docstr: Iterate through the lines and remove any that are
  either empty or contain only one whitespace value
  
  Parameters
  ----------
  lines : list of list of Scalars
      The array of lines that we are to filter.
  
  Returns
  -------
  filtered_lines : list of list of Scalars
      The same array of lines with the "empty" ones removed.
docstr_tok: ["Iterate","through","the","lines","and","remove","any","that","are","either","empty","or","contain","only","one","whitespace","value","Parameters","--","--","--","--","--","lines",":","list","of","list","of","Scalars","The","array","of","lines","that","we","are","to","filter",".","Returns","--","--","--","-","filtered_lines",":","list","of","list","of","Scalars","The","same","array","of","lines","with","the","``","empty","''","ones","removed","."]
code: def _remove_empty_lines(self, lines: list[list[T]]) -> list[list[T]]:
      """
      Iterate through the lines and remove any that are
      either empty or contain only one whitespace value
  
      Parameters
      ----------
      lines : list of list of Scalars
          The array of lines that we are to filter.
  
      Returns
      -------
      filtered_lines : list of list of Scalars
          The same array of lines with the "empty" ones removed.
      """
      # Remove empty lines and lines with only one whitespace value
      ret = [
          line
          for line in lines
          if (
              len(line) > 1
              or len(line) == 1
              and (not isinstance(line[0], str) or line[0].strip())
          )
      ]
      return ret
  
imports: from __future__ import annotations
  from collections import abc, defaultdict
  import csv
  from io import StringIO
  import re
  from typing import IO, TYPE_CHECKING, DefaultDict, Literal, cast
  import warnings
  import numpy
  from pandas._libs import lib
  from pandas.errors import EmptyDataError, ParserError, ParserWarning
  from pandas.util._decorators import cache_readonly
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import is_bool_dtype, is_integer, is_numeric_dtype
  from pandas.core.dtypes.inference import is_dict_like
  from pandas.io.common import dedup_names, is_potential_multi_index
  from pandas.io.parsers.base_parser import ParserBase, parser_defaults
label_desc: Use image node_id 19 for calling the PythonParser obj's underlying member method code with example usage: obj._remove_empty_lines(lines) and returns: ret