human
Solve the following python programming problem given the following code:
def _flex_binary_moment(arg1, arg2, f, pairwise = False) : 
    from pandas import Series, DataFrame, Panel 
    if (not (isinstance (arg1, (np.ndarray, Series, DataFrame)) and isinstance (arg2, (np.ndarray, Series, DataFrame)))) : 
        raise TypeError ('arguments to moment function must be of type np.ndarray/Series/DataFrame') 
if (isinstance (arg1, (np.ndarray, Series)) and isinstance (arg2, (np.ndarray, Series))) : 
        (X, Y) = _prep_binary (arg1, arg2) 
        return f (X, Y) 
else : 
        if isinstance (arg1, DataFrame) : 
            def dataframe_from_int_dict(data, frame_template) : 
                result = DataFrame (data, index = frame_template.index) 
                if (len (result.columns) > 0) : 
                    result.columns = frame_template.columns [result.columns] 
return result 
results = { 
                
} 
            if isinstance (arg2, DataFrame) : 
                if (pairwise is False) : 
                    if (arg1 is arg2) : 
                        for (i, col) in enumerate (arg1.columns) : 
                            results [i] = f (arg1.iloc [:, i], pairwise.iloc [:, i]) 
return dataframe_from_int_dict (results, arg1) 
else : 
                        if (not arg1.columns.is_unique) : 
                            raise ValueError ("'arg1' columns are not unique") 
if (not arg2.columns.is_unique) : 
                            raise ValueError ("'arg2' columns are not unique") 
(X, Y) = arg1.align (arg2, join = 'outer') 
                        X = (X + (0 * Y)) 
                        Y = (Y + (0 * X)) 
                        res_columns = arg1.columns.union (arg2.columns) 
                        for col in res_columns : 
                            if ((col in X) and (col in Y)) : 
                                results [col] = f (X [col], Y [col]) 
return DataFrame (results, index = X.index, columns = res_columns) 
else : 
                    if (pairwise is True) : 
                        results = defaultdict (dict) 
                        for...

    
    

    Fix the buggy line: results [i] = f (arg1.iloc [:, i], pairwise.iloc [:, i])
assistant
#Here is Python code to fix the buggy line: results [i] = f (arg1.

results [i] = f (arg1.iloc [:, i], arg2.iloc [:, i])