I'm trying to rank a data frame based on reverse order for dates. For example, see below:
| user | start_time |
|---|---|
| ID | 2022-05-31 18:13:43 |
| BB | 2020-11-07 00:42:36 |
| RL | 2021-11-25 01:01:15 |
| ID | 2020-05-30 03:30:19 |
| KF | 2021-05-18 00:26:32 |
| MT | 2021-07-02 22:44:01 |
| BB | 2021-08-01 16:06:37 |
| RL | 2021-02-02 20:54:08 |
| BB | 2022-06-25 22:52:56 |
| KF | 2021-04-24 01:45:18 |
The reverse order rank should be:
| user | start_time | rank |
|---|---|---|
| ID | 2022-05-31 18:13:43 | 1 |
| BB | 2020-11-07 00:42:36 | 3 |
| RL | 2021-11-25 01:01:15 | 1 |
| ID | 2020-05-30 03:30:19 | 2 |
| KF | 2021-05-18 00:26:32 | 1 |
| MT | 2021-07-02 22:44:01 | 1 |
| BB | 2021-08-01 16:06:37 | 2 |
| RL | 2021-02-02 20:54:08 | 2 |
| BB | 2022-06-25 22:52:56 | 1 |
| KF | 2021-04-24 01:45:18 | 2 |
CodePudding user response：
One
do.call(
rbind,
lapply(split(df,df$user),function(x){
cbind(x,"rank"=order(x$start_time,decreasing=T))
})
)
user start_time rank
BB.2 BB 2020-11-07 00:42:36 3
BB.7 BB 2021-08-01 16:06:37 2
BB.9 BB 2022-06-25 22:52:56 1
ID.1 ID 2022-05-31 18:13:43 1
ID.4 ID 2020-05-30 03:30:19 2
KF.5 KF 2021-05-18 00:26:32 1
KF.10 KF 2021-04-24 01:45:18 2
MT MT 2021-07-02 22:44:01 1
RL.3 RL 2021-11-25 01:01:15 1
RL.8 RL 2021-02-02 20:54:08 2
CodePudding user response：
Using dplyr,
library(dplyr)
df %>%
group_by(user) %>%
mutate(rank = order(start_time, decreasing = T))
user start_time rank
<chr> <chr> <int>
1 ID 2022-05-31 18:13:43 1
2 BB 2020-11-07 00:42:36 3
3 RL 2021-11-25 01:01:15 1
4 ID 2020-05-30 03:30:19 2
5 KF 2021-05-18 00:26:32 1
6 MT 2021-07-02 22:44:01 1
7 BB 2021-08-01 16:06:37 2
8 RL 2021-02-02 20:54:08 2
9 BB 2022-06-25 22:52:56 1
10 KF 2021-04-24 01:45:18 2