Warning: file_get_contents(/data/phpspider/zhask/data//catemap/2/python/336.json): failed to open stream: No such file or directory in /data/phpspider/zhask/libs/function.php on line 167

Warning: Invalid argument supplied for foreach() in /data/phpspider/zhask/libs/tag.function.php on line 1116

Notice: Undefined index: in /data/phpspider/zhask/libs/function.php on line 180

Warning: array_chunk() expects parameter 1 to be array, null given in /data/phpspider/zhask/libs/function.php on line 181
Python 操作以字符串形式存储的CSV数据_Python_String_Csv - Fatal编程技术网

Python 操作以字符串形式存储的CSV数据

Python 操作以字符串形式存储的CSV数据,python,string,csv,Python,String,Csv,我有一个API字符串,它以XML页面响应,并将我的数据作为CSV存储在数据标记中。我可以以JSON格式请求它,但我无法以该格式在Python脚本中正确处理数据 <reports.getAccountsStatsResponse xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="urn:com:gigya:api" xsi:schemaLocation="urn:com:gigya:api http://socializ

我有一个API字符串,它以XML页面响应,并将我的数据作为CSV存储在数据标记中。我可以以JSON格式请求它,但我无法以该格式在Python脚本中正确处理数据

<reports.getAccountsStatsResponse xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="urn:com:gigya:api" xsi:schemaLocation="urn:com:gigya:api http://socialize-api.gigya.com/schema">
<statusCode>200</statusCode>
<errorCode>0</errorCode>
<statusReason>OK</statusReason>
<callId>ae1b3f13ba1c4e62ad3120afb1269c76</callId>
<time>2015-09-01T09:01:46.511Z</time>
<headers>
<header>date</header>
<header>initRegistrations</header>
<header>registrations</header>
<header>siteLogins</header>
<header>newUsers</header>
</headers>
<data xmlns:q1="http://www.w3.org/2001/XMLSchema" xsi:type="q1:string">
"date","initRegistrations","registrations","siteLogins","newUsers" "01/01/2015","0","0","0","0" "01/02/2015","0","0","0","0" "01/03/2015","0","0","0","0" "01/04/2015","0","0","0","0" "01/05/2015","0","0","0","0" "01/06/2015","0","0","0","0" "01/07/2015","0","0","0","0" "01/08/2015","0","0","0","0" "01/09/2015","0","0","0","0" "01/10/2015","0","0","0","0" "01/11/2015","0","0","0","0" "01/12/2015","0","0","0","0" "01/13/2015","0","0","0","0" "01/14/2015","0","0","0","0" "01/15/2015","0","0","0","0" "01/16/2015","0","0","0","0" "01/17/2015","0","0","0","0" "01/18/2015","0","0","0","0" "01/19/2015","0","0","0","0" "01/20/2015","34","34","72","34" "01/21/2015","33","23","58","23" "01/22/2015","19","19","49","19" "01/23/2015","21","21","50","21" "01/24/2015","1","1","2","1" "01/25/2015","0","0","0","0" "01/26/2015","8","4","49","4" "01/27/2015","8","8","35","8" "01/28/2015","4","2","16","2" "01/29/2015","7","7","27","7" "01/30/2015","69","58","516","58" "01/31/2015","9","6","76","6" "02/01/2015","0","0","2","0" "02/02/2015","304","203","2317","203" "02/03/2015","122","93","786","93" "02/04/2015","69","47","435","47" "02/05/2015","93","64","677","64" "02/06/2015","294","255","1327","255" "02/07/2015","0","0","0","0" "02/08/2015","0","0","0","0" "02/09/2015","0","0","3","0" "02/10/2015","1","0","1","0" "02/11/2015","3","3","7","3" "02/12/2015","0","0","0","0" "02/13/2015","2","2","4","2" "02/14/2015","0","0","1","0" "02/15/2015","0","0","0","0" "02/16/2015","0","0","0","0" "02/17/2015","3","3","7","3" "02/18/2015","0","0","0","0" "02/19/2015","1","1","3","1" "02/20/2015","3","3","10","3" "02/21/2015","0","0","0","0" "02/22/2015","0","0","1","0" "02/23/2015","1","1","4","1" "02/24/2015","0","0","1","0" "02/25/2015","0","0","0","0" "02/26/2015","0","0","0","0" "02/27/2015","0","0","1","0" "02/28/2015","1","1","2","1" "03/01/2015","1","1","3","1" "03/02/2015","19","9","348","9" "03/03/2015","14","9","132","9" "03/04/2015","4","4","41","4" "03/05/2015","8","5","101","5" "03/06/2015","6","5","71","5" "03/07/2015","8","4","42","4" "03/08/2015","7","4","45","4" "03/09/2015","5","4","30","4" "03/10/2015","7","7","39","7" "03/11/2015","9","9","41","9" "03/12/2015","1","1","20","1" "03/13/2015","3","3","26","3" "03/14/2015","2","0","21","0" "03/15/2015","3","3","28","3" "03/16/2015","3","3","38","3" "03/17/2015","4","4","43","4" "03/18/2015","5","3","45","3" "03/19/2015","19","16","108","16" "03/20/2015","11","8","96","8" "03/21/2015","276","261","807","261" "03/22/2015","197","192","604","192" "03/23/2015","0","0","3","0" "03/24/2015","1","1","4","1" "03/25/2015","181","166","401","166" "03/26/2015","124","109","265","109" "03/27/2015","53","47","124","47" "03/28/2015","41","39","99","39" "03/29/2015","75","65","173","65" "03/30/2015","249","239","536","239" "03/31/2015","222","212","487","212" "04/01/2015","40","29","394","29" "04/02/2015","16","10","132","10" "04/03/2015","13","10","125","10" "04/04/2015","6","4","49","4" "04/05/2015","2","1","46","1" "04/06/2015","4","3","38","3" "04/07/2015","1","0","32","0" "04/08/2015","4","2","16","2" "04/09/2015","9","8","30","8" "04/10/2015","31","29","96","29" "04/11/2015","17","14","90","14" "04/12/2015","10","7","46","7" "04/13/2015","19","13","69","13" "04/14/2015","63","58","199","58" "04/15/2015","17","16","58","16" "04/16/2015","13","12","41","12" "04/17/2015","7","5","51","5" "04/18/2015","51","46","165","46" "04/19/2015","51","45","179","45" "04/20/2015","28","21","110","21" "04/21/2015","32","24","290","24" "04/22/2015","47","31","329","31" "04/23/2015","30","27","183","27" "04/24/2015","71","65","284","65" "04/25/2015","25","17","268","17" "04/26/2015","26","24","268","24" "04/27/2015","72","67","172","67" "04/28/2015","28","25","96","25" "04/29/2015","72","48","159","48" "04/30/2015","50","22","136","22" "05/01/2015","33","23","126","23" "05/02/2015","22","17","112","17" "05/03/2015","31","21","169","21" "05/04/2015","29","21","182","21" "05/05/2015","12","10","24","10" "05/06/2015","369","354","790","354" "05/07/2015","409","401","839","401" "05/08/2015","258","253","539","253" "05/09/2015","227","221","469","221" "05/10/2015","138","134","297","134" "05/11/2015","14","13","32","13" "05/12/2015","57","24","452","24" "05/13/2015","23","12","300","12" "05/14/2015","7","5","70","5" "05/15/2015","7","6","15","6" "05/16/2015","3","3","7","3" "05/17/2015","3","3","8","3" "05/18/2015","2","4","4","2" "05/19/2015","10","16","24","8" "05/20/2015","4","8","10","4" "05/21/2015","7","12","14","6" "05/22/2015","9","14","33","7" "05/23/2015","9","14","19","7" "05/24/2015","16","32","39","16" "05/25/2015","11","9","21","7" "05/26/2015","23","16","87","16" "05/27/2015","30","24","87","24" "05/28/2015","12","12","39","12" "05/29/2015","14","12","37","12" "05/30/2015","8","7","19","7" "05/31/2015","5","4","17","4" "06/01/2015","10","10","31","10" "06/02/2015","23","20","95","20" "06/03/2015","11","9","31","9" "06/04/2015","14","13","36","13" "06/05/2015","12","11","27","11" "06/06/2015","8","6","20","6" "06/07/2015","9","9","21","9" "06/08/2015","16","16","37","16" "06/09/2015","24","17","40","17" "06/10/2015","8","8","34","8" "06/11/2015","46","27","464","27" "06/12/2015","45","23","383","23" "06/13/2015","12","9","143","9" "06/14/2015","22","15","112","15" "06/15/2015","14","13","74","13" "06/16/2015","63","56","197","56" "06/17/2015","28","25","114","25" "06/18/2015","17","15","85","15" "06/19/2015","143","135","460","135" "06/20/2015","54","46","217","46" "06/21/2015","60","55","211","55" "06/22/2015","91","78","249","78" "06/23/2015","99","87","295","87" "06/24/2015","115","103","315","103" "06/25/2015","455","380","964","380" "06/26/2015","585","489","1144","489" "06/27/2015","345","300","695","300" "06/28/2015","349","320","783","320" "06/29/2015","113","98","362","98" "06/30/2015","128","113","424","113" "07/01/2015","115","99","277","99" "07/02/2015","73","65","323","65" "07/03/2015","22","16","184","16" "07/04/2015","13","12","69","12" "07/05/2015","15","12","71","12" "07/06/2015","31","25","107","25" "07/07/2015","15","10","63","10" "07/08/2015","16","12","60","12" "07/09/2015","35","32","103","32" "07/10/2015","22","19","72","19" "07/11/2015","7","7","25","7" "07/12/2015","4","4","27","4" "07/13/2015","81","73","195","73" "07/14/2015","60","53","157","53" "07/15/2015","44","40","115","40" "07/16/2015","40","40","112","40" "07/17/2015","27","23","64","23" "07/18/2015","15","11","56","11" "07/19/2015","19","14","63","14" "07/20/2015","21","17","48","17" "07/21/2015","11","10","30","10" "07/22/2015","13","12","40","12" "07/23/2015","9","6","43","6" "07/24/2015","9","8","32","8" "07/25/2015","8","5","20","5" "07/26/2015","20","18","64","18" "07/27/2015","15","14","80","14" "07/28/2015","9","8","48","8" "07/29/2015","21","13","88","13" "07/30/2015","9","5","92","5" "07/31/2015","4","3","81","3" "08/01/2015","4","3","23","3" "08/02/2015","11","5","29","5" "08/03/2015","19","17","50","17" "08/04/2015","15","10","32","10" "08/05/2015","14","9","31","9" "08/06/2015","26","5","338","5" "08/07/2015","22","13","182","13" "08/08/2015","9","7","72","7" "08/09/2015","7","4","58","4" "08/10/2015","17","14","88","14" "08/11/2015","23","17","100","17" "08/12/2015","20","20","62","20" "08/13/2015","23","21","81","21" "08/14/2015","30","26","136","26" "08/15/2015","12","7","59","7" "08/16/2015","12","8","61","8" "08/17/2015","68","46","331","46" "08/18/2015","72","48","327","48" "08/19/2015","149","75","542","75" "08/20/2015","95","59","358","59" "08/21/2015","93","54","342","54" "08/22/2015","69","40","300","40" "08/23/2015","150","103","505","103" "08/24/2015","39","30","105","30"
</data>
</reports.getAccountsStatsResponse>
首先,我希望通过引用数据标记的名称来存储数据标记中的文本,但我目前仅通过使用以下方法获得了成功:

response = requests.get(url)
root = ElementTree.fromstring(response.content)

dataString = root[6].text
是否有单独的命令可以指定标记的名称

接下来,我的目标是遍历对应于不同帐户的不同URL,并将这些帐户的名称附加到数据的末尾。如果数据存储为字符串,并且我需要将其添加到每行的末尾,那么这可能吗?接下来,在变量中保存多个值以便能够循环(即帐户列表)的最佳约定是什么


抱歉,如果不清楚,我很乐意提供更多信息,如果这意味着任何人都可以提供帮助。

据我所知,您为每个用户都有一个特定的URL,并且您希望为给定的所有用户收集数据

但是,由于您无法从响应中获取用户名,因此必须将响应与发送请求的URL对应的用户名结合起来。如果是这样,您可以使用字典来存储响应的数据,因为JSON格式与Python的字典是等效的

下面的代码只是在包含不同用户名和相应URL的列表中进行迭代。对于每个发送请求的URL,数据都从JSON格式的响应中提取出来,并以用户名作为密钥存储在URL中。然后,该词典存储在一种主词典中,其中包含所有收集的数据集

# replace names 'url_xyz' with corresponding names and url
users = {('Albert', 'url_albert'), ('Steven', 'url_steven'), ('Mike', 'url_mike')}

all_data = dict()

for name, url in users:
    response = requests.get(url)
    data = response['data'].replace('\"', '')
    all_data.update({name: data})
谢谢你,艾伯特

您的JSON建议让我能够更好地控制数据。下面的代码是我最终获得所需输出的代码。现在,我们来研究一下如何将日期从MM/DD/YYYY转换为DD/MM/YYYY

startDate = '2015-01-01' # Must be in format YYYY-MM-DD
endDate = '2015-12-31' # Must be in format YYYY-MM-DD
dimensions = 'date' # Available dimensions are 'date' and 'cid'
format = 'json'
dataFormat = 'json'
measures = 'initRegistrations,registrations,siteLogins,newUsers'
allData = []

# Construct API URL
for i in range(0,len(apiKey)):

      url = ('https://reports.eu1.gigya.com/reports.getAccountsStats?secret=' + secret + '&apiKey=' + apiKey[i] + \
            '&uid=' + uid + '&startDate=' + startDate + '&endDate=' + endDate + '&dimensions='+ dimensions +\
            '&measures=' + measures + '&format=' + format + '&dataFormat=' + dataFormat)

      response = requests.get(url)

      json = response.json()
      data = json['data']

      if i == 0:
            headers = json['headers']
            headers.append('brand')

            for x in range(0,len(data)):
                  data[x].append(brand[i])

            brandData = [headers] + data
      else:
            for x in range(0,len(data)):
                  data[x].append(brand[i])

            brandData = data

      allData += brandData


with open("testDataJSON.csv", "wb") as f:
      writer = csv.writer(f)
      writer.writerows(allData)

我不知道这在多大程度上符合Python的最佳实践,但正如我所说的,我对它非常陌生。

您是说您还可以将数据格式化为JSON格式。如果是这样,请您使用JSON格式的数据提供代码段?使用JSON格式的响应编辑JSON格式提取数据很容易,因为JSON数据可以像字典一样访问:data=response['data']好的,如果我有这种格式的数据,我需要循环遍历列表中的每个值,并在末尾附加一个额外的字符串以满足按帐户命名的需要?这是我无法理解的一点。你能用一些扩展你的问题的示例片段更详细地描述一下吗?顺便说一句,到目前为止你都尝试了什么?请注意Stackoverflow不是一个论坛,而是一个问答平台。只需重新排列日期和月份的快速字符串方法如下:date='09/01/2015'date_parts=date.split'/'new_date='{}/{}/{}'。formatdate_parts[1]、date_parts[0]、date_parts[2]然而,使用datetime模块有更优雅的方法来实现这一点。
startDate = '2015-01-01' # Must be in format YYYY-MM-DD
endDate = '2015-12-31' # Must be in format YYYY-MM-DD
dimensions = 'date' # Available dimensions are 'date' and 'cid'
format = 'json'
dataFormat = 'json'
measures = 'initRegistrations,registrations,siteLogins,newUsers'
allData = []

# Construct API URL
for i in range(0,len(apiKey)):

      url = ('https://reports.eu1.gigya.com/reports.getAccountsStats?secret=' + secret + '&apiKey=' + apiKey[i] + \
            '&uid=' + uid + '&startDate=' + startDate + '&endDate=' + endDate + '&dimensions='+ dimensions +\
            '&measures=' + measures + '&format=' + format + '&dataFormat=' + dataFormat)

      response = requests.get(url)

      json = response.json()
      data = json['data']

      if i == 0:
            headers = json['headers']
            headers.append('brand')

            for x in range(0,len(data)):
                  data[x].append(brand[i])

            brandData = [headers] + data
      else:
            for x in range(0,len(data)):
                  data[x].append(brand[i])

            brandData = data

      allData += brandData


with open("testDataJSON.csv", "wb") as f:
      writer = csv.writer(f)
      writer.writerows(allData)