9 must-have Python time series libraries everyone working with data should know:
sktime
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation and forecasting.
github.com
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation and forecasting.
github.com
tslearn
The machine learning toolkit for time series analysis in Python. Preprocess, train, and analyze machine learning models based on time series data.
github.com
The machine learning toolkit for time series analysis in Python. Preprocess, train, and analyze machine learning models based on time series data.
github.com
tick
tick is a machine learning library for Python 3. The focus is on statistical learning for time-dependent systems, such as point processes. Tick features also tools for generalized linear models and a generic optimization toolbox.
github.com
tick is a machine learning library for Python 3. The focus is on statistical learning for time-dependent systems, such as point processes. Tick features also tools for generalized linear models and a generic optimization toolbox.
github.com
Prophet
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.
From Facebook.
github.com
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.
From Facebook.
github.com
PyFlux
PyFlux is an open-source time series library for Python. The library has a good array of modern time series models, as well as a flexible array of inference options (frequentist and Bayesian) that can be applied to these models.
github.com
PyFlux is an open-source time series library for Python. The library has a good array of modern time series models, as well as a flexible array of inference options (frequentist and Bayesian) that can be applied to these models.
github.com
bayesloop
bayesloop is a python module that focuses on fitting time series models with time-varying parameters and model selection based on Bayesian inference.
github.com
bayesloop is a python module that focuses on fitting time series models with time-varying parameters and model selection based on Bayesian inference.
github.com
luminol
Luminol is a lightweight python library for time series data analysis. The two major functionalities it supports are anomaly detection and correlation. It can be used to investigate possible causes of anomaly.
github.com
Luminol is a lightweight python library for time series data analysis. The two major functionalities it supports are anomaly detection and correlation. It can be used to investigate possible causes of anomaly.
github.com
dateutil
The dateutil module provides powerful extensions to the standard datetime module, available in Python.
github.com
The dateutil module provides powerful extensions to the standard datetime module, available in Python.
github.com
maya
Ok most people know dateutil - but not maya.
maya exists to make the simple things much easier, while admitting that time is an illusion (timezones doubly so).
github.com
Ok most people know dateutil - but not maya.
maya exists to make the simple things much easier, while admitting that time is an illusion (timezones doubly so).
github.com
The 9 time series libraries everyone needs:
• tick
• maya
• sktime
• PyFlux
• tslearn
• luminol
• dateutil
• Prophet
• bayesloop
• tick
• maya
• sktime
• PyFlux
• tslearn
• luminol
• dateutil
• Prophet
• bayesloop
That's a wrap!
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