pythonテーブル変換(データピボット)

1、データのインポート

import pandas as pd
import numpy as np

import pandas as pd
table = pd.DataFrame({'cust_id':[10001,10001,10002,10002,10003],
                      'type':['Normal','Special_offer',\
                              'Normal','Special_offer','Special_offer'],
                      'Monetary':[3608,420,1894,3503,4567]})

Out[3]: 
   Monetary  cust_id           type
0      3608    10001         Normal
1       420    10001  Special_offer
2      1894    10002         Normal
3      3503    10002  Special_offer
4      4567    10003  Special_offer

表形式変換(データ・ピボット)

result=pd.pivot_table(table,index='cust_id',columns='type',values='Monetary')

Out[5]: 
type     Normal  Special_offer
cust_id                       
10001    3608.0          420.0
10002    1894.0         3503.0
10003       NaN         4567.0

pd.pivot_table(table,index='cust_id',columns='type',values='Monetary',
        fill_value=0,aggfunc='sum')

Out[6]: 
type     Normal  Special_offer
cust_id                       
10001      3608            420
10002      1894           3503
10003         0           4567

table1 = pd.pivot_table(table,index='cust_id',
                        columns='type',
                        values='Monetary',
                        fill_value=0,
                        aggfunc=np.sum).reset_index()

type  cust_id  Normal  Special_offer
0       10001    3608            420
1       10002    1894           3503
2       10003       0           4567

pd.melt(table1,
	id_vars='cust_id',
value_vars=['Normal','Special_offer'],
value_name='Monetary',
var_name='TYPE')
Out[8]: 
   cust_id           TYPE  Monetary
0    10001         Normal      3608
1    10002         Normal      1894
2    10003         Normal         0
3    10001  Special_offer       420
4    10002  Special_offer      3503
5    10003  Special_offer      4567