我正在处理2个数据帧。第一种是信息不完整。第二个数据帧具有时间范围为首次看到和最后看到的信息。我尝试使用df2的源地址和时间范围来填充sourcehostname和sourceusername,其中df1的datetime属于该时间范围
df1
sourceaddress sourcehostname sourceusername endtime datetime
0 10.0.0.59 computer1 NaN 1564666638000 2019-08-01 09:37:18
1 10.0.0.59 NaN NaN 1564666640000 2019-08-01 09:37:20
2 10.0.0.59 NaN NaN 1564666642000 2019-08-01 09:37:22
3 10.0.0.59 NaN NaN 1564666643000 2019-08-01 09:37:23
4 10.0.0.59 NaN NaN 1564666643000 2019-08-01 09:37:23
5 10.0.0.59 NaN NaN 1564666645000 2019-08-01 09:37:25
6 10.0.0.59 computer1 NaN 1564666646000 2019-08-01 09:37:26
7 10.0.0.59 NaN NaN 1564666646000 2019-08-01 09:37:26
8 10.0.0.59 computer1 NaN 1564666649000 2019-08-01 09:37:29
9 10.0.0.59 computer1 NaN 1564666650000 2019-08-01 09:37:30
10 10.0.0.59 NaN NaN 1564666850000 2019-08-01 09:40:50
...
43196 10.0.0.187 computer2 NaN 1564718395000 2019-08-01 23:59:55
43197 10.0.0.187 computer2 user1 1564718397000 2019-08-01 23:59:57
43198 10.0.0.187 computer2 NaN 1564718397000 2019-08-01 23:59:57
43199 10.0.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58
43200 10.0.0.187 NaN NaN 1564718398000 2019-08-01 23:59:58
43201 10.0.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58
df2
sourceaddress sourcehostname sourceusername firstseen lastseen
0 10.0.0.59 computer1 user1 2019-08-01 09:37:59 2019-08-01 09:46:08
1 10.0.0.187 computer2 user1 2019-08-01 00:00:03 2019-08-01 23:59:58
期望结果:
df3
sourceaddress sourcehostname sourceusername endtime datetime
0 10.0.0.59 computer1 NaN 1564666638000 2019-08-01 09:37:18
1 10.0.0.59 NaN NaN 1564666640000 2019-08-01 09:37:20
2 10.0.0.59 NaN NaN 1564666642000 2019-08-01 09:37:22
3 10.0.0.59 NaN NaN 1564666643000 2019-08-01 09:37:23
4 10.0.0.59 NaN NaN 1564666643000 2019-08-01 09:37:23
5 10.0.0.59 NaN NaN 1564666645000 2019-08-01 09:37:25
6 10.0.0.59 computer1 NaN 1564666646000 2019-08-01 09:37:26
7 10.0.0.59 NaN NaN 1564666646000 2019-08-01 09:37:26
8 10.0.0.59 computer1 NaN 1564666649000 2019-08-01 09:37:29
9 10.0.0.59 computer1 NaN 1564666650000 2019-08-01 09:37:30
10 10.0.0.59 computer1 user1 1564668650000 2019-08-01 10:10:50
...
43196 10.0.0.187 computer2 user1 1564718395000 2019-08-01 23:59:55
43197 10.0.0.187 computer2 user1 1564718397000 2019-08-01 23:59:57
43198 10.0.0.187 computer2 user1 1564718397000 2019-08-01 23:59:57
43199 10.0.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58
43200 10.0.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58
43201 10.0.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58
**以下为示例:
df3[-5:]
sourceaddress sourcehostname sourceusername endtime datetime firstseen lastseen
43197 10.99.0.187 computer2 user1 1564718397000 2019-08-01 23:59:57 2019-08-01 00:00:03 2019-08-01 23:59:58
43198 10.99.0.187 computer2 NaN 1564718397000 2019-08-01 23:59:57 2019-08-01 00:00:03 2019-08-01 23:59:58
43199 10.99.0.187 computer2 NaN 1564718398000 2019-08-01 23:59:58 2019-08-01 00:00:03 2019-08-01 23:59:58
43200 10.99.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58 2019-08-01 00:00:03 2019-08-01 23:59:58
43201 10.99.0.187 computer2 user1 1564718398000 2019-08-01 23:59:58 2019-08-01 00:00:03 2019-08-01 23:59:58
它看起来像一个
merge
问题:然后你可以删除
sourcehostname_df2
和sourceusername_df2
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