json_normalize JSON 文件，其中包含包含字典的列表（包括示例）

Question

这是我正在使用 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}]

我试图得到一个数据帧在实体ID的水平（提取Amy，并Jon从记录1和Bob，Jon，Jack从记录2）。

但是，我很早就收到了错误。到目前为止，这是我的代码，假设示例 json 保存为sample.json：

data = json.load(open('sample.json'))
test = json_normalize(data, record_path=['Content', 'Story'])

导致此错误：

TypeError: string indices must be integers

我怀疑这是因为 Content.Story 实际上是一个包含字典的列表，而不是字典本身。但我不清楚如何真正克服这一点？

编辑：澄清一下，我最终试图达到实体 ID 的级别（内容 > 故事 > 派生 ID > 实体 > Id）。展示 Content.Story 代码示例只是为了说明我现在在解决这个问题。

Answer 1

json_normalize(data, record_path=[['Content', 'Story']])

那应该工作。