Chameleon-company/MOP-Code
Nov 2024 – May 2025
4 Months active
Languages Used
JSONJupyter NotebookPythonSQLMarkdownCSSHTMLJavaScript
Technical Skills
API IntegrationData CollectionData PreparationData ScienceExploratory Data AnalysisFile Management
Poojith Girish
PROFILE
Poojith Girish
Poojith Girish developed data-driven urban planning and sustainability analysis workflows in the Chameleon-company/MOP-Code repository over four months. He built reproducible Jupyter Notebook pipelines for analyzing Melbourne’s green spaces and sustainable mobility, integrating data from public APIs and geospatial datasets. Using Python, Pandas, and GeoPandas, he implemented data ingestion, preprocessing, visualization, and emissions quantification to support urban planning decisions. His work included establishing documentation scaffolding, maintaining repository hygiene, and removing obsolete files to ensure clarity and reproducibility. The depth of his contributions is reflected in end-to-end data pipelines and clear workflows that enable experimentation and stakeholder communication in urban analytics.
Overall Statistics
Feature vs Bugs
86%Features
Repository Contributions
37Total
Bugs
1
Commits
37
Features
6
Lines of code
126,462
Activity Months4
Your Network
98 people
Work History
May 2025
17 Commits • 2 Features
May 1, 2025Concise monthly summary for 2025-05 focused on delivering business value through notebook-based data science work and repository hygiene improvements for Chameleon-company/MOP-Code.
17 Commits • 2 Features
May 1, 2025Concise monthly summary for 2025-05 focused on delivering business value through notebook-based data science work and repository hygiene improvements for Chameleon-company/MOP-Code.
May 2025
April 2025
12 Commits • 1 Features
Apr 1, 2025April 2025: Delivered end-to-end mobility data capabilities in Chameleon-company/MOP-Code and improved repo hygiene, enabling data-driven planning and maintainability. Key outcomes: (1) End-to-end Sustainable Mobility Data Integration and Visualization for Melbourne with ingestion from City of Melbourne Open Data API, preprocessing, and time-based/spatial visualizations; groundwork established for estimating emissions avoided via active transport; aligns with Melbourne sustainability and urban-planning goals. (2) Repository hygiene improvements by removing placeholder files/notebooks and restoring production-focused structure to reduce confusion and maintenance overhead.
April 2025
12 Commits • 1 Features
Apr 1, 2025April 2025: Delivered end-to-end mobility data capabilities in Chameleon-company/MOP-Code and improved repo hygiene, enabling data-driven planning and maintainability. Key outcomes: (1) End-to-end Sustainable Mobility Data Integration and Visualization for Melbourne with ingestion from City of Melbourne Open Data API, preprocessing, and time-based/spatial visualizations; groundwork established for estimating emissions avoided via active transport; aligns with Melbourne sustainability and urban-planning goals. (2) Repository hygiene improvements by removing placeholder files/notebooks and restoring production-focused structure to reduce confusion and maintenance overhead.
December 2024
2 Commits • 1 Features
Dec 1, 2024Concise monthly summary for 2024-12 focusing on features delivered, bugs fixed (if any), impact, and technologies demonstrated for Chameleon-company/MOP-Code. Delivered foundational documentation and reproducible workflow for the Urban Green Space use case. No major bugs fixed this month.
2 Commits • 1 Features
Dec 1, 2024Concise monthly summary for 2024-12 focusing on features delivered, bugs fixed (if any), impact, and technologies demonstrated for Chameleon-company/MOP-Code. Delivered foundational documentation and reproducible workflow for the Urban Green Space use case. No major bugs fixed this month.
December 2024
November 2024
6 Commits • 2 Features
Nov 1, 2024November 2024: Delivered foundational notebook scaffolding for Accessibility to Green Spaces and initiated Melbourne Urban Green Spaces Data Analysis workflow in Chameleon-code repo. These efforts establish a reproducible data-science foundation, improve onboarding, and set the stage for data-driven urban planning insights. No critical bugs fixed this month; focus on feature delivery and repository hygiene.
November 2024
6 Commits • 2 Features
Nov 1, 2024November 2024: Delivered foundational notebook scaffolding for Accessibility to Green Spaces and initiated Melbourne Urban Green Spaces Data Analysis workflow in Chameleon-code repo. These efforts establish a reproducible data-science foundation, improve onboarding, and set the stage for data-driven urban planning insights. No critical bugs fixed this month; focus on feature delivery and repository hygiene.
Activity
Loading activity data...
Quality Metrics
Correctness91.4%
Maintainability90.8%
Architecture90.8%
Performance88.6%
AI Usage23.2%
Skills & Technologies
Programming Languages
CSSHTMLJSONJavaScriptJupyter NotebookMarkdownPythonSQL
Technical Skills
API IntegrationCode CleanupData AnalysisData CleaningData CollectionData PreparationData PreprocessingData ScienceData VisualizationDocumentationExploratory Data AnalysisFile ManagementFoliumGeoPandasGeospatial Analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline