组中每一行的Dplyr时差

debugcn 发表于 Dev

林内特

我正在尝试计算我的电子邮件持续时间。我有按ID分组的电子邮件。在此示例中，我已经按组A对电子邮件进行了分组。我希望计算组A的电子邮件读取持续时间。我当前使用的代码以秒为单位计算其上一次和第一次。

data <-rawdata %>%
    group_by(ID) %>%
    summarize(diff = difftime(last(as.POSIXct(Endtime, format ="%m/%d/%Y %I:%M:%S %p")),
            first(as.POSIXct(Starttime, format = "%m/%d/%Y %I:%M:%S %p" )), units = "secs"))

但是，我认为这不是我邮件阅读的准确显示。总的来说，我希望每行的时差可以使读数更准确。期望的输出将是（以下），因为它显示了每一行的时间差，从而允许我进一步求和整个diff列，以便确定我的电子邮件持续时间（以秒为单位）。

        Starttime               Endtime                     ID         diff

        12/18/2019 4:06:59PM    12/18/2019 4:07:05 PM        A        6 secs
        12/18/2019 4:07:26PM    12/18/2019 4:07:28 PM        A        1 secs
        12/17/2019 6:48:06PM    12/17/2019 6:48:07PM         A        1 sec
        12/17/2019 6:25:16PM    12/17/2019 6:25:22PM         A        6 secs

任何帮助表示赞赏。我将继续对此进行研究！

罗纳克·沙

如果您希望阅读电子邮件的开始时间和结束时间有所不同，可以

library(dplyr)

rawdata %>%
  mutate_at(vars(ends_with('time')), lubridate::mdy_hms) %>%
  mutate(diff = difftime(Endtime, Starttime, units = "secs"))

#            Starttime             Endtime ID   diff
#1 2019-12-18 16:06:59 2019-12-18 16:07:05  A 6 secs
#2 2019-12-18 16:07:26 2019-12-18 16:07:28  A 2 secs
#3 2019-12-17 18:48:06 2019-12-17 18:48:07  A 1 secs
#4 2019-12-17 18:25:16 2019-12-17 18:25:22  A 6 secs

或在基数R中：

transform(transform(rawdata, 
     Starttime = as.POSIXct(Starttime, format = "%m/%d/%Y %I:%M:%S %p"), 
     Endtime = as.POSIXct(Endtime, format = "%m/%d/%Y %I:%M:%S %p")), 
               diff = difftime(Endtime, Starttime, units = "secs"))

数据

rawdata <- structure(list(Starttime = structure(c(3L, 4L, 2L, 1L), 
.Label = c("12/17/2019 6:25:16PM", "12/17/2019 6:48:06PM", "12/18/2019 4:06:59PM", 
"12/18/2019 4:07:26PM"), class = "factor"), Endtime = structure(c(3L, 4L, 2L, 1L), 
.Label = c("12/17/2019 6:25:22PM", "12/17/2019 6:48:07PM", "12/18/2019 4:07:05 PM", 
"12/18/2019 4:07:28 PM"), class = "factor"), ID = structure(c(1L, 1L, 1L, 1L), 
.Label = "A", class = "factor")), row.names = c(NA, -4L), class = "data.frame")

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