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
Developed end-to-end analytics features for the nh-spipitone/DataAnalyst-course repository, focusing on travel cost prediction and car price regression analysis. Established foundational project scaffolding to streamline onboarding and future development, then delivered a data-driven platform integrating data cleaning, exploratory data analysis, SQL data extraction, and machine learning for travel cost forecasting. Leveraged Python, SQL, and scikit-learn to build reproducible pipelines, including a regression tool for car pricing with preprocessing, model evaluation, and visualization. Incorporated OpenAI API for generative insights and interactive analysis, enabling faster decision-making and improved cost visibility. Emphasized reproducibility, clear repository structure, and scalable analytics workflows throughout.
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 peopleWork 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
Repositories Contributed To
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