[Python] Using json_normalize with pandas

I'm using the following code in python to flatten the json structure below, however it doesn't work for all levels. I'm interested in the tags.tags column data specifically shown on the picture below

pd.json_normalize(data['conversations'])
pd.set_option('display.max_columns', None)


Json structure:

[{'type': 'conversation.list',
'pages': {'type': 'pages',
'next': {'page': 3,
'starting_after': 'WzE3MTU3ODIxOTc=='},
'page': 2,
'per_page': 1,
'total_pages': 46969},
'total_count': 46969,
'conversations': [{'type': 'conversation',
'id': '1384780',
'created_at': 1715780970,
'updated_at': 1715782197,
'waiting_since': None,
'snoozed_until': None,
'source': {'type': 'conversation',
'id': '2197597651',
'delivered_as': 'customer_initiated',
'subject': '',
'body': '<p>Outros</p>',
'author': {'type': 'user',
'id': '64ac5cacccd2b047',
'name': 'Claudiney Pinho',
'email': 'irmao.ir@hotmail.com'},
'attachments': [],
'url': None,
'redacted': False},
'contacts': {'type': 'contact.list',
'contacts': [{'type': 'contact',
'id': '64accccd71982047',
'external_id': 'b363-cc8f--fb270b5e72e8'}]},
'first_contact_reply': {'created_at': 1715780970,
'type': 'conversation',
'url': None},
'admin_assignee_id': 5614527,
'team_assignee_id': 5045796,
'open': False,
'state': 'closed',
'read': True,
'tags': {'type': 'tag.list',
'tags': [{'type': 'tag',
'id': '5379642',
'name': '[BOT] Other',
'applied_at': 1715781024,
'applied_by': {'type': 'admin', 'id': '4685750'}},
{'type': 'tag',
'id': '5379660',
'name': '[BOT] Connected Agent',
'applied_at': 1715781025,
'applied_by': {'type': 'admin', 'id': '4685750'}},
{'type': 'tag',
'id': '5379654',
'name': '[BOT] Not Resolved',
'applied_at': 1715781027,
'applied_by': {'type': 'admin', 'id': '4685750'}},
{'type': 'tag',
'id': '7046337',
'name': '[BOT] Portuguese',
'applied_at': 1715781029,
'applied_by': {'type': 'admin', 'id': '4685750'}}]},
'priority': 'not_priority',
'sla_applied': None,
'statistics': {'type': 'conversation_statistics',
'time_to_assignment': 0,
'time_to_admin_reply': 189,
'time_to_first_close': 1158,
'time_to_last_close': 1228,
'median_time_to_reply': 139,
'first_contact_reply_at': 1715780970,
'first_assignment_at': 1715780970,
'first_admin_reply_at': 1715781159,
'first_close_at': 1715782128,
'last_assignment_at': 1715781159,
'last_assignment_admin_reply_at': 1715781159,
'last_contact_reply_at': 1715782179,
'last_admin_reply_at': 1715782125,
'last_close_at': 1715782198,
'last_closed_by_id': 5614527,
'count_reopens': 1,
'count_assignments': 3,
'count_conversation_parts': 28},
'conversation_rating': None,
'teammates': {'type': 'admin.list',
'admins': [{'type': 'admin', 'id': '5614527'}]},
'title': None,
'custom_attributes': {'Language': 'Portuguese',
'Conversation status': 'Open',
'From': 'iOS / Android'},
'topics': {'type': 'topic.list', 'topics': [], 'total_count': 0},
'ticket': None,
'linked_objects': {'type': 'list',
'data': [],
'total_count': 0,
'has_more': False}}]}]


how the dataset is displayed

I wish to create a pandas data frame with flatten key:values in a table

Continue reading...