如何使用字符串和整数将 pandas 列拆分为两列

Question

我希望将日期范围列拆分为两列，即开始日期和结束日期。但是它拆分似乎不起作用，因为它不识别“-”。有什么建议吗？

我试过使用

''' ebola1 = pd.DataFrame(ebola['Date range'].str.split('-',1).to_list(),columns = ['start date','end date']) '''

但是，它 returns 以下内容：

所以 (1) 它无法识别“-”，(2) 我如何区分 'Jun-Nov 1976' 和 'Oct 2001-Mar 2002'，(3) 我如何将新列包含在现有 table?

感谢您的帮助！

Answer 1

使用–代替-，所以使用Series.str.split和expand=True用于DataFrame:

data = ['Jun–Nov 1976', 'Sep–Oct 1976', 'Jun 1977', 'Jul–Oct 1979', 'Nov 1994', 'Nov 1994–Feb 1995', 'Jan–Jul 1995', 'Jan–Mar 1996', 'Jul 1996–Jan 1997', 'Oct 2000–Feb 2001', 'Oct 2001–Mar 2002', 'Oct 2001–Mar 2002', 'Oct 2001–Mar 2002', 'Oct 2001–Mar 2002', 'Oct 2001–Mar 2002', 'Dec 2002–Apr 2003', 'Dec 2002–Apr 2003', 'Dec 2002–Apr 2003', 'Oct–Dec 2003', 'Apr–Jun 2004'] 

ebola = pd.DataFrame(data, columns=['Date range'])

ebola1 = ebola['Date range'].str.split('–', 1, expand=True)
ebola1.columns = ['start date','end date']

然后numpy.where for add years from end date by Series.str.extract but only if not exist in start date column tested by Series.str.contains:

mask = ebola1['start date'].str.contains('\d')
years = ebola1['end date'].str.extract('(\d+)', expand=False)
ebola1['start date'] = np.where(mask, 
                                ebola1['start date'], 
                                ebola1['start date'] + ' ' + years)

print (ebola1)

   start date  end date
0    Jun 1976  Nov 1976
1    Sep 1976  Oct 1976
2    Jun 1977      None
3    Jul 1979  Oct 1979
4    Nov 1994      None
5    Nov 1994  Feb 1995
6    Jan 1995  Jul 1995
7    Jan 1996  Mar 1996
8    Jul 1996  Jan 1997
9    Oct 2000  Feb 2001
10   Oct 2001  Mar 2002
11   Oct 2001  Mar 2002
12   Oct 2001  Mar 2002
13   Oct 2001  Mar 2002
14   Oct 2001  Mar 2002
15   Dec 2002  Apr 2003
16   Dec 2002  Apr 2003
17   Dec 2002  Apr 2003
18   Oct 2003  Dec 2003
19   Apr 2004  Jun 2004

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