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python json nested

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Accepted Answer
March 30, 2025 Score: 0 Rep: 148,941 Quality: High Completeness: 60%

I don't know what exactly you expect in output but if you want every item in new row then you could use normal code with for-loop for this.

orderlist = {
    "return": {
        "statusprocessing": "3",
        "status": "OK",
        "order": {
            "id": "872102042",
            "number": "123831",
            "dateorder": "dd/mm/yyyy",
             "itens": [
                {
                    "item": {
                        "idproduct": "684451795",
                        "code": "VPOR",
                        "description": "Product 1",
                        "unit": "Un",
                        "quantity": "1.00",
                        "value": "31.76"
                    }
                },
                {
                    "item": {
                        "idproduct": "684451091",
                        "code": "VSAP",
                        "description": "Product 2",
                        "unit": "Un",
                        "quantity": "1.00",
                        "value": "31.76"
                    }
                }
            ]
        }
    }
}
import pandas as pd
data = []
order = orderlist['return']['order']
for iten in order['itens']:
    for key, val in iten.items():
        row = {
            #'key': key, 
            'id': order['id'], 
            'dateorder': order['dateorder'], 
            'number': order['number'], 
            'idproduct': val['idproduct'],
            #'code': val['code'],
            #'description': val['description'],
            #'quantity': val['quantity'],
            #'value': val['value'],
        }
        data.append(row)
df = pd.DataFrame(data)
print(df)

Result:

          id  dateorder  number idproduct
0  872102042  dd/mm/yyyy  123831  684451795
1  872102042  dd/mm/yyyy  123831  684451091

If you need other information in rows then you should show it in question.

March 31, 2025 Score: 1 Rep: 29,144 Quality: Medium Completeness: 60%

You're code is fine. You are getting the data, perhaps you just wanted to specify which columns to keep (or maybe rename)?

import json
import pandas as pd
data = '''   { "return": {
        "statusprocessing": "3",
        "status": "OK",
        "order": {
            "id": "872102042",
            "number": "123831",
            "dateorder": "dd/mm/yyyy",
             "itens": [
                {
                    "item": {
                        "idproduct": "684451795",
                        "code": "VPOR",
                        "description": "Product 1",
                        "unit": "Un",
                        "quantity": "1.00",
                        "value": "31.76"
                    }
                },
                {
                    "item": {
                        "idproduct": "684451091",
                        "code": "VSAP",
                        "description": "Product 2",
                        "unit": "Un",
                        "quantity": "1.00",
                        "value": "31.76"
                    }
                }
            ]
        }
    }
}'''
orderlist = json.loads(data)
df = pd.jsonnormalize(orderlist, 
                       recordpath= ["return", "order", "itens"],
                       meta=[["return", "order", "id"], ["return", "order", "number"], ["return", "order", "dateorder"]])
df = df[['return.order.id', 'return.order.number', 'return.order.dateorder', 'item.idproduct']]

Output:

print(df)
  return.order.id return.order.number return.order.dateorder item.description
0       872102042              123831              dd/mm/yyyy        Product 1
1       872102042              123831              dd/mm/yyyy        Product 2