woodwork.table_schema.ColumnSchema#

class woodwork.table_schema.ColumnSchema(logical_type=None, semantic_tags=None, use_standard_tags=False, description=None, origin=None, metadata=None, validate=True)[source]#
__init__(logical_type=None, semantic_tags=None, use_standard_tags=False, description=None, origin=None, metadata=None, validate=True)[source]#

Create ColumnSchema

Parameters:
  • logical_type (LogicalType, optional) – The column’s LogicalType.

  • semantic_tags (str, list, set, optional) – The semantic tag(s) specified for the column.

  • use_standard_tags (boolean, optional) – If True, will add standard semantic tags to the column based on the specified logical type if a logical type is defined for the column. Defaults to False.

  • description (str, optional) – User description of the column.

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

  • metadata (dict[str -> json serializable], optional) – Extra metadata provided by the user. The dictionary must contain data types that are JSON serializable such as string, integers, and floats. DataFrame and Series types are not supported.

  • validate (bool, optional) – Whether to perform parameter validation. Defaults to True.

Methods

__init__([logical_type, semantic_tags, ...])

Create ColumnSchema

Attributes

custom_tags

The custom semantic tag(s) specified for the column.

description

Description of the column

is_boolean

Whether the ColumnSchema is a Boolean column

is_categorical

Whether the ColumnSchema is categorical in nature

is_datetime

Whether the ColumnSchema is a Datetime column

is_latlong

Whether the ColumnSchema is a LatLong column

is_natural_language

Whether the ColumnSchema is a Natural Language column

is_numeric

Whether the ColumnSchema is numeric in nature

is_ordinal

Whether the ColumnSchema is a Ordinal column

is_unknown

Whether the ColumnSchema is a Unknown column

metadata

Metadata of the column

origin

Origin of the column