Chameleon-company/MOP-Code
Nov 2024 – May 2025
2 Months active
Languages Used
Jupyter NotebookPythonCSSHTMLJavaScriptMarkdownSQL
Technical Skills
Data CleaningData LoadingData PreprocessingPandasPythonAPI Integration
s223739584
PROFILE
S223739584
Soham worked on the Chameleon-company/MOP-Code repository, developing a data-driven urban heat vulnerability mapping feature for Melbourne. He built an end-to-end pipeline using Python and Pandas, integrating data loading, cleaning, and preprocessing for microclimate sensor and tree canopy datasets. Soham applied clustering and geospatial analysis with GeoPandas to identify risk zones, then visualized results interactively using Folium and Matplotlib. His work included refactoring data cleaning functions for maintainability and establishing documentation scaffolds to support reproducibility. Over two months, Soham delivered three features that established a robust foundation for urban environmental analysis, demonstrating depth in data engineering and spatial analytics.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
3
Lines of code
11,520
Activity Months2
Your Network
186 people
Work History
May 2025
6 Commits • 2 Features
May 1, 2025May 2025 performance summary for Chameleon-company/MOP-Code focused on delivering a data-driven urban heat vulnerability feature for Melbourne, establishing foundational documentation, and preparing for scale. Key outcomes include an end-to-end vulnerability analysis pipeline, interactive visualizations, and improved reproducibility through notebooks and docs.
6 Commits • 2 Features
May 1, 2025May 2025 performance summary for Chameleon-company/MOP-Code focused on delivering a data-driven urban heat vulnerability feature for Melbourne, establishing foundational documentation, and preparing for scale. Key outcomes include an end-to-end vulnerability analysis pipeline, interactive visualizations, and improved reproducibility through notebooks and docs.
May 2025
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11: Delivered foundational data ingestion and cleaning work in the Chameleon-company/MOP-Code repository. Implemented a robust data loading and cleaning pipeline for microclimate sensors and tree canopy datasets, including handling of missing values, dropping duplicates, and standardizing column names. Refactored data cleaning functions used in proto3.ipynb to remove redundant comments and improve readability and maintainability. These changes establish a reliable data baseline for analytics and modeling, improve cross-dataset consistency, and reduce downstream data preparation time.
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11: Delivered foundational data ingestion and cleaning work in the Chameleon-company/MOP-Code repository. Implemented a robust data loading and cleaning pipeline for microclimate sensors and tree canopy datasets, including handling of missing values, dropping duplicates, and standardizing column names. Refactored data cleaning functions used in proto3.ipynb to remove redundant comments and improve readability and maintainability. These changes establish a reliable data baseline for analytics and modeling, improve cross-dataset consistency, and reduce downstream data preparation time.
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture75.0%
Performance75.0%
AI Usage25.0%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptJupyter NotebookMarkdownPythonSQL
Technical Skills
API IntegrationClusteringData AnalysisData CleaningData LoadingData PreprocessingData VisualizationEnvironmental ScienceFoliumGeoPandasGeospatial AnalysisJupyter NotebooksMachine LearningMatplotlibPandas
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