nvtabular.ops.Rename

class nvtabular.ops.Rename(f=None, postfix=None, name=None)[source]

Bases: nvtabular.ops.operator.Operator

This operation renames columns by one of several methods:

using a user defined lambda function to transform column names

appending a postfix string to every column name

renaming a single column to a single fixed string

Example usage:

# Rename columns after LogOp
cont_features = cont_names >> nvt.ops.LogOp() >> Rename(postfix='_log')
processor = nvt.Workflow(cont_features)

Parameters

f (callable, optional) – Function that takes a column name and returns a new column name
postfix (str, optional) – If set each column name in the output will have this string appended to it
name (str, optional) – If set, a single input column will be renamed to this string

__init__(f=None, postfix=None, name=None)[source]

Methods

`__init__`([f, postfix, name])
`column_mapping`(col_selector)
`compute_column_schema`(col_name, input_schema)
`compute_input_schema`(root_schema, …)	Given the schemas coming from upstream sources and a column selector for the input columns, returns a set of schemas for the input columns this operator will use
`compute_output_schema`(input_schema, col_selector)	Given a set of schemas and a column selector for the input columns, returns a set of schemas for the transformed columns this operator will produce
`compute_selector`(input_schema, selector[, …])	Provides a hook method for sub-classes to override to implement custom column selection logic.
`create_node`(selector)
`inference_initialize`(col_selector, model_config)	Configures this operator for use in inference.
`load_artifacts`([artifact_path])	Load artifacts from disk required for operator function.
`output_column_names`(col_selector)	Given a set of columns names returns the names of the transformed columns this operator will produce
`save_artifacts`([artifact_path])	Save artifacts required to be reload operator state from disk
`transform`(col_selector, df)	Transform the dataframe by applying this operator to the set of input columns
`validate_schemas`(parents_schema, …[, …])	Provides a hook method that sub-classes can override to implement schema validation logic.

Attributes

`dependencies`	Defines an optional list of column dependencies for this operator.
`dynamic_dtypes`
`is_subgraph`
`label`
`output_dtype`
`output_properties`
`output_tags`
`supported_formats`
`supports`	Returns what kind of data representation this operator supports

transform(col_selector: merlin.dag.selector.ColumnSelector, df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]

Transform the dataframe by applying this operator to the set of input columns

Parameters

columns (list of str or list of list of str) – The columns to apply this operator to
df (Dataframe) – A pandas or cudf dataframe that this operator will work on

Returns

Returns a transformed dataframe for this operator

Return type

DataFrame

column_mapping(col_selector)[source]