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Section Navigation

  • Installation
  • Tutorials
  • Notebook Examples
    • Introduction to sktime
    • Forecasting with sktime
    • Forecasting with sktime - appendix: forecasting, supervised regression, and pitfalls in confusing the two
    • Probabilistic Forecasting with sktime
    • Hierarchical, Panel and Global Forecasting with sktime
    • Time Series Classification, Regression, Clustering & More
    • Transformers in sktime
    • Transformers cheat sheets
    • Forecasting Pipelines, Tuning, and AutoML
    • Anomaly, changepoint, and segment detection with sktime and skchange
    • Time Series Segmentation with sktime and ClaSP
    • Overview of this notebook
    • In-memory data representations and data loading
    • Benchmarking with sktime
    • Benchmarking - comparing estimator performance
  • Estimator Overview
  • Glossary of Common Terms
  • Changelog
  • Related Software
  • Documentation
  • Related Software

Related Software#

The Python ecosystem contains numerous packages that can be used to store and process time series data. The following list is by no means exhaustive. If you miss anything, feel free to open a PR.

Table of contents

  • Packages for machine learning, statistics or analytics with time series,

  • Other time series related frameworks or database systems.

For time series data containers, see our wiki entry.

Machine learning#

Libraries#

Project Name

Description

adtk

Anomaly Detection Tool Kit, a Python package for unsupervised/rule-based time series anomaly detection

atspy

Collection of forecasting models, wraps existing statistical and machine learning models for forecasting, automated benchmarking

Arrow

A sensible, human-friendly approach to creating, manipulating, formatting and converting dates, times, and timestamps

cesium

Time series platform with feature extraction aiming for non uniformly sampled signals

catch22

Feature selection pipeline for hctsa and the so-called catch22 feature set

crystalball

A python library for forecasting with scikit-learn like API

darts

Python collection of time series forecasting tools, from preprocessing to models (uni-/multivariate, prophet, neural networks) and backtesting utilities

deeptime

Library for unsupervised learning with time series including dimensionality reduction, clustering, and Markov model estimation

deltapy

Collection of data augmentation tools, including feature extraction from time series, wraps existing toolkits like tsfresh

diviner

Diviner by Databricks enables large-scale time series forecasting and serves as a wrapper around other open source forecasting libraries

dtaidistance

Time series distances

dtw

Scipy-based dynamic time warping

Featuretools

Time series feature extraction, with possible conditionality on other variables with a pandas compatible relational-database-like data container

fecon235

Computational tools for financial economics

ffn

financial function library

flint

A Time Series Library for Apache Spark

GENDIS

Shapelet discovery by genetic algorithms

glm-sklearn

scikit-learn compatible wrapper around the GLM module in statsmodels

gluon-ts

Probabilistic forecasting and anomaly detection using deep learning by Amazon

greykite

A Time Series Library for rorecasting by LinkedIn which contains the interpretable “Silverkite” algorithm.

hctsa

Matlab based feature extraction which can be controlled from python

HMMLearn

Hidden Markov Models with scikit-learn compatible API

kats

A toolkit by Facebook for time series analysis, including detection, forecasting, feature extraction/embedding, multivariate analysis, etc.

khiva-python

A Time Series library with accelerated analytics on GPUS, it provides feature extraction and motif discovery among other functionalities.

lifelines

Toolkit for survival analysis

linearmodels

Add linear models including instrumental variable and panel data models that are missing from statsmodels.

loudML

Time series inference engine built on top of TensorFlow to forecast data, detect outliers, and automate your process using future knowledge.

matrixprofile-ts

A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

mcfly

Deep learning for time series classification with automated hyperparameter selection

neuralprophet

A Neural Network based model, inspired by Facebook Prophet and AR-Net, built on PyTorch

Nitime

Time series analysis for neuroscience data

NoLiTSA

Non-linear time series analysis

orbit

Bayesian time series forecasting package by uber

pomegranate

Probabilistic models ranging from individual probability distributions to compositional models such as Bayesian networks and hidden Markov models.

Pastas

Time series analysis for hydrological data

prophet

Time series forecasting for time series data that has multiple seasonality with linear or non-linear growth

pyDSE

ARMA models for dynamic system Estimation

PyEMMA

Analysis of extensive molecular dynamics simulations based on Markov models

PyFlux

Classical time series forecasting models

PyHubs

Hubness-aware machine learning in Python including time series classification via dynamic time warping based KNN classification

PyOD

Toolbox for outlier detection

pysf

A scikit-learn compatible machine learning library for supervised/panel forecasting

pmdarima

Port of R’s auto.arima method to Python

pyts

Contains time series preprocessing, transformation as well as classification techniques

ruptures

time series annotation: change point detection, segmentation

salesforce-merlion

Library from salesforce for forecasting, anomaly detection, and change point detection

scikit-fda

A Python library to perform Functional Data Analysis, compatible with scikit-learn, including representation, preprocessing, exploratory analysis and machine learning methods

scikit-multiflow

Extension of scikit-learn to supervised learning of streaming data (dynamic online learning), including regression/classification and change detection

scikit-survival

Survival analysis built on top of scikit-learn

seasonal

Toolkit to estimate trends and seasonality in time series

seqlearn

Extends the scikit-learn pipeline concept to time series annotation

seglearn

Extends the scikit-learn pipeline concept to time series data for classification, regression and forecasting

sktime

A scikit-learn compatible library for learning with time series/panel data including time series classification/regression and (supervised/panel) forecasting

statsforecast

StatsForecast by Nixtla offers a collection of widely used univariate time series forecasting models optimized for high performance using numba

statsmodels

Contains a submodule for classical time series models and hypothesis tests

stumpy

Calculates matrix profile for time series subsequence all-pairs-similarity-search

tbats

Package provides BATS and TBATS time series forecasting methods

tensorflow_probability.sts

Bayesian Structural Time Series model in Tensorflow Probability

timechop

Toolkit for temporal cross-validation, part of the Data Science for Social Good predictive analytics framework

Traces

A library for unevenly-spaced time series analysis

ta-lib

Calculate technical indicators for financial time series (python wrapper around TA-Lib)

ta

Calculate technical indicators for financial time series

tseries

scikit-learn compatible time series regressor as a meta-estimator for forecasting

tsfresh

Extracts and filters features from time series, allowing supervised classificators and regressor to be applied to time series data

tslearn

Direct time series classifiers and regressors

tspreprocess

Preprocess time series (resampling, denoising etc.), still WIP

alibi-detect

Toolbox for Outlier, Adversarial and Drift detection

Specific model implementations#

Project name

Description

ES-RNN forecasting algorithm

Python implementation of the winning forecasting method of the M4 competition combining exponential smoothing with a recurrent neural network using PyTorch

Deep learning methods for time series classification

A collection of common deep learning architectures for time series classification

M4 competition

Collection of statistical and machine learning forecasting methods

Microsoft forecasting

Collection of forecasting models and best practices, interfaces existing libraries in Python and R

LSTM-Neural-Network-for-Time-Series-Prediction

LSTM for forecasting model

LSTM_tsc

An LSTM for time series classification

shapelets-python

Shapelet classifier based on a multi layer neural network

ROCKET

Time series classification using random convolutional kernels

TensorFlow-Time-Series-Examples

Time Series Prediction with tf.contrib.timeseries

UCR_Time_Series_Classification_Deep_Learning_Baseline

Fully convolutional neural networks for state-of-the-art time series classification

WTTE-RNN

Time to event forecast by RNN based Weibull density estimation

TimeSeers

alternative to Prophet for timeseries modelling when multiple time series are expected

Time series databases and frameworks#

Project Name

Description

arctic

High performance datastore for time series and tick data

automl_service

Fully automated time series classification pipeline, deployed as a web service

cesium

Time series platform with feature extraction aiming for non uniformly sampled signals

thunder

Scalable analysis of image and time series data in Python based on spark

whisper

File-based time-series database format

FinTime

Financial time series database framework, design, benchmarks

MNE

Python software for exploring, visualizing, and analyzing neurophysiological time series data (MEG, EEG, etc)

Acknowledgements#

Thanks to Max Christ who started the list here.

On this page
  • Machine learning
    • Libraries
    • Specific model implementations
  • Time series databases and frameworks
  • Acknowledgements

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