如何将数据从 mongodb 导入到 Pandas? [英] How to import data from mongodb to pandas?

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本文介绍了如何将数据从 mongodb 导入到 Pandas?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我在 mongodb 的集合中有大量数据需要分析.我如何将该数据导入熊猫?

I have a large amount of data in a collection in mongodb which I need to analyze. How do i import that data to pandas?

我是 Pandas 和 numpy 的新手.

I am new to pandas and numpy.

mongodb 集合包含用日期和时间标记的传感器值.传感器值是浮点数据类型.

The mongodb collection contains sensor values tagged with date and time. The sensor values are of float datatype.

样本数据:

{
"_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
}

推荐答案

pymongo 可能会帮到你,以下是我正在使用的一些代码:

pymongo might give you a hand, followings are some codes I'm using:

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 df

这篇关于如何将数据从 mongodb 导入到 Pandas?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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