dhis2-chap/chap-core
Oct 2025 – Oct 2025
1 Month active
Languages Used
Python
Technical Skills
API integrationJSON handlingPandasPythondata analysisdata processing
Andre gregussen
PROFILE
Andre Gregussen
Worked on the dhis2-chap/chap-core repository to deliver two core features focused on dengue forecasting. Developed a data integration and evaluation pipeline that loads dengue data, transforms JSON into Pandas DataFrames, and aligns datasets with forecasting models. Introduced new forecast accuracy metrics and visualization capabilities to support analysis across time and location. Additionally, restructured the codebase by removing legacy files and streamlining data processing modules, resulting in a more focused and scalable project structure. Leveraged Python, Pandas, and data visualization techniques to establish a clearer data-to-model pipeline, enabling faster iteration and supporting improved decision-making for dengue forecasting workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
417,629
Activity Months1
Your Network
29 peopleShared Repositories
29
Abyot Asalefew GizawMember
Andreas JensenMember
AndreGreguMember
audunMember
Boris SimovskiMember
BumpVersion ActionMember
kanduricMember
Eirik HaugstulenMember
geirksaMember
Work History
October 2025
3 Commits • 2 Features
Oct 1, 2025Concise monthly summary for 2025-10 focusing on key features delivered, major fixes, impact, and skills demonstrated. Highlights include the Dengue Forecast Data Integration and Evaluation feature and Codebase Restructuring for Dengue Forecasting, with new forecast metrics and a streamlined project structure that supports scalable forecasting and visualization.
3 Commits • 2 Features
Oct 1, 2025Concise monthly summary for 2025-10 focusing on key features delivered, major fixes, impact, and skills demonstrated. Highlights include the Dengue Forecast Data Integration and Evaluation feature and Codebase Restructuring for Dengue Forecasting, with new forecast metrics and a streamlined project structure that supports scalable forecasting and visualization.
October 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API integrationJSON handlingPandasPythondata analysisdata processingdata visualizationforecastingmetric developmentpandas
Repositories Contributed To
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