当我尝试规范化后面的 Json 结构时，我发现一条错误消息。
我粘贴了 JSON 结构和 python 代码来规范化，给出错误消息
目标：将all_data标准化到一张表中，以便我能够看到所有标签的信息。
为了识别标签属于哪个用户而需要保留的重要变量
创建于：
更新于：
id：
名称：
标签：
[{'type': 'conversation.list',
'pages': {'type': 'pages',
'next': {'page': 3,
'starting_after': 'WzE3MTU4NDc3NywzXQ=='},
'page': 2,
'per_page': 5,
'total_pages': 9525},
'total_count': 47622,
'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': '64ac5cacccd1982047',
'name': 'Claudinho',
'email': '[email protected]'},
'attachments': [],
'url': None,
'redacted': False},
'contacts': {'type': 'contact.list',
'contacts': [{'type': 'contact',
'id': '64ac5cabc0271982047',
'external_id': 'b363b00b5e72e8'}]},
'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}},
NEXT PAGES
{'type': 'conversation.list',
'pages': {'type': 'pages',
'next': {'page': 4,
'starting_after': 'WzE3MTU3IwMDAs=='},
'page': 3,
'per_page': 5,
'total_pages': 9525},
'total_count': 47622,
'conversations': [{'type': 'conversation',
'id': '1384768',
data_1 = [] # This will store the normalized data
i=0
for i in all_data: # Iterating directly over items in all_data
normalized_data = pd.json_normalize(
all_data[i]["conversations"],
record_path=["tags", "tags"],
meta=[
"id",
"created_at",
"updated_at",
["source", "id"],
["source", "author", "name"],
],
meta_prefix="meta_", # Avoiding conflicts with available ids
errors="ignore",
)
pd.set_option("display.max_columns", None)
# Append the normalized data to date_1
data_1.append(normalized_data)
i += 1
# If you want to combine all DataFrames into one:
if data_1: # Check if date_1 is not empty
final_data = pd.concat(data_1, ignore_index=True)
错误信息
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[149], line 6
2 i=0
4 for i in all_data: # Iterating directly over items in all_data
5 normalized_data = pd.json_normalize(
----> 6 all_data[i]["conversations"],
7 record_path=["tags", "tags"],
8 meta=[
9 "id",
10 "created_at",
11 "updated_at",
12 ["source", "id"],
13 ["source", "author", "name"],
14 ],
15 meta_prefix="meta_", # Avoiding conflicts with available ids
16 errors="ignore",
17 )
19 pd.set_option("display.max_columns", None)
21 # Append the normalized data to date_1
TypeError: list indices must be integers or slices, not dict
你们都在那里。再次查看 for 循环，以更好地了解其中发生的情况。迭代列表时无需存储和索引值，并且如注释中所述，
ifor each_data in all_data: # <- each element in your all_data list is being stored as each_data
normalized_data = pd.json_normalize(
each_data["conversations"], # <- then you want to normalize that here
record_path=["tags", "tags"],
meta=[
"id",
"created_at",
"updated_at",
["source", "id"],
["source", "author", "name"],
],
meta_prefix="meta_", # Avoiding conflicts with available ids
errors="ignore",
)
pd.set_option("display.max_columns", None)
# Append the normalized data to date_1
data_1.append(normalized_data)
# If you want to combine all DataFrames into one:
if data_1: # Check if date_1 is not empty
final_data = pd.concat(data_1, ignore_index=True)