小编典典

将Json嵌套到具有特定格式的Pandas DataFrame

json

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它。

文件= C:\ scoring_model \ json.js(“文件”的内容如下)

{
"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,同一行上的所有值都试图对此问题进行最佳格式化):

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

我查看了有关此主题的所有其他问题,尝试了各种方法将Json文件加载到熊猫中

`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过pd.Panel()PythonPandas:如何在数据框的列中拆分已排序的字典

[yo =f.readlines()]的数据帧结果与考虑过尝试基于(“”)拆分每个单元格的内容,并找到了一种将拆分后的内容放入不同列的方法,但到目前为止还算不上成功。非常感谢您的专业知识。先感谢您。


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2020-07-27

共1个答案

小编典典

如果您将整个json作为字典(或列表)加载(例如使用)json.load,则可以使用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
2020-07-27