The python ecosystem contains different packages that can be used to process time series.
The following list is by no means exhaustive, feel free to submit a pr if you miss something.
Project Name | Description |
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Arrow | A sensible, human-friendly approach to creating, manipulating, formatting and converting dates, times, and timestamps |
cesium | Time series platform with feature extraction aming for non uniformly sampled signals |
fecon235 | Computational tools for financial economics |
hctsa | Matlab based feature extraction which can be controlled from python |
Nitime | Timeseries analysis for neuroscience 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 |
PyFlux | Classical time series forecasting models |
statsmodels | Contains a submodule for classical time series models and hypothesis tests |
TensorFlow-Time-Series-Examples | Time Series Prediction with tf.contrib.timeseries |
Traces | A library for unevenly-spaced time series analysis |
ta-lib | Calculate technical indicators for financial time series |
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 |
Project Name | Description |
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LSTM-Neural-Network-for-Time-Series-Prediction | LSTM based forecasting model |
LSTM_tsc | An LSTM based time-series classification neural network |
shapelets-python | Shapelet Classifier based on a multi layer neural network |
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 |
Project Name | Description |
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ecmwf_models | Readers and converters for climate reanalysis data |
pandas-datareader | Pulls financial data from different sources (e.g. yahoo, google, Quandl) |
Project Name | Description |
---|---|
artic | 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 aming 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 |
We would like to trigger a homogenization of the formats which are used in the python time series community, please see the concept page