Etna

Added
- Backtest cli ([223](https://github.com/tinkoff-ai/etna/pull/223), [#259](https://github.com/tinkoff-ai/etna/pull/259))
- TreeFeatureSelectionTransform ([229](https://github.com/tinkoff-ai/etna/pull/229))
- Feature relevance table calculation using tsfresh ([227](https://github.com/tinkoff-ai/etna/pull/227), [#249](https://github.com/tinkoff-ai/etna/pull/249))
- Method to_flatten to TSDataset ([241](https://github.com/tinkoff-ai/etna/pull/241)
- Out_column parameter to not inplace transforms([211](https://github.com/tinkoff-ai/etna/pull/211))
- omegaconf config parser in cli ([258](https://github.com/tinkoff-ai/etna/pull/258))
- Feature relevance table calculation using feature importance ([261](https://github.com/tinkoff-ai/etna/pull/261))
- MeanSegmentEncoderTransform ([265](https://github.com/tinkoff-ai/etna/pull/265))

Changed
- Add possibility to set custom in_column for ConfidenceIntervalOutliersTransform ([240](https://github.com/tinkoff-ai/etna/pull/240))
- Make `in_column` the first argument in every transform ([247](https://github.com/tinkoff-ai/etna/pull/247))
- Update mypy checking and fix issues with it ([248](https://github.com/tinkoff-ai/etna/pull/248))
- Add histogram method in outliers notebook ([252](https://github.com/tinkoff-ai/etna/pull/252))
- Joblib parameters for backtest and ensembles ([253](https://github.com/tinkoff-ai/etna/pull/253))
- Replace cycle over segments with vectorized expression in TSDataset._check_endings ([264](https://github.com/tinkoff-ai/etna/pull/264))

Fixed
- Fixed broken links in docs command section ([223](https://github.com/tinkoff-ai/etna/pull/223))
- Fix default value for TSDataset.tail ([245](https://github.com/tinkoff-ai/etna/pull/245))
- Fix raising warning on fitting SklearnModel on dataset categorical columns ([250](https://github.com/tinkoff-ai/etna/issues/207))
- Fix working TSDataset.make_future with empty exog values ([244](https://github.com/tinkoff-ai/etna/pull/244))
- Fix issue with aggregate_metrics=True for ConsoleLogger and WandbLogger ([254](https://github.com/tinkoff-ai/etna/pull/254))
- Fix binder requirements to work with optional dependencies ([257](https://github.com/tinkoff-ai/etna/pull/257))

Added
- BinsegTrendTransform, ChangePointsTrendTransform ([87](https://github.com/tinkoff-ai/etna/pull/87))
- Interactive plot for anomalies ([95](https://github.com/tinkoff-ai/etna/pull/95))
- Examples to TSDataset methods with doctest ([92](https://github.com/tinkoff-ai/etna/pull/92))
- WandbLogger ([71](https://github.com/tinkoff-ai/etna/pull/71))
- Pipeline ([78](https://github.com/tinkoff-ai/etna/pull/78))
- Sequence anomalies ([96](https://github.com/tinkoff-ai/etna/pull/96)), Histogram anomalies ([#79](https://github.com/tinkoff-ai/etna/pull/79))
- 'is_weekend' feature in DateFlagsTransform ([101](https://github.com/tinkoff-ai/etna/pull/101))
- Documentation example for models and note about inplace nature of forecast ([112](https://github.com/tinkoff-ai/etna/pull/112))
- Property regressors to TSDataset ([82](https://github.com/tinkoff-ai/etna/pull/82))
- Clustering ([110](https://github.com/tinkoff-ai/etna/pull/110))
- Outliers notebook ([123](https://github.com/tinkoff-ai/etna/pull/123)))
- Method inverse_transform in TimeSeriesImputerTransform ([135](https://github.com/tinkoff-ai/etna/pull/135))
- VotingEnsemble ([150](https://github.com/tinkoff-ai/etna/pull/150))
- Forecast command for cli ([133](https://github.com/tinkoff-ai/etna/issues/133))
- MyPy checks in CI/CD and lint commands ([39](https://github.com/tinkoff-ai/etna/issues/39))
- TrendTransform ([139](https://github.com/tinkoff-ai/etna/pull/139))
- Running notebooks in ci ([134](https://github.com/tinkoff-ai/etna/issues/134))
- Cluster plotter to EDA ([169](https://github.com/tinkoff-ai/etna/pull/169))
- Pipeline.backtest method ([161](https://github.com/tinkoff-ai/etna/pull/161), [#192](https://github.com/tinkoff-ai/etna/pull/192))
- STLTransform class ([158](https://github.com/tinkoff-ai/etna/pull/158))
- NN_examples notebook ([159](https://github.com/tinkoff-ai/etna/pull/159))
- Example for ProphetModel ([178](https://github.com/tinkoff-ai/etna/pull/178))
- Instruction notebook for custom model and transform creation ([180](https://github.com/tinkoff-ai/etna/pull/180))
- Add inverse_transform in *OutliersTransform ([160](https://github.com/tinkoff-ai/etna/pull/160))
- Examples for CatBoostModelMultiSegment and CatBoostModelPerSegment ([181](https://github.com/tinkoff-ai/etna/pull/181))
- Simplify TSDataset.train_test_split method by allowing to pass not all values ([191](https://github.com/tinkoff-ai/etna/pull/191))
- Confidence interval anomalies detection to EDA ([182](https://github.com/tinkoff-ai/etna/pull/182))
- ConfidenceIntervalOutliersTransform ([196](https://github.com/tinkoff-ai/etna/pull/196))
- Add 'in_column' parameter to get_anomalies methods([199](https://github.com/tinkoff-ai/etna/pull/199))
- Clustering notebook ([152](https://github.com/tinkoff-ai/etna/pull/152))
- StackingEnsemble ([195](https://github.com/tinkoff-ai/etna/pull/195))
- Add AutoRegressivePipeline ([209](https://github.com/tinkoff-ai/etna/pull/209))
- Ensembles notebook ([218](https://github.com/tinkoff-ai/etna/pull/218))
- Function plot_backtest_interactive ([225](https://github.com/tinkoff-ai/etna/pull/225))
- Confidence intervals in Pipeline ([221](https://github.com/tinkoff-ai/etna/pull/221))

Changed
- Delete offset from WindowStatisticsTransform ([111](https://github.com/tinkoff-ai/etna/pull/111))
- Add Pipeline example in Get started notebook ([115](https://github.com/tinkoff-ai/etna/pull/115))
- Internal implementation of BinsegTrendTransform ([141](https://github.com/tinkoff-ai/etna/pull/141))
- Colorebar scaling in Correlation heatmap plotter ([143](https://github.com/tinkoff-ai/etna/pull/143))
- Add Correlation heatmap in EDA notebook ([144](https://github.com/tinkoff-ai/etna/pull/144))
- Add `__repr__` for Pipeline ([151](https://github.com/tinkoff-ai/etna/pull/151))
- Defined random state for every test cases ([155](https://github.com/tinkoff-ai/etna/pull/155))
- Add confidence intervals to Prophet ([153](https://github.com/tinkoff-ai/etna/pull/153))
- Add confidence intervals to SARIMA ([172](https://github.com/tinkoff-ai/etna/pull/172))
- Add badges to all example notebooks ([220](https://github.com/tinkoff-ai/etna/pull/220))
- Update backtest notebook by adding Pipeline.backtest ([222](https://github.com/tinkoff-ai/etna/pull/222))

Fixed
- Set default value of `TSDataset.head` method ([170](https://github.com/tinkoff-ai/etna/pull/170))
- Categorical and fillna issues with pandas >=1.2 ([190](https://github.com/tinkoff-ai/etna/pull/190))
- Fix `TSDataset.to_dataset` method sorting bug ([183](https://github.com/tinkoff-ai/etna/pull/183))
- Undefined behaviour of DataFrame.loc[:, pd.IndexSlice[:, ["a", "b"]]] between 1.1.* and >= 1.2 ([188](https://github.com/tinkoff-ai/etna/pull/188))
- Fix typo in word "length" in `get_segment_sequence_anomalies`,`get_sequence_anomalies`,`SAXOutliersTransform` arguments ([212](https://github.com/tinkoff-ai/etna/pull/212))
- Make possible to send backtest plots with many segments ([225](https://github.com/tinkoff-ai/etna/pull/225))

Fixed
- Limit version of pandas by 1.2 (excluding) ([163](https://github.com/tinkoff-ai/etna/pull/163))

Changed
- SklearnTransform out column names ([99](https://github.com/tinkoff-ai/etna/pull/99))
- Update EDA notebook ([96](https://github.com/tinkoff-ai/etna/pull/96))
- Add 'regressor_' prefix to output columns of LagTransform, DateFlagsTransform, SpecialDaysTransform, SegmentEncoderTransform
Fixed
- Add more obvious Exception Error for forecasting with unfitted model ([102](https://github.com/tinkoff-ai/etna/pull/102))
- Fix bug with hardcoded frequency in PytorchForecastingTransform ([107](https://github.com/tinkoff-ai/etna/pull/107))
- Bug with inverse_transform method of TimeSeriesImputerTransform ([148](https://github.com/tinkoff-ai/etna/pull/148))

Fixed
- Documentation build workflow ([85](https://github.com/tinkoff-ai/etna/pull/85))

Added
- MedianOutliersTransform, DensityOutliersTransform ([30](https://github.com/tinkoff-ai/etna/pull/30))
- Issues and Pull Request templates
- TSDataset checks ([24](https://github.com/tinkoff-ai/etna/pull/24), [#20](https://github.com/tinkoff-ai/etna/pull/20))\
- Pytorch-Forecasting models ([29](https://github.com/tinkoff-ai/etna/pull/29))
- SARIMAX model ([10](https://github.com/tinkoff-ai/etna/pull/10))
- Logging, including ConsoleLogger ([46](https://github.com/tinkoff-ai/etna/pull/46))
- Correlation heatmap plotter ([77](https://github.com/tinkoff-ai/etna/pull/77))

Changed
- Backtest is fully parallel
- New default hyperparameters for CatBoost
- Add 'regressor_' prefix to output columns of LagTransform, DateFlagsTransform, SpecialDaysTransform, SegmentEncoderTransform

Fixed
- Documentation fixes ([55](https://github.com/tinkoff-ai/etna/pull/55), [#53](https://github.com/tinkoff-ai/etna/pull/53), [#52](https://github.com/tinkoff-ai/etna/pull/52))
- Solved warning in LogTransform and AddConstantTransform ([26](https://github.com/tinkoff-ai/etna/pull/26))
- Regressors do not have enough history bug ([35](https://github.com/tinkoff-ai/etna/pull/35))
- make_future(1) and make_future(2) bug
- Fix working with 'cap' and 'floor' features in Prophet model ([62](https://github.com/tinkoff-ai/etna/pull/62))
- Fix saving init params for SARIMAXModel ([81](https://github.com/tinkoff-ai/etna/pull/81))
- Imports of nn models, PytorchForecastingTransform and Transform ([80](https://github.com/tinkoff-ai/etna/pull/80))