ValueError:将json作为pandas dataframe读取时的预期对象或值

Question

样本数据:

{
   "_id": "OzE5vaa3p7",
   "categories": [
      {
         "__type": "Pointer",
         "className": "Category",
         "objectId": "nebCwWd2Fr"
      }
   ],
   "isActive": true,
   "imageUrl": "https://firebasestorage.googleapis.com/v0/b/shopgro-1376.appspot.com/o/Barcode%20Data%20Upload%28II%29%2FAnil_puttu_flour_500g.png?alt=media&token=9cf63197-0925-4360-a31a-4675f4f46ae2",
   "barcode": "8908001921015",
   "isFmcg": true,
   "itemName": "Anil puttu flour 500g",
   "mrp": 58,
   "_created_at": "2016-10-02T13:49:03.281Z",
   "_updated_at": "2017-02-22T08:48:09.548Z"
}

{
   "_id": "ENPCL8ph1p",
   "categories": [
      {
         "__type": "Pointer",
         "className": "Category",
         "objectId": "B4nZeUHmVK"
      }
   ],
   "isActive": true,
   "imageUrl": "https://firebasestorage.googleapis.com/v0/b/kirananearby-9eaa8.appspot.com/o/Barcode%20data%20upload%2FYippee_Magic_Masala_Noodles,_70_g.png?alt=media&token=d9e47bd7-f847-4d6f-9460-4be8dbcaae00",
   "barcode": "8901725181222",
   "isFmcg": true,
   "itemName": "Yippee Magic Masala Noodles, 70 G",
   "mrp": 12,
   "_created_at": "2016-10-02T13:49:03.284Z",
   "_updated_at": "2017-02-22T08:48:09.074Z"
}

我试过了:

import pandas as pd
data= pd.read_json('Data.json')

获取错误ValueError:预期的对象或值

也

import json
with open('gdb.json') as datafile:
    data = json.load(datafile)
retail = pd.DataFrame(data)

错误:json.decoder.JSONDecodeError:额外数据:第2行第1列(char 509)

with open('gdb.json') as datafile:
for line in datafile:
    data = json.loads(line)
retail = pd.DataFrame(data)

错误:json.decoder.JSONDecodeError:额外数据:第1行第577行(字符576)

如何将这个json读成大熊猫

Answer 1

我遇到了同样的错误，阅读函数文档并使用不同的参数。

我通过使用下面的一个解决了它，

data= pd.read_json('Data.json', lines=True)

你可以尝试其他的东西，比如

data= pd.read_json('Data.json', lines=True, orient='records')

data= pd.read_json('Data.json', orient=str)

Answer 2

您的 JSON 格式错误。

ValueError: Expected object or value如果您输入错误的文件名，可能会发生。是否Data.json存在？我注意到你使用的其他尝试gdb.json。

确认文件名正确后，您必须修复 JSON。您现在拥有的是两个由空格分隔的断开连接的记录。JSON 中的列表必须是方括号内的有效数组，并用逗号分隔：[{record1}, {record2}, ...]

此外，对于熊猫，您应该将数组放在名为 的根元素下"data"：

{ "data": [ {record1}, {record2}, ... ] }

您的 JSON 最终应如下所示：

{"data":
    [{
        "_id": "OzE5vaa3p7",
        "categories": [
            {
                "__type": "Pointer",
                "className": "Category",
                "objectId": "nebCwWd2Fr"
            }
        ],
        "isActive": true,
        "imageUrl": "https://firebasestorage.googleapis.com/v0/b/shopgro-1376.appspot.com/o/Barcode%20Data%20Upload%28II%29%2FAnil_puttu_flour_500g.png?alt=media&token=9cf63197-0925-4360-a31a-4675f4f46ae2",
        "barcode": "8908001921015",
        "isFmcg": true,
        "itemName": "Anil puttu flour 500g",
        "mrp": 58,
        "_created_at": "2016-10-02T13:49:03.281Z",
        "_updated_at": "2017-02-22T08:48:09.548Z"
    }
    ,
    {
        "_id": "ENPCL8ph1p",
        "categories": [
            {
                "__type": "Pointer",
                "className": "Category",
                "objectId": "B4nZeUHmVK"
            }
        ],
        "isActive": true,
        "imageUrl": "https://firebasestorage.googleapis.com/v0/b/kirananearby-9eaa8.appspot.com/o/Barcode%20data%20upload%2FYippee_Magic_Masala_Noodles,_70_g.png?alt=media&token=d9e47bd7-f847-4d6f-9460-4be8dbcaae00",
        "barcode": "8901725181222",
        "isFmcg": true,
        "itemName": "Yippee Magic Masala Noodles, 70 G",
        "mrp": 12,
        "_created_at": "2016-10-02T13:49:03.284Z",
        "_updated_at": "2017-02-22T08:48:09.074Z"
    }]}

最后，pandas 调用此格式split orientation，因此您必须按如下方式加载它：

{ "data": [ {record1}, {record2}, ... ] }

df 现在包含以下数据框：

{"data":
    [{
        "_id": "OzE5vaa3p7",
        "categories": [
            {
                "__type": "Pointer",
                "className": "Category",
                "objectId": "nebCwWd2Fr"
            }
        ],
        "isActive": true,
        "imageUrl": "https://firebasestorage.googleapis.com/v0/b/shopgro-1376.appspot.com/o/Barcode%20Data%20Upload%28II%29%2FAnil_puttu_flour_500g.png?alt=media&token=9cf63197-0925-4360-a31a-4675f4f46ae2",
        "barcode": "8908001921015",
        "isFmcg": true,
        "itemName": "Anil puttu flour 500g",
        "mrp": 58,
        "_created_at": "2016-10-02T13:49:03.281Z",
        "_updated_at": "2017-02-22T08:48:09.548Z"
    }
    ,
    {
        "_id": "ENPCL8ph1p",
        "categories": [
            {
                "__type": "Pointer",
                "className": "Category",
                "objectId": "B4nZeUHmVK"
            }
        ],
        "isActive": true,
        "imageUrl": "https://firebasestorage.googleapis.com/v0/b/kirananearby-9eaa8.appspot.com/o/Barcode%20data%20upload%2FYippee_Magic_Masala_Noodles,_70_g.png?alt=media&token=d9e47bd7-f847-4d6f-9460-4be8dbcaae00",
        "barcode": "8901725181222",
        "isFmcg": true,
        "itemName": "Yippee Magic Masala Noodles, 70 G",
        "mrp": 12,
        "_created_at": "2016-10-02T13:49:03.284Z",
        "_updated_at": "2017-02-22T08:48:09.074Z"
    }]}

Answer 3

我今天遇到了这个错误消息，在我的例子中，问题是文本文件的编码是 UTF-8-BOM 而不是 UTF-8，这是 read_json() 的默认编码。可以通过指定编码来解决：

data= pd.read_json('Data.json', encoding = 'utf-8-sig')

Answer 4

你应该确保终端目录与文件目录相同（当我发生这个错误时，因为我使用了vscode，对我来说意味着vscode中的终端目录与我想要的python文件不同执行）

Answer 5

我不认为这会是问题，因为它应该是默认的（我认为）。但你尝试过这个吗？添加“r”以指定该文件是只读的。

import json with open('gdb.json', 'r') as datafile: data = json.load(datafile) retail = pd.DataFrame(data)