如何防止Pandas Dataframe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，并且响应是一个字典列表。像这样：

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 = "aaa@aaa.aaa" 
    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项目，但作为一个测试在我的代码只拉回3个值。 ID，PartnerKey，CreatedDate。

我已经将这些变量提供给熊猫数据框，并且它们已经成功填充。我的问题是列名在每一行都连续重复，左侧的行号都是零。

如何避免列名重复使行号连续？

代码：现在

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 

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 

预先感谢您。

Answer 1

您正在为ResponseResults中的每个项目创建（并打印）一个数据框，而不是包含所有结果的单个数据框。尝试这样的：

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