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
Developed two core features for the pcamarillor/O2025_ESI3914O repository, focusing on data analysis and financial simulation within Jupyter Notebooks using Python. Delivered a Playlist Analyzer Lab01 notebook that enables users to calculate unique songs per user, remove duplicates, and identify the most popular song, streamlining onboarding by removing unnecessary placeholders. Introduced a BankAccount class that supports deposits, withdrawals, and balance inquiries, incorporating robust error handling for invalid operations and insufficient funds. Emphasized object-oriented programming principles and reproducible analysis patterns, resulting in more reliable experimentation and improved code clarity for analytics and financial transaction simulations in educational or onboarding contexts.
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 peopleShared Repositories
15
Arantxa AnguloMember
JosMember
Renata TejedaMember
EduNav04Member
thexavirooMember
Juan LópezMember
luci-efeMember
danielarellMember
Luis GonzalezMember
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
Repositories Contributed To
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