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