QLAB-Courses/summer_python_econ
Jan 2025 – Jan 2025
1 Month active
Languages Used
JSONJupyter NotebookMarkdownPython
Technical Skills
AlgorithmsArray ManipulationBasic ArithmeticClassesCode DocumentationControl Flow
mafer-vasquez
PROFILE
Mafer-vasquez
Contributed to the QLAB-Courses/summer_python_econ repository by developing core course content across three assignments, focusing on practical Python programming for data analysis. Leveraged Jupyter Notebooks to deliver interactive exercises covering Python fundamentals, NumPy for array manipulation, and Pandas for data loading and cleaning. Implemented object-oriented programming concepts through custom classes and functions, supporting a modular and maintainable codebase. Addressed environment configuration and repository hygiene to ensure cross-platform consistency and reduce setup time for learners. The work emphasized clear code documentation and structured data workflows, laying a foundation for future course expansion and streamlined onboarding in an educational setting.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
16Total
Bugs
0
Commits
16
Features
4
Lines of code
7,842
Activity Months1
Your Network
84 peopleWork History
January 2025
16 Commits • 4 Features
Jan 1, 2025Concise monthly summary for 2025-01: In QLAB-Courses/summer_python_econ, delivered core course content across three assignments, integrated essential data handling, and completed repository hygiene to stabilize cross-platform usage. Key outcomes include streamlined learner onboarding, faster progress through practical exercises, and a maintainable codebase ready for future course expansions. Technologies demonstrated include Python fundamentals, NumPy, Pandas, object-oriented programming, notebook-based pedagogy, and robust environment setup and version-control hygiene.
16 Commits • 4 Features
Jan 1, 2025Concise monthly summary for 2025-01: In QLAB-Courses/summer_python_econ, delivered core course content across three assignments, integrated essential data handling, and completed repository hygiene to stabilize cross-platform usage. Key outcomes include streamlined learner onboarding, faster progress through practical exercises, and a maintainable codebase ready for future course expansions. Technologies demonstrated include Python fundamentals, NumPy, Pandas, object-oriented programming, notebook-based pedagogy, and robust environment setup and version-control hygiene.
January 2025
Activity
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Quality Metrics
Correctness83.8%
Maintainability83.8%
Architecture81.2%
Performance80.0%
AI Usage21.2%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
AlgorithmsArray ManipulationBasic ArithmeticClassesCode DocumentationControl FlowData AnalysisData CleaningData LoadingData MergingData StructuresData TypesDictionariesEnvironment ConfigurationFunctions
Repositories Contributed To
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