Welcome to TSFEL documentation!
Time Series Feature Extraction Library (TSFEL for short) is a Python package for feature extraction on time series data. It provides exploratory feature extraction tasks on time series without requiring significant programming effort. TSFEL automatically extracts over 60 different features on the statistical, temporal and spectral domains. TSFEL was built by data scientists for data scientists!
Highlights
Intuitive, fast deployment and reproducible: interactive UI for feature selection and customization
Computational complexity evaluation: estimate the computational effort before extracting features
Comprehensive documentation: each feature extraction method has a detailed explanation
Unit tested: we provide unit tests for each feature
Easily extended: adding new features is easy and we encourage you to contribute with your custom features
Installation
Installation can be easily done with pip
:
$ pip install tsfel
Get started
The code below extracts all the available features on an example dataset.
import tsfel
import pandas as pd
# load dataset
df = pd.read_csv('Dataset.txt')
# Retrieves a pre-defined feature configuration file to extract all available features
cfg = tsfel.get_features_by_domain()
# Extract features
X = tsfel.time_series_features_extractor(cfg, df)
How to cite TSFEL?
Note
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