Getting a empty dataframe using pandas

Question

I'm using pandas to create a dataframe in python, but I get only the columns when I try this.

This is my code:

def suitecrm_get_account_data(account_id):
    suitecrm_acces_token()
    url = base_url+'/V8/module/Accounts/'+account_id
    headers = {'Authorization': 'Bearer '+suitecrm_acces_token.access_token}
    response= requests.request("GET", url , headers=headers)
    account_attributes = json.loads(response.text)['data']['attributes']
    print(account_attributes)
    df = pd.DataFrame(account_attributes)
    print(df)

print(account_attributes)
{'name': '5D Investments', 'date_entered': '2021-12-13T15:17:00+00:00', 'date_modified': '2021-12-13T15:17:00+00:00', 'modified_user_id': '1', 'modified_by_name': 'Administrator', 'created_by': '1', 'created_by_name': 'Administrator', 'description': '', 'deleted': '0', 'created_by_link': '', 'modified_user_link': '', 'assigned_user_id': '1', 'assigned_user_name': 'Administrator', 'assigned_user_link': '', 'SecurityGroups': '', 'account_type': 'Customer', 'industry': 'Other', 'annual_revenue': '', 'phone_fax': '', 'billing_address_street': '48920 San Carlos Ave', 'billing_address_street_2': '', 'billing_address_street_3': '', 'billing_address_street_4': '', 'billing_address_city': 'Persistance', 'billing_address_state': 'NY', 'billing_address_postalcode': '', 'billing_address_country': 'USA', 'rating': '', 'phone_office': '(893) 969-8036', 'phone_alternate': '', 'website': 'www.kidqa.co.jp', 'ownership': '', 'employees': '', 'ticker_symbol': '', 'shipping_address_street': '48920 San Carlos Ave', 'shipping_address_street_2': '', 'shipping_address_street_3': '', 'shipping_address_street_4': '', 'shipping_address_city': 'Persistance', 'shipping_address_state': 'NY', 'shipping_address_postalcode': '', 'shipping_address_country': 'USA', 'email1': '[email protected]', 'email_addresses_primary': '', 'email_addresses': '', 'email_addresses_non_primary': '', 'parent_id': '', 'sic_code': '', 'parent_name': '', 'members': '', 'member_of': {}, 'email_opt_out': '0', 'invalid_email': '0', 'cases': '', 'email': '', 'tasks': '', 'notes': '', 'meetings': '', 'calls': '', 'emails': '', 'documents': '', 'bugs': '', 'contacts': '', 'opportunities': '', 'project': '', 'leads': '', 'campaigns': '', 'campaign_accounts': {}, 'campaign_id': '', 'campaign_name': '', 'prospect_lists': '', 'aos_quotes': '', 'aos_invoices': '', 'aos_contracts': '', 'jjwg_maps_geocode_status_c': '', 'jjwg_maps_lng_c': '0.00000000', 'jjwg_maps_address_c': '', 'jjwg_maps_lat_c': '0.00000000'}

print(ds)
Empty DataFrame
Columns: [name, date_entered, date_modified, modified_user_id, modified_by_name, created_by, created_by_name, description, deleted, created_by_link, modified_user_link, assigned_user_id, assigned_user_name, assigned_user_link, SecurityGroups, account_type, industry, annual_revenue, phone_fax, billing_address_street, billing_address_street_2, billing_address_street_3, billing_address_street_4, billing_address_city, billing_address_state, billing_address_postalcode, billing_address_country, rating, phone_office, phone_alternate, website, ownership, employees, ticker_symbol, shipping_address_street, shipping_address_street_2, shipping_address_street_3, shipping_address_street_4, shipping_address_city, shipping_address_state, shipping_address_postalcode, shipping_address_country, email1, email_addresses_primary, email_addresses, email_addresses_non_primary, parent_id, sic_code, parent_name, members, member_of, email_opt_out, invalid_email, cases, email, tasks, notes, meetings, calls, emails, documents, bugs, contacts, opportunities, project, leads, campaigns, campaign_accounts, campaign_id, campaign_name, prospect_lists, aos_quotes, aos_invoices, aos_contracts, jjwg_maps_geocode_status_c, jjwg_maps_lng_c, jjwg_maps_address_c, jjwg_maps_lat_c]
Index: []

Tim Roberts · Accepted Answer · 2021-12-14 19:07:01Z

1

You need to provide an index. With one row, it can't guess what the index should be.

df = pd.DataFrame(account_attributes,index=[0])

If you have multiple rows, then something like:

df = pd.DataFrame(account_attributes,index=range(len(account_attributes)))

answered Dec 14, 2021 at 19:07

Tim Roberts

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Data21 · Accepted Answer · 2021-12-14 19:24:11Z

Pandas needs an index in order to create a dataframe. You provided only single row of data without an index. Please try the following code:

account_attributes ={'name': '5D Investments', 'date_entered': '2021-12-13T15:17:00+00:00', 'date_modified': '2021-12-13T15:17:00+00:00', 'modified_user_id': '1', 'modified_by_name': 'Administrator', 'created_by': '1', 'created_by_name': 'Administrator', 'description': '', 'deleted': '0', 'created_by_link': '', 'modified_user_link': '', 'assigned_user_id': '1', 'assigned_user_name': 'Administrator', 'assigned_user_link': '', 'SecurityGroups': '', 'account_type': 'Customer', 'industry': 'Other', 'annual_revenue': '', 'phone_fax': '', 'billing_address_street': '48920 San Carlos Ave', 'billing_address_street_2': '', 'billing_address_street_3': '', 'billing_address_street_4': '', 'billing_address_city': 'Persistance', 'billing_address_state': 'NY', 'billing_address_postalcode': '', 'billing_address_country': 'USA', 'rating': '', 'phone_office': '(893) 969-8036', 'phone_alternate': '', 'website': 'www.kidqa.co.jp', 'ownership': '', 'employees': '', 'ticker_symbol': '', 'shipping_address_street': '48920 San Carlos Ave', 'shipping_address_street_2': '', 'shipping_address_street_3': '', 'shipping_address_street_4': '', 'shipping_address_city': 'Persistance', 'shipping_address_state': 'NY', 'shipping_address_postalcode': '', 'shipping_address_country': 'USA', 'email1': '[email protected]', 'email_addresses_primary': '', 'email_addresses': '', 'email_addresses_non_primary': '', 'parent_id': '', 'sic_code': '', 'parent_name': '', 'members': '', 'member_of': {}, 'email_opt_out': '0', 'invalid_email': '0', 'cases': '', 'email': '', 'tasks': '', 'notes': '', 'meetings': '', 'calls': '', 'emails': '', 'documents': '', 'bugs': '', 'contacts': '', 'opportunities': '', 'project': '', 'leads': '', 'campaigns': '', 'campaign_accounts': {}, 'campaign_id': '', 'campaign_name': '', 'prospect_lists': '', 'aos_quotes': '', 'aos_invoices': '', 'aos_contracts': '', 'jjwg_maps_geocode_status_c': '', 'jjwg_maps_lng_c': '0.00000000', 'jjwg_maps_address_c': '', 'jjwg_maps_lat_c': '0.00000000'}
df = pd.DataFrame(data=account_attributes, index=[0])
print(df)

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