有没有办法在R中使其他变量保持不变的同时拆分时间和持续时间变量？

好问题。因此，每行隐式包含一个或两个间隔，因此您应该能够仅在每行上定义这些间隔，然后将其旋转为long，但不能使用间隔值进行旋转（还可以吗？）。因此，这是我的方法，该方法最多为每条线计算两个班次的开始时间，然后从旋转后的下一个班次的开始推断班次的结束。内联评论。

library(lubridate, warn.conflicts = FALSE)
library(tidyverse)
library(magrittr, warn.conflicts = FALSE)
library(hablar, warn.conflicts = FALSE)

(mydf <- tibble(
  id    = "m1",
  start = as_datetime(c("2020-01-03 10:00:00", "2020-01-03 19:20:00")),
  end   = as_datetime(c("2020-01-03 16:00:00", "2020-01-03 20:50:00")),
  day   = 1
))
#> # A tibble: 2 x 4
#>   id    start               end                   day
#>   <chr> <dttm>              <dttm>              <dbl>
#> 1 m1    2020-01-03 10:00:00 2020-01-03 16:00:00     1
#> 2 m1    2020-01-03 19:20:00 2020-01-03 20:50:00     1

(mydf2 <- 
    mydf %>% 
    # Assume the relevant noontime cutoff is on the same day as the start
    mutate(midday = 
             start %>% as_date() %>% 
             add(12 %>% hours()) %>% 
             fit_to_timeline() %>% 
             # No relevant midday if the shift doesn't include noon
             na_if(not(. %within% interval(start, end)))) %>% 

    # Make an original row ID since there doesn't seem to be one, and we will need
    # to build intervals within the data stemming from each original row
    rownames_to_column("orig_shift") %>% 

    pivot_longer(cols = c(start, midday, end),
                 # The timestamps we have here will be treated as start times
                 values_to = "start",
                 # Drop rows that would exist due to irrelevant middays
                 values_drop_na = TRUE) %>% 
    select(-name) %>% 

    # Infer shift end times as the start of the next shift, within lines defined
    # by the original shifts
    group_by(orig_shift) %>% 
    arrange(start) %>% 
    mutate(end = lead(start)) %>% 
    ungroup() %>% 

    # Drop lines that represent the end of the last shift and not a full one
    drop_na() %>% 

    # Compute those durations and times (should times really be globally
    # cumulative? Also, your specified mydf2 seems to have an incorrect first time
    # value)
    mutate(duration = start %--% end %>% as.numeric("hours"),
           time = cumsum(duration)) %>% 
    select(id, start, end, day, duration, time))
#> # A tibble: 3 x 6
#>   id    start               end                   day duration  time
#>   <chr> <dttm>              <dttm>              <dbl>    <dbl> <dbl>
#> 1 m1    2020-01-03 10:00:00 2020-01-03 12:00:00     1      2     2  
#> 2 m1    2020-01-03 12:00:00 2020-01-03 16:00:00     1      4     6  
#> 3 m1    2020-01-03 19:20:00 2020-01-03 20:50:00     1      1.5   7.5

^{由reprex软件包（v0.3.0）创建于2019-10-23}