Chameleon-company/MOP-Code
Nov 2024 – Dec 2024
2 Months active
Languages Used
HTMLPythonJavaScript
Technical Skills
Data AnalysisData VisualizationFoliumJupyter NotebookMatplotlibPandas
Taehwan Jung
PROFILE
Taehwan Jung
Te Hoan developed two public transport demand analysis use cases within the Chameleon-company/MOP-Code repository over a two-month period, focusing on data-driven transit planning for Melbourne. Leveraging Python, pandas, and folium, he implemented workflows for data ingestion, preprocessing, and geospatial visualization of pedestrian sensor data near train stations. His work included packaging HTML, JSON, and Jupyter Notebook assets to support exploratory analysis and scenario evaluation. By updating use-case documentation and delivering reusable analytics components, Te Hoan established a foundation for future analytics features. The work demonstrated depth in data analysis and visualization, though no major bug fixes were required during this period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
620,130
Activity Months2
Your Network
98 people
Work History
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024: Delivered a new Public Transport Demand Visualization Use Case within the MOP-Code repository, enabling data-driven transport planning through visualization and mapping of pedestrian sensor data near train stations. The use case ships HTML, JSON, and IPYNB assets to support quick exploratory analysis and scenario evaluation.
1 Commits • 1 Features
Dec 1, 2024December 2024: Delivered a new Public Transport Demand Visualization Use Case within the MOP-Code repository, enabling data-driven transport planning through visualization and mapping of pedestrian sensor data near train stations. The use case ships HTML, JSON, and IPYNB assets to support quick exploratory analysis and scenario evaluation.
December 2024
November 2024
1 Commits • 1 Features
Nov 1, 2024Concise monthly summary for 2024-11 focusing on key accomplishments, including the delivery of the Melbourne Public Transport Demand Analysis use case and initial data loading/visualization steps. No major bugs fixed this month. Provides foundation for data-driven transit planning and reusable analytics components.
November 2024
1 Commits • 1 Features
Nov 1, 2024Concise monthly summary for 2024-11 focusing on key accomplishments, including the delivery of the Melbourne Public Transport Demand Analysis use case and initial data loading/visualization steps. No major bugs fixed this month. Provides foundation for data-driven transit planning and reusable analytics components.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLJavaScriptPython
Technical Skills
Data AnalysisData VisualizationFoliumJupyter NotebookJupyter NotebooksMatplotlibPandas
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