Chameleon-company/MOP-Code
Dec 2024 – Jan 2025
2 Months active
Languages Used
CSSHTMLJSONJavaScriptPython
Technical Skills
ARIMACSS StylingData AnalysisData VisualizationFront-end DevelopmentMachine Learning
Glo333
PROFILE
Glo333
Gloria Kiplagat developed data visualization and forecasting features for Melbourne’s real estate market within the Chameleon-company/MOP-Code repository. She implemented heatmaps and stacked area charts using Python, Pandas, and Seaborn to analyze development density and composition over time, supporting data-driven decision making for urban planners. Gloria also established a time-series forecasting framework leveraging ARIMA, XGBoost, and Prophet, with ARIMA yielding the strongest results for residential dwellings. Her work included targeted codebase improvements, such as resolving naming conflicts and restructuring directories, which enhanced maintainability and publication readiness. The project advanced reproducibility and enabled scalable analytics for external review.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
81,250
Activity Months2
Your Network
98 people
Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for Chameleon-company/MOP-Code focused on finalizing the Publication-ready Real Estate Market Dynamics Use Case, including directory restructuring and dataset reference updates to meet publication standards. The work advances publication readiness and reproducibility for external review and dissemination.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for Chameleon-company/MOP-Code focused on finalizing the Publication-ready Real Estate Market Dynamics Use Case, including directory restructuring and dataset reference updates to meet publication standards. The work advances publication readiness and reproducibility for external review and dissemination.
January 2025
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 performance summary for Chameleon-company/MOP-Code: Delivered data visualization and forecasting capabilities for Melbourne's real estate market, with focused business value outcomes for developers and planners. Key features include heatmap and stacked area charts to analyze development density and composition over time, and a time-series forecasting framework incorporating XGBoost, ARIMA, and Prophet models (ARIMA showing strongest performance for residential dwellings). The work included targeted code adjustments to resolve naming conflicts and improve maintainability, contributing to faster iteration and more reliable analytics.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 performance summary for Chameleon-company/MOP-Code: Delivered data visualization and forecasting capabilities for Melbourne's real estate market, with focused business value outcomes for developers and planners. Key features include heatmap and stacked area charts to analyze development density and composition over time, and a time-series forecasting framework incorporating XGBoost, ARIMA, and Prophet models (ARIMA showing strongest performance for residential dwellings). The work included targeted code adjustments to resolve naming conflicts and improve maintainability, contributing to faster iteration and more reliable analytics.
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance80.0%
AI Usage33.4%
Skills & Technologies
Programming Languages
CSSHTMLJSONJavaScriptPython
Technical Skills
ARIMACSS StylingData AnalysisData PreparationData ScienceData VisualizationFront-end DevelopmentMachine LearningMatplotlibPandasProphetScikit-learnSeabornTime Series ForecastingWeb Development
Repositories Contributed To
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