This exploratory analysis examines hourly energy consumption and weather data in Spain. It includes temporal pattern analysis, correlation studies, and insights to guide further modeling.

In this report, I present the exploratory data analysis (EDA) phase of a fraud detection system. It includes an in-depth look at transaction data, customer behavior, and key correlations between fraud patterns and temporal-spatial variables. This EDA sets the foundation for building robust machine learning models for fraud classification.