dataforgoodfr/13_potentiel_solaire
Mar 2025 – Apr 2025
2 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisGeoPandasGeospatial AnalysisPandasPythonAPI Development
THIBAULT_ROMAO
PROFILE
Thibault_romao
Thibault Romao contributed to the dataforgoodfr/13_potentiel_solaire repository by enhancing the accuracy and reliability of solar potential assessments using Python, GeoPandas, and Pandas. He refactored the building-to-school association logic to better handle spatial overlaps and educational zones, introducing a new dataclass to standardize item relationships for future mapping features. Thibault also improved the robustness of solar potential calculations by iterating through building locations to ensure valid PVGIS API responses, and strengthened error handling for API calls, including server errors. His work resulted in more reliable data pipelines, supporting informed planning and resource allocation for solar deployment projects.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
1,687
Activity Months2
Your Network
18 peopleWork History
April 2025
3 Commits • 1 Features
Apr 1, 2025April 2025: Delivered robust solar potential workflow and strengthened API resilience for dataforgoodfr/13_potentiel_solaire. The work enhanced data reliability for solar potential estimates and improved stability of downstream calculations.
3 Commits • 1 Features
Apr 1, 2025April 2025: Delivered robust solar potential workflow and strengthened API resilience for dataforgoodfr/13_potentiel_solaire. The work enhanced data reliability for solar potential estimates and improved stability of downstream calculations.
April 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Focused on enhancing Building-to-School association using spatial data enhancements. Implemented refactors to the attachment pipeline to handle overlaps and educational zones, and introduced a new dataclass for items of interest to support future mapping. These changes improve data quality for solar potential assessments and planning, enabling more accurate targeting and resource allocation.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Focused on enhancing Building-to-School association using spatial data enhancements. Implemented refactors to the attachment pipeline to handle overlaps and educational zones, and introduced a new dataclass for items of interest to support future mapping. These changes improve data quality for solar potential assessments and planning, enabling more accurate targeting and resource allocation.
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture80.0%
Performance70.0%
AI Usage25.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
API DevelopmentAPI IntegrationAPI integrationData AnalysisError HandlingGeoPandasGeospatial AnalysisPandasPythondata analysiserror handlinggeospatial analysis
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