merlin.schema.Schema#

class merlin.schema.Schema(column_schemas=None)[source]#

Bases: object

A collection of column schemas for a dataset.

__init__(column_schemas=None)[source]#

Methods

`__init__`([column_schemas])
`apply`(selector)
`apply_inverse`(selector)
`copy`()	Return a copy of the schema
`excluding`(selector)	Select non-matching columns from this Schema object using a ColumnSelector
`excluding_by_name`(col_names)	Remove columns from this Schema object by name
`excluding_by_tag`(tags[, pred_fn])	Remove columns from the schema that match ANY of the supplied tags.
`get`(col_name[, default])	Get a ColumnSchema by name
`remove_by_tag`(tags[, pred_fn])
`remove_col`(col_name)	Remove a column from this Schema object by name
`select`(selector)	Select matching columns from this Schema object using a ColumnSelector
`select_by_name`(names)	Select matching columns from this Schema object using a list of column names
`select_by_tag`(tags[, pred_fn])	Select columns from this Schema that match ANY of the supplied tags.
`to_pandas`()	Convert this Schema object to a pandas DataFrame
`without`(col_names)

Attributes

`column_names`
`first`	Returns the first ColumnSchema in the Schema.

property column_names#

select(selector) → Schema[source]#

Select matching columns from this Schema object using a ColumnSelector

Parameters:: selector (ColumnSelector) – Selector that describes which columns match
Returns:: New object containing only the ColumnSchemas of selected columns
Return type:: Schema

apply(selector) → Schema[source]#

excluding(selector) → Schema[source]#

Select non-matching columns from this Schema object using a ColumnSelector

Parameters:: selector (ColumnSelector) – Selector that describes which columns match
Returns:: New object containing only the ColumnSchemas of selected columns
Return type:: Schema

apply_inverse(selector) → Schema[source]#

select_by_tag(tags: str | Tags | List[str | Tags], pred_fn=None) → Schema[source]#

Select columns from this Schema that match ANY of the supplied tags.

Parameters:

tags (List[Union[str, Tags]] :) – List of tags that describes which columns match
pred_fn (any or all) – Predicate function that decides if the column should be selected. Receives iterable of bool values indicating whether each of the provided tags is present on a column schema. Returning True selects this column, False will not return that column.

Returns:

New object containing only the ColumnSchemas of selected columns

Return type:

Schema

excluding_by_tag(tags, pred_fn=None) → Schema[source]#

Remove columns from the schema that match ANY of the supplied tags.

Parameters:

tags (_type_) – List of tags that describes which columns remove
pred_fn (any or all, optional, by default None (ANY)) – Predicate function that decides if a column should be selected. all can be provided to remove columns that contain ALL the tags provided

Returns:

New Schema containing only the columns that don’t contain the provided tags

Return type:

Schema

remove_by_tag(tags, pred_fn=None) → Schema[source]#

select_by_name(names: List[str]) → Schema[source]#

Select matching columns from this Schema object using a list of column names

Parameters:: names (List[str] :) – List of column names that describes which columns match
Returns:: New object containing only the ColumnSchemas of selected columns
Return type:: Schema

excluding_by_name(col_names: List[str])[source]#

Remove columns from this Schema object by name

Parameters:: col_names (List[str]) – Names of the column to remove
Returns:: New Schema object after the columns are removed
Return type:: Schema

remove_col(col_name: str) → Schema[source]#

Remove a column from this Schema object by name

Parameters:: col_name (str) – Name of the column to remove
Returns:: This Schema object after the column is removed
Return type:: Schema

without(col_names: List[str]) → Schema[source]#

get(col_name: str, default: ColumnSchema | None = None) → ColumnSchema[source]#

Get a ColumnSchema by name

Parameters:

col_name (str) – Name of the column to get
default (ColumnSchema :) –

Default value to return if column is not found.
(Default value = None)

Returns:

Retrieved column schema (or default value, if not found)

Return type:

ColumnSchema

property first: ColumnSchema#

Returns the first ColumnSchema in the Schema. Useful for cases where you select down to a single column via select_by_name or select_by_tag, and just want the value

Returns:: The first column schema present in this Schema object
Return type:: ColumnSchema
Raises:: ValueError – If this Schema object contains no column schemas

to_pandas() → DataFrame[source]#

Convert this Schema object to a pandas DataFrame

Returns:: DataFrame containing the column schemas in this Schema object
Return type:: pd.DataFrame

copy() → Schema[source]#: Return a copy of the schema

merlin.schema.Schema

Contents

merlin.schema.Schema#