pcamarillor/O2025_ESI3914B
Aug 2025 – Oct 2025
3 Months active
Languages Used
Jupyter NotebookPythonJSONSQL
Technical Skills
Data AnalysisJupyter NotebookJupyter NotebooksPython ProgrammingBig DataBig Data Processing
Carolina Arellano
PROFILE
Carolina Arellano
Over a three-month period, contributed to the pcamarillor/O2025_ESI3914B repository by building data analytics and engineering solutions using Python, PySpark, and Jupyter Notebooks. Developed reusable notebooks for playlist analysis, financial utilities, and airline data transformation, focusing on data de-duplication, schema generation, and feature engineering. Implemented a BankAccount utility with robust validation and error handling, and created Spark SQL and Power BI workflows for end-to-end analytics. Delivered a Neo4j data ingestion pipeline for the Vienna subway network, validating data integrity through graph queries. Emphasized maintainability and onboarding by providing thorough documentation, testing, and clear, reproducible notebook artifacts.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
14Total
Bugs
0
Commits
14
Features
6
Lines of code
2,204
Activity Months3
Your Network
40 peopleShared Repositories
27
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for developer work on repository pcamarillor/O2025_ESI3914B. Delivered a new data ingestion notebook and established end-to-end validation for a Neo4j graph pipeline using Vienna subway network data.
1 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for developer work on repository pcamarillor/O2025_ESI3914B. Delivered a new data ingestion notebook and established end-to-end validation for a Neo4j graph pipeline using Vienna subway network data.
October 2025
September 2025
11 Commits • 4 Features
Sep 1, 2025September 2025 performance: Delivered critical features across financial utilities and data engineering, with strong emphasis on reliability, onboarding, and stakeholder value. Key outcomes include a robust BankAccount utility with validation and error handling, reusable Spark schema tooling and Spark SQL notebooks, end-to-end PySpark data cleaning/transformation workflows for airline data, and integrated rental analytics with data unions/joins plus a Power BI dashboard. All work was paired with proper testing and refactoring to improve maintainability and quality.
September 2025
11 Commits • 4 Features
Sep 1, 2025September 2025 performance: Delivered critical features across financial utilities and data engineering, with strong emphasis on reliability, onboarding, and stakeholder value. Key outcomes include a robust BankAccount utility with validation and error handling, reusable Spark schema tooling and Spark SQL notebooks, end-to-end PySpark data cleaning/transformation workflows for airline data, and integrated rental analytics with data unions/joins plus a Power BI dashboard. All work was paired with proper testing and refactoring to improve maintainability and quality.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary: Delivered Lab 01 Playlist Analysis Notebook for repo pcamarillor/O2025_ESI3914B. Implemented data processing features to de-duplicate listening records, compute per-user unique song counts, and identify the most popular song using Python collections. Added clarifying comments and minor improvements to enhance readability and maintainability. No major bugs fixed this month; focus remained on delivering a reusable analytics notebook and a clear, reviewable artifact.
2 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary: Delivered Lab 01 Playlist Analysis Notebook for repo pcamarillor/O2025_ESI3914B. Implemented data processing features to de-duplicate listening records, compute per-user unique song counts, and identify the most popular song using Python collections. Added clarifying comments and minor improvements to enhance readability and maintainability. No major bugs fixed this month; focus remained on delivering a reusable analytics notebook and a clear, reviewable artifact.
August 2025
Activity
Loading activity data...
Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture81.4%
Performance72.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPythonSQL
Technical Skills
Big DataBig Data ProcessingData AnalysisData EngineeringData IngestionData TransformationData VisualizationGraph DatabasesJSON ProcessingJupyter NotebookJupyter NotebooksNeo4jNotebook ManagementObject-Oriented ProgrammingPySpark
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline