ITACADEMYprojectes/ProjecteData
Mar 2025 – Apr 2025
2 Months active
Languages Used
CSVJSONJupyter NotebookPythonSQL
Technical Skills
Data AnalysisData CleaningData EngineeringData ImputationData ManagementData Visualization
ErrePad
PROFILE
Errepad
Over two months, Rodrigo Padilla Araneda developed and enhanced data engineering and analytics workflows for the ITACADEMYprojectes/ProjecteData repository. He built a robust data export pipeline using Python and SQLAlchemy, enabling reliable transfer of cleaned datasets into MySQL with integrity checks and environment-based configuration. Rodrigo improved data quality through imputation and cleaning, leveraging Pandas and machine learning techniques to support analytics-ready data. He also advanced a marketing analytics suite in Jupyter Notebook, implementing pricing analysis, correlation matrices, and regression modeling. His work focused on scalable, reproducible data provisioning and analytics, enabling actionable business insights across cities and neighborhoods.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
15Total
Bugs
0
Commits
15
Features
5
Lines of code
25,990
Activity Months2
Your Network
36 people
Work History
April 2025
9 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for ITACADEMYprojectes/ProjecteData: End-to-end data engineering and analytics enhancements that improve data reliability and enable data-driven pricing decisions across markets. Implemented a robust Data Export Pipeline to MySQL with cleaning and integrity checks, performed data quality improvements on the cleaned dataset, and advanced the Marketing Analytics Suite for pricing, correlations, and optimization across cities and neighborhoods. These efforts reduce data load errors, ensure analytics-ready data, and enable actionable business insights.
9 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for ITACADEMYprojectes/ProjecteData: End-to-end data engineering and analytics enhancements that improve data reliability and enable data-driven pricing decisions across markets. Implemented a robust Data Export Pipeline to MySQL with cleaning and integrity checks, performed data quality improvements on the cleaned dataset, and advanced the Marketing Analytics Suite for pricing, correlations, and optimization across cities and neighborhoods. These efforts reduce data load errors, ensure analytics-ready data, and enable actionable business insights.
April 2025
March 2025
6 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for ITACADEMYprojectes/ProjecteData focusing on data quality, analytics improvements, and scalable data provisioning to support business decisions.
March 2025
6 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for ITACADEMYprojectes/ProjecteData focusing on data quality, analytics improvements, and scalable data provisioning to support business decisions.
Activity
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Quality Metrics
Correctness80.6%
Maintainability80.0%
Architecture77.4%
Performance78.8%
AI Usage32.0%
Skills & Technologies
Programming Languages
CSVJSONJupyter NotebookPythonSQL
Technical Skills
Data AnalysisData CleaningData EngineeringData ExportData ImputationData ManagementData VisualizationDatabase InteractionDatabase ManagementEnvironment VariablesJupyter NotebookMachine LearningMatplotlibMySQLNumPy
Repositories Contributed To
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