计算不同行的列之间的时间差（difftime）

Question

我有不同工作的“开始”和“结束”时间数据，按“所有者”分组：

Data <- data.frame(
  job = c(1, 2, 3, 4, 5),
  owner = c("name1", "name2", "name1", "name1", "name2"),
  Start = as.POSIXct(c("2015-01-01 15:00:00", "2015-01-01 15:01:00", "2015-01-01 15:13:00", "2015-01-01 15:20:00", "2015-01-01 15:39:02"), format="%Y-%m-%d %H:%M:%S"),
  End =   as.POSIXct(c("2015-01-01 15:11:11", "2015-01-01 15:17:21", "2015-01-01 15:17:00", "2015-01-01 15:31:21", "2015-01-01 15:40:11"), format="%Y-%m-%d %H:%M:%S")
)

对于每个所有者，我想计算每个所有者的作业之间的空闲时间，即一个作业的“结束”时间与下一个作业的“开始”时间之间的差异。

如何使用difftime()计算不同列中特定行和时间之间的时间差？

结果应如下所示：

job, owner, idletime
1, name1, NA
2, name2, NA
3, name1, 1.816667  # End of row 1 minus Start of row 3
4, name1, 3.0       # End of row 3 minus Start of row 4
...

Answer 1

这是使用data.table的可能解决方案

library(data.table) # v 1.9.5+
setDT(Data)[, idletime := difftime(Start, shift(End), units = "mins"), by = owner]
#    job owner               Start                 End       idletime
# 1:   1 name1 2015-01-01 15:00:00 2015-01-01 15:11:11        NA mins
# 2:   2 name2 2015-01-01 15:01:00 2015-01-01 15:17:21        NA mins
# 3:   3 name1 2015-01-01 15:13:00 2015-01-01 15:17:00  1.816667 mins
# 4:   4 name1 2015-01-01 15:20:00 2015-01-01 15:31:21  3.000000 mins
# 5:   5 name2 2015-01-01 15:39:02 2015-01-01 15:40:11 21.683333 mins

或者使用dplyr

library(dplyr)
Data %>%
  group_by(owner) %>%
  mutate(idletime = difftime(Start, lag(End), units = "mins"))

# Source: local data frame [5 x 5]
# Groups: owner
# 
#   job owner               Start                 End       idletime
# 1   1 name1 2015-01-01 15:00:00 2015-01-01 15:11:11        NA mins
# 2   2 name2 2015-01-01 15:01:00 2015-01-01 15:17:21        NA mins
# 3   3 name1 2015-01-01 15:13:00 2015-01-01 15:17:00  1.816667 mins
# 4   4 name1 2015-01-01 15:20:00 2015-01-01 15:31:21  3.000000 mins
# 5   5 name2 2015-01-01 15:39:02 2015-01-01 15:40:11 21.683333 mins

Answer 2

如果我们使用base R ，那么ave将是一种选择。 我们使用ave得到“所有者”分组的“结束”的lag ，将其用作difftime的第二个参数来创建“idtime”。

Data$idtime <- with(Data, difftime(Start, ave(End, owner,FUN=lag), units='mins'))

Data
#  job owner               Start                 End         idtime
#1   1 name1 2015-01-01 15:00:00 2015-01-01 15:11:11        NA mins
#2   2 name2 2015-01-01 15:01:00 2015-01-01 15:17:21        NA mins
#3   3 name1 2015-01-01 15:13:00 2015-01-01 15:17:00  1.816667 mins
#4   4 name1 2015-01-01 15:20:00 2015-01-01 15:31:21  3.000000 mins
#5   5 name2 2015-01-01 15:39:02 2015-01-01 15:40:11 21.683333 mins

注意：我将列名称命名为“idtime”以将代码保存在一行中:-)

Answer 3

library(dplyr)


Data <- data.frame(
  job = c(1, 2, 3, 4, 5),
  owner = c("name1", "name2", "name1", "name1", "name2"),
  Start = as.POSIXct(c("2015-01-01 15:00:00", "2015-01-01 15:01:00", "2015-01-01 15:13:00", "2015-01-01 15:20:00", "2015-01-01 15:39:02"), format="%Y-%m-%d %H:%M:%S"),
  End =   as.POSIXct(c("2015-01-01 15:11:11", "2015-01-01 15:17:21", "2015-01-01 15:17:00", "2015-01-01 15:31:21", "2015-01-01 15:40:11"), format="%Y-%m-%d %H:%M:%S")
)


Data %>% 
  group_by(owner) %>% 
  arrange(Start) %>% 
  mutate(lagEnd = lag(End),
         idletime = difftime(Start,lagEnd, units="mins")) %>%
  ungroup %>%
  arrange(job) %>%
  select(job,owner,idletime)

#   job owner        idletime
# 1   1 name1         NA mins
# 2   2 name2         NA mins
# 3   3 name1   1.816667 mins
# 4   4 name1   3.000000 mins
# 5   5 name2  21.683333 mins