class_docstr: Python interface for VegaFusion DataFrame
docstr: Computes a layout of stacking groups of values
  
  See: https://vega.github.io/vega/docs/transforms/stack/
  
  :param field: Column that determines stack height
  :param orderby: Criteria for sorting values within each stack
  :param groupby: List of columns by which to partition data into separate stacks
  :param start_field: Name of output stack start column
  :param stop_field: Name of output stack stop column
  :param mode: Stack mode. One of: "zero", "center", "normalize"
  :return:
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code: def stack(
      self,
      field: str,
      orderby: List[LogicalExprNode],
      groupby: List[str],
      start_field: str,
      stop_field: str,
      mode: Literal["zero", "center", "normalize"],
  ) -> "DataFrameDataset":
      """
      Computes a layout of stacking groups of values
  
      See: https://vega.github.io/vega/docs/transforms/stack/
  
      :param field: Column that determines stack height
      :param orderby: Criteria for sorting values within each stack
      :param groupby: List of columns by which to partition data into separate stacks
      :param start_field: Name of output stack start column
      :param stop_field: Name of output stack stop column
      :param mode: Stack mode. One of: "zero", "center", "normalize"
      :return:
      """
      raise DataFrameOperationNotSupportedError()
  
imports: from abc import ABC, abstractmethod
  import pyarrow
  from vegafusion.proto.datafusion_pb2 import LogicalExprNode
  from typing import Optional, List, Literal, Union, Any
label_desc: Use image node_id 12 for calling the DataFrameDataset obj's underlying member method code with example usage: obj.stack(field, orderby, groupby, start_field, stop_field, mode) without return types