CODEWITHSUNDEEP
pythonpandas
lsdmctrubey
lsdmctrubey

Reputation: 31

Type Error for Path Data. Must be list or null

I am getting the following error when attempting to convert json data to a dataframe. I have successfully used this same method to convert json to a dataframe with similar data in the same script.

The full error:

TypeError: {'success': True, 'data': {'data1': 1, 'data2': 1, 'data3': 1, 'data4': True, 'data5': 0, 'data6': 0, 'data7': False, 'data8': 'ABC', 'start_date': '2000-04-14', 'end_date': '2000-09-23', 'data9': None, 'add_time': '2000-07-12 23:00:11', 'update_time': '2000-06-1420:18:55', 'data10': 1, 'data11': 'custom', 'data12': None}}

has non list value

{'data1': 1, 'data2': 1, 'data3': 1, 'data4': True, 'data5': 0, 'data6': 0, 'data7': False, 'data8': 'ABC', 'start_date': '2000-04-14', 'end_date': '2000-09-23', 'data9': None, 'add_time': '2000-07-12 23:00:11', 'update_time': '2000-06-1420:18:55', 'data10': 1, 'data11': 'custom', 'data12': None}

for path data. Must be list or null.

the function:

def get_subscriptions(id, df):
subscriptions_params = {'api_token': 'abc'}

subscriptions_headers = {'Content-Type': 'application/json'}

subscriptions_response = requests.get('https://url/{}'.format(id), params=subscriptions_params,
                                  headers=subscriptions_headers)

subscriptions_data = subscriptions_response.json()

subscriptions_temp_df = pd.json_normalize(subscriptions_data, record_path=['data'])

I do the exact same thing with a similar (but actually more complex) piece of data with no problems. An example of the response that works:

{'success': True, 'data': [{'data1': 1, 'data2': {'data3': 1, 'name': 'name', 'email': '[email protected]', 'data4': 0, 'data5': None, 'data6': False, 'data7': 1}, 'data8': {'data9': 1, 'name': 'name', 'email': '[email protected]', 'data10': 0, 'data11': None, 'data12': True, 'data13': 1}, 'data14': {'data15': True, 'name': 'name' .... etc.

this one is actually massive, where as for the one with issues the error includes the full length of the data.

removed the actual data, but did not change the type of data. strings inside single quotes are just other strings. 1s are just other numbers, etc.

any ideas why one succeeds and another fails?

Upvotes: 0

Views: 2474

Answers (1)

lsdmctrubey
lsdmctrubey

Reputation: 31

I do not know what the issue/difference is, but this small change works:

def get_subscriptions(id, df):
    subscriptions_params = {'api_token': 'abc'}

    subscriptions_headers = {'Content-Type': 'application/json'}

    subscriptions_response = requests.get('https://url/{}'.format(id), params=subscriptions_params, headers=subscriptions_headers)

    subscriptions_data = subscriptions_response.json()

    subscriptions_data = subscriptions_data['data']

    subscriptions_temp_df = pd.json_normalize(subscriptions_data)

Upvotes: 0

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