根据多个过滤条件（R、dplyr）创建时间戳列

Question

我有一个数据集，df

 Read      Box       ID      Time                             Subject 
 T         out               10/1/2019 9:00:01 AM
 T         out               10/1/2019 9:00:02 AM             Re:
 T         out               10/1/2019 9:00:03 AM             Re:
 T         out               10/1/2019 9:02:59 AM             Re:
 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             Fwd:
 T         out               10/1/2019 9:06:02 AM             Fwd:
 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             Fw:
 T         out               10/1/2019 9:07:06 AM             Fw:
           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 starttime 列和一个 endtime 列。

我想在以下情况发生时创建一个“开始时间”：如果主题列的第一个单词以 RE:、re、FWD 或 FW 开头（以连续方式），则 Read == "T"，Box = =“出”和ID ==“”

当这种情况的第一个实例发生时，将生成一个开始时间。例如对于这个数据集，开始时间将是 10/1/2019 9:00:02 AM，因为这是我们首先看到所需条件的地方（主题是 FW:、RE: 或 FWD，Read = T，Box =出和 ID = "" ) 但是，当这些条件中的任何一个不成立时，就会创建一个结束时间。因此，第一个结束时间将发生在第 4 行之前，时间是 2019 年 10 月 1 日上午 9:02:59。我的最终目标是为此创建一个持续时间列。

这是包含 RE、Fwd 和 Fw 时我想要的输出

  starttime                    endtime                     duration

  10/1/2019 9:00:02 AM        10/1/2019 9:02:59 AM         177 secs
  10/1/2019 9:06:00 AM        10/1/2019 9:06:02 AM         2 secs
  10/1/2019 9:07:05 AM        10/1/2019 9:07:06 AM         1 secs

此外，我将如何在单独的代码中指定为这些条件创建开始和结束时间： Read = T, Box = out, ID = "" 并且当主题列的第一个单词不包含 Re、Fwd 或 Fw 时？

 Read      Box       ID      Time                             Subject 
 T         out               10/1/2019 9:00:01 AM
 T         out               10/1/2019 9:00:02 AM             Re:
 T         out               10/1/2019 9:00:03 AM             Re:
 T         out               10/1/2019 9:02:59 AM             Re:
 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             Fwd:
 T         out               10/1/2019 9:06:02 AM             Fwd:
 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             Fw:
 T         out               10/1/2019 9:07:06 AM             Fw:
           hello             10/1/2019 9:07:08 AM

这是排除 RE、Fwd 和 Fw 时我想要的输出

  starttime                    endtime                     duration

  10/1/2019 9:00:01 AM        10/1/2019 9:00:01 AM         0 secs
  10/1/2019 9:03:00 AM        10/1/2019 9:03:00 AM         0 secs
  10/1/2019 9:07:04 AM        10/1/2019 9:07:04 AM         0 secs

输入：

 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"), Subject = structure(c(1L, 
4L, 4L, 4L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 1L), .Label = c("", 
"Fw:", "Fwd:", "Re:"), class = "factor")), class = "data.frame", row.names = c(NA, 
-14L))

建议的代码有效，我也想加入主题列条件：
其中 Subject == FW、FWD、RE（忽略大写/小写） 和 其中 Subject 不等于 FW、FWD、Re（忽略大小写）

library(dplyr)

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

库（dplyr）

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

Answer 1

您的问题的一部分已在您的其他问题 (Create start and endtime columns based on multiple conditions in R (dplyr, lubridate)) 中得到解答。我知道这可能很困难，但下次请尝试通过专注于您不知道的内容来将您的问题减少到较小的问题。

如果要检测子字符串，最好的方法是使用stringr 包中的str_detect（tidyverse 的一部分）：

library(tidyverse)
library(lubridate)
df %>%
  mutate(Time = mdy_hms(Time), 
         # cond = Read == "T" & Box == "out" & ID == "", #from the answer https://stackoverflow.com/a/60068929/3888000
         cond = Read == "T" & Box == "out" & ID == "" & str_detect(Subject, regex('FW|FWD|RE', ignore_case=TRUE)), #including those subjects
         # cond = Read == "T" & Box == "out" & ID == "" & !str_detect(Subject, regex('FW|FWD|RE', ignore_case=TRUE)), #excluding those subjects
         grp = cumsum(!cond)) %>%
  filter(cond) %>%
  group_by(grp) %>%
  summarise(starttime = first(Time), 
            endtime = last(Time), 
            duration = difftime(endtime, starttime, units = "secs")) %>%
  select(-grp)

这使用了正则表达式（regex），这是一个非常值得学习的东西。这个很容易阅读，因为它只有 OR (|) 运算符，但可能性是无限的。