code: def test_to_csv_from_csv_categorical(self):
      # CSV with categoricals should result in the same output
      # as when one would add a "normal" Series/DataFrame.
      s = Series(
          pd.Categorical(["a", "b", "b", "a", "a", "c", "c", "c"])
      )
      s2 = Series(["a", "b", "b", "a", "a", "c", "c", "c"])
      res = StringIO()
  
      s.to_csv(res, header=False)
      exp = StringIO()
  
      s2.to_csv(exp, header=False)
      assert res.getvalue() == exp.getvalue()
  
      df = DataFrame({"s": s})
      df2 = DataFrame({"s": s2})
  
      res = StringIO()
      df.to_csv(res)
  
      exp = StringIO()
      df2.to_csv(exp)
  
      assert res.getvalue() == exp.getvalue()
  
imports: import csv
  from io import StringIO
  import os
  import numpy
  import pytest
  from pandas.errors import ParserError
  import pandas
  from pandas import DataFrame, Index, MultiIndex, NaT, Series, Timestamp, date_range, period_range, read_csv, to_datetime
  import pandas._testing
  import pandas.core.common
  from pandas.io.common import get_handle
label_desc: Use image node_id 42 for calling the TestDataFrameToCSV obj's underlying member method code with example usage: obj.test_to_csv_from_csv_categorical() without return types