Chameleon-company/MOP-Code
Aug 2025 – Sep 2025
2 Months active
Languages Used
MarkdownPythonSQLJupyter Notebook
Technical Skills
Data AnalysisData CleaningData VisualizationDocumentationFoliumJupyter Notebooks
ruvinyaye
PROFILE
Ruvinyaye
Ruvinya Ekanayake developed analytics and documentation features for the Chameleon-company/MOP-Code repository, focusing on Melbourne’s education access and capacity planning. She built Jupyter Notebooks using Python and Pandas to load, clean, and analyze school location and population forecast data, enabling quantification of demand and identification of capacity shortfalls at the suburban level. Her work included modeling geographic resilience and potential capacity expansions to inform future planning. Ruvinya also established foundational project documentation and commit-level traceability, supporting reproducibility and onboarding. The solutions delivered were technically robust, emphasizing scalable data pipelines and workflows that enhance data-driven decision-making for education planning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
3
Lines of code
20,200
Activity Months2
Your Network
98 people
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Chameleon-company/MOP-Code: Delivered a feature-focused milestone on Melbourne Education Access and Capacity Planning, enabling data-driven demand quantification, capacity assessment, and planning for capacity additions. The work enhances forecasting accuracy at suburban levels, informs resilience planning, and sets up scalable data pipelines for ongoing planning. No critical bugs reported this month; ongoing work to integrate with forecasting pipelines and broader rollout.
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Chameleon-company/MOP-Code: Delivered a feature-focused milestone on Melbourne Education Access and Capacity Planning, enabling data-driven demand quantification, capacity assessment, and planning for capacity additions. The work enhances forecasting accuracy at suburban levels, informs resilience planning, and sets up scalable data pipelines for ongoing planning. No critical bugs reported this month; ongoing work to integrate with forecasting pipelines and broader rollout.
September 2025
August 2025
2 Commits • 2 Features
Aug 1, 2025Concise monthly summary for performance review focusing on key accomplishments, business value, and technical achievements for 2025-08.
August 2025
2 Commits • 2 Features
Aug 1, 2025Concise monthly summary for performance review focusing on key accomplishments, business value, and technical achievements for 2025-08.
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPythonSQL
Technical Skills
Data AnalysisData CleaningData VisualizationDocumentationFoliumJupyter NotebooksMatplotlibNumPyNumpyPandas
Repositories Contributed To
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