tfdv.DatasetView

View of statistics for a dataset (slice).

tfdv.DatasetView(
    stats_proto: statistics_pb2.DatasetFeatureStatistics
)

Methods

`get_cross_feature`

View source

get_cross_feature(
    x_path: Union[str, tfdv.FeaturePath, Iterable[str]],
    y_path: Union[str, tfdv.FeaturePath, Iterable[str]]
) -> Optional['CrossFeatureView']

Retrieve a cross-feature if it exists, or None.

`get_derived_feature`

View source

get_derived_feature(
    deriver_name: str,
    source_paths: Sequence[tfdv.FeaturePath]
) -> Optional['FeatureView']

Retrieve a derived feature based on a deriver name and its inputs.

Args
`deriver_name`	The name of a deriver. Matches validation_derived_source deriver_name.
`source_paths`	Source paths for derived features. Matches validation_derived_source.source_path.

Returns
FeatureView of derived feature.

Raises
ValueError if multiple derived features match.

`get_feature`

View source

get_feature(
    feature_id: Union[str, tfdv.FeaturePath, Iterable[str]]
) -> Optional['FeatureView']

Retrieve a feature if it exists.

Features specified within the underlying proto by name (instead of path) are normalized to a length 1 path, and can be referred to as such.

Args
`feature_id`	A types.FeaturePath, Iterable[str] consisting of path steps, or a str, which is converted to a length one path.

Returns
A FeatureView, or None if feature_id is not present.

`list_cross_features`

View source

list_cross_features() -> Iterable[Tuple[types.FeaturePath, types.FeaturePath]]

Lists cross-feature identifiers.

`list_features`

View source

list_features() -> Iterable[tfdv.FeaturePath]

Lists feature identifiers.

`proto`

View source

proto() -> statistics_pb2.DatasetFeatureStatistics

Retrieve the underlying proto.