Tsfresh

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- Drop python 2.7 support (568)
- Fixed bugs
- Fix cache in friedrich_coefficients and agg_linear_trend (593)
- Added a check for wrong column names and a test for this check (586)
- Make sure to not install the tests folder (599)
- Make sure there is at least a single column which we can use for data (589)
- Avoid division by zero in energy_ratio_by_chunks (588)
- Ensure that get_moment() uses float computations (584)
- Preserve index when column_value and column_kind not provided (576)
- Add set_property("input", "pd.Series") when needed (582)
- Fix off-by-one error in longest strike features (fixes 577) (578)
- Add `set_property` import (572)
- Fix typo (571)
- Fix indexing of melted normalized input (563)
- Fix travis (569)
- Remove warnings (583)
- Update to newest python version (594)
- Optimizations
- Early return from change_quantiles if ql >= qh (591)
- Optimize mean_second_derivative_central (587)
- Improve performance with Numpy's sum function (567)
- Optimize mean_change (fixes issue 542) and correct documentation (574)

==============

- fixed bugs
- wrong calculation of friedrich coefficients
- feature selection selected too many features
- an ignored max_timeshift parameter in roll_time_series
- add deprecation warning for python 2
- added support for index based features
- new feature calculator
- linear_trend_timewise
- enable the RelevantFeatureAugmenter to be used in cross validated pipelines
- increased scipy dependency to 1.2.0

==============
- change chunking in energy_ratio_by_chunks to use all data points
- fix warning for spkt_welch_density
- adapt default settings for "value_count" and "range_count"
- added
- maxlag parameter to agg_autocorrelation function
- now, the kind column of the input DataFrame is cast as str, old derived FC_Settings can become invalid
- only set default_fc_parameters to ComprehensiveFCParameters() if also kind_to_fc_parameters is set None in `extract_features`
- removed pyscaffold
- use asymptotic algorithm to derive kendal tau

==============
- general performance improvements
- removed hard pinning of dependencies
- fixed bugs
- the stock price forecasting notebook
- the multi classification notebook

==============
- new feature calculators:
- fft_aggregated
- cid_ce
- renamed mean_second_derivate_central to mean_second_derivative_central
- add warning if no relevant features were found in feature selection
- add columns_to_ignore parameter to from_columns method
- add distribution module, contains support for distributed feature extraction on Dask

==============
- split test suite into unit and integration tests
- fixed the following bugs
- use name of value column as time series kind
- prevent the spawning of subprocesses which lead to high memory consumption
- fix deployment from travis to pypi