ITACADEMYprojectes/ProjecteData
May 2025 – May 2025
1 Month active
Languages Used
CSVJupyter NotebookMarkdownPythonSQL
Technical Skills
Chi-squared testCredit Risk AnalysisData AnalysisData CleaningData EngineeringData Management
FEC1
PROFILE
Fec1
Fabio Esparza enhanced analytics capabilities in the ITACADEMYprojectes/ProjecteData repository by developing robust data pipelines and scalable risk analysis tools. He focused on data cleaning, transformation, and visualization, integrating decile calculations and threshold-based risk signaling to support financial modeling and decision-making. Using Python, Pandas, and Scikit-learn, Fabio implemented logistic regression and decision tree models, along with ROC and Lift curve evaluations, to improve model assessment. His work included standardizing dashboard visuals, synchronizing data infrastructure, and refining documentation, resulting in a more reliable analytics foundation that streamlines data-driven insights and supports ongoing model development and evaluation workflows.
Overall Statistics
Feature vs Bugs
79%Features
Repository Contributions
53Total
Bugs
5
Commits
53
Features
19
Lines of code
254,330
Activity Months1
Your Network
36 people
Work History
May 2025
53 Commits • 19 Features
May 1, 2025May 2025: Delivered a focused uplift of analytics capabilities in ITACADEMYprojectes/ProjecteData, with a strong emphasis on data cleanliness, robust analytics, and engaging visualizations. Achieved major feature work, fixed critical data/test issues, and reinforced the foundation for scalable insights and decision support. Key outcomes include enhanced decile analysis, richer risk visualizations, standardized color palette across dashboards, and a solid data infrastructure to support ongoing analytics and model evaluations. These improvements reduce churn, improve confidence in risk signals, and enable faster iteration on data-driven decisions.
53 Commits • 19 Features
May 1, 2025May 2025: Delivered a focused uplift of analytics capabilities in ITACADEMYprojectes/ProjecteData, with a strong emphasis on data cleanliness, robust analytics, and engaging visualizations. Achieved major feature work, fixed critical data/test issues, and reinforced the foundation for scalable insights and decision support. Key outcomes include enhanced decile analysis, richer risk visualizations, standardized color palette across dashboards, and a solid data infrastructure to support ongoing analytics and model evaluations. These improvements reduce churn, improve confidence in risk signals, and enable faster iteration on data-driven decisions.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness83.8%
Maintainability83.4%
Architecture79.2%
Performance79.6%
AI Usage24.2%
Skills & Technologies
Programming Languages
CSVJupyter NotebookMarkdownPythonSQL
Technical Skills
Chi-squared testCredit Risk AnalysisData AnalysisData CleaningData EngineeringData ManagementData ManipulationData PreparationData SplittingData TransformationData VisualizationDecision TreesDocumentationExploratory Data AnalysisFinancial Analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline