Converting from json to dataframe to sql

I'm trying to save all the json data to the sql database and I'm using python so I decided to use pandas.
Part of the JSON:

{
"stores": [
    {
        "ID": "123456",
        "name": "Store 1",
        "status": "Active",
        "date": "2019-03-28T15:20:00Z",
        "tagIDs": null,
        "location": {
            "cityID": 2,
            "countryID": 4,
            "geoLocation": {
                "latitude": 1.13121,
                "longitude": 103.4324231
            },
            "postcode": "123456",
            "address": ""
        },
        "new": false
    },
    {
        "ID": "223456",
        "name": "Store 2",
        "status": "Active",
        "date": "2020-03-28T15:20:00Z",
        "tagIDs": [
            12,
            35
        ],
        "location": {
            "cityID": 21,
            "countryID": 5,
            "geoLocation": {
                "latitude": 1.12512,
                "longitude": 103.23342
            },
            "postcode": "223456",
            "address": ""
        },
        "new": true
    }
]

}

My Code:

response = requests.get(.....)
result = response.text
data = json.loads(result)
df = pd.json_normalize(data["store"])
.....

db_connection = sqlalchemy.create_engine(.....)
df.to_sql(con=db_connection, name="store", if_exists="append" )

Error: _mysql_connector.MySQLInterfaceError: Python type list cannot be converted
How I want the dataframe to actually look like:

     ID          tagIDs             date
0   123456        []         2020-04-23T09:32:26Z               
1   223456      [12,35]      2019-05-24T03:21:39Z                 
2   323456     [709,1493]    2019-03-28T15:38:39Z 

I tried using different dataframes & json objects so far and they all work. So I discovered the issue is with the json object. Without the "tagIDs", everything else works fine.
I was thinking maybe if I converted the object to a string it can be parsed to sql but it didn't work either. How do I change the tagIDs such that I can parse everything to sql? Or is there another more efficient way to do this?