python 2.7 - 如何防止 Pandas 数据帧在每一行重复列名

Question

我正在使用ExactTarget Saleforce营销云SOAP API进行工作。我已经获得了 API 来响应我的应用程序，响应是字典列表。这样：

ClickEvent){
   Client = 
      (ClientID){
         ID = 111111
      }
   PartnerKey = None
   CreatedDate = 2016-07-12 00:40:17
   ModifiedDate = 2016-07-12 00:40:17
   ID = 11111
   ObjectID = "11111"
   SendID = 111111
   SubscriberKey = "[e-mail]"
   EventDate = 2016-07-12 00:40:17
   EventType = "aaaa"
   TriggeredSendDefinitionObjectID = None
   BatchID = 1
   URLID = 11111
   URL =

我已经成功地迭代了这些项目，但作为我代码中的测试，只拉回了 3 个值。ID、合作伙伴密钥、创建日期。

我已经将变量输入到熊猫数据帧中，它们已成功填充。我的问题和问题是列名在每个行级别连续重复，左侧的行号均为零。

如何在使行号连续时阻止列名重复？

法典：

import ET_Client
import pandas as pd
import json

try:
    debug = False
    stubObj = ET_Client.ET_Client(False, debug)
    ## Modify the date below to reduce the number of results returned from the request
    ## Setting this too far in the past could result in a very large response size
    retrieveDate = '2014-07-11T13:00:00.000'
    #ET call for clicks
    print '>>>ClickEvents'
    getClickEvent = ET_Client.ET_ClickEvent()
    getClickEvent.auth_stub = stubObj   
    getResponse = getClickEvent.get()
    ResponseResults = getResponse.results
    for ClickEvent in ResponseResults:
        ID = str(ClickEvent['ID'])
        PartnerKey = ClickEvent['PartnerKey']
        CreatedDate = ClickEvent['CreatedDate']


        df = pd.DataFrame({'ID':[ID],'PartnerKey':[PartnerKey], 'ClickEvent' :[CreatedDate]})
        print df

现在输出：

 ClickEvent          ID            PartnerKey
0 2016-05-21 10:41:46  111111111       None
           ClickEvent          ID PartnerKey
0 2016-05-21 11:29:25  111111111       None
           ClickEvent          ID PartnerKey

提前谢谢你。

Answer 1

您

正在为ResponseResults中的每个项目创建一个数据帧，而不是包含所有结果的单个数据帧。尝试这样的事情：

ids = []
partner_keys = []
created_dates = []
for ClickEvent in ResponseResults:
    ids.append(str(ClickEvent['ID']))
    partner_keys.append(ClickEvent['PartnerKey'])
    created_dates.append(ClickEvent['CreatedDate'])
df = pd.DataFrame({'ID': ids, 'PartnerKey': partner_keys,
                   'ClickEvent' : created_dates})
print df