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
根据此数据集中的某些条件,我想创建一个startime列和一个endtime列。
在发生以下情况时,我想创建一个“开始时间”:如果“主题”列的第一个单词以RE:,re,FWD或FW(以连续方式)开头,则Read ==“ T”,Box = =“ out”和ID ==“”
第一次出现这种情况时,将生成一个开始时间。例如,对于此数据集,开始时间将为10/1/2019 9:00:02 AM,因为这是我们首先看到所需条件的位置(主题为FW:,RE:或FWD,Read = T,Box =出,ID =“”“) 但是,当这些条件中的任何一个都不成立时,将创建结束时间。因此,第一个结束时间将发生在第4行之前,该时间为10/1/2019 9:02:59 AM。我的最终目标是为此创建一个工期列。
当包含RE,Fwd和Fw时,这是我想要的输出
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这些条件的开始时间和结束时间: 读取= T,方框=输出,ID =“”,并且主题列的第一个单词不包含Re,Fwd或Fw?
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
dput:
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,我也想同时包含Subject列条件:
其中Subject == FW,FWD,RE(忽略大写/小写)
和
如果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)
答案 0 :(得分:1)
您的问题的整个部分已经在您的其他问题(Create start and endtime columns based on multiple conditions in R (dplyr, lubridate))中得到了回答。我知道这很困难,但是下次请着重于您尚不了解的问题,将问题缩小到较小的范围。
如果要检测子字符串,最好的方法是使用str_detect
包(stringr
的一部分)中的tidyverse
:
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)
这使用正则表达式(regex
),这是一件非常好的事情。该代码只有OR(|
)运算符,非常易于阅读,但可能性是无限的。