This project focuses on analyzing historical fuel prices in Argentina through a complete data pipeline, from data processing to interactive visualization.
The goal is to identify trends, variations and patterns in fuel prices over time to support data-driven insights.
- Data cleaning and validation
- Handling missing values
- Data normalization and transformation
- Time-series preparation
- Structured storage of processed data
- Query optimization for analytical purposes
- Data aggregation for reporting
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Interactive dashboards including:
- Price trends over time
- Comparisons between fuel types
- Regional variations (if applicable)
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User-friendly filters and segmentation
- Analyze fuel price evolution in Argentina
- Detect patterns and anomalies
- Provide clear and actionable visual insights
- Python (pandas, numpy, matplotlib)
- SQL
- Power BI
- Clean and structured dataset
- Automated data workflow
- Insightful dashboards for decision-making
Ezequiel Vidal
📧 pezequielvidal@gmail.com