dsi-clinic/CMAP
Feb 2025 – Feb 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Configuration ManagementData ExplorationGeospatial Data HandlingJupyter NotebooksPython
Anna Poon
PROFILE
Anna Poon
Anna Poon developed a River Data Exploration Notebook for the dsi-clinic/CMAP repository, focusing on integrating Kane County data with existing river datasets. She used Python and Jupyter Notebooks to create a workflow that enables unified data visualization and analysis, streamlining geospatial data exploration. Her work included configuration management to ensure seamless data integration and reproducibility, with all changes tracked through Git for traceability. While no bugs were addressed during this period, Anna’s contribution established a reusable foundation for scalable river analytics and future dashboard development, demonstrating depth in data exploration, geospatial data handling, and collaborative workflow design within the project.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
4,333
Activity Months1
Your Network
23 people
Work History
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 — CMAP (dsi-clinic/CMAP): River Data Exploration Notebook with Kane County Data Integration. Delivered a new Jupyter Notebook for exploring river data with visualization and analysis capabilities, including configuration changes to enable Kane County (KC) data integration with river data for a unified exploration workflow. No major bugs fixed this month; backlog items remain for enhancements. Overall impact: accelerates data-driven river analytics, improves data interoperability between Kane County and river datasets, and establishes a foundation for future dashboards and advanced analytics. Technologies/skills demonstrated: Python data analysis, Jupyter Notebook workflow, data visualization, data integration configuration, and Git-based traceability.
1 Commits • 1 Features
Feb 1, 2025February 2025 — CMAP (dsi-clinic/CMAP): River Data Exploration Notebook with Kane County Data Integration. Delivered a new Jupyter Notebook for exploring river data with visualization and analysis capabilities, including configuration changes to enable Kane County (KC) data integration with river data for a unified exploration workflow. No major bugs fixed this month; backlog items remain for enhancements. Overall impact: accelerates data-driven river analytics, improves data interoperability between Kane County and river datasets, and establishes a foundation for future dashboards and advanced analytics. Technologies/skills demonstrated: Python data analysis, Jupyter Notebook workflow, data visualization, data integration configuration, and Git-based traceability.
February 2025
Activity
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Quality Metrics
Correctness60.0%
Maintainability60.0%
Architecture60.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Configuration ManagementData ExplorationGeospatial Data HandlingJupyter NotebooksPython
Repositories Contributed To
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