iramler/slu_score_module_development
Feb 2025 – Apr 2025
3 Months active
Languages Used
QuartoRMarkdown
Technical Skills
DocumentationCode OrganizationData CleaningData VisualizationR ProgrammingRefactoring
amsiko21
PROFILE
Amsiko21
Developed and enhanced interactive data applications in the iramler/slu_score_module_development repository, focusing on NCAA women’s basketball statistics. Built Shiny apps that enabled users to load, clean, and visualize player data, implementing robust data wrangling and refactoring practices to ensure reliability and maintainability. Established a repeatable content scaffold using Quarto and Markdown, streamlining documentation and future content creation. Improved project structure through repository reorganization and removal of obsolete files, reducing technical debt. Leveraged R, R Markdown, and R Shiny to deliver features supporting internal demos and stakeholder communications, demonstrating strengths in data analysis, code organization, and collaborative development workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
10Total
Bugs
0
Commits
10
Features
4
Lines of code
6,016
Activity Months3
Your Network
22 peopleShared Repositories
22
phoebecharMember
AlixfritzMember
Brendan KaradenesMember
cwgartMember
Cooper OlneyMember
deeriMember
emiliaagostinelliMember
ferhin23Member
iramlerMember
Work History
April 2025
5 Commits • 2 Features
Apr 1, 2025April 2025: Delivered core NCAA Women's Basketball Stats Shiny App and enhanced basketball module assets. Implemented data loading and cleaning pipeline, refactored data extraction and Visualization for reliability, and removed a draft file to align project direction. Added and updated presentation assets for the basketball module to support internal demos and stakeholder communications. These efforts improved data-driven decision support, reduced technical debt, and positioned the product for upcoming reviews.
5 Commits • 2 Features
Apr 1, 2025April 2025: Delivered core NCAA Women's Basketball Stats Shiny App and enhanced basketball module assets. Implemented data loading and cleaning pipeline, refactored data extraction and Visualization for reliability, and removed a draft file to align project direction. Added and updated presentation assets for the basketball module to support internal demos and stakeholder communications. These efforts improved data-driven decision support, reduced technical debt, and positioned the product for upcoming reviews.
April 2025
March 2025
4 Commits • 1 Features
Mar 1, 2025Concise monthly summary for 2025-03 focusing on key accomplishments, major bug fixes (if any), impact, and technical skills demonstrated. Highlights the primary feature delivered in the iramler/slu_score_module_development repo and its business value.
March 2025
4 Commits • 1 Features
Mar 1, 2025Concise monthly summary for 2025-03 focusing on key accomplishments, major bug fixes (if any), impact, and technical skills demonstrated. Highlights the primary feature delivered in the iramler/slu_score_module_development repo and its business value.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025: Delivered the foundational content scaffold for the slu_score_module_development project by initializing a placeholder Quarto document (test.qmd) in the asikora directory and setting up metadata to streamline future content creation, reviews, and QA. This work establishes a repeatable pattern for content generation and enables early validation of content structure within the repository.
1 Commits • 1 Features
Feb 1, 2025February 2025: Delivered the foundational content scaffold for the slu_score_module_development project by initializing a placeholder Quarto document (test.qmd) in the asikora directory and setting up metadata to streamline future content creation, reviews, and QA. This work establishes a repeatable pattern for content generation and enables early validation of content structure within the repository.
February 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance78.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownQuartoR
Technical Skills
Code OrganizationData AnalysisData CleaningData VisualizationData WranglingDocumentationRR MarkdownR ProgrammingR ShinyRefactoringShinyShiny App DevelopmentWeb DevelopmentWeb Scraping
Repositories Contributed To
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