Question

> log_df[1:10, ]
      tagid            happened status
1  03B2ACE7 2016-06-28 18:07:36   open
2  03B2ACE7 2016-06-28 18:36:15 closed
3  03B2ACE7 2016-06-29 07:29:59   open
4  03B2ACE7 2016-06-29 08:06:23 closed
5  03B2ACE7 2016-06-30 16:10:48   open
6  03B2ACE7 2016-06-30 17:23:55   open
7  03B2ACE7 2016-07-01 10:12:06 closed
8  03B2ACE7 2016-07-01 13:39:58 closed
9  03B2ACE7 2016-07-02 10:08:40   open
10 03B2ACE7 2016-07-02 13:33:01 closed
...

以上是我的数据。我想要制作的是：

      tagid                open               closed
1  03B2ACE7 2016-06-28 18:07:36  2016-06-28 18:36:15
2  03B2ACE7 2016-06-29 07:29:59  2016-06-29 08:06:23
3  03B2ACE7 2016-06-30 16:10:48  2016-07-01 10:12:06
...

我试图在reshape2包中使用dcast。但是，我必须选择性地选择

“打开”，这是第一个，只有那些在关闭之后出现并且在关闭之前出现的“关闭”。

因此，从log_df开始，第6行和第7行将被忽略..

我真的被卡住了，不知道我怎么能这样做.. 也许dcast不是最好的方法？

请帮忙！非常感谢你！

Answer 1

使用dplyr和tidyr（来自tidiverse，重塑的演变）：

library(dplyr)
library(tidyr)

df %>% 
    filter((status == 'open' & lag(status, default = "") != 'open') | (status == 'closed' & lead(status, default = "") != "closed")) %>% 
    mutate(r = ceiling(row_number() / 2)) %>% 
    spread(status, happened)

#>      tagid r              closed                open
#> 1 03B2ACE7 1 2016-06-28 18:36:15 2016-06-28 18:07:36
#> 2 03B2ACE7 2 2016-06-29 08:06:23 2016-06-29 07:29:59
#> 3 03B2ACE7 3 2016-07-01 13:39:58 2016-06-30 16:10:48
#> 4 03B2ACE7 4 2016-07-02 13:33:01 2016-07-02 10:08:40

它：

使用特定条件过滤data.frame
添加一列以存储＆＃39; <＆＃39;
将值传播到列（相当于dcast）

数据：

df <- read.table(text = '      tagid            happened status
1  03B2ACE7 "2016-06-28 18:07:36"   open
2  03B2ACE7 "2016-06-28 18:36:15" closed
3  03B2ACE7 "2016-06-29 07:29:59"   open
4  03B2ACE7 "2016-06-29 08:06:23" closed
5  03B2ACE7 "2016-06-30 16:10:48"   open
6  03B2ACE7 "2016-06-30 17:23:55"   open
7  03B2ACE7 "2016-07-01 10:12:06" closed
8  03B2ACE7 "2016-07-01 13:39:58" closed
9  03B2ACE7 "2016-07-02 10:08:40"   open
10 03B2ACE7 "2016-07-02 13:33:01" closed', h = T)

r

1 个答案:

数据：