如何从mongodb导入数据到pandas？
如何从mongodb导入数据到pandas？
提问于 2013-04-27 15:59:07
我在mongodb中的一个集合中有大量数据需要分析。如何将这些数据导入到pandas？
我是第一次接触熊猫和麻木。
编辑: mongodb集合包含用日期和时间标记的感应器值。传感器的值是浮点数据类型。
示例数据：
{
"_cls" : "SensorReport",
"_id" : ObjectId("515a963b78f6a035d9fa531b"),
"_types" : [
"SensorReport"
],
"Readings" : [
{
"a" : 0.958069536790466,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:26:35.297Z"),
"b" : 6.296118156595,
"_cls" : "Reading"
},
{
"a" : 0.95574014778624,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:27:09.963Z"),
"b" : 6.29651468650064,
"_cls" : "Reading"
},
{
"a" : 0.953648289182713,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:27:37.545Z"),
"b" : 7.29679823731148,
"_cls" : "Reading"
},
{
"a" : 0.955931884300997,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:28:21.369Z"),
"b" : 6.29642922525632,
"_cls" : "Reading"
},
{
"a" : 0.95821381,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:41:20.801Z"),
"b" : 7.28956613,
"_cls" : "Reading"
},
{
"a" : 4.95821335,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:41:36.931Z"),
"b" : 6.28956574,
"_cls" : "Reading"
},
{
"a" : 9.95821341,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:42:09.971Z"),
"b" : 0.28956488,
"_cls" : "Reading"
},
{
"a" : 1.95667927,
"_types" : [
"Reading"
],
"ReadingUpdatedDate" : ISODate("2013-04-02T08:43:55.463Z"),
"b" : 0.29115237,
"_cls" : "Reading"
}
],
"latestReportTime" : ISODate("2013-04-02T08:43:55.463Z"),
"sensorName" : "56847890-0",
"reportCount" : 8
}回答 10
Stack Overflow用户
回答已采纳
发布于 2013-04-28 02:45:56
pymongo可能会帮你一把，以下是我正在使用的一些代码：
import pandas as pd
from pymongo import MongoClient
def _connect_mongo(host, port, username, password, db):
""" A util for making a connection to mongo """
if username and password:
mongo_uri = 'mongodb://%s:%s@%s:%s/%s' % (username, password, host, port, db)
conn = MongoClient(mongo_uri)
else:
conn = MongoClient(host, port)
return conn[db]
def read_mongo(db, collection, query={}, host='localhost', port=27017, username=None, password=None, no_id=True):
""" Read from Mongo and Store into DataFrame """
# Connect to MongoDB
db = _connect_mongo(host=host, port=port, username=username, password=password, db=db)
# Make a query to the specific DB and Collection
cursor = db[collection].find(query)
# Expand the cursor and construct the DataFrame
df = pd.DataFrame(list(cursor))
# Delete the _id
if no_id:
del df['_id']
return dfStack Overflow用户
发布于 2014-12-23 17:15:24
您可以使用以下代码将mongodb数据加载到pandas DataFrame。这对我很管用。希望对你也是如此。
import pymongo
import pandas as pd
from pymongo import MongoClient
client = MongoClient()
db = client.database_name
collection = db.collection_name
data = pd.DataFrame(list(collection.find()))Stack Overflow用户
发布于 2016-10-23 19:43:19
根据PEP，简单比复杂更好：
import pandas as pd
df = pd.DataFrame.from_records(db.<database_name>.<collection_name>.find())您可以像处理常规mongoDB数据库一样包含条件，甚至可以使用find_one()从数据库中仅获取一个元素，等等。
瞧！
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/16249736
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