QLAB-Courses/summer_python_econ
Jan 2025 – Jan 2025
1 Month active
Languages Used
JSONJupyter NotebookMarkdownPython
Technical Skills
Array ManipulationArraysBasic Programming ConceptsBasic Python ProgrammingContainersData Analysis
Joaquín Ramirez
PROFILE
Joaquín Ramirez
Worked on the QLAB-Courses/summer_python_econ repository to deliver end-to-end lifecycle management for Jupyter Notebook-based assignments, focusing on batch creation, updating, and deletion of group and individual assignment notebooks. Leveraged Python and NumPy for data structure manipulation and implemented robust file management practices to streamline notebook provisioning and cleanup of legacy artifacts. Addressed commit hygiene by reverting unintended changes and removing placeholder commits, which improved maintainability and reproducibility. The work reduced manual overhead for future coursework, centralized status tracking, and enabled scalable reuse of educational content, demonstrating a solid grasp of array operations, dictionary manipulation, and Jupyter Notebook configuration.
Overall Statistics
Feature vs Bugs
43%Features
Repository Contributions
23Total
Bugs
4
Commits
23
Features
3
Lines of code
16,678
Activity Months1
Your Network
65 peopleWork History
January 2025
23 Commits • 3 Features
Jan 1, 2025January 2025 performance: QLAB-Courses/summer_python_econ delivered end-to-end notebook lifecycle features for Group1 Assignment and Assignment_1 notebooks, implemented batch create/update/delete operations, cleaned up legacy artifacts, and reinforced commit hygiene through reverts of unintended changes and removal of placeholder commits. These efforts improved notebook reuse, batch provisioning, and overall maintainability, reducing stale artifacts and enabling scalable coursework for future cohorts.
23 Commits • 3 Features
Jan 1, 2025January 2025 performance: QLAB-Courses/summer_python_econ delivered end-to-end notebook lifecycle features for Group1 Assignment and Assignment_1 notebooks, implemented batch create/update/delete operations, cleaned up legacy artifacts, and reinforced commit hygiene through reverts of unintended changes and removal of placeholder commits. These efforts improved notebook reuse, batch provisioning, and overall maintainability, reducing stale artifacts and enabling scalable coursework for future cohorts.
January 2025
Activity
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Quality Metrics
Correctness91.4%
Maintainability91.4%
Architecture91.4%
Performance91.4%
AI Usage20.8%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
Array ManipulationArraysBasic Programming ConceptsBasic Python ProgrammingContainersData AnalysisData StructuresData TypesDictionariesDictionary ManipulationDictionary OperationsEducational Content CreationFile ManagementJupyter NotebookJupyter Notebook Configuration
Repositories Contributed To
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