docs: def fuzzy_get_value(obj, approximate_key, default=None, **kwargs):
      """ Like fuzzy_get, but assume the obj is dict-like and return the value without the key
  
      Notes:
        Argument order is in reverse order relative to `fuzzywuzzy.process.extractOne()`
          but in the same order as get(self, key) method on dicts
  
      Arguments:
        obj (dict-like): object to run the get method on using the key that is most similar to one within the dict
        approximate_key (str): key to look for a fuzzy match within the dict keys
        default (obj): the value to return if a similar key cannote be found in the `possible_keys`
        similarity (str): fractional similiarity between the approximate_key and the dict key
          (0.9 means 90% of characters must be identical)
        tuple_joiner (str): Character to use as delimitter/joiner between tuple elements.
          Used to create keys of any tuples to be able to use fuzzywuzzy string matching on it.
        key_and_value (bool): Whether to return both the key and its value (True) or just the value (False).
          Default is the same behavior as dict.get (i.e. key_and_value=False)
        dict_keys (list of str): if you already have a set of keys to search, this will save this funciton
          a little time and RAM
  
      Examples:
        >>> fuzzy_get_value({'seller': 2.7, 'sailor': set('e')}, 'sail') == set(['e'])
        True
        >>> fuzzy_get_value({'seller': 2.7, 'sailor': set('e'), 'camera': object()}, 'SLR')
        2.7
        >>> fuzzy_get_value({'seller': 2.7, 'sailor': set('e'), 'camera': object()}, 'I') == set(['e'])
        True
        >>> fuzzy_get_value({'word': tuple('word'), 'noun': tuple('noun')}, 'woh!', similarity=.3)
        ('w', 'o', 'r', 'd')
        >>> df = pd.DataFrame(np.arange(6*2).reshape(2,6), columns=('alpha','beta','omega','begin','life','end'))
        >>> fuzzy_get_value(df, 'life')[0], fuzzy_get(df, 'omega')[0]
        (4, 2)
      """
      dict_obj = OrderedDict(obj)
      try:
          return dict_obj[list(dict_obj.keys())[int(approximate_key)]]
      except (ValueError, IndexError):
          pass
      return fuzzy_get(dict_obj, approximate_key, key_and_value=False, **kwargs)