根据 R 中的多个条件创建开始和结束时间列（dplyr、lubridate）

Question

我有一个数据集，df

 Read      Box       ID      Time
 T         out               10/1/2019 9:00:01 AM
 T         out               10/1/2019 9:00:02 AM
 T         out               10/1/2019 9:00:03 AM
 T         out               10/1/2019 9:02:59 AM
 T         out               10/1/2019 9:03:00 AM
 F                           10/1/2019 9:05:00 AM
 T         out               10/1/2019 9:06:00 AM
 T         out               10/1/2019 9:06:02 AM
 T         in                10/1/2019 9:07:00 AM
 T         in                10/1/2019 9:07:02 AM
 T         out               10/1/2019 9:07:04 AM
 T         out               10/1/2019 9:07:05 AM
 T         out               10/1/2019 9:07:06 AM
           hello             10/1/2019 9:07:08 AM

基于此数据集中的某些条件，我想创建一个开始时间列和一个结束时间列。我想在发生以下情况时创建一个 'starttime'：Read == "T"、Box == "out" 和 ID == "" 当这种情况的第一个实例发生时，将生成开始时间。例如，对于此数据集，开始时间将为 10/1/2019 9:00:01 AM，因为这是我们首先看到所需条件发生的地方（Read = T，Box = out 和 ID = ""）但是，当这些条件中的任何一个不成立时，就会创建结束时间。因此，第一个结束时间将发生在第 6 行之前，时间为 10/1/2019 9:03:00 AM。我的最终目标是为此创建一个持续时间列。

这是我想要的输出：

  starttime                    endtime                     duration

  10/01/2019 9:00:01 AM        10/01/2019 9:03:00 AM       179 secs
  10/1/2019 9:06:00 AM         10/1/2019 9:06:02 AM        2 secs
  10/1/2019 9:07:04 AM         10/1/2019 9:07:06 AM        2 secs

输出：

  structure(list(Read = structure(c(3L, 3L, 3L, 3L, 3L, 2L, 3L, 
  3L, 3L, 3L, 4L, 4L, 3L, 1L), .Label = c("", "F", "T", "T "), class = "factor"), 
  Box = structure(c(3L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 2L, 2L, 
  3L, 3L, 3L, 1L), .Label = c("", "in", "out"), class = "factor"), 
  ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 1L, 2L), .Label = c("", "hello"), class = "factor"), 
  Time = structure(1:14, .Label = c("10/1/2019 9:00:01 AM", 
 "10/1/2019 9:00:02 AM", "10/1/2019 9:00:03 AM", "10/1/2019 9:02:59 AM", 
 "10/1/2019 9:03:00 AM", "10/1/2019 9:05:00 AM", "10/1/2019 9:06:00 AM", 
 "10/1/2019 9:06:02 AM", "10/1/2019 9:07:00 AM", "10/1/2019 9:07:02 AM", 
 "10/1/2019 9:07:04 AM", "10/1/2019 9:07:05 AM", "10/1/2019 9:07:06 AM", 
 "10/1/2019 9:07:08 AM"), class = "factor")), class = "data.frame", row.names = c(NA, 
 -14L))

我认为总的来说，我必须创建一个循环。我相信我的思维过程是正确的，只是不确定如何制定代码。这就是我正在尝试的：

 df2 <- mutate(df,
      Date = lubridate::mdy_hms(Date))




   for ( i in 2:nrow(df2))
    {
  if(df2$Read[[i]] == 'T')

     }

我认为这可能是一个开始（只是将我的条件放在循环中，我不确定如何完成）

欢迎任何建议。

Answer 1

你可以不用循环就可以做到这一点。使用 dplyr 因为使用管道很容易做很多事情。

我们首先将Time列转换为POSIXctclass，创建一个cond列，根据我们要检查的条件给出逻辑值，创建一个列使用 cond 列的累积总和创建组。仅保留满足条件的行，并获得 Time 的 first 和 last 值以及它们之间的差异。

library(dplyr)

df %>%
  mutate(Time = lubridate::mdy_hms(Time), 
         cond = Read == "T" & Box == "out" & ID == "", 
         grp = cumsum(!cond)) %>%
  filter(cond) %>%
  group_by(grp) %>%
  summarise(starttime = first(Time), 
            endtime = last(Time), 
            duration = difftime(endtime, starttime, units = "secs")) %>%
  select(-grp)

# A tibble: 3 x 3
#  starttime           endtime             duration
#  <dttm>              <dttm>              <drtn>  
#1 2019-10-01 09:00:01 2019-10-01 09:03:00 179 secs
#2 2019-10-01 09:06:00 2019-10-01 09:06:02   2 secs
#3 2019-10-01 09:07:04 2019-10-01 09:07:06   2 secs

数据

我已经稍微清理了你的数据并将其用作 df。

df <- structure(list(Read = c("T", "T", "T", "T", "T", "F", "T", "T", 
"T", "T", "T", "T", "T", ""), Box = c("out", "out", "out", "out", 
"out", "", "out", "out", "in", "in", "out", "out", "out", "hello"
), ID = c("", "", "", "", "", "", "", "", "", "", "", "", "", 
""), Time = c("10/1/2019 9:00:01 AM", "10/1/2019 9:00:02 AM", 
"10/1/2019 9:00:03 AM", "10/1/2019 9:02:59 AM", "10/1/2019 9:03:00 AM", 
"10/1/2019 9:05:00 AM", "10/1/2019 9:06:00 AM", "10/1/2019 9:06:02 AM", 
"10/1/2019 9:07:00 AM", "10/1/2019 9:07:02 AM", "10/1/2019 9:07:04 AM", 
"10/1/2019 9:07:05 AM", "10/1/2019 9:07:06 AM", "10/1/2019 9:07:08 AM"
)), row.names = c(NA, -14L), class = "data.frame")

根据 R 中的多个条件创建开始和结束时间列（dplyr、lubridate）

Create start and endtime columns based on multiple conditions in R (dplyr, lubridate)

loops

r

lubridate

dplyr