Chameleon-company/MOP-Code
Aug 2025 – Sep 2025
2 Months active
Languages Used
PythonSQLCSSHTMLJSONJavaScriptJupyter NotebookText
Technical Skills
API IntegrationData AnalysisData CleaningData VisualizationFoliumGeospatial Analysis
manya0033
PROFILE
Manya0033
Manya Mahajan developed data-driven urban planning tools for the Chameleon-company/MOP-Code repository, focusing on mapping Melbourne’s tourist demand against hospitality capacity within a 200-meter radius. She engineered notebook-based workflows using Python, Pandas, and Folium to collect, clean, and visualize pedestrian and hospitality data, enabling reproducible geospatial analysis for city planning and visitor experience optimization. Manya also reorganized the repository for maintainability, introducing standardized scaffolding and rigorous code cleanup to streamline onboarding and reduce technical debt. Her work balanced rapid prototyping with robust data science practices, delivering maintainable pipelines and reproducible results while addressing both feature development and bug resolution.
Overall Statistics
Feature vs Bugs
58%Features
Repository Contributions
32Total
Bugs
5
Commits
32
Features
7
Lines of code
130,467
Activity Months2
Your Network
98 people
Work History
September 2025
28 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for Chameleon-company/MOP-Code: Delivered initial UC00201_Tourist_Hotspot_Vs_Hospitality_Capacity content, reorganized repository for publish readiness, and established assets and scaffolding while eliminating noise. The work focused on enabling rapid demos, reproducible pipelines, and maintainable data-science workflows.
28 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for Chameleon-company/MOP-Code: Delivered initial UC00201_Tourist_Hotspot_Vs_Hospitality_Capacity content, reorganized repository for publish readiness, and established assets and scaffolding while eliminating noise. The work focused on enabling rapid demos, reproducible pipelines, and maintainable data-science workflows.
September 2025
August 2025
4 Commits • 2 Features
Aug 1, 20252025-08 Monthly Summary for Chameleon-company/MOP-Code: Implemented two feature workstreams delivering measurable business value and laid groundwork for scalable content scaffolding. Data-driven Melbourne analysis provides a notebook-based workflow to map tourist demand against hospitality capacity within 200m, supporting urban planning and visitor experience optimization. Introduced a placeholder lifecycle for Playground/Manya to streamline content scaffolding, including creation and cleanup steps to improve development velocity and consistency. No major bugs fixed this month; ongoing maintenance and data quality improvements were addressed via commits.
August 2025
4 Commits • 2 Features
Aug 1, 20252025-08 Monthly Summary for Chameleon-company/MOP-Code: Implemented two feature workstreams delivering measurable business value and laid groundwork for scalable content scaffolding. Data-driven Melbourne analysis provides a notebook-based workflow to map tourist demand against hospitality capacity within 200m, supporting urban planning and visitor experience optimization. Introduced a placeholder lifecycle for Playground/Manya to streamline content scaffolding, including creation and cleanup steps to improve development velocity and consistency. No major bugs fixed this month; ongoing maintenance and data quality improvements were addressed via commits.
Activity
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Quality Metrics
Correctness97.6%
Maintainability97.0%
Architecture97.0%
Performance93.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSSHTMLJSONJavaScriptJupyter NotebookPythonSQLText
Technical Skills
API IntegrationCode CleanupData AnalysisData CleaningData ScienceData VisualizationFeature EngineeringFile ManagementFoliumFront-end DevelopmentGeospatial AnalysisGeospatial MappingJupyter NotebookJupyter NotebooksMapping
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