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我如何 gsub 后面的完整时间字符串 @

[英]How do I gsub the complete time string behind @

(这是我的第一个问题,如果我需要改进它,请告诉我!)

我正在分析一个大型观测数据集。 已指示每次观察的开始和停止时间,以便我能够计算持续时间。 但是有一个注释栏,其中包含有关没有看到动物的“暂停”/“休息”或“看不见”时期的信息。 我想从总持续时间中减去这些时间段。

我的问题是,一列包含几个注释,不仅是暂停(“HH:MM-HH:MM”),还包括某些事件的信息(xy 发生了“@HH:MM”)。

我只想查看格式为 HH:MM-HH:MM 的时间段,并且我想排除所有标记为“@HH:MM”的事件时间。 我设法删除了所有单词,只剩下数字,所以看起来像这样

id <- c("3990", "3989", "3004")

timepoints <- c("@6:19,,7:16-7:23,7:25-7:43,@7:53,", "@6:19,,7:25-7:43,@7:53", "7:30-7:39,7:45-7:48,7:49-7:54")

df <- data.frame(id, timepoints)

尝试了 grep 或 gsub 的几种方法,试图指示要保留哪个,或者忽略哪个,但我失败了。 我得到的最接近的是 r 删除“@HH”但保留“:MM”。 为此我使用

gsub("@([[:digit:]]|[_])*", "", df$timepoints)

,正如在此处发现的与单词类似的问题: 从字符串中删除所有以“@”开头的单词

目的是获得(例如):

ID 时间点
3990 “7:16-7:23、7:25-7:43”

或者

ID 时间点
3990 “7:16-7:23”、“7:25-7:43”

如果可能的话,用逗号分隔,或者直接分成不同的列,这样我就可以提取时间并将其从我的总观察时间中减去。

任何帮助将不胜感激!

你可以这样做:

f <- function(x) {
  lapply(x, \(s) {
    s = strsplit(s,",")[[1]]
    s[grepl("^\\d",s)]
  })
}

然后将 function 应用于时间点列

library(tidyverse)
mutate(df %>% as_tibble(), timepoints = f(timepoints)) %>% 
  unnest(timepoints)

Output:

  id    timepoints
  <chr> <chr>     
1 3990  7:16-7:23 
2 3990  7:25-7:43 
3 3989  7:25-7:43 
4 3004  7:30-7:39 
5 3004  7:45-7:48 
6 3004  7:49-7:54 

您还可以使用unnest_wider()将这些作为列; 为此,我会调整我的f()以包含时间点的名称:

f <- function(x) {
  lapply(x, \(s) {
    s = strsplit(s,",")[[1]]
    s = s[grepl("^\\d",s)]
    setNames(s, paste0("tp", 1:length(s)))
  })
}

library(tidyverse)
mutate(df %>% as_tibble(), timepoints = f(timepoints)) %>% 
  unnest_wider(timepoints)

Output:

  id    tp1       tp2       tp3      
  <chr> <chr>     <chr>     <chr>    
1 3990  7:16-7:23 7:25-7:43 NA       
2 3989  7:25-7:43 NA        NA       
3 3004  7:30-7:39 7:45-7:48 7:49-7:54

如何匹配您感兴趣的字符串呢?

base

df$new_timepoints <- regmatches(df$timepoints, gregexpr("\\d{1,2}:\\d{2}-\\d{1,2}:\\d{2}", df$timepoints))

Output(带列表栏):

    id                        timepoints                  new_timepoints
1 3990 @6:19,,7:16-7:23,7:25-7:43,@7:53,            7:16-7:23, 7:25-7:43
2 3989            @6:19,,7:25-7:43,@7:53                       7:25-7:43
3 3004     7:30-7:39,7:45-7:48,7:49-7:54 7:30-7:39, 7:45-7:48, 7:49-7:54

使用tidyverse (为便于计算采用长格式:):

library(stringr)
library(dplyr)
library(tidyr)

df |>
  group_by(id) |>
  mutate(new_timepoints = str_extract_all(timepoints, "\\d{1,2}:\\d{2}-\\d{1,2}:\\d{2}")) |>
  unnest_longer(new_timepoints) |>
  ungroup()

Output:

# A tibble: 6 × 3
  id    timepoints                        new_timepoints
  <chr> <chr>                             <chr>         
1 3990  @6:19,,7:16-7:23,7:25-7:43,@7:53, 7:16-7:23     
2 3990  @6:19,,7:16-7:23,7:25-7:43,@7:53, 7:25-7:43     
3 3989  @6:19,,7:25-7:43,@7:53            7:25-7:43     
4 3004  7:30-7:39,7:45-7:48,7:49-7:54     7:30-7:39     
5 3004  7:30-7:39,7:45-7:48,7:49-7:54     7:45-7:48     
6 3004  7:30-7:39,7:45-7:48,7:49-7:54     7:49-7:54     

1) 用逗号列出拆分,然后用破折号列出 grep 的组件。 不使用任何包。 这给出了一个字符向量列表作为时间点列。

df2 <- df
df2$timepoints <- lapply(strsplit(df$timepoints, ","), 
  grep, pattern = "-", value = TRUE)

df2
##     id                      timepoints
## 1 3990            7:16-7:23, 7:25-7:43
## 2 3989                       7:25-7:43
## 3 3004 7:30-7:39, 7:45-7:48, 7:49-7:54

str(df2)
## 'data.frame':   3 obs. of  2 variables:
##  $ id        : chr  "3990" "3989" "3004"
##  $ timepoints:List of 3
##   ..$ : chr  "7:16-7:23" "7:25-7:43"
##   ..$ : chr "7:25-7:43"
##   ..$ : chr  "7:30-7:39" "7:45-7:48" "7:49-7:54"

2)字符如果你想在每行中添加一个逗号分隔的字符串:

transform(df2, timepoints = sapply(timepoints, paste, collapse = ","))
##     id                    timepoints
## 1 3990           7:16-7:23,7:25-7:43
## 2 3989                     7:25-7:43
## 3 3004 7:30-7:39,7:45-7:48,7:49-7:54

3)长格式,或者如果您更喜欢长格式,请使用:

long <- with(df2, stack(setNames(timepoints, id))[2:1])
names(long) <- names(df2)
long
##     id timepoints
## 1 3990  7:16-7:23
## 2 3990  7:25-7:43
## 3 3989  7:25-7:43
## 4 3004  7:30-7:39
## 5 3004  7:45-7:48
## 6 3004  7:49-7:54

4)宽格式或宽格式矩阵:

nr <- nrow(long)
L <- transform(long, seq = ave(1:nr, id, FUN = seq_along))
tapply(L$timepoints, L[c("id", "seq")], c)
##       seq
## id     1           2           3          
##   3990 "7:16-7:23" "7:25-7:43" NA         
##   3989 "7:25-7:43" NA          NA         
##   3004 "7:30-7:39" "7:45-7:48" "7:49-7:54"

使用 package data.table设置数据

library(data.table)
id <- c("3990", "3989", "3004")

timepoints <- c("@6:19,,7:16-7:23,7:25-7:43,@7:53,", "@6:19,,7:25-7:43,@7:53", "7:30-7:39,7:45-7:48,7:49-7:54")

df <- data.table(id, timepoints)

请注意,我将其保存为data.table

用逗号分割时间点并将值存储在new_time列中。

df[,new_time:=strsplit(timepoints, ",")]

删除具有@的字符串值

df[,new_time:=sapply(new_time, function(x) return(x[!grepl("[@]", x)]))]

由于timepoints列在一行中有多个逗号空字符串( "" )存在我删除它们

df[,new_time:=sapply(new_time, function(x) return(x[!stringi::stri_isempty(x)]))]

现在new_time列看起来像这样

df$new_time
[[1]]
[1] "7:16-7:23" "7:25-7:43"

[[2]]
[1] "7:25-7:43"

[[3]]
[1] "7:30-7:39" "7:45-7:48" "7:49-7:54"

如果您想让new_time列包含整个字符串

df[,new_time:=sapply(new_time, paste, collapse=", ")]
df$new_time
[1] "7:16-7:23, 7:25-7:43"            "7:25-7:43"                       "7:30-7:39, 7:45-7:48, 7:49-7:54"

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