nh-spipitone/DataAnalyst-course
Jun 2025 – Jul 2025
2 Months active
Languages Used
PythonSQL
Technical Skills
Basic ProgrammingConditional StatementsData AnalysisData StructuresFile ManagementLoops
matteovegni
PROFILE
Matteovegni
Over a two-month period, contributed foundational analytics features to the nh-spipitone/DataAnalyst-course repository, focusing on practical data processing and reporting workflows. Developed Python scripts for loading and analyzing CSV data, including student grades analytics with per-student and per-subject averages, top performer identification, and bar chart visualization using Matplotlib and Pandas. Built a data pipeline to ingest Pokemon data into PostgreSQL, perform SQL queries for fire-type selection, and export results to Excel, refining SQL handling with SQLAlchemy. Emphasized modular scripting, robust error handling, and clear repository organization to support hands-on learning, rapid iteration, and scalable analytics project development. No bugs reported.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
4
Lines of code
289
Activity Months2
Your Network
12 peopleWork History
July 2025
3 Commits • 2 Features
Jul 1, 2025July 2025 performance summary for nh-spipitone/DataAnalyst-course: Delivered end-to-end data analytics and reporting capabilities, enabling data-driven decision making for course outcomes and operational reporting. Implemented two core features: Student Grades Analytics with visualization, and Pokemon data ingestion/query/export pipeline. Added robustness improvements and refined SQL handling to support dynamic reporting.
3 Commits • 2 Features
Jul 1, 2025July 2025 performance summary for nh-spipitone/DataAnalyst-course: Delivered end-to-end data analytics and reporting capabilities, enabling data-driven decision making for course outcomes and operational reporting. Implemented two core features: Student Grades Analytics with visualization, and Pokemon data ingestion/query/export pipeline. Added robustness improvements and refined SQL handling to support dynamic reporting.
July 2025
June 2025
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for nh-spipitone/DataAnalyst-course: Delivered foundational features to enable future analytics development. Key features: (1) Project scaffolding with placeholder prova.py in Studenti/MatteoVegni, (2) Data processing utilities with Python scripts for loading CSV data, summarizing sales, filtering numbers, and analyzing employee data, plus illustrative data structures. Major bugs fixed: None reported. Overall impact: establishes a reusable analytics base, accelerates hands-on exercises, and improves onboarding for contributors. Technologies/skills demonstrated: Python, CSV processing, data structures (lists/dicts), modular scripting, and repository organization.
June 2025
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for nh-spipitone/DataAnalyst-course: Delivered foundational features to enable future analytics development. Key features: (1) Project scaffolding with placeholder prova.py in Studenti/MatteoVegni, (2) Data processing utilities with Python scripts for loading CSV data, summarizing sales, filtering numbers, and analyzing employee data, plus illustrative data structures. Major bugs fixed: None reported. Overall impact: establishes a reusable analytics base, accelerates hands-on exercises, and improves onboarding for contributors. Technologies/skills demonstrated: Python, CSV processing, data structures (lists/dicts), modular scripting, and repository organization.
Activity
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Quality Metrics
Correctness70.0%
Maintainability70.0%
Architecture63.4%
Performance63.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
Basic ProgrammingConditional StatementsData AnalysisData StructuresDatabase ManagementFile ExportFile ManagementLoopsMatplotlibPandasPython ScriptingSQLSQLAlchemyUser Input Handling
Repositories Contributed To
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