nvtabular.ops.DropLowCardinality

class nvtabular.ops.DropLowCardinality(min_cardinality=2)

Bases: Operator

DropLowCardinality drops low cardinality categorical columns. This requires the cardinality of these columns to be known in the schema - for instance by first encoding these columns using Categorify.

__init__(min_cardinality=2)

Methods

__init__([min_cardinality])
column_mapping(col_selector)	Compute which output columns depend on which input columns
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, ...)	Checks the cardinality of the input columns and drops any categorical columns with cardinality less than the specified minimum.
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)	Selects all non-categorical columns and any categorical columns of at least the minimum cardinality from the dataframe.
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

Selects all non-categorical columns and any categorical columns of at least the minimum cardinality from the dataframe.

Parameters:

• col_selector (ColumnSelector) – The columns to select.

• df (DataFrameType) – The dataframe to transform

Returns:

Dataframe with only the selected columns.

Return type:

DataFrameType

compute_selector(input_schema: Schema, selector: ColumnSelector, parents_selector: ColumnSelector, dependencies_selector: ColumnSelector) → ColumnSelector

Checks the cardinality of the input columns and drops any categorical columns with cardinality less than the specified minimum.

Parameters:

• input_schema (Schema) – The current node’s input schema

• selector (ColumnSelector) – The current node’s selector

• parents_selector (ColumnSelector) – A selector for the output columns of the current node’s parents

• dependencies_selector (ColumnSelector) – A selector for the output columns of the current node’s dependencies

Returns:

Selector that contains all non-categorical columns and any categorical columns of at least the minimum cardinality.

Return type:

ColumnSelector