Question

这是一个玩具数据。

datetime <- c('2019-11-06 13:05:07',
'2019-11-06 13:05:08',
'2019-11-06 13:05:09',
'2019-11-06 13:05:10',
'2019-11-06 13:05:11',
'2019-11-06 13:05:12',
'2019-11-06 13:05:13',
'2019-11-06 13:05:14',
'2019-11-06 13:05:15',
'2019-11-06 13:05:16',
'2019-11-06 13:05:17',
'2019-11-06 13:05:18',
'2019-11-06 13:05:19',
'2019-11-06 13:05:20',
'2019-11-06 13:05:21',
'2019-11-06 13:05:22')

active <- c(1,1,1,1,0,0,0,0,0,1,1,1,1,1,0,0)

df <- data.frame(datetime, active)

我正在寻找可以计算活动块的矢量化代码。在上面的示例中，我们有2个活动块。

13:05:07-13:05:10

13:05:16-13:05:20

Answer 1

aggregate(as.POSIXct(datetime) ~ id,
          subset(transform(df, id = with(rle(df$active), rep(seq_along(lengths), lengths))),
                 active == 1),
          function(x) toString(range(x)))
#  id             lubridate::ymd_hms(datetime)
#1  1 2019-11-06 13:05:07, 2019-11-06 13:05:10
#2  3 2019-11-06 13:05:16, 2019-11-06 13:05:20

OR

library(dplyr)
library(data.table)
df %>%
    mutate(datetime = as.POSIXct(datetime),
           id = rleid(active)) %>%
    filter(active == 1) %>%
    group_by(id) %>%
    summarise(min = min(datetime),
              max = max(datetime))
## A tibble: 2 x 3
#     id min                 max                
#  <int> <dttm>              <dttm>             
#1     1 2019-11-06 13:05:07 2019-11-06 13:05:10
#2     3 2019-11-06 13:05:16 2019-11-06 13:05:20

计算来自物联网设备的活动块

1 个答案: