import pandas as pd
1、定義一個字典
data = {'sales_volume': [100, 123, 446, 233, 456], 'month': ['1月', '2月', '3月', '4月', '5月']
, 'product_id': ['1112', '1113', '1114','1115','1116'], 'color':['red', 'red', 'black', 'green', 'black']}
2、將字典放入dataframe數據結構，自動生成一列數據做索引0-4
df = DataFrame(data)
print df
color month product_id sales_volume
0 red 1月 1112 100
1 red 2月 1113 123
2 black 3月 1114 446
3 green 4月 1115 233
4 black 5月 1116 456
3、將dataframe數據處理爲字典格式
keys = list(df.keys())
values = df.values
print keys,values
dicts = [dict(zip(keys, value)) for value in values]
print dicts
[{'color': 'red', 'sales_volume': 100L, 'product_id': '1112', 'month': '1\xe6\x9c\x88'}, {'color': 'red', 'sales_volume': 123L, 'product_id': '1113', 'month': '2\xe6\x9c\x88'}, {'color': 'black', 'sales_volume': 446L, 'product_id': '1114', 'month': '3\xe6\x9c\x88'}, {'color': 'green', 'sales_volume': 233L, 'product_id': '1115', 'month': '4\xe6\x9c\x88'}, {'color': 'black', 'sales_volume': 456L, 'product_id': '1116', 'month': '5\xe6\x9c\x88'}]
4、通過groupy計算和，精確到color
print df.groupby(['product_id', 'color']).sum()
product_id color sales_volume
1112 red 223
1113 black 446
green 233
1116 black 456