v0.20.3

• Bugfixes/Typos/Documentation:
  • Fixes issue #1073: Updated setup.cfg to require newer scipy version (#1081)
  • extract_relevant_features now passes chunksize to extract_features (#1083)
  • Fix code and tests for numpy >= 2.0 (#1085)
  • Update tsfresh.feature_extraction.feature_calculators.skewness to make it consistent with the design principle of not ignoring nan (#1066)
  • Fix spelling/grammar in pipeline notebook (#1082)
  • Added recommendation to revert thread limitations (#1069)
  • Fix the 01 example notebook to not leak information between train and test set
  • Feature calculator return type documentation (#1070)

v0.20.2

• Added Features

  • Make Dask and Distributed optional dependencies (#1061)
  • View and Set N Jobs (#1029)

• Bugfixes/Typos/Documentation:

  • Extra notes on parallelization efficiencies (#1046)
  • Update doc extraction settings for clarity and formatting (#1033)
  • Typos (#1031, #1034, #1049, #1048)

v0.20.1

• Added Features

  • Make tsfresh compatible with numpy 1.24 (#1018) and pandas 2.0 (#1028)

• Bugfixes/Typos/Documentation:

  • Use pandas Index.equals in check_if_pandas_series (#963)
  • Updates to package layout, CI/CD and developer setup

v0.20.0

• Breaking Change

  • The matrixprofile package becomes an optional dependency

• Bugfixes/Typos/Documentation:

  • Fix feature extraction of Friedrich coefficients for pandas>1.3.5
  • Fix file paths after example notebooks were moved

v0.19.0

• Breaking Change

  • Drop Python 3.6 support due to dependency on statsmodels 0.13

• Added Features

  • Improve documentation (#831, #834, #851, #853, #870)
  • Add absolute_maximum and mean_n_absolute_max features (#833)
  • Make settings pickable (#845, #847, #910)
  • Disable multiprocessing for n_jobs=1 (#852)
  • Add black, isort, and pre-commit (#876)

• Bugfixes/Typos/Documentation:

  • Fix conversion of time-series into sequence for lempel_ziv_complexity (#806)
  • Fix range count config (#827)
  • Reword documentation (#893)
  • Fix statsmodels deprecation issues (#898, #912)
  • Fix typo in requirements (#903)
  • Updated references

v0.18.0

• Added Features

  • Allow arbitrary rolling sizes (#766)
  • Allow for multiclass significance tests (#762)
  • Add multiclass option to RelevantFeatureAugmenter (#782)
  • Addition of matrix_profile feature (#793)
  • Added new query similarity counter feature (#798)
  • Add root mean square feature (#813)

• Bugfixes/Typos/Documentation:

  • Do not send coverage of notebook tests to codecov (#759)
  • Fix typos in notebook (#757, #780)
  • Fix output format of make_forecasting_frame (#758)
  • Fix badges and remove benchmark test
  • Fix BY notebook plot (#760)
  • Ts forecast example improvement (#763)
  • Also surpress warnings in dask (#769)
  • Update relevant_feature_augmenter.py (#779)
  • Fix column names in quick_start.rst (#778)
  • Improve relevance table function documentation (#781)
  • Fixed #789 Typo in "how to add custom feature" (#790)
  • Convert to the correct type on warnings (#799)
  • Fix minor typos in the docs (#802)
  • Add unwanted filetypes to gitignore (#819)
  • Fix build and test failures (#815)
  • Fix imputing docu (#800)
  • Bump the scikit-learn version (#822)

v0.17.0

We changed the default branch from "master" to "main".

• Breaking Change
  • Changed constructed id in roll_time_series from string to tuple (#700)
  • Same for add_sub_time_series_index (#720)
• Added Features
  • Implemented the Lempel-Ziv-Complexity and the Fourier Entropy (#688)
  • Prevent #524 by adding an assert for common identifiers (#690)
  • Added permutation entropy (#691)
  • Added a logo :-) (#694)
  • Implemented the benford distribution feature (#689)
  • Reworked the notebooks (#701, #704)
  • Speed up the result pivoting (#705)
  • Add a test for the dask bindings (#719)
  • Refactor input data iteration to need less memory (#707)
  • Added benchmark tests (#710)
  • Make dask a possible input format (#736)
• Bugfixes:
  • Fixed a bug in the selection, that caused all regression tasks with un-ordered index to be wrong (#715)
  • Fixed readthedocs (#695, #696)
  • Fix spark and dask after #705 and for non-id named id columns (#712)
  • Fix in the forecasting notebook (#729)
  • Let tsfresh choose the value column if possible (#722)
  • Move from coveralls github action to codecov (#734)
  • Improve speed of data processing (#735)
  • Fix for newer, more strict pandas versions (#737)
  • Fix documentation for feature calculators (#743)

v0.16.0

• Breaking Change
  • Fix the sorting of the parameters in the feature names (#656)
    The feature names consist of a sorted list of all parameters now.
    That used to be true for all non-combiner features, and is now also true for combiner features.
    If you relied on the actual feature name, this is a breaking change.
  • Change the id after the rolling (#668)
    Now, the old id of your data is still kept. Additionally, we improved the way
    dataframes without a time column are rolled and how the new sub-time series
    are named.
    Also, the documentation was improved a lot.
• Added Features
  • Added variation coefficient (#654)
  • Added the datetimeindex explanation from the notebook to the docs (#661)
  • Optimize RelevantFeatureAugmenter to avoid re-extraction (#669)
  • Added a function add_sub_time_series_index (#666)
  • Added Dockerfile
  • Speed optimizations and speed testing script (#681)
• Bugfixes
  • Increase the extracted ar coefficients to the full parameter range. (#662)
  • Documentation fixes (#663, #664, #665)
  • Rewrote the sample_entropy feature calculator (#681)
    It is now faster and (hopefully) more correct.
    But your results will change!

v0.15.1

Changelog and documentation fixes

v0.15.0

• Added Features
  • Add count_above and count_below feature (#632)
  • Add convenience bindings for dask dataframes and pyspark dataframes (#651)
• Bugfixes
  • Fix documentation build and feature table in sphinx (#637, #631, #627)
  • Add scripts to API documentation
  • Skip dask test for older python versions (#649)
  • Add missing distributor keyword (#648)
  • Fix tuple input for cwt (#645)