python - 如何使用python将csv数据推送到mongodb

Question

尝试使用 python 将 csv 数据推送到 mongodb。我是 python 和 mongodb 的初学者。我使用以下代码

import csv
import json
import pandas as pd
import sys, getopt, pprint
from pymongo import MongoClient
#CSV to JSON Conversion
csvfile = open('C://test//final-current.csv', 'r')
jsonfile = open('C://test//6.json', 'a')
reader = csv.DictReader( csvfile )
header= [ "S.No", "Instrument Name", "Buy Price", "Buy Quantity", "Sell Price", "Sell Quantity", "Last Traded Price", "Total Traded Quantity", "Average Traded Price", "Open Price", "High Price", "Low Price", "Close Price", "V" ,"Time"]
#fieldnames=header
output=[]
for each in reader:
    row={}
    for field in header:
        row[field]=each[field]
    output.append(row)

json.dump(output, jsonfile, indent=None, sort_keys=False , encoding="UTF-8")
mongo_client=MongoClient() 
db=mongo_client.october_mug_talk
db.segment.drop()
data=pd.read_csv('C://test//6.json', error_bad_lines=0)
df = pd.DataFrame(data)
records = csv.DictReader(df)
db.segment.insert(records)

但输出是以这种格式给出的

/* 0 */
{
  "_id" : ObjectId("54891c4ffb2a0303b0d43134"),
  "[{\"AverageTradedPrice\":\"0\"" : "BuyPrice:\"349.75\""
}

/* 1 */
{
  "_id" : ObjectId("54891c4ffb2a0303b0d43135"),
  "[{\"AverageTradedPrice\":\"0\"" : "BuyQuantity:\"3000\""
}

/* 2 */
{
  "_id" : ObjectId("54891c4ffb2a0303b0d43136"),
  "[{\"AverageTradedPrice\":\"0\"" : "ClosePrice:\"350\""
}

/* 3 */
{
  "_id" : ObjectId("54891c4ffb2a0303b0d43137"),
  "[{\"AverageTradedPrice\":\"0\"" : "HighPrice:\"0\""
}

实际上我希望输出喜欢单个 id 所有其他字段应显示为子类型例如:

 _id" : ObjectId("54891c4ffb2a0303b0d43137")
    AveragetradedPrice :0
    HighPrice:0
    ClosePrice:350
    buyprice:350.75

请帮帮我。在此先感谢

Answer 1

感谢您的建议。这是更正后的代码:

import csv
import json
import pandas as pd
import sys, getopt, pprint
from pymongo import MongoClient
#CSV to JSON Conversion
csvfile = open('C://test//final-current.csv', 'r')
reader = csv.DictReader( csvfile )
mongo_client=MongoClient() 
db=mongo_client.october_mug_talk
db.segment.drop()
header= [ "S No", "Instrument Name", "Buy Price", "Buy Quantity", "Sell Price", "Sell Quantity", "Last Traded Price", "Total Traded Quantity", "Average Traded Price", "Open Price", "High Price", "Low Price", "Close Price", "V" ,"Time"]

for each in reader:
    row={}
    for field in header:
        row[field]=each[field]

    db.segment.insert(row)