class_docstr: Accepts or displays 2D input through a spreadsheet-like component for dataframes.
  Preprocessing: passes the uploaded spreadsheet data as a {pandas.DataFrame}, {numpy.array}, or {List[List]} depending on `type`
  Postprocessing: expects a {pandas.DataFrame}, {pandas.Styler}, {numpy.array}, {List[List]}, {List}, a {Dict} with keys `data` (and optionally `headers`), or {str} path to a csv, which is rendered in the spreadsheet.
  Examples-format: a {str} filepath to a csv with data, a pandas dataframe, or a list of lists (excluding headers) where each sublist is a row of data.
  Demos: filter_records, matrix_transpose, tax_calculator
code: def process_example(
      self,
      value: pd.DataFrame
      | Styler
      | np.ndarray
      | list
      | list[list]
      | dict
      | str
      | None,
  ):
      if value is None:
          return ""
      value_df_data = self.postprocess(value)
      value_df = pd.DataFrame(
          value_df_data.data, columns=value_df_data.headers
      )
      return value_df.head(n=5).to_dict(orient="split")["data"]
  
imports: from __future__ import annotations
  import warnings
  from typing import Any, Callable, Dict, List, Literal, Optional
  import numpy
  import pandas
  import semantic_version
  from gradio_client.documentation import document, set_documentation_group
  from pandas.io.formats.style import Styler
  from gradio.components import Component
  from gradio.data_classes import GradioModel
  from gradio.events import Events
label_desc: Use image node_id 8 for calling the Dataframe obj's underlying member method code with example usage: obj.process_example(value) and returns: value_df, str