woodwork.column_accessor.WoodworkColumnAccessor.init#

WoodworkColumnAccessor.init(logical_type=None, semantic_tags=None, use_standard_tags=True, description=None, origin=None, metadata=None, schema=None, validate=True)[source]#

Initializes Woodwork typing information for a Series.

Parameters:

  • logical_type (LogicalType or str, optional) – The logical type that should be assigned to the series. If no value is provided, the LogicalType for the series will be inferred. If the LogicalType provided or inferred does not have a dtype that is compatible with the series dtype, an error will be raised.

  • semantic_tags (str or list or set, optional) – Semantic tags to assign to the series. Defaults to an empty set if not specified. There are two options for specifying the semantic tags: (str) If only one semantic tag is being set, a single string can be passed. (list or set) If multiple tags are being set, a list or set of strings can be passed.

  • use_standard_tags (bool, optional) – If True, will add standard semantic tags to the series based on the inferred or specified logical type of the series. Defaults to True.

  • description (str, optional) – Optional text describing the contents of the series.

  • origin (str, optional) – Optional text specifying origin of the column (i.e. “base” or “engineered”).

  • metadata (dict[str -> json serializable], optional) – Metadata associated with the series.

  • schema (Woodwork.ColumnSchema, optional) – Typing information to use for the Series instead of performing inference. Any other arguments provided will be ignored. Note that any changes made to the schema object after initialization will propagate to the Series. Similarly, to avoid unintended typing information changes, the same schema object should not be shared between Series.

  • validate (bool, optional) – Whether parameter and data validation should occur. Defaults to True. Warning: Should be set to False only when parameters and data are known to be valid. Any errors resulting from skipping validation with invalid inputs may not be easily understood.