human
Solve the following python programming problem given the following code:
def cat_to_polar(df, cat_cols, agg_col = None, agg = 'mean', level_width = 0.5) : 
    'Return start and end angles for each index in series.

    Returns:
        df: a `pandas.DataFrame` describing each aggregated wedge

    ' 
    (agg_col, agg) = derive_aggregation (cat_cols, agg_col, agg) 
    def calc_span_proportion(data) : 
        'How much of the circle should be assigned.' 
        return (data / data.sum ()) 
levels_cols = [] 
    starts = [] 
    ends = [] 
    levels = [] 
    agg_values = [] 
    for i in range (0, len (cat_cols)) : 
        level_cols = cat_cols [: (i + 1)] 
        if ((agg_col is not None) and (agg is not None)) : 
            gb = getattr (getattr (df.groupby (level_cols), agg_col), agg) () 
else : 
            cols = [col for col in df.columns if (col != 'index')] 
            gb = df [cols [0]] 
group_level = (i - 1) 
        if (group_level >= 0) : 
            levels.append (gb.groupby (level = group_level).apply (calc_span_proportion)) 
else : 
            levels.append (calc_span_proportion (gb)) 
start_ends = _create_start_end (levels) 
        starts.append (start_ends [0]) 
        ends.append (start_ends [1]) 
        agg_values.append (gb) 
        this_level = start_ends [0].copy () 
        this_level [:] = i 
        levels_cols.append (this_level) 
df = pd.DataFrame ({ 
        'start' : pd.concat (starts), 
        'end' : pd.concat (ends), 
        'level' : pd.concat (df), 
        'values' : pd.concat (agg_values), 
}) 
    if (len (cat_cols) > 1) : 
        idx = df.index.copy ().values 
        for (i, val) in enumerate (df.index) : 
            if (not isinstance (val, tuple)) : 
                val = (val, '') 
idx [i] = val 
df.index = pd.MultiIndex.from_tuples (idx) 
        df.index.names = cat_cols 
        df.sortlevel (inplace = True) 
(inners, outers) = calc_wedge_bounds (df ['level'], level_width) 
    df ['inners'] = inners 
    df ['outers'] = outers 
    return df 

    
    

    Fix the buggy line: 'level' : pd.concat (df) ,
assistant
#Here is Python program to fix the buggy line: 'level' : pd.

'level' : pd.concat (levels_cols) ,