如何计算R中带有条件的数据框列中不同值的数量

Question

I have a data frame that looks like this:

  date     timestamp    transfer ID IP Address          Username Encryption File                        Bytes Speed                                                                DateTimeStamp 
1 20160525 08:22:06.838 F798256B    10.199.194.38:57708 wei2dt   -          ""                          264   "1.62 seconds (1.30 kilobits/sec)"                                   20160525 08:22:06.838
2 20160525 08:28:26.920 F798256C    10.19.105.15:57708  wei2dt   -          "isi_audit_log.dmp-sv.tmp"  69    "0.29 seconds (1.93 kilobits/sec)"                                   20160525 08:28:26.920
3 20160525 08:28:26.923 F798256D    10.19.105.15:57708  wei2dt   -          "isi_audit_log.dmp-sv.met"  0     "Unable to stat isi_audit_log.dmp-sv.met: No such file or directory" 20160525 08:28:26.923
4 20160525 08:28:26.933 F798256E    10.19.105.15:57708  wei2dt   -          "CG0009 1364_GT_report.txt" 34    "0.01 seconds (34.0 kilobits/sec)"                                   20160525 08:28:26.933

I want to count the number of users (usernames) that were online at a certain time. Essentially, I want to check every five minutes or so how many users were active. I need to use the DateTimestamp column to create my intervals and utilize it as a condition to count the number of distinct users at that period of time. I've tried using a while loop to do something of the sort, but it did not work. Are there any suggestions on how I should go about this?

Answer 1

With dplyr

df %>% mutate(timeInt=cut(DateTimeStamp,breaks="5 min")) %>% 
group_by(timeInt) %>% summarise(numberUniqueUsers=length(unique(Username)))