具有特定格式的嵌套 Json 到 pandas DataFrame

Nested Json to pandas DataFrame with specific format

我需要在 pandas DataFrame 中以某种格式格式化 Json 文件的内容,以便我可以 运行 pandassql转换数据并通过评分模型运行。

file = C:\scoring_model\json.js ('file'内容如下)

{
"response":{
  "version":"1.1",
  "token":"dsfgf",
   "body":{
     "customer":{
         "customer_id":"1234567",
         "verified":"true"
       },
     "contact":{
         "email":"mr@abc.com",
         "mobile_number":"0123456789"
      },
     "personal":{
         "gender": "m",
         "title":"Dr.",
         "last_name":"Muster",
         "first_name":"Max",
         "family_status":"single",
         "dob":"1985-12-23",
     }
   }
 }

我需要数据框看起来像这样(显然所有值都在同一行,针对这个问题尝试尽可能地格式化):

version | token | customer_id | verified | email      | mobile_number | gender |
1.1     | dsfgf | 1234567     | true     | mr@abc.com | 0123456789    | m      |

title | last_name | first_name |family_status | dob
Dr.   | Muster    | Max        | single       | 23.12.1985

我查看了关于该主题的所有其他问题,尝试了各种方法将 Json 文件加载到 pandas

`with open(r'C:\scoring_model\json.js', 'r') as f:`
    c = pd.read_json(f.read())

 `with open(r'C:\scoring_model\json.js', 'r') as f:`
    c = f.readlines()

在此解决方案中尝试了 pd.Panel()

使用 [yo = f.readlines()] 的数据框结果考虑尝试根据 ("") 拆分每个单元格的内容并找到一种方法将拆分的内容放入不同的列但没有运气迄今为止。非常感谢您的专业知识。提前谢谢你。

如果您将整个 json 作为字典(或列表)加载,例如使用 json.load,您可以使用 json_normalize:

In [11]: d = {"response": {"body": {"contact": {"email": "mr@abc.com", "mobile_number": "0123456789"}, "personal": {"last_name": "Muster", "gender": "m", "first_name": "Max", "dob": "1985-12-23", "family_status": "single", "title": "Dr."}, "customer": {"verified": "true", "customer_id": "1234567"}}, "token": "dsfgf", "version": "1.1"}}

In [12]: df = pd.json_normalize(d)

In [13]: df.columns = df.columns.map(lambda x: x.split(".")[-1])

In [14]: df
Out[14]:
        email mobile_number customer_id verified         dob family_status first_name gender last_name title  token version
0  mr@abc.com    0123456789     1234567     true  1985-12-23        single        Max      m    Muster   Dr.  dsfgf     1.1