nvtabular.ops.Rename

class nvtabular.ops.Rename(f=None, postfix=None, name=None)

Bases: 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)

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)
export(path, input_schema, output_schema, ...)	Export the class object as a config and all related files to the user defined path.
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
export_name	Provides a clear common english identifier for this operator.
is_subgraph
label
output_dtype
output_properties
output_tags
supported_formats
supports	Returns what kind of data representation this operator supports

transform(col_selector: ColumnSelector, df: DataFrame) → DataFrame

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)