我有一个pandas数据框，其中包含两个人（客户和服务台操作员）之间的网络聊天实例。
当客户进入会话时，总是在网络聊天的第一行中宣布客户名称。
示例1：
在：df['log'][0]
退出：[14:40:48] You are joining a chat with James[14:40:48] James: Hello, I\'m looking to find out more about the services and products you offer.[14:41:05] Greg: Thank you for contacting us. [17:41:14] Greg: Could I start by asking what services lines or products you are interested in knowing more about, please?[14:41:23] James: I would like to know more about your gardening and guttering service.[14:43:20] James: hello?[14:43:32] Greg: thank you, for more information on those please visit www.example.com/more_examples.[14:44:12] James: Thanks[14:44:38] James has exited the session.
示例2：
在：df['log'][1]
退出：[09:01:25] You are joining a chat with Roy Andrews[09:01:25] Roy Andrews: I\'m asking on behalf of partner whether she is able to still claim warranty on a coffee machine she purchased a year and a half ago? [09:02:00] Jamie: Thank you for contacting us. Could I start by asking for the type of coffee machine purchased please, and whether she still has a receipt?[09:02:23] Roy Andrews: BRX0403, she no longer has a receipt.[09:05:30] Jamie: Thank you, my interpretation is that she would not be able to claim as she is no longer under warranty. [09:08:46] Jamie: for more information on our product warranty policy please see www.brandx.com/warranty-policy/information[09:09:13] Roy Andrews: Thanks for the links, I will let her know.[09:09:15] Roy Andrews has exited the session.
由于不同的客户使用网络聊天服务，因此聊天中的名称始终会有所不同。
客户可以输入具有一个或多个名称的聊天。例：
James
Ravi
Roy Andrews。
要求：
我想将客户聊天的所有实例（例如，由James和Roy Andrews进行的聊天）从df['log']列中分离到新列df[text_analysis]中。
在上面的示例1中，它看起来像：
在：df['text_analysis][0]
退出：[14:40:48] You are joining a chat with James[14:40:48] James: Hello, I\'m looking to find out more about the services and products you offer.[14:41:23] James: I would like to know more about your gardening and guttering service.[14:43:20] James: hello?[14:44:12] James: Thanks
编辑：
最佳解决方案将按照上面的示例提取子字符串，并省略最终时间戳记[14:44:38] James has exited the session.。
到目前为止我已经尝试过：
我使用以下方法将客户名称从df['log']列提取到名为df['names']的新列中：
df['names'] = df['log'].apply(lambda x: x.split(' ')[7].split('[')[0])
我想在df['names']熊猫函数中使用str.split()列中的名称-类似于：
df['log'].str.split(df['names'])但是，这不起作用，并且如果在这种情况下确实发生了拆分，我认为它将无法正确拆分客户，并且服务运营商会分开聊天。
我还尝试将名称合并到正则表达式类型的解决方案中：
df['log'].str.extract('([^.]*{}[^.]*)').format(df['log']))
但是这也不起作用（因为我猜测.extract()不支持格式。
任何帮助将不胜感激。
答案 0 :(得分：0)
使用regex，longs是第一段：
import re
re.match(r'^.*(?=\[)', longs).group()
结果：
"[14:40:48] You are joining a chat with James[14:40:48] James: Hello, I'm looking to find out more about the services and products you offer.[14:41:05] Greg: Thank you for contacting us. [17:41:14] Greg: Could I start by asking what services lines or products you are interested in knowing more about, please?[14:41:23] James: I would like to know more about your gardening and guttering service.[14:43:20] James: hello?[14:43:32] Greg: thank you, for more information on those please visit www.example.com/more_examples.[14:44:12] James: Thanks"
您可以将此正则表达式功能打包到您的数据框中：
df['text_analysis'] = df['log'].apply(lambda x: re.match(r'^.*(?=\[)', x).group())
说明：正则表达式字符串'^.*(?=\[)'的含义是：从^开始，匹配任意数量的任何字符.*，以[结尾，但不包括{{1} }。由于正则表达式匹配最长的字符串，因此它将从头到尾(?=\[)为止，并且不包括[。
可以通过以下方式提取单独的行：
[输出：
import re
customerspeak = re.findall(r'(?<=\[(?:\d{2}:){2}\d{2}\]) James:[^\[]*', s)
如果您希望它们在同一行中，则可以[" James: Hello, I'm looking to find out more about the services and products you offer.",
' James: I would like to know more about your gardening and guttering service.',
' James: hello?',
' James: Thanks']