你能帮我，通过python，json_normalize，把2个数组的json打包吗？
下面是代码：

import json
from pandas.io.json import json_normalize

data5 = {
    "id": "0001",
    "type": "donut",
    "name": "Cake",
    "ppu": 0.55,
    "batters":
        {
            "batter":
                [
                    { "id": "1001", "type": "Regular" },
                    { "id": "1002", "type": "Chocolate" },
                    { "id": "1003", "type": "Blueberry" },
                    { "id": "1004", "type": "Devil's Food" }
                ]
        },
    "topping":
        [
            { "id": "5001", "type": "None" },
            { "id": "5002", "type": "Glazed" },
            { "id": "5005", "type": "Sugar" },
            { "id": "5007", "type": "Powdered Sugar" },
            { "id": "5006", "type": "Chocolate with Sprinkles" },
            { "id": "5003", "type": "Chocolate" },
            { "id": "5004", "type": "Maple" }
        ]
} 

df2 = json_normalize(data5
                      , record_path = ['topping']
                             , meta = ['id', 'type', 'name', 'ppu', 'batters']
                     , record_prefix='_'
                     , errors='ignore'
                   )

这个包"topping"对象，但不包"batters"。要包"batters"可以应用代码：

# parce the part of json string into another dataframe
df3 = json_normalize(data5
              ,record_path = ['batters', 'batter'])

# cross join 2 dataframes
df2['key_'] = 1
df3['key_'] = 1

result = pd.merge(df2, df3, on ='key_').drop("key_", 1)

但这看起来很复杂。是否可以在一个查询中组合上述两个步骤？例如：

df2 = json_normalize(data5
                          , record_path = ['topping', ['batters', 'batter']]
                                 , meta = ['id', 'type', 'name', 'ppu', ]
                         , record_prefix='_'
                         , errors='ignore'
                       )

谢谢你。