logml.data.base

Classes

`BaseTransformer`(params[, metadata_cfg, cfg, ...])	Interface class for objects that perform transformations on dataframes.
`KnownFeatureProperties`()	Features properties introduced by transformers.

class logml.data.base.BaseTransformer(params: logml.data.config.BaseTransformerParams, metadata_cfg: logml.configuration.modeling.ModelingTaskSpec = None, cfg: GlobalConfig = None, global_params: Dict = None, logger=None)

Bases: object

Interface class for objects that perform transformations on dataframes.

get_scope_dataset(dataframe: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame: Returns a given dataframe in case transformation scope is local, otherwise returns the raw dataset.

get_affected_columns(dataframe: pandas.core.frame.DataFrame, dataset_metadata: Optional[logml.data.metadata.DatasetMetadata] = None) → List[str]: Returns a list of a given dataframe’s columns that would be affected by a transformer.

fit(dataframe: pandas.core.frame.DataFrame, dataset_metadata: Optional[logml.data.metadata.DatasetMetadata] = None, **kwargs): Fit method prepares a transformer for further ‘transform’ calls.

transform(dataframe: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame: Applies transformations and returns the result dataframe.

update_metadata(dataset_metadata: Optional[logml.data.metadata.DatasetMetadata] = None, dataframe: Optional[pandas.core.frame.DataFrame] = None) → None: Update metadata according to the change made.

update_transform_log(change: logml.data.utils.DataTransformLogItem): Add custom data to the log.

class logml.data.base.KnownFeatureProperties

Bases: object

Features properties introduced by transformers.