采用：
#if necessary convert TYPE column to string
df['TYPE'] = df['TYPE'].astype(str)
df = df.groupby(["SCENARIO", "STATUS", "TYPE"])['TYPE'].count()
#aggregate sum by first 2 levels
df1 = df.groupby(["SCENARIO", "STATUS"]).sum()
#add 3 level of MultiIndex
df1.index = [df1.index.get_level_values(0),
df1.index.get_level_values(1),
['Total'] * len(df1)]
#thanks MaxU for improving
#df1 = df1.set_index(np.array(['Total'] * len(df1)), append=True)
print (df1)
SCENARIO STATUS
AAA 51 Total 3
53 Total 1
BBB 51 Total 1
CCC 51 Total 1
Name: TYPE, dtype: int64
#join together and sorts
df = pd.concat([df, df1]).sort_index(level=[0,1])
print (df)
SCENARIO STATUS TYPE
AAA 51 1 2
9 1
Total 3
53 228 1
Total 1
BBB 51 43 1
Total 1
CCC 51 187 1
Total 1
Name: TYPE, dtype: int64
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