Question

（最初来自previous question，但针对更笼统的问题进行了重新构架）

这是我正在处理的2条记录的示例json文件：

[{"Time":"2016-01-10",
"ID"
:13567,
"Content":{
    "Event":"UPDATE",
    "Id":{"EventID":"ABCDEFG"},
    "Story":[{
        "@ContentCat":"News",
        "Body":"Related Meeting Memo: Engagement with target firm for potential M&A.  Please be on call this weekend for news updates.",
        "BodyTextType":"PLAIN_TEXT",
        "DerivedId":{"Entity":[{"Id":"Amy","Score":70}, {"Id":"Jon","Score":70}]},
        "DerivedTopics":{"Topics":[
                            {"Id":"Meeting","Score":70},
                            {"Id":"Performance","Score":70},
                            {"Id":"Engagement","Score":100},
                            {"Id":"Salary","Score":70},
                            {"Id":"Career","Score":100}]
                        },
        "HotLevel":0,
        "LanguageString":"ENGLISH",
        "Metadata":{"ClassNum":50,
                    "Headline":"Attn: Weekend",
                    "WireId":2035,
                    "WireName":"IIS"},
        "Version":"Original"}
                ]},
"yyyymmdd":"20160110",
"month":201601},
{"Time":"2016-01-12",
"ID":13568,
"Content":{
    "Event":"DEAL",
    "Id":{"EventID":"ABCDEFG2"},
    "Story":[{
        "@ContentCat":"Details",
        "Body":"Test email contents",
        "BodyTextType":"PLAIN_TEXT",
        "DerivedId":{"Entity":[{"Id":"Bob","Score":100}, {"Id":"Jon","Score":70}, {"Id":"Jack","Score":60}]},
        "DerivedTopics":{"Topics":[
                            {"Id":"Meeting","Score":70},
                            {"Id":"Engagement","Score":100},
                            {"Id":"Salary","Score":70},
                            {"Id":"Career","Score":100}]
                        },
        "HotLevel":0,
        "LanguageString":"ENGLISH",
        "Metadata":{"ClassNum":70,
                    "Headline":"Attn: Weekend",
                    "WireId":2037,
                    "WireName":"IIS"},
        "Version":"Original"}
                ]},
"yyyymmdd":"20160112",
"month":201602}]

我正在尝试获取实体ID级别的数据帧（从记录1和Amy，Jon，{{提取Bob和Jon 1}}（来自记录2）。我该怎么做呢？要澄清的是，这些级别是（内容>故事>派生ID>实体> ID）

Answer 1

使用list comprehension，您可以进入该结构，例如：

with open('test.json', 'rU') as f:
    data = json.load(f)

df = pd.DataFrame(sum([i['Content']['Story'][0]['DerivedId']['Entity']
                       for i in data], []))

print(df)

或者，如果您有大量数据并且不想做笨拙的sum()，请使用itertools.chain.from_iterable，例如：

import itertools as it
df = pd.DataFrame.from_records(it.chain.from_iterable(
    i['Content']['Story'][0]['DerivedId']['Entity'] for i in data))

结果：

     Id  Score
0   Amy     70
1   Jon     70
2   Bob    100
3   Jon     70
4  Jack     60

json_normalize JSON文件，其中包含字典的多级列表（包括示例）

1 个答案:

结果：