nh-spipitone/DataAnalyst-course
Jun 2025 – Jul 2025
2 Months active
Languages Used
PythonSQL
Technical Skills
File ManagementAPI IntegrationData AnalysisData CleaningData PreprocessingData Visualization
Riccardo9813
PROFILE
Riccardo9813
Riccardo Ghisu contributed to the nh-spipitone/DataAnalyst-course repository by establishing foundational project scaffolding and delivering two end-to-end analytics features over two months. He set up a reproducible development environment to streamline onboarding and future enhancements, then built a travel cost prediction platform that integrated data cleaning, exploratory data analysis, SQL data extraction, and a machine learning model for cost forecasting, enhanced with OpenAI-powered generative insights. Additionally, Riccardo developed a Python-based car price regression analysis tool using scikit-learn, implementing preprocessing, model evaluation, and visualization. His work demonstrated depth in Python, SQL, data preprocessing, and cross-domain analytics engineering.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
1,039
Activity Months2
Your Network
12 people
Work History
July 2025
4 Commits • 2 Features
Jul 1, 2025July 2025 performance summary for nh-spipitone/DataAnalyst-course: Delivered end-to-end analytics features enabling data-driven travel cost management and car pricing insights. Key work included consolidating travel cost analysis into a platform with data cleaning, exploratory data analysis, SQL data extraction, a machine learning model to predict total travel costs, and OpenAI-powered generative insights with an interactive analysis loop. Also delivered a Python-based car price regression analysis tool with preprocessing, train-test split, model training, evaluation (RMSE/MAE/R2), and visualization of predictions with coefficients/intercept reporting. No major bugs were reported this month. This work accelerates decision-making, improves cost visibility, and demonstrates strong cross-domain data science, software engineering, and AI-assisted analytics capabilities.
4 Commits • 2 Features
Jul 1, 2025July 2025 performance summary for nh-spipitone/DataAnalyst-course: Delivered end-to-end analytics features enabling data-driven travel cost management and car pricing insights. Key work included consolidating travel cost analysis into a platform with data cleaning, exploratory data analysis, SQL data extraction, a machine learning model to predict total travel costs, and OpenAI-powered generative insights with an interactive analysis loop. Also delivered a Python-based car price regression analysis tool with preprocessing, train-test split, model training, evaluation (RMSE/MAE/R2), and visualization of predictions with coefficients/intercept reporting. No major bugs were reported this month. This work accelerates decision-making, improves cost visibility, and demonstrates strong cross-domain data science, software engineering, and AI-assisted analytics capabilities.
July 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for nh-spipitone/DataAnalyst-course focusing on delivering foundational scaffolding, enabling rapid future development, and ensuring a clean baseline for teammate contributions. The month was centered on project initialization and repository readiness, with no major bug fixes recorded. Highlights include introducing a placeholder Python file to bootstrap Riccardo Ghisu's work, establishing a reproducible development baseline, and maintaining clear commit traceability to support future reviews and handoffs.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for nh-spipitone/DataAnalyst-course focusing on delivering foundational scaffolding, enabling rapid future development, and ensuring a clean baseline for teammate contributions. The month was centered on project initialization and repository readiness, with no major bug fixes recorded. Highlights include introducing a placeholder Python file to bootstrap Riccardo Ghisu's work, establishing a reproducible development baseline, and maintaining clear commit traceability to support future reviews and handoffs.
Activity
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Quality Metrics
Correctness70.0%
Maintainability68.0%
Architecture70.0%
Performance68.0%
AI Usage32.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
API IntegrationData AnalysisData CleaningData PreprocessingData VisualizationExploratory Data Analysis (EDA)File ManagementLinear RegressionMachine LearningMatplotlibOpenAI APIPandasPythonSQLSQLite
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