Dr-Eberle-Zentrum/Data-projects-with-R-and-GitHub
Mar 2026 – Mar 2026
1 Month active
Languages Used
HTMLMarkdownPlain TextRTexttext
Technical Skills
RR programmingTestingdata analysisdata cleaningdata documentation
Jakob Felix Raatschen
PROFILE
Jakob Felix Raatschen
Jakob Raatschen established a robust foundation for the Dr-Eberle-Zentrum/Data-projects-with-R-and-GitHub repository by creating three reproducible study setups and implementing automated test scaffolding. Using R and R programming, he focused on data cleaning, documentation management, and repository maintenance to streamline onboarding and ensure auditability. Jakob removed obsolete project artifacts and legacy content, reducing maintenance overhead and confusion. He enhanced project documentation and README files to clarify data cleaning steps and dataset access, supporting better governance. His work delivered a well-structured, maintainable environment for ongoing data science experiments, demonstrating depth in statistical analysis, experimental design, and collaborative project management.
Overall Statistics
Feature vs Bugs
86%Features
Repository Contributions
26Total
Bugs
1
Commits
26
Features
6
Lines of code
2,646
Activity Months1
Your Network
78 peopleSame Organization
@student.uni-tuebingen.de18
Shared Repositories
60
Work History
March 2026
26 Commits • 6 Features
Mar 1, 2026March 2026 performance highlights for the Dr-Eberle-Zentrum/Data-projects-with-R-and-GitHub repo: established baseline repository and study orchestration, added reproducible study setup, and cleaned up legacy content to reduce risk and maintenance burden. Key features delivered include creating Studies 1–3, introducing test scaffolding, and uploading project assets to initialize the repository. Documentation updates and README improvements were completed to reflect current state, data cleaning notes, and dataset links, improving onboarding and governance. Major maintenance and bug work focused on removing obsolete JakobRaatschen project content and unused artifacts to streamline the repo and reduce confusion. Overall, these efforts deliver a reliable, auditable foundation for ongoing data science experiments with higher quality documentation and faster onboarding.
26 Commits • 6 Features
Mar 1, 2026March 2026 performance highlights for the Dr-Eberle-Zentrum/Data-projects-with-R-and-GitHub repo: established baseline repository and study orchestration, added reproducible study setup, and cleaned up legacy content to reduce risk and maintenance burden. Key features delivered include creating Studies 1–3, introducing test scaffolding, and uploading project assets to initialize the repository. Documentation updates and README improvements were completed to reflect current state, data cleaning notes, and dataset links, improving onboarding and governance. Major maintenance and bug work focused on removing obsolete JakobRaatschen project content and unused artifacts to streamline the repo and reduce confusion. Overall, these efforts deliver a reliable, auditable foundation for ongoing data science experiments with higher quality documentation and faster onboarding.
March 2026
Activity
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Quality Metrics
Correctness98.4%
Maintainability97.6%
Architecture97.6%
Performance97.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLMarkdownPlain TextRTexttext
Technical Skills
RR programmingTestingdata analysisdata cleaningdata documentationdata visualizationdocumentationdocumentation managementexperimental designmemory researchproject documentationproject managementrepository maintenancerepository management
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline