There are several Python packages for time series analysis. The list below is not exhaustive, and the packages are not mutually exclusive.

Feature extraction:

  • tsfresh - Feature extraction from time series, 1200 features (usage examples)
  • tsfel - Feature extraction from time series
  • catch22 - Feature extraction from time series (22 the most informative features for general time series classification)
  • hctsa - Highly Comparative Time-Series Analysis (HCTSA) feature extraction package (Matlab, 7000+ features)
  • tsfeatures - Time series feature extraction (Python implementation of the R package). Additional documentation is available from the original R package

Time series classification and forecasting:

  • sktime - Python framework for ML and AI with time series
  • aeon - scikit-learn compatible toolkit for time series tasks such as classification, clustering, segmentation and anomaly detection (fork of sktime)
  • tslearn - Machine learning tools for the analysis of time series
  • tsai - A state-of-the-art deep learning library for time series and sequential data
  • scale-cast - A Python package for time series forecast
  • ml-forecast - Scalable machine learning for time series forecasting
  • prophet - A forecasting procedure implemented in R and Python (Facebook)
  • MrSQM - Multiple Representations Sequence Miner is a time series classifier
  • Nixtlaverse - Set of Python tools for time series forecasting: StatsForecast, MLForecast, NeuralForecast and more
  • darts - A Python library for forecasting and anomaly detection of time series
  • Kats - A time series analysis toolkit developed by Facebook
  • Merlion - A time series forecasting library developed by Salesforce
  • greykite - A Python library for forecasting time series data by LinkedIn
  • arch - Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics
  • PyPOTS - a Python toolbox for machine learning on Partially-Observed Time Series

System-based approach:

  • sysidentpy - A Python package for system identification in time series analysis
  • GEKKO - A Python package for optimization of dynamic systems, with time-series capabilities, e.g. ARX

Deep learning:

Datasets:

Depreciated (not maintained):

  • pyts - A Python Package for Time Series Classification
  • seglearn - A Python package for time series classification
  • gluonts - Probabilistic deep learning time series modeling in Python (Amazon)
  • EdgeML - A machine learning library for resource-constrained devices developed by Microsoft (India)

Feature selection packages

  • FeatureWiz - Minimum Redundancy Maximum Relevance (MRMR) algorithm
  • AutoFeatSelect - Various feature selection methods
  • BorutaPy - Tree-based feature selection
  • scikit-learn Scikit-learn feature selection methods: statistical, greed search, recursive feature elimination, etc.
  • Py_FS - Evolutionary feature selection
  • shap-hypetune - Hyperparameters Tuning and Features Selection for Gradient Boosting Models

Unmaintained:

  • XuniVerse - Collection of transformers for feature engineering and feature selection

Feature engineering packages

List of time series packages