更新
我破解了 ol Python 来破解一下 - 下面的代码可以完美运行！
from pymongo import MongoClient
import pandas as pd
uri = "mongodb://<your_mongo_uri>:27017"
database_name = "<your_database_name"
collection_name = "<your_collection_name>"
mongo_client = MongoClient(uri)
database = mongo_client[database_name]
collection = database[collection_name]
# I used this code to insert a doc into a test collection
# before querying (just incase you wanted to know lol)
"""
data = {
"_id": 1,
"name": "Growth Lead Momentum",
"factors": [
{
"factorId": "C24",
"index": 0,
"weight": 1
},
{
"factorId": "D74",
"index": 7,
"weight": 9
}
]
}
insert_result = collection.insert_one(data)
print(insert_result)
"""
# This is the query that
# answers your question
results = collection.aggregate([
{
"$unwind": "$factors"
},
{
"$project": {
"_id": 1, # Change to 0 if you wish to ignore "_id" field.
"name": 1,
"factorId": "$factors.factorId",
"index": "$factors.index",
"weight": "$factors.weight"
}
}
])
# This is how we turn the results into a DataFrame.
# We can simply pass `list(results)` into `DataFrame(..)`,
# due to how our query works.
results_as_dataframe = pd.DataFrame(list(results))
print(results_as_dataframe)
哪些输出：
_id name factorId index weight
0 1 Growth Lead Momentum C24 0 1
1 1 Growth Lead Momentum D74 7 9
原答案
您可以使用聚合管道展开factors，然后投影您想要的字段。
这样的事情应该可以解决问题。
直播demo here.
数据库结构
[
{
"_id": 1,
"name": "Growth Lead Momentum",
"factors": [
{
factorId: "C24",
index: 0,
weight: 1
},
{
factorId: "D74",
index: 7,
weight: 9
}
]
}
]
查询
db.collection.aggregate([
{
$unwind: "$factors"
},
{
$project: {
_id: 1,
name: 1,
factorId: "$factors.factorId",
index: "$factors.index",
weight: "$factors.weight"
}
}
])
结果
（.csv 友好）
[
{
"_id": 1,
"factorId": "C24",
"index": 0,
"name": "Growth Lead Momentum",
"weight": 1
},
{
"_id": 1,
"factorId": "D74",
"index": 7,
"name": "Growth Lead Momentum",
"weight": 9
}
]