QLAB-Courses/summer_python_econ
Jan 2025 – Jan 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Basic OperationsClassesControl FlowData AnalysisData CleaningData Loading
Sheylabz
PROFILE
Sheylabz
Developed three foundational Jupyter Notebooks for the QLAB-Courses/summer_python_econ repository, establishing a structured introduction to Python programming for educational use. The work focused on building core modules covering Python data types, basic operations, and conditional logic, followed by practical data loading, cleaning, and analysis using Pandas. Functional programming concepts and object-oriented design were introduced through assignments involving functions and custom classes. All features were delivered with attention to documentation and code organization, supporting scalable onboarding and future content expansion. The approach emphasized clarity and modularity, leveraging Python and NumPy to create a robust baseline for student assignments and instructor tooling.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
3
Lines of code
3,761
Activity Months1
Your Network
65 peopleWork History
January 2025
6 Commits • 3 Features
Jan 1, 2025In January 2025, the QLAB-Courses team delivered three foundational notebooks for the summer_python_econ track, establishing core Python fundamentals, practical data manipulation with Pandas, and the groundwork for functional programming and object-oriented concepts. No major defects were reported; work focused on feature delivery, documentation, and code organization to enable scalable onboarding and faster content iteration. These efforts create a solid baseline for student progress tracking and instructor tooling, and position the course for upcoming assignments and assessments.
6 Commits • 3 Features
Jan 1, 2025In January 2025, the QLAB-Courses team delivered three foundational notebooks for the summer_python_econ track, establishing core Python fundamentals, practical data manipulation with Pandas, and the groundwork for functional programming and object-oriented concepts. No major defects were reported; work focused on feature delivery, documentation, and code organization to enable scalable onboarding and faster content iteration. These efforts create a solid baseline for student progress tracking and instructor tooling, and position the course for upcoming assignments and assessments.
January 2025
Activity
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Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture76.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Basic OperationsClassesControl FlowData AnalysisData CleaningData LoadingData TypesFunctionsJupyter NotebookJupyter NotebooksNumPyObject-Oriented ProgrammingPandasPython Programming
Repositories Contributed To
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