pandas split list into columns with regex

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I have a string list:

content
01/09/15, 10:07 - message1
01/09/15, 10:32 - message2
01/09/15, 10:44 - message3

I want a data frame, like:

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2条回答

清歌不尽

2020-12-11 17:52

You can use str.extract - where named groups can become column names

In [5827]: df['content'].str.extract('(?P<date>[\s\S]+) - (?P<message>[\s\S]+)', 
                                     expand=True)
Out[5827]:
              date   message
0  01/09/15, 10:07  message1
1  01/09/15, 10:32  message2
2  01/09/15, 10:44  message3

Details

In [5828]: df
Out[5828]:
                      content
0  01/09/15, 10:07 - message1
1  01/09/15, 10:32 - message2
2  01/09/15, 10:44 - message3

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我在风中等你

2020-12-11 17:57

Use str.split by \s+-\s+ - \s+ is one or more whitespaces:

df[['date','message']] = df['content'].str.split('\s+-\s+', expand=True)
print (df)
                      content             date   message
0  01/09/15, 10:07 - message1  01/09/15, 10:07  message1
1  01/09/15, 10:32 - message2  01/09/15, 10:32  message2
2  01/09/15, 10:44 - message3  01/09/15, 10:44  message3

If need remove content column add DataFrame.pop:

df[['date','message']] = df.pop('content').str.split('\s+-\s+', expand=True)

print (df)
              date   message
0  01/09/15, 10:07  message1
1  01/09/15, 10:32  message2
2  01/09/15, 10:44  message3

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