clessn/datagotchi_federal_2024
Nov 2024 – Apr 2025
4 Months active
Languages Used
RLaTeXQuarto
Technical Skills
Data CleaningData TransformationR ProgrammingData AnalysisData VisualizationReport Generation
elsalabonte
PROFILE
Elsalabonte
Elsa Labonté developed robust data engineering and analytics features for the clessn/datagotchi_federal_2024 repository, focusing on standardizing and transforming lifestyle activity and transportation datasets to support downstream modeling. She implemented R-based pipelines for data cleaning, variable reclassification, and feature engineering, ensuring alignment with evolving federal data requirements. Elsa delivered end-to-end workflows for voter turnout analysis and prediction, utilizing statistical modeling and visualization in R and Quarto to produce reproducible, publish-ready reports. Her work demonstrated depth in data transformation, statistical analysis, and report generation, resulting in reliable, well-documented pipelines that improved data quality and analytics readiness without introducing bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
5
Lines of code
1,275
Activity Months4
Your Network
11 peopleShared Repositories
11
Work History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 performance summary for clessn/datagotchi_federal_2024 focusing on feature delivery, impact, and technical proficiency.
1 Commits • 1 Features
Apr 1, 2025April 2025 performance summary for clessn/datagotchi_federal_2024 focusing on feature delivery, impact, and technical proficiency.
April 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025: Key feature delivered in clessn/datagotchi_federal_2024 – Voter Turnout Analysis and Visualization, an end-to-end R-based workflow for loading data, selecting features, computing group differences, and visualizing discriminative patterns, paired with a Quarto report scaffold that uses custom fonts and a dedicated title page. No major bugs reported. This work delivers reproducible turnout insights and a publish-ready analysis artifact, strengthening data-informed decision making for federal datasets. Technologies demonstrated include R, Quarto, data visualization, and Git-driven reproducible research.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025: Key feature delivered in clessn/datagotchi_federal_2024 – Voter Turnout Analysis and Visualization, an end-to-end R-based workflow for loading data, selecting features, computing group differences, and visualizing discriminative patterns, paired with a Quarto report scaffold that uses custom fonts and a dedicated title page. No major bugs reported. This work delivers reproducible turnout insights and a publish-ready analysis artifact, strengthening data-informed decision making for federal datasets. Technologies demonstrated include R, Quarto, data visualization, and Git-driven reproducible research.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 — Data quality and pipeline reliability improvements in clessn/datagotchi_federal_2024. Delivered the Data Cleaning Standardization and Dataset Alignment feature for Lifestyle Exercise & Transportation, including: standardizing lifestyle_exercise labels, updating the dataset loading path to the latest data file, and reclassifying transportation types into general categories (car, active_transport, shared_transport) with updated choice_transport mappings. Implemented via two commits (0bcdf0fecc967dcb206a323080352d9aa4f34c84; dbb4424cd5ee1dde62eb088b912ae1eb9f6e6fa8), enabling more reliable downstream analytics and cleaner feature engineering.
2 Commits • 1 Features
Dec 1, 2024December 2024 — Data quality and pipeline reliability improvements in clessn/datagotchi_federal_2024. Delivered the Data Cleaning Standardization and Dataset Alignment feature for Lifestyle Exercise & Transportation, including: standardizing lifestyle_exercise labels, updating the dataset loading path to the latest data file, and reclassifying transportation types into general categories (car, active_transport, shared_transport) with updated choice_transport mappings. Implemented via two commits (0bcdf0fecc967dcb206a323080352d9aa4f34c84; dbb4424cd5ee1dde62eb088b912ae1eb9f6e6fa8), enabling more reliable downstream analytics and cleaner feature engineering.
December 2024
November 2024
4 Commits • 2 Features
Nov 1, 2024Month: 2024-11 — Data engineering and feature engineering efforts for clessn/datagotchi_federal_2024 focused on standardizing lifestyle activity and transportation datasets to enable downstream analytics and model readiness. No explicit bugs documented this month; main work delivered robust pre-cleaning pipelines and data representations that align with federal project requirements.
November 2024
4 Commits • 2 Features
Nov 1, 2024Month: 2024-11 — Data engineering and feature engineering efforts for clessn/datagotchi_federal_2024 focused on standardizing lifestyle activity and transportation datasets to enable downstream analytics and model readiness. No explicit bugs documented this month; main work delivered robust pre-cleaning pipelines and data representations that align with federal project requirements.
Activity
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Quality Metrics
Correctness82.6%
Maintainability80.0%
Architecture72.6%
Performance82.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
LaTeXQuartoR
Technical Skills
Data AnalysisData CleaningData TransformationData VisualizationR ProgrammingReport GenerationStatistical AnalysisStatistical ModelingSurvey Analysis
Repositories Contributed To
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