PyCon PT 24 | Comparing Time Series Forecasting Models: A Clustering Analysis Approach with Python

Time series analysis is vital for trends and forecasting in finance and healthcare. This talk explores ARIMA models for clustering disease data in 48 European countries, using Python libraries like pmdarima and TimeSeriesSplit. We’ll examine how distance measures like Piccolo, Maharaj, and LPC reveal health disparities, showcasing how Python enhances public health surveillance and interventions.