arvindkrishna87/STAT390_LegalAid_Fall2025
Sep 2025 – Dec 2025
4 Months active
Languages Used
PythonPDF
Technical Skills
Data AnalysisData CleaningDocumentationJupyter NotebookMatplotlibPandas
hyunnie01
PROFILE
Hyunnie01
Contributed to the arvindkrishna87/STAT390_LegalAid_Fall2025 repository by developing analytics tooling and comprehensive documentation to support legal aid call center analysis. Delivered a suite of Jupyter Notebooks and presentation PDFs that analyzed main menu redundancies, call flow metrics, and success rates, enabling data-driven insights for stakeholders. Applied Python, Pandas, and Seaborn to clean, model, and visualize call data, while maintaining robust version control and clear documentation standards. Focused on improving onboarding and discoverability through standardized naming conventions and consolidated findings, the work emphasized reproducibility, stakeholder communication, and efficient access to actionable insights without introducing or fixing code-level defects.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
18Total
Bugs
0
Commits
18
Features
7
Lines of code
3,726
Activity Months4
Your Network
134 peopleSame Organization
@u.northwestern.edu112
Work History
December 2025
6 Commits • 2 Features
Dec 1, 2025Month: 2025-12 — Focused on delivering documentation improvements and analytics tooling for redundancy analysis in the STAT390_LegalAid_Fall2025 project. Key features delivered include: 1) Project Documentation Improvements and Redundancy Analysis Findings with consolidated PDFs summarizing findings and recommendations; 2) Redundancy Analysis Tooling and Notebook featuring a Jupyter notebook for redundancy analysis on legal aid call data and a refactored session splitting logic to categorize sessions by outcomes. No critical defects were reported or fixed this month. Overall impact: improved documentation accuracy, faster access to redundancy insights, and enhanced data analytics capabilities, enabling data-driven decisions and more efficient stakeholder onboarding. Technologies and skills demonstrated: Git-based version control, comprehensive documentation practices, Python/Jupyter data analysis, notebook-based tooling, and data modeling.
6 Commits • 2 Features
Dec 1, 2025Month: 2025-12 — Focused on delivering documentation improvements and analytics tooling for redundancy analysis in the STAT390_LegalAid_Fall2025 project. Key features delivered include: 1) Project Documentation Improvements and Redundancy Analysis Findings with consolidated PDFs summarizing findings and recommendations; 2) Redundancy Analysis Tooling and Notebook featuring a Jupyter notebook for redundancy analysis on legal aid call data and a refactored session splitting logic to categorize sessions by outcomes. No critical defects were reported or fixed this month. Overall impact: improved documentation accuracy, faster access to redundancy insights, and enhanced data analytics capabilities, enabling data-driven decisions and more efficient stakeholder onboarding. Technologies and skills demonstrated: Git-based version control, comprehensive documentation practices, Python/Jupyter data analysis, notebook-based tooling, and data modeling.
December 2025
November 2025
5 Commits • 2 Features
Nov 1, 2025Nov 2025 monthly work summary focusing on key accomplishments and business value in arvindkrishna87/STAT390_LegalAid_Fall2025. Delivered the Menu Analysis Analytics Suite consisting of two notebooks analyzing main menu success rates and call flow metrics, plus a leadership-facing presentation PDF. Completed documentation updates to improve project clarity and stakeholder guidance. No major bugs fixed this month; effort centered on feature delivery and documentation. Technologies demonstrated include Python/Jupyter notebooks, data analysis, visualization, and formal documentation management.
November 2025
5 Commits • 2 Features
Nov 1, 2025Nov 2025 monthly work summary focusing on key accomplishments and business value in arvindkrishna87/STAT390_LegalAid_Fall2025. Delivered the Menu Analysis Analytics Suite consisting of two notebooks analyzing main menu success rates and call flow metrics, plus a leadership-facing presentation PDF. Completed documentation updates to improve project clarity and stakeholder guidance. No major bugs fixed this month; effort centered on feature delivery and documentation. Technologies demonstrated include Python/Jupyter notebooks, data analysis, visualization, and formal documentation management.
October 2025
5 Commits • 2 Features
Oct 1, 2025October 2025 focused on delivering data-driven UI analysis tooling and keeping project documentation current for arvindkrishna87/STAT390_LegalAid_Fall2025. Delivered a Menu Redundancy Analysis artifact (slide and notebook) to enable evaluation of main menu redundancies and navigation patterns; updated project PDFs and documentation to reflect the latest scope. No code changes beyond artifact additions.
5 Commits • 2 Features
Oct 1, 2025October 2025 focused on delivering data-driven UI analysis tooling and keeping project documentation current for arvindkrishna87/STAT390_LegalAid_Fall2025. Delivered a Menu Redundancy Analysis artifact (slide and notebook) to enable evaluation of main menu redundancies and navigation patterns; updated project PDFs and documentation to reflect the latest scope. No code changes beyond artifact additions.
October 2025
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for arvindkrishna87/STAT390_LegalAid_Fall2025. Focused on documenting asset hygiene and naming conventions within the Documentation directory to improve discoverability and onboarding. Implemented a clear naming cleanup for documentation artifacts and added a binary document to support project artifacts. No feature deliveries beyond documentation changes in this period.
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for arvindkrishna87/STAT390_LegalAid_Fall2025. Focused on documenting asset hygiene and naming conventions within the Documentation directory to improve discoverability and onboarding. Implemented a clear naming cleanup for documentation artifacts and added a binary document to support project artifacts. No feature deliveries beyond documentation changes in this period.
Activity
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Quality Metrics
Correctness94.4%
Maintainability94.4%
Architecture94.4%
Performance93.4%
AI Usage22.2%
Skills & Technologies
Programming Languages
PDFPython
Technical Skills
Data AnalysisData CleaningDocumentationJupyter NotebookMatplotlibPandasPythonSeaborndata analysisdata visualizationdocumentationpresentation design
Repositories Contributed To
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