human
Solve the following python programming problem given the following code:
def _wrap_result(self, result, use_codes = True, name = None, expand = None) : 
    from pandas.core.index import Index, MultiIndex 
    if (use_codes and self._is_categorical) : 
        result = take_1d (result, cons_row._orig.cat.codes) 
if ((not hasattr (result, 'ndim')) or (not hasattr (result, 'dtype'))) : 
        return result 
assert (result.ndim < 3) 
    if (expand is None) : 
        expand = (False if (result.ndim == 1) else True) 
else : 
        if ((expand is True) and (not isinstance (self._orig, Index))) : 
            def cons_row(x) : 
                if is_list_like (x) : 
                    return x 
else : 
                    return [x] 
result = [cons_row (x) for x in result] 
if (not isinstance (expand, bool)) : 
        raise ValueError ('expand must be True or False') 
if (expand is False) : 
        if (name is None) : 
            name = getattr (result, 'name', None) 
if (name is None) : 
            name = self._orig.name 
if isinstance (self._orig, Index) : 
        if is_bool_dtype (result) : 
            return result 
if expand : 
            result = list (result) 
            return MultiIndex.from_tuples (result, names = name) 
else : 
            return Index (result, name = name) 
else : 
        index = self._orig.index 
        if expand : 
            cons = self._orig._constructor_expanddim 
            return cons (result, columns = name, index = index) 
else : 
            cons = self._orig._constructor 
            return cons (result, name = name, index = index) 

    
    

    Fix the buggy line: result = take_1d (result, cons_row._orig.cat.codes)
assistant
#Here is Python program to fix the buggy line: result = take_1d (result, cons_row.

result = take_1d (result, self._orig.cat.codes)