小計和

MultiIndex.from_arrays的解決方案.最后

concat和所有數據幀,

sort_index并添加所有總和：

#replace km/h and convert to int

df.windspeed = df.windspeed.str.replace('km/h','').astype(int)

print (df)

FID admin0 admin1 admin2 windspeed population

0 0 cntry1 state1 city1 60 700

1 1 cntry1 state1 city1 90 210

2 2 cntry1 state1 city2 60 100

3 3 cntry1 state2 city3 60 70

4 4 cntry1 state2 city4 60 180

5 5 cntry1 state2 city4 90 370

6 6 cntry2 state3 city5 60 890

7 7 cntry2 state3 city6 60 120

8 8 cntry2 state3 city6 90 420

9 9 cntry2 state3 city6 120 360

10 10 cntry2 state4 city7 60 740

#pivoting

table = pd.pivot_table(df,

index=["admin0","admin1","admin2"],

columns=["windspeed"],

values=["population"],

fill_value=0)

print (table)

population

windspeed 60 90 120

admin0 admin1 admin2

cntry1 state1 city1 700 210 0

city2 100 0 0

state2 city3 70 0 0

city4 180 370 0

cntry2 state3 city5 890 0 0

city6 120 420 360

state4 city7 740 0 0

#groupby and create sum dataframe by levels 0,1

df1 = table.groupby(level=[0,1]).sum()

df1.index = pd.MultiIndex.from_arrays([df1.index.get_level_values(0),

df1.index.get_level_values(1)+ '_sum',

len(df1.index) * ['']])

print (df1)

population

windspeed 60 90 120

admin0

cntry1 state1_sum 800 210 0

state2_sum 250 370 0

cntry2 state3_sum 1010 420 360

state4_sum 740 0 0

df2 = table.groupby(level=0).sum()

df2.index = pd.MultiIndex.from_arrays([df2.index.values + '_sum',

len(df2.index) * [''],

len(df2.index) * ['']])

print (df2)

population

windspeed 60 90 120

cntry1_sum 1050 580 0

cntry2_sum 1750 420 360

#concat all dataframes together, sort index

df = pd.concat([table, df1, df2]).sort_index(level=[0])

#add km/h to second level in columns

df.columns = pd.MultiIndex.from_arrays([df.columns.get_level_values(0),

df.columns.get_level_values(1).astype(str) + 'km/h'])

#add all sum

df.loc[('All_sum','','')] = table.sum().values

print (df)

population

60km/h 90km/h 120km/h

admin0 admin1 admin2

cntry1 state1 city1 700 210 0

city2 100 0 0

state1_sum 800 210 0

state2 city3 70 0 0

city4 180 370 0

state2_sum 250 370 0

cntry1_sum 1050 580 0

cntry2 state3 city5 890 0 0

city6 120 420 360

state3_sum 1010 420 360

state4 city7 740 0 0

state4_sum 740 0 0

cntry2_sum 1750 420 360

All_sum 2800 1000 360

編輯評論：

def f(x):

print (x)

if (len(x) > 1):

return x.sum()

df1 = table.groupby(level=[0,1]).apply(f).dropna(how='all')

df1.index = pd.MultiIndex.from_arrays([df1.index.get_level_values(0),

df1.index.get_level_values(1)+ '_sum',

len(df1.index) * ['']])

print (df1)

population

windspeed 60 90 120

admin0

cntry1 state1_sum 800.0 210.0 0.0

state2_sum 250.0 370.0 0.0

cntry2 state3_sum 1010.0 420.0 360.0

總結

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