iramler/slu_score_module_development
Apr 2025 – May 2025
2 Months active
Languages Used
CSVMarkdownRHTML
Technical Skills
Data AnalysisData CleaningData EngineeringData LoadingData PreprocessingData Visualization
jlars88
PROFILE
Jlars88
During a two-month period, John Larsen developed and enhanced data analysis modules for the iramler/slu_score_module_development repository, focusing on powerlifting performance trends. He built end-to-end features including the Powerlifting Score Open Module and the Age vs Strength Analysis Module, applying R and Quarto for data cleaning, quantile regression modeling, and visualization. His work stabilized the data pipeline, introduced gender-specific insights, and improved the clarity of analytics through refined R Markdown and HTML deliverables. By integrating statistical modeling and robust documentation, John enabled repeatable, business-focused insights for coaches and analysts, demonstrating technical depth in data engineering and presentation within the project.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
3
Lines of code
112,327
Activity Months2
Your Network
23 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for the developer role focusing on the iramler/slu_score_module_development project. Delivered the Age vs. Strength Analysis work stream, introducing an HTML page for age-related strength analysis and refining the R Markdown to improve the presentation of powerlifting data analysis. This work included data cleaning, visualization, and modeling of age-related strength performance trends, with a completion commit noted as 2d18cc983a39d59a95b1ffc1042ac1960090e2a8 (Final).
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for the developer role focusing on the iramler/slu_score_module_development project. Delivered the Age vs. Strength Analysis work stream, introducing an HTML page for age-related strength analysis and refining the R Markdown to improve the presentation of powerlifting data analysis. This work included data cleaning, visualization, and modeling of age-related strength performance trends, with a completion commit noted as 2d18cc983a39d59a95b1ffc1042ac1960090e2a8 (Final).
May 2025
April 2025
11 Commits • 2 Features
Apr 1, 2025April 2025 monthly performance for iramler/slu_score_module_development focused on delivering two end-to-end features, improving data processing and visualization capabilities, and stabilizing the data pipeline for repeatable insights.
April 2025
11 Commits • 2 Features
Apr 1, 2025April 2025 monthly performance for iramler/slu_score_module_development focused on delivering two end-to-end features, improving data processing and visualization capabilities, and stabilizing the data pipeline for repeatable insights.
Activity
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Quality Metrics
Correctness86.6%
Maintainability85.8%
Architecture84.2%
Performance80.0%
AI Usage23.2%
Skills & Technologies
Programming Languages
CSVHTMLMarkdownR
Technical Skills
Data AnalysisData CleaningData EngineeringData LoadingData PreprocessingData VisualizationDocumentationQuantile RegressionQuartoRR ProgrammingStatistical Modeling
Repositories Contributed To
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