alexanderquispe/Diplomado_PUCP
Aug 2025 – Sep 2025
2 Months active
Languages Used
MarkdownPythonCSVJupyter Notebook
Technical Skills
Data AnalysisDocumentationJupyter NotebooksPandasPythonBasic Functions
anarciso90
PROFILE
Anarciso90
Contributed to the Diplomado_PUCP repository by developing and refining seven features over two months, focusing on educational materials and data analysis workflows. Built and updated Jupyter notebooks to demonstrate Python fundamentals, including conditional logic, loops, and control flow, while enhancing assignments with practical data manipulation using Pandas. Improved course documentation and organization, ensuring clarity and reproducibility for students and contributors. Integrated new datasets, such as presidential election results in CSV format, and managed package environments for consistent execution. Addressed repository hygiene by removing obsolete files, supporting maintainability. The work emphasized Python programming, data cleaning, and statistical analysis in an instructional context.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
17Total
Bugs
1
Commits
17
Features
7
Lines of code
1,774
Activity Months2
Your Network
43 peopleWork History
September 2025
11 Commits • 5 Features
Sep 1, 2025September 2025 (2025-09) Monthly Summary for alexanderquispe/Diplomado_PUCP: Delivered practical learning modules and data-analysis enhancements to improve student outcomes and reproducibility. Key features include new and refined notebooks for Python conditionals and loops, a data merging and statistics module with inner-join examples and grouping by ESTRATO, and a new Presidential Election Results dataset with environment setup updates to ensure reproducibility. Added Assignment 3 resources (text document) to support group 11. Fixed repository cleanliness by removing macOS .DS_Store files and obsolete materials to reduce noise and maintenance overhead. Overall, these contributions improved hands-on learning experiences, established consistent execution environments, and reduced onboarding time for new contributors. Technologies demonstrated include Python, Jupyter notebooks, data loading, inner joins, grouping, and environment management (kernel specs, package installation).
11 Commits • 5 Features
Sep 1, 2025September 2025 (2025-09) Monthly Summary for alexanderquispe/Diplomado_PUCP: Delivered practical learning modules and data-analysis enhancements to improve student outcomes and reproducibility. Key features include new and refined notebooks for Python conditionals and loops, a data merging and statistics module with inner-join examples and grouping by ESTRATO, and a new Presidential Election Results dataset with environment setup updates to ensure reproducibility. Added Assignment 3 resources (text document) to support group 11. Fixed repository cleanliness by removing macOS .DS_Store files and obsolete materials to reduce noise and maintenance overhead. Overall, these contributions improved hands-on learning experiences, established consistent execution environments, and reduced onboarding time for new contributors. Technologies demonstrated include Python, Jupyter notebooks, data loading, inner joins, grouping, and environment management (kernel specs, package installation).
September 2025
August 2025
6 Commits • 2 Features
Aug 1, 2025In August 2025, two primary deliverables in Diplomado_PUCP advanced course quality and analytics capabilities: (1) Course materials and documentation updates, including creation and renaming of notes and notebooks, plus refinements to Lecture materials to improve organization and clarity; (2) Pandas Series data analysis enhancement with practical demonstrations of data manipulation (grades, statistics, and uppercase transformations) embedded in the assignments.
August 2025
6 Commits • 2 Features
Aug 1, 2025In August 2025, two primary deliverables in Diplomado_PUCP advanced course quality and analytics capabilities: (1) Course materials and documentation updates, including creation and renaming of notes and notebooks, plus refinements to Lecture materials to improve organization and clarity; (2) Pandas Series data analysis enhancement with practical demonstrations of data manipulation (grades, statistics, and uppercase transformations) embedded in the assignments.
Activity
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Quality Metrics
Correctness91.6%
Maintainability91.6%
Architecture88.2%
Performance87.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVJupyter NotebookMarkdownPython
Technical Skills
Basic FunctionsConditional StatementsControl FlowData AnalysisData CleaningData ManipulationData MergingDocumentationJupyter Notebook UsageJupyter NotebooksPackage ManagementPandasPythonPython ProgrammingStatistical Analysis
Repositories Contributed To
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