https://github.com/MaxBenChrist/tspreprocess
A Python package to preprocess time series
https://github.com/MaxBenChrist/tspreprocess
Last synced: 19 days ago
JSON representation
A Python package to preprocess time series
- Host: GitHub
- URL: https://github.com/MaxBenChrist/tspreprocess
- Owner: MaxBenChrist
- License: mit
- Created: 2017-07-20T14:34:00.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-11-01T20:56:42.000Z (over 7 years ago)
- Last Synced: 2025-03-18T08:21:30.030Z (about 1 month ago)
- Language: Python
- Homepage:
- Size: 23.4 KB
- Stars: 60
- Watchers: 14
- Forks: 11
- Open Issues: 12
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Metadata Files:
- Readme: README.rst
- Changelog: CHANGES.rst
- License: LICENSE.txt
- Authors: AUTHORS.rst
Awesome Lists containing this project
- awesome_time_series_in_python - tspreprocess
README
**Disclaimer: This package is WIP. Do not take any APIs for granted.**
============
tspreprocess
============Time series can contain noise, may be sampled under a non fitting rate or just need to be compressed.
*tspreprocess* is a library for such preprocessing tasks. It contains tools to transform and clean time series data for better analyses.In detail, we are planning to add methods to do
* Denoising
* Compression
* Resampling
* ...Our goal is to make this the most comprehensive time series preprocessing library.
Installation
============Clone the repo, cd into it and install it with pip locally
.. code-block:: Python
git clone https://github.com/MaxBenChrist/tspreprocess
cd tspreprocess
pip install -e .You can run the test suite by
.. code-block:: Python
python setup.py test
Relation to *tsfresh*
=====================This package will based on the data formats from the python feature extraction pacakge *tsfresh*
(https://github.com/blue-yonder/tsfresh), allowing a seamless integration between both packages.