ValueError: expected object or value when reading json as pandas dataframe

I got the same error, read the function documentation and played around with different parameters.

I solved it with the one below,

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

You can try other things like

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

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

Your JSON is mangled.

ValueError: Expected object or value

can happen if you misspelled the filename. Does it exist Data.json

? I noticed that for your other attempts, you used gdb.json

.

Once you confirm that the filename is correct, you should correct your JSON. You now have two unrelated records separated by a space. Lists in JSON must be valid arrays in square brackets and separated by commas:[{record1}, {record2}, ...]

Also, for pandas, you have to put your array on the root element named "data"

:

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

      

        
        
        
      

    

Your JSON should look like this:

{"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"
    }]}

      

        
        
        
      

    

Finally, pandas calls this format split orientation

, so you have to load it like this:

df = pd.read_json('gdb.json', orient='split')

      

        
        
        
      

    

df

now contains the following dataframe:

          _id                                                   categories  isActive                                                     imageUrl        barcode  isFmcg                           itemName  mrp                      _created_at                      _updated_at
0  OzE5vaa3p7  [{'__type': 'Pointer', 'className': 'Category', 'objectI...      True  https://firebasestorage.googleapis.com/v0/b/shopgro-1376...  8908001921015    True              Anil puttu flour 500g   58 2016-10-02 13:49:03.281000+00:00 2017-02-22 08:48:09.548000+00:00
1  ENPCL8ph1p  [{'__type': 'Pointer', 'className': 'Category', 'objectI...      True  https://firebasestorage.googleapis.com/v0/b/kirananearby...  8901725181222    True  Yippee Magic Masala Noodles, 70 G   12 2016-10-02 13:49:03.284000+00:00 2017-02-22 08:48:09.074000+00:00


      

        
        
        
      

    

make your way easy, it will be helpful to read the data. in the meantime, just put your file on your desktop and point that path to read data. It works.