将开始时间和总持续时间转换为每小时经过的时间

奥列克桑德尔

我有关于开始时间（“ startTime”，日期时间变量，POSIXct）和持续时间（以分钟为单位）的数据（“ duration_minutes”）：

df <- data.frame(id = c(1, 2, 3),
                 startTime = as.POSIXct(c("2018-01-01 12:15:31",
                                          "2018-01-02 23:43:00",
                                          "2018-01-03 11:00:11")), 
                 duration_minutes = c(315, 120, 45))

我想将开始时间和持续时间转换为每小时从每小时开始时间到持续时间结束时的最后一个小时的每小时经过时间：

df_result <- data.frame(id = c(1, 1, 1, 1, 1, 1, 2, 2, 2, 3),
                        startTime = c("2018-01-01 12:15:31","2018-01-01 13:00:00",
                                "2018-01-01 14:00:00","2018-01-01 15:00:00",
                                "2018-01-01 16:00:00","2018-01-01 17:00:00",

                                "2018-01-02 23:43:00","2018-01-03 00:00:00",
                                "2018-01-03 01:00:00",

                                "2018-01-03 11:00:11"),
                        duration_minutes = c(44.48, 60, 60, 60, 60, 30.5, 17, 60, 43, 45))

请提供可能的解决方案的建议。

arg0naut91

尝试这个：

library(data.table)
library(lubridate)
library(magrittr)

df <-
  setDT(df)[, start_ceiling := ceiling_date(startTime, "hour", change_on_boundary = TRUE)] %>%
  .[, `:=` (
    reps = ifelse(
      startTime + (duration_minutes * 60) <= start_ceiling, 1, pmax(2, floor(duration_minutes / 60) + 1)
    ),
    initial_diff = as.numeric(difftime(start_ceiling[1], startTime[1], units = "mins"))
  ), by = id] %>%
  .[, df[df[, rep(.I, reps)]]] %>%
  .[, startTime := pmax(startTime, floor_date(startTime, "hour") + hours(0:(.N - 1))), by = id] %>%
  .[reps > 1, duration_minutes := c(initial_diff[.N], 
                                    rep(60, reps[.N] - 2),
                                    (duration_minutes[.N] - initial_diff[.N]) %% 60), by = id] %>%
  .[!(duration_minutes == 0 & reps > 1), ] %>%
  .[, c("reps", "start_ceiling", "initial_diff") := NULL]

我已经用我们到目前为止收集的所有场景对它进行了测试，这是输出：

    id           startTime duration_minutes
 1:  1 2018-01-01 12:15:31         44.48333
 2:  1 2018-01-01 13:00:00         60.00000
 3:  1 2018-01-01 14:00:00         60.00000
 4:  1 2018-01-01 15:00:00         60.00000
 5:  1 2018-01-01 16:00:00         60.00000
 6:  1 2018-01-01 17:00:00         30.51667
 7:  2 2018-01-02 23:43:00         17.00000
 8:  2 2018-01-03 00:00:00         60.00000
 9:  2 2018-01-03 01:00:00         43.00000
10:  3 2018-01-03 11:00:11         45.00000
11:  4 2018-01-04 10:00:00         60.00000
12:  4 2018-01-04 11:00:00          5.00000
13:  5 2018-01-05 00:00:00         60.00000
14:  6 2018-01-06 11:35:00         25.00000
15:  6 2018-01-06 12:00:00         10.00000
16:  7 2018-01-07 00:00:00         60.00000
17:  7 2018-01-07 01:00:00         60.00000

使用的数据：

df <- data.frame(
  id = c(1, 2, 3, 4, 5, 6, 7),
  startTime = as.POSIXct(
    c(
      "2018-01-01 12:15:31",
      "2018-01-02 23:43:00",
      "2018-01-03 11:00:11",
      "2018-01-04 10:00:00",
      "2018-01-05 00:00:00",
      "2018-01-06 11:35:00",
      "2018-01-07 00:00:00"
    )
  ),
  duration_minutes = c(315, 120, 45, 65, 60, 35, 120)
)

df

  id           startTime duration_minutes
1  1 2018-01-01 12:15:31              315
2  2 2018-01-02 23:43:00              120
3  3 2018-01-03 11:00:11               45
4  4 2018-01-04 10:00:00               65
5  5 2018-01-05 00:00:00               60
6  6 2018-01-06 11:35:00               35
7  7 2018-01-07 00:00:00              120

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