pcamarillor/O2025_ESI3914O
Sep 2025 – Sep 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisJupyter NotebooksObject-Oriented ProgrammingPythonPython ProgrammingSoftware Development
perrionsky
PROFILE
Perrionsky
During September 2025, Jair Camarillo developed two core features for the pcamarillor/O2025_ESI3914O repository, focusing on practical data analysis and financial simulation. He created the Playlist Analyzer Lab01 notebooks in Jupyter, providing Python-based examples for calculating unique songs per user, removing duplicates, and identifying the most popular track, thereby streamlining onboarding and reproducibility. Additionally, he designed a robust BankAccount class using object-oriented programming principles, enabling deposits, withdrawals, and balance checks with comprehensive error handling for invalid operations. Jair’s work emphasized clarity, reliability, and hands-on experimentation, demonstrating proficiency in Python, Jupyter Notebooks, and software development fundamentals.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
506
Activity Months1
Your Network
15 people
Work History
September 2025
2 Commits • 2 Features
Sep 1, 2025September 2025 monthly summary for pcamarillor/O2025_ESI3914O. Key features delivered include the Playlist Analyzer Lab01 notebooks and a new BankAccount class for financial transactions. The Playlist Analyzer Lab01 notebooks introduce example code for calculating unique songs per user, removing duplicates from a playlist, and determining the most popular song, with the placeholder notebook removed to streamline learning. The BankAccount class provides deposits, withdrawals, and balance inquiries with robust error handling for invalid operations and insufficient funds, demonstrated in a Jupyter notebook. Major improvements focus on reliability and clarity of experiments, with endpoint-like examples ready for onboarding and reproducible analysis. Technologies and skills demonstrated include Python class design, exception handling, and notebook-based demonstrations of basic data-analysis patterns. Overall impact includes faster hands-on experimentation for analytics and more reliable financial operation simulations, contributing to business value through improved onboarding, reproducibility, and code quality.
2 Commits • 2 Features
Sep 1, 2025September 2025 monthly summary for pcamarillor/O2025_ESI3914O. Key features delivered include the Playlist Analyzer Lab01 notebooks and a new BankAccount class for financial transactions. The Playlist Analyzer Lab01 notebooks introduce example code for calculating unique songs per user, removing duplicates from a playlist, and determining the most popular song, with the placeholder notebook removed to streamline learning. The BankAccount class provides deposits, withdrawals, and balance inquiries with robust error handling for invalid operations and insufficient funds, demonstrated in a Jupyter notebook. Major improvements focus on reliability and clarity of experiments, with endpoint-like examples ready for onboarding and reproducible analysis. Technologies and skills demonstrated include Python class design, exception handling, and notebook-based demonstrations of basic data-analysis patterns. Overall impact includes faster hands-on experimentation for analytics and more reliable financial operation simulations, contributing to business value through improved onboarding, reproducibility, and code quality.
September 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AnalysisJupyter NotebooksObject-Oriented ProgrammingPythonPython ProgrammingSoftware Development
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