major bugs were reported, and all deliverables were completed within the first sprint’s commitments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
12,551
Activity Months1
Your Network
186 people
Work History
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 summary for Chameleon-company/MOP-Code: Delivered a new geospatial-ready hydrant coverage analysis for Melbourne (UC00196). Implemented data import, cleaning, and preparation steps to enable geospatial visualization and support for urban planning and fire safety analytics. No major bugs reported; work completed within sprint 1 commitments. This lays the foundation for data-driven decision making and future visualization features.
2 Commits • 1 Features
Aug 1, 2025August 2025 summary for Chameleon-company/MOP-Code: Delivered a new geospatial-ready hydrant coverage analysis for Melbourne (UC00196). Implemented data import, cleaning, and preparation steps to enable geospatial visualization and support for urban planning and fire safety analytics. No major bugs reported; work completed within sprint 1 commitments. This lays the foundation for data-driven decision making and future visualization features.
August 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture70.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLJavaScriptJupyter NotebookPython
Technical Skills
Data AnalysisData CleaningData VisualizationFoliumGeospatial AnalysisMatplotlibPandasPython
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