electricitymaps/electricitymaps-contrib
May 2025 – May 2025
1 Month active
Languages Used
CSVPythonZIP
Technical Skills
API IntegrationData ParsingHistorical Data HandlingPandasPythonRequests
Christian Wassermann
PROFILE
Christian Wassermann
Christian Wassermann enhanced historical data retrieval for the US-NY-NYIS zone in the electricitymaps-contrib repository by enabling backfill of data beyond nine days through zip archive extraction. He extended the existing parser to seamlessly handle both recent and archived data sources, ensuring compatibility with production and consumption forecast workflows. Using Python, Pandas, and the Requests library, Christian modernized the data ingestion pipeline and updated the test suite to validate the new retrieval logic. This work addressed historical data gaps, improved reliability for analytics and forecasting, and demonstrated depth in data parsing, archive management, and robust test-driven development within a production environment.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
6,175
Activity Months1
Work History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025: Delivered historical data backfill for the US-NY-NYIS zone in electricitymaps-contrib. Extended data retrieval beyond 9 days by pulling from zip archives, enabling longer historical coverage and smoother backfill for older dates. Updated the parser to handle both recent and historical data sources and refreshed tests to cover the extended workflow. This enhancement reduces historical data gaps, improving reliability for dashboards and forecasting models. Demonstrated strong data ingestion, archive-based retrieval, and test modernization skills, aligning with data governance and analytics needs.
1 Commits • 1 Features
May 1, 2025May 2025: Delivered historical data backfill for the US-NY-NYIS zone in electricitymaps-contrib. Extended data retrieval beyond 9 days by pulling from zip archives, enabling longer historical coverage and smoother backfill for older dates. Updated the parser to handle both recent and historical data sources and refreshed tests to cover the extended workflow. This enhancement reduces historical data gaps, improving reliability for dashboards and forecasting models. Demonstrated strong data ingestion, archive-based retrieval, and test modernization skills, aligning with data governance and analytics needs.
May 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVPythonZIP
Technical Skills
API IntegrationData ParsingHistorical Data HandlingPandasPythonRequestsTestingZipfile
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