PyPOTS is a specialized machine learning toolkit focused on handling incomplete, irregularly-sampled multivariate time series data. It offers implementations of 50+ state-of-the-art neural network architectures for tasks including imputation, classification, clustering, forecasting, anomaly detection, and data cleaning. Built on PyTorch, it targets industrial and scientific applications where missing values are common.