fpsim/fpsim
May 2025 – Oct 2025
3 Months active
Languages Used
PythonStataCSVMarkdownRRSTYAMLrst
Technical Skills
DHS DataData AnalysisData ProcessingMatplotlibNumPyPandas
lrkbruce
PROFILE
Lrkbruce
Over a three-month period, contributed to the fpsim/fpsim repository by developing and refining automated data processing pipelines for demographic modeling. Built Python and R scripts to ingest, clean, and calibrate DHS, PMA, UN, and World Bank datasets across multiple countries and regions, enabling reproducible calculation of demographic indicators. Addressed data integrity and calibration issues, such as type mismatches and naming inconsistencies, to ensure simulation accuracy and reliable reporting. Enhanced documentation and configuration management, supporting broader geographic coverage and streamlined workflows. Leveraged skills in data engineering, statistical data management, and simulation modeling to deliver robust, maintainable solutions for public health analysis.
Overall Statistics
Feature vs Bugs
64%Features
Repository Contributions
38Total
Bugs
8
Commits
38
Features
14
Lines of code
77,082
Activity Months3
Work History
October 2025
1 Commits
Oct 1, 2025Concise monthly summary for fpsim/fpsim focusing on calibration data integrity and delivery quality. October 2025 delivered a critical calibration data type update for Côte d'Ivoire to ensure consistent parameter handling across data and scripts, reinforcing model fidelity and decision support reliability.
1 Commits
Oct 1, 2025Concise monthly summary for fpsim/fpsim focusing on calibration data integrity and delivery quality. October 2025 delivered a critical calibration data type update for Côte d'Ivoire to ensure consistent parameter handling across data and scripts, reinforcing model fidelity and decision support reliability.
October 2025
September 2025
36 Commits • 13 Features
Sep 1, 2025September 2025 monthly summary for fpsim/fpsim: Expanded data ingestion coverage, enhanced data processing pipelines, and improved data quality and documentation across multiple locations and countries, delivering measurable business value for modeling accuracy, risk assessment, and decision support.
September 2025
36 Commits • 13 Features
Sep 1, 2025September 2025 monthly summary for fpsim/fpsim: Expanded data ingestion coverage, enhanced data processing pipelines, and improved data quality and documentation across multiple locations and countries, delivering measurable business value for modeling accuracy, risk assessment, and decision support.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for fpsim/fpsim: Delivered automated DHS data processing scripts for debut_age and mcpr_by_parity, enabling reproducible demographic indicator calculations across specific countries/regions. The feature set includes parsing raw .dta files, computing debut_age probabilities and mcpr_by_parity metrics, and exporting location-specific CSV outputs (e.g., pakistan sindh; nigeria kano & kaduna; niger; cote d'voir). The workflow also supports data filtering, weight calculations, and optional plotting to support downstream analyses and reporting. Impact includes faster, more accurate reporting and reduced manual data wrangling, with ready-to-use datasets and plots for dashboards/reports. Technologies demonstrated: Python data processing, .dta parsing, CSV I/O, data filtering/weighting, plotting scaffolding. Commit reference: 7067702cb18983af2e2f42b4561aecb1df063681.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for fpsim/fpsim: Delivered automated DHS data processing scripts for debut_age and mcpr_by_parity, enabling reproducible demographic indicator calculations across specific countries/regions. The feature set includes parsing raw .dta files, computing debut_age probabilities and mcpr_by_parity metrics, and exporting location-specific CSV outputs (e.g., pakistan sindh; nigeria kano & kaduna; niger; cote d'voir). The workflow also supports data filtering, weight calculations, and optional plotting to support downstream analyses and reporting. Impact includes faster, more accurate reporting and reduced manual data wrangling, with ready-to-use datasets and plots for dashboards/reports. Technologies demonstrated: Python data processing, .dta parsing, CSV I/O, data filtering/weighting, plotting scaffolding. Commit reference: 7067702cb18983af2e2f42b4561aecb1df063681.
May 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.8%
Architecture88.2%
Performance83.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVMarkdownPythonRRSTStataYAMLrst
Technical Skills
API IntegrationBug FixingCode MaintenanceConfiguration ManagementDHS DataData AnalysisData CalibrationData CleaningData ConfigurationData CorrectionData DocumentationData EngineeringData FilteringData IntegrationData Loading
Repositories Contributed To
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