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]