OutliersTransform

class OutliersTransform(in_column: str)

Bases: etna.transforms.base.ReversibleTransform, abc.ABC

Finds outliers in specific columns of DataFrame and replaces it with NaNs.

Create instance of OutliersTransform.

Parameters

in_column (str) – name of processed column

Inherited-members

Methods

detect_outliers(ts)	Call function for detection outliers with self parameters.
fit(ts)	Fit the transform.
fit_transform(ts)	Fit and transform TSDataset.
get_regressors_info()	Return the list with regressors created by the transform.
inverse_transform(ts)	Inverse transform TSDataset.
load(path)	Load an object.
params_to_tune()	Get grid for tuning hyperparameters.
save(path)	Save the object.
set_params(**params)	Return new object instance with modified parameters.
to_dict()	Collect all information about etna object in dict.
transform(ts)	Transform TSDataset inplace.

abstract detect_outliers(ts: etna.datasets.tsdataset.TSDataset) → Dict[str, List[pandas._libs.tslibs.timestamps.Timestamp]]

Call function for detection outliers with self parameters.

Parameters

ts (etna.datasets.tsdataset.TSDataset) – dataset to process

Returns

dict of outliers in format {segment: [outliers_timestamps]}

Return type

Dict[str, List[pandas._libs.tslibs.timestamps.Timestamp]]

get_regressors_info() → List[str]

Return the list with regressors created by the transform.

Returns

List with regressors created by the transform.

Return type

List[str]