ONSdigital/construction-survey-results
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
PythonPython programmingdata analysisdata manipulationdata processing
KateyMatthews1
PROFILE
Kateymatthews1
Katey Matthews contributed to the ONSdigital/monthly-business-survey-results repository by engineering features that improved data quality, reporting accuracy, and analytical reliability. She enhanced the turnover analysis pipeline by cleaning unused columns and aligning test data, reducing processing errors and supporting more robust analytics. In subsequent months, Katey developed a weighted growth rates calculation, applying data weighting and aggregation techniques in Python and Pandas to improve metric comparability. She also delivered devolved nations reporting enhancements, refactoring percentage calculations and extending outputs with time-series support. Her work demonstrated careful data engineering, schema management, and a focus on maintainability, directly addressing business and governance needs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
22
Activity Months1
Your Network
51 peopleWork History
December 2025
2 Commits • 1 Features
Dec 1, 2025December 2025: Delivered a QA Output 290_flag Enhancement and Aggregation feature in ONSdigital/construction-survey-results, introducing a 290_flag to filter QA outputs and aggregating results to differentiate total-only records. This improved data integrity and reporting accuracy by reducing misclassification and clarifying reporting baselines for QA analytics. Work is tracked across two commits and focuses on robust data modeling and reliable analytics.
2 Commits • 1 Features
Dec 1, 2025December 2025: Delivered a QA Output 290_flag Enhancement and Aggregation feature in ONSdigital/construction-survey-results, introducing a 290_flag to filter QA outputs and aggregating results to differentiate total-only records. This improved data integrity and reporting accuracy by reducing misclassification and clarifying reporting baselines for QA analytics. Work is tracked across two commits and focuses on robust data modeling and reliable analytics.
December 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
PythonPython programmingdata analysisdata manipulationdata processing
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