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_counts(count, default=3) -> tuple[int, str]:
      if count is None:
          return (default, "dynamic")
      if isinstance(count, (int, float)):
          return (int(count), "dynamic")
      else:
          return count
  
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 6 for calling the Dataframe obj's underlying member method code with example usage: obj.__process_counts(count, default) and returns: default,  str, int,  str, count