正则表达式和熊猫：在名称匹配时提取部分字符串

Question

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。

当客户进入对话时，客户姓名总是在网络聊天的第一行公布。

示例 1：

在：df['log'][0]

输出：[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]

输出：[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.

聊天中的名称总是随着不同客户使用网络聊天服务而变化。

客户可以输入具有一个或多个名称的聊天。例子： James Ravi Roy Andrews.

要求：

我想将所有客户聊天实例（例如 James 和 Roy Andrews 的聊天）从 df['log'] 列分离到一个新列 df[text_analysis]。

从上面的示例 1 看起来像：

在：df['text_analysis][0]

输出：[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： 最佳解决方案将提取上面示例中提供的子字符串并省略最终时间戳[14:44:38] James has exited the session.。

到目前为止我所做的尝试： 我已将 df['log'] 列中的客户名称提取到名为 df['names'] 的新列中，使用：

df['names'] = df['log'].apply(lambda x: x.split(' ')[7].split('[')[0])

我想在str.split() pandas 函数中使用df['names'] 列中的名称——类似于：

df['log'].str.split(df['names']) 但是这不起作用，如果在这种情况下确实发生了拆分，我认为它不会正确地将客户和服务运营商的聊天分开。

我还尝试将名称合并到正则表达式类型解决方案中：

df['log'].str.extract('([^.]*{}[^.]*)').format(df['log']))

但这也不起作用（因为我猜.extract() 不支持格式。

任何帮助将不胜感激。

Answer 1

使用regex，longs是你的第一段：

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函数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'^.*(?=\[)'表示：从^开始，匹配任意数量的任意字符.*，以[结尾但不包括(?=\[)。由于正则表达式匹配最长的字符串，这将从开头一直到最后一个[，并且不包括[。

可以这样提取单独的行：

import re
customerspeak = re.findall(r'(?<=\[(?:\d{2}:){2}\d{2}\]) James:[^\[]*', s)

输出：

[" 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']

如果你想要这些在同一行，你可以''.join(customerspeak)