code: def _read_csv_with_offset_pandas_on_ray(
      fname, num_splits, start, end, kwargs, header
  ):  # pragma: no cover
      
      index_col = kwargs.get("index_col", None)
      bio = file_open(fname, "rb")
      bio.seek(start)
      to_read = header + bio.read(end - start)
      bio.close()
      pandas_df = pandas.read_csv(BytesIO(to_read), **kwargs)
      pandas_df.columns = pandas.RangeIndex(len(pandas_df.columns))
      if index_col is not None:
          index = pandas_df.index
          # Partitions must have RangeIndex
          pandas_df.index = pandas.RangeIndex(0, len(pandas_df))
      else:
          # We will use the lengths to build the index if we are not given an
          # `index_col`.
          index = len(pandas_df)
      return _split_result_for_readers(1, num_splits, pandas_df) + [index]
docs: Use a Ray task to read a chunk of a CSV into a Pandas DataFrame.
  
      Note: Ray functions are not detected by codecov (thus pragma: no cover)
  
      Args:
          fname: The filename of the file to open.
          num_splits: The number of splits (partitions) to separate the DataFrame into.
          start: The start byte offset.
          end: The end byte offset.
          kwargs: The kwargs for the Pandas `read_csv` function.
          header: The header of the file.
  
      Returns:
           A list containing the split Pandas DataFrames and the Index as the last
              element. If there is not `index_col` set, then we just return the length.
              This is used to determine the total length of the DataFrame to build a
              default Index.