dataforgoodfr/13_reveler_inegalites_cinema
Feb 2025 – Feb 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
API IntegrationData EngineeringDatabase DesignDatabase ManagementDependency ManagementPandas
LudivineLacour
PROFILE
Ludivinelacour
Contributed core data platform enhancements to the dataforgoodfr/13_reveler_inegalites_cinema repository, focusing on improving film analytics capabilities. Developed a TMDB API-based ingestion script in Python and SQL to automate film data population, incorporating change detection, origin-country filtering, and deduplication using pandas for efficient processing. Enhanced the database schema by introducing genre categorization through new genres and film_genres tables, enabling more flexible querying and analysis. Updated dependency management with Poetry to ensure compatibility and support for pandas-driven workflows. These efforts improved data quality, streamlined reporting, and provided a foundation for richer business insights without introducing new bugs during the period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
3
Lines of code
1,345
Activity Months1
Your Network
12 peopleShared Repositories
12
Audrey DuranMember
FitzfoufouMember
Florian_YunMember
hadrien PoinseauxMember
ndretexMember
Julien-CommesMember
Nicolas RevelMember
Paul GabrielMember
lina kaciMember
Work History
February 2025
3 Commits • 3 Features
Feb 1, 2025February 2025 highlights: Delivered core data platform enhancements for cinema analytics in dataforgoodfr/13_reveler_inegalites_cinema. Key features delivered include (1) dependency management updates via Poetry to ensure compatibility and enable pandas data processing, (2) a film data model enhancement introducing genres and a film_genres linking table for robust categorization and genre-based querying, and (3) a TMDB-based data ingestion script to populate the films table with change detection, origin-country filtering, pandas-driven processing, and deduplication against existing records. No major bugs reported this month. These changes improve data quality, analytical flexibility, and automation, enabling faster reporting and richer business insights.
3 Commits • 3 Features
Feb 1, 2025February 2025 highlights: Delivered core data platform enhancements for cinema analytics in dataforgoodfr/13_reveler_inegalites_cinema. Key features delivered include (1) dependency management updates via Poetry to ensure compatibility and enable pandas data processing, (2) a film data model enhancement introducing genres and a film_genres linking table for robust categorization and genre-based querying, and (3) a TMDB-based data ingestion script to populate the films table with change detection, origin-country filtering, pandas-driven processing, and deduplication against existing records. No major bugs reported this month. These changes improve data quality, analytical flexibility, and automation, enabling faster reporting and richer business insights.
February 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
API IntegrationData EngineeringDatabase DesignDatabase ManagementDependency ManagementPandasPython PackagingSQLSQLAlchemy
Repositories Contributed To
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