PyPOTS

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PyPOTS: A comprehensive Python library for time series analysis with machine learning and deep learning. Offering 50+ state-of-the-art (SOTA) algorithms for time series imputation, forecasting, classification, anomaly detection, and clustering. Specifically designed for partially-observed time series (POTS) with missing values. Built on PyTorch with unified APIs, extensive documentation, and benchmarking tools. Trusted by researchers and engineers at MIT, Stanford, Oxford, Microsoft, IBM, and more. Install with: pip install pypots. PyPOTS is the first (and so far the only) Python toolbox/library specifically designed for data mining and machine learning on partially-observed time series (POTS), namely, incomplete time series with missing values, A.K.A.