arvindkrishna87/STAT390_LegalAid_Fall2025
Sep 2025 – Dec 2025
4 Months active
Languages Used
PythonSQLMarkdownN/APDFPower BI
Technical Skills
Data AnalysisData CleaningData WranglingDocumentationJupyter NotebookMatplotlib
BingoMuse
PROFILE
Bingomuse
Simiao worked on the arvindkrishna87/STAT390_LegalAid_Fall2025 repository, building a suite of data analytics tools to support legal aid call center operations. Over four months, Simiao developed Jupyter Notebooks and dashboards for analyzing call volume trends, inbound/outbound classifications, and time-based patterns, using Python, pandas, and Power BI. The work included robust data cleaning, multi-file ingestion, timezone conversion, and aggregation by Correlation ID, enabling reproducible and scalable analytics. Simiao also produced detailed PDF reports and maintained comprehensive documentation, improving onboarding and audit readiness. The engineering approach emphasized maintainability, clear stakeholder communication, and efficient data-driven decision-making for legal aid teams.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
23Total
Bugs
0
Commits
23
Features
6
Lines of code
12,891
Activity Months4
Your Network
94 peopleWork History
December 2025
3 Commits • 2 Features
Dec 1, 2025December 2025 achievements focused on delivering data-driven capabilities to support legal aid operations. Key deliverables: (1) Call Volume Analysis Notebook with data cleaning, transformation, and visualization to enable rapid inbound call analytics; (2) PDF report with detailed insights, including the DrillDownCallVolume_AllCallsData_Dec8_Muse.pdf, to support decision-making by legal aid teams; (3) Documentation updates reflecting changes and improvements for maintainability and onboarding. Impact: reduced manual analysis time, clearer stakeholder reporting, and a foundation for future analytics iterations. Technologies/skills demonstrated: Python data analysis (pandas, matplotlib/seaborn), Jupyter notebooks, PDF report generation, data cleaning and transformation, Git-based collaboration, and documentation practices.
3 Commits • 2 Features
Dec 1, 2025December 2025 achievements focused on delivering data-driven capabilities to support legal aid operations. Key deliverables: (1) Call Volume Analysis Notebook with data cleaning, transformation, and visualization to enable rapid inbound call analytics; (2) PDF report with detailed insights, including the DrillDownCallVolume_AllCallsData_Dec8_Muse.pdf, to support decision-making by legal aid teams; (3) Documentation updates reflecting changes and improvements for maintainability and onboarding. Impact: reduced manual analysis time, clearer stakeholder reporting, and a foundation for future analytics iterations. Technologies/skills demonstrated: Python data analysis (pandas, matplotlib/seaborn), Jupyter notebooks, PDF report generation, data cleaning and transformation, Git-based collaboration, and documentation practices.
December 2025
November 2025
9 Commits • 1 Features
Nov 1, 2025November 2025 — Delivered the Call Data Analytics Suite for arvindkrishna87/STAT390_LegalAid_Fall2025, consolidating notebooks, dashboards, presentations, and documentation to analyze inbound call trends, call volume, and time-based patterns, enabling data-driven insights and improved visibility into call-center operations. No major bugs reported; minor polish included refreshed visuals, standardized dashboard naming, and direct links for easier access. Completed code and artifact delivery with comprehensive documentation to support reproducibility and stakeholder communication. Technologies demonstrated: data analytics, dashboards, Python notebooks, documentation, and Git-based version control.
November 2025
9 Commits • 1 Features
Nov 1, 2025November 2025 — Delivered the Call Data Analytics Suite for arvindkrishna87/STAT390_LegalAid_Fall2025, consolidating notebooks, dashboards, presentations, and documentation to analyze inbound call trends, call volume, and time-based patterns, enabling data-driven insights and improved visibility into call-center operations. No major bugs reported; minor polish included refreshed visuals, standardized dashboard naming, and direct links for easier access. Completed code and artifact delivery with comprehensive documentation to support reproducibility and stakeholder communication. Technologies demonstrated: data analytics, dashboards, Python notebooks, documentation, and Git-based version control.
October 2025
8 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for arvindkrishna87/STAT390_LegalAid_Fall2025. Focused on delivering feature work and improving project documentation to enhance data-driven decision making and developer productivity. Key features delivered include two Jupyter Notebooks for call data trends (processing, cleaning, and analysis) with multi-file CSV/Excel ingestion, timezone conversion, and Correlation ID-based aggregation. Documentation updates were also completed, including new PDFs and metadata adjustments (macOS DS_Store) to ensure consistency and onboarding reliability. No major bug fixes were reported this month; the emphasis was on robust data workflows and comprehensive documentation. Technologies demonstrated include Python, Jupyter, pandas, timezone handling, CSV/Excel I/O, and documentation tooling to support scalable analytics and maintainable codebase.
8 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for arvindkrishna87/STAT390_LegalAid_Fall2025. Focused on delivering feature work and improving project documentation to enhance data-driven decision making and developer productivity. Key features delivered include two Jupyter Notebooks for call data trends (processing, cleaning, and analysis) with multi-file CSV/Excel ingestion, timezone conversion, and Correlation ID-based aggregation. Documentation updates were also completed, including new PDFs and metadata adjustments (macOS DS_Store) to ensure consistency and onboarding reliability. No major bug fixes were reported this month; the emphasis was on robust data workflows and comprehensive documentation. Technologies demonstrated include Python, Jupyter, pandas, timezone handling, CSV/Excel I/O, and documentation tooling to support scalable analytics and maintainable codebase.
October 2025
September 2025
3 Commits • 1 Features
Sep 1, 2025Month: 2025-09 — Focus: Documentation updates and repository maintenance for arvindkrishna87/STAT390_LegalAid_Fall2025. This month delivered essential documentation improvements, repository hygiene, and metadata updates to support onboarding, compliance, and future development. Commits were made to push to remote main, ensuring the latest docs are available to stakeholders.
September 2025
3 Commits • 1 Features
Sep 1, 2025Month: 2025-09 — Focus: Documentation updates and repository maintenance for arvindkrishna87/STAT390_LegalAid_Fall2025. This month delivered essential documentation improvements, repository hygiene, and metadata updates to support onboarding, compliance, and future development. Commits were made to push to remote main, ensuring the latest docs are available to stakeholders.
Activity
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Quality Metrics
Correctness94.0%
Maintainability94.0%
Architecture94.0%
Performance92.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownN/APDFPower BIPythonSQL
Technical Skills
Data AnalysisData CleaningData WranglingDocumentationJupyter NotebookMatplotlibN/APandasSeaborndashboard designdashboard developmentdata analysisdata visualizationdocumentationpresentation design
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