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 __validate_headers(headers: list[str] | None, col_count: int):
      if headers is not None and len(headers) != col_count:
          raise ValueError(
              f"The length of the headers list must be equal to the col_count int.\n"
              f"The column count is set to {col_count} but `headers` has {len(headers)} items. "
              f"Check the values passed to `col_count` and `headers`."
          )
  
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 7 for calling the Dataframe obj's underlying member method code with example usage: obj.__validate_headers(headers, col_count) without return types