code: def split_to_letters(f, c):
      r"""Separate text into distinct characters.
  
      Parameters
      ----------
      f : pandas.DataFrame
          Dataframe containing the column ``c``.
      c : str
          Name of the text column in the dataframe ``f``.
  
      Returns
      -------
      new_feature : pandas.Series
          The array containing the new feature.
  
      Example
      -------
      The value 'abc' becomes 'a b c'.
  
      """
      fc = f[c]
      new_feature = None
      dtype = fc.dtypes
      if dtype == "object":
          fc.fillna(NULLTEXT, inplace=True)
          maxlen = fc.astype(str).str.len().max()
          if maxlen > 1:
              new_feature = fc.apply(lambda x: BSEP.join(list(x)))
      return new_feature
  
imports: from alphapy.calendrical import biz_day_month
  from alphapy.calendrical import biz_day_week
  from alphapy.globals import NULLTEXT
  from alphapy.globals import BSEP, PSEP, USEP
  from alphapy.variables import vexec
  import itertools
  import logging
  import math
  import numpy
  import pandas
label_desc: Use image node_id 42 for calling a global function with example usage: split_to_letters(f, c) and returns: new_feature