open-energy-transition/pypsa-earth
Apr 2025 – May 2025
2 Months active
Languages Used
CSVPythonRSTSnakefile
Technical Skills
API IntegrationData CleaningData EngineeringData ManagementData PreprocessingDocumentation
ljansen
PROFILE
Ljansen
Contributed to the open-energy-transition/pypsa-earth repository by engineering enhancements to transport and urban data pipelines over a two-month period. Focused on expanding and stabilizing transport emissions datasets, the work included integrating Wikipedia vehicle registration data, implementing ISO2 country code mapping, and refactoring Python scripts for maintainability. Addressed data quality by replacing deprecated API endpoints, filling missing values, and standardizing country identifiers. Improved urban population data aggregation and streamlined input validation for hydrogen export constraints using Pandas and Snakefile. These efforts resulted in more reliable analytics, cleaner data processing, and improved documentation, supporting reproducible workflows and broader coverage for transportation and population analysis.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
11Total
Bugs
1
Commits
11
Features
4
Lines of code
259
Activity Months2
Your Network
27 peopleWork History
May 2025
5 Commits • 2 Features
May 1, 2025May 2025: Delivered two major feature initiatives in pypsa-earth focused on data quality and input handling. Improved urban_percent aggregation to a single mean per country/year, removed unnecessary columns, and updated release notes. Enhanced h2export input handling to allow decimal numbers in wildcard constraints, with validation updates in the Snakefile and corresponding release notes. These changes increase data reliability for population layout generation and provide greater pipeline flexibility. Documentation and release notes were updated to reflect the fixes and enhancements. Overall impact: cleaner data pipelines, improved data integrity, and clearer traceability for downstream analytics.
5 Commits • 2 Features
May 1, 2025May 2025: Delivered two major feature initiatives in pypsa-earth focused on data quality and input handling. Improved urban_percent aggregation to a single mean per country/year, removed unnecessary columns, and updated release notes. Enhanced h2export input handling to allow decimal numbers in wildcard constraints, with validation updates in the Snakefile and corresponding release notes. These changes increase data reliability for population layout generation and provide greater pipeline flexibility. Documentation and release notes were updated to reflect the fixes and enhancements. Overall impact: cleaner data pipelines, improved data integrity, and clearer traceability for downstream analytics.
May 2025
April 2025
6 Commits • 2 Features
Apr 1, 2025April 2025 — pypsa-earth transport data improvements, pipeline stabilization, and dataset expansion delivering clearer emissions insights and more reliable analytics. Summary highlights three core outcomes: (1) Transport data input enrichment by incorporating Wikipedia vehicle-registration data, adding an ISO2 conversion function, and refactoring prepare_transport_data_input.py for maintainability; (2) Data pipeline reliability and quality improvements, including replacing a discontinued World Bank API endpoint with a web-archive URL, filling missing fuel-efficiency data with averages, and aligning country identification to ISO2 codes; (3) Transport data dataset expansion by adding new country entries (codes, cars, and fuel efficiency) to transport_data.csv to broaden coverage for transportation analysis. These changes reduce data gaps, improve accuracy of transport emissions calculations, and improve reproducibility and maintenance. Technologies demonstrated: Python data engineering, ETL design, data quality automation, and ISO2 country mapping." ,
April 2025
6 Commits • 2 Features
Apr 1, 2025April 2025 — pypsa-earth transport data improvements, pipeline stabilization, and dataset expansion delivering clearer emissions insights and more reliable analytics. Summary highlights three core outcomes: (1) Transport data input enrichment by incorporating Wikipedia vehicle-registration data, adding an ISO2 conversion function, and refactoring prepare_transport_data_input.py for maintainability; (2) Data pipeline reliability and quality improvements, including replacing a discontinued World Bank API endpoint with a web-archive URL, filling missing fuel-efficiency data with averages, and aligning country identification to ISO2 codes; (3) Transport data dataset expansion by adding new country entries (codes, cars, and fuel efficiency) to transport_data.csv to broaden coverage for transportation analysis. These changes reduce data gaps, improve accuracy of transport emissions calculations, and improve reproducibility and maintenance. Technologies demonstrated: Python data engineering, ETL design, data quality automation, and ISO2 country mapping." ,
Activity
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Quality Metrics
Correctness89.0%
Maintainability92.8%
Architecture85.4%
Performance87.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVPythonRSTSnakefile
Technical Skills
API IntegrationConfiguration ManagementData CleaningData EngineeringData ManagementData PreprocessingData ProcessingDocumentationPandasPythonScriptingWeb Scraping
Repositories Contributed To
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