根据列值中第一次出现的项目将数据框列拆分为两个
[英]Split dataframe column into two based on first occurrence of an item in column value
问题描述
I have the following dataframe with 4 columns:
我有以下 4 列数据框：
IP Time URL Staus
0 10.128.2.1 [29/Nov/2017:06:58:55 GET /login.php HTTP/1.1 200
1 10.128.2.1 [29/Nov/2017:06:59:02 POST /process.php HTTP/1.1 302
2 10.128.2.1 [29/Nov/2017:06:59:03 GET /home.php HTTP/1.1 200
3 10.131.2.1 [29/Nov/2017:06:59:04 GET /js/vendor/moment.min.js HTTP/1.1 200
4 10.130.2.1 [29/Nov/2017:06:59:06 GET /bootstrap-3.3.7/js/bootstrap.js HTTP/1.1 200
5 10.130.2.1 [29/Nov/2017:06:59:19 GET /profile.php?user=bala HTTP/1.1 200
I need to split the Time column into two new columns titled 'date' and 'time'.我需要将时间列拆分为两个名为“日期”和“时间”的新列。 I need to split the current value under the Time column by the first occurrence of ':'.我需要通过第一次出现“：”来拆分时间列下的当前值。
I have tried the split function for the first instance of ':' as follows:我已经为 ':' 的第一个实例尝试了 split 函数，如下所示：
df['date','time']=df.Time.str.split(":", 1)
But this is what i end up getting:但这就是我最终得到的：
IP Time URL Staus (date, time)
0 10.128.2.1 [29/Nov/2017:06:58:55 GET /login.php HTTP/1.1 200 [[29/Nov/2017, 06:58:55]
1 10.128.2.1 [29/Nov/2017:06:59:02 POST /process.php HTTP/1.1 302 [[29/Nov/2017, 06:59:02]
2 10.128.2.1 [29/Nov/2017:06:59:03 GET /home.php HTTP/1.1 200 [[29/Nov/2017, 06:59:03]
3 10.131.2.1 [29/Nov/2017:06:59:04 GET /js/vendor/moment.min.js HTTP/1.1 200 [[29/Nov/2017, 06:59:04]
How do I properly split into two columns?我如何正确地分成两列？ What am I doing wrong?我究竟做错了什么？ Help :(帮助 ：（
1 个解决方案
解决方案1
1 已采纳 2020-03-01 06:33:29
Add parameter expand=True for DataFrame and then add [] for new columns:为DataFrame添加参数expand=True ，然后为新列添加[] ：
df[['date','time']] = df.Time.str.split(":", 1, expand=True)
print (df)
IP Time URL Staus \
0 10.128.2.1 [29/Nov/2017:06:58:55 GET/login.php HTTP/1.1 200
1 10.128.2.1 [29/Nov/2017:06:59:02 POST/process.php HTTP/1.1 302
date time
0 [29/Nov/2017 06:58:55
1 [29/Nov/2017 06:59:02
Or also add Series.str.strip for remove trailing [] :或者也添加Series.str.strip以删除尾随[] ：
df[['date','time']] = df.Time.str.strip('[]').str.split(":", 1, expand=True)
print (df)
IP Time URL Staus \
0 10.128.2.1 [29/Nov/2017:06:58:55 GET/login.php HTTP/1.1 200
1 10.128.2.1 [29/Nov/2017:06:59:02 POST/process.php HTTP/1.1 302
date time
0 29/Nov/2017 06:58:55
1 29/Nov/2017 06:59:02
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