tfdv.DatasetView
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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.
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Last updated 2024-10-18 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-10-18 UTC."],[],[],null,["# tfdv.DatasetView\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L428-L559) |\n\nView of statistics for a dataset (slice). \n\n tfdv.DatasetView(\n stats_proto: statistics_pb2.DatasetFeatureStatistics\n )\n\nMethods\n-------\n\n### `get_cross_feature`\n\n[View source](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L493-L507) \n\n get_cross_feature(\n x_path: Union[str, ../tfdv/FeaturePath, Iterable[str]],\n y_path: Union[str, ../tfdv/FeaturePath, Iterable[str]]\n ) -\u003e Optional['CrossFeatureView']\n\nRetrieve a cross-feature if it exists, or None.\n\n### `get_derived_feature`\n\n[View source](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L520-L559) \n\n get_derived_feature(\n deriver_name: str,\n source_paths: Sequence[../tfdv/FeaturePath]\n ) -\u003e Optional['FeatureView']\n\nRetrieve a derived feature based on a deriver name and its inputs.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------------|-----------------------------------------------------------------------------------|\n| `deriver_name` | The name of a deriver. Matches validation_derived_source deriver_name. |\n| `source_paths` | Source paths for derived features. Matches validation_derived_source.source_path. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| FeatureView of derived feature. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ||\n|---|---|\n| ValueError if multiple derived features match. ||\n\n\u003cbr /\u003e\n\n### `get_feature`\n\n[View source](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L471-L491) \n\n get_feature(\n feature_id: Union[str, ../tfdv/FeaturePath, Iterable[str]]\n ) -\u003e Optional['FeatureView']\n\nRetrieve a feature if it exists.\n\nFeatures specified within the underlying proto by name (instead of path) are\nnormalized to a length 1 path, and can be referred to as such.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|--------------|-------------------------------------------------------------------------------------------------------------------|\n| `feature_id` | A types.FeaturePath, Iterable\\[str\\] consisting of path steps, or a str, which is converted to a length one path. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A FeatureView, or None if feature_id is not present. ||\n\n\u003cbr /\u003e\n\n### `list_cross_features`\n\n[View source](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L514-L518) \n\n list_cross_features() -\u003e Iterable[Tuple[types.FeaturePath, types.FeaturePath]]\n\nLists cross-feature identifiers.\n\n### `list_features`\n\n[View source](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L509-L512) \n\n list_features() -\u003e Iterable[../tfdv/FeaturePath]\n\nLists feature identifiers.\n\n### `proto`\n\n[View source](https://github.com/tensorflow/data-validation/blob/v1.16.1/tensorflow_data_validation/utils/stats_util.py#L467-L469) \n\n proto() -\u003e statistics_pb2.DatasetFeatureStatistics\n\nRetrieve the underlying proto."]]
View source on GitHub