R 根据后续条目修改分组数据的第一个条目

使用以下数据集：

df <- structure(list(test = c("1st", "2nd", "3rd", "1st", "2nd", "3rd", "1st", "2nd", "3rd"),
                 id = c("PID1", "PID1", "PID1", "PID2", "PID2", "PID2", "PID3", "PID3", "PID3"),
                 date = c("2020-01-01", "2020-01-13", "2020-01-17", "2020-01-01", "2020-01-13", "2020-01-20", "2020-01-01", "2020-01-14", "2020-01-18"),
                 status_1 = c("Symp", "Symp", "uninfected", "Asymp", "Symp", "uninfected", "Asymp", "Asymp", "uninfected"),
                 status_2 = c("Symp", "Symp", "uninfected", "pre-Symp", "Symp", "uninfected", "Asymp", "Asymp", "uninfected")),
            class = "data.frame",
            row.names = c(NA, -9L)
            )

---

您可以创建自己的自定义函数，用于检查该时间间隔内的状态

library(dplyr)

check_status <- function(x, date) {
  if(first(x) == 'Asymp' & any(x == 'Symp')) {
    if (date[which.max(x == 'Symp')] - first(date) < 14)
      x[1] <- 'pre-Symp'
  }
  return(x)
}

库（dplyr）
检查状态%
分组依据（id）%>%
变异（状态2=检查状态（状态1，日期））
#测试id日期状态\u 1状态\u 2
#                    
#第一批PID1 2020-01-01研讨会
#2第二届PID1 2020-01-13研讨会
#3第三PID1 2020-01-17未感染未感染
#4第一批PID2 2020-01-01 Asymp预研讨会
#第二届PID2 2020-01-13研讨会
#6第三PID2 2020-01-20未感染未感染
#7第1 PID3 2020-01-01 Asymp Asymp
#8第二PID3 2020-01-14 Asymp Asymp
#9第3 PID3 2020-01-18未感染未感染

library(dplyr)

check_status <- function(x, date) {
  if(first(x) == 'Asymp' & any(x == 'Symp')) {
    if (date[which.max(x == 'Symp')] - first(date) < 14)
      x[1] <- 'pre-Symp'
  }
  return(x)
}

df %>%
  mutate(date = as.Date(date)) %>%
  group_by(id) %>%
  mutate(status_2 = check_status(status_1, date))

# test  id    date       status_1   status_2  
#  <chr> <chr> <date>     <chr>      <chr>     
#1 1st   PID1  2020-01-01 Symp       Symp      
#2 2nd   PID1  2020-01-13 Symp       Symp      
#3 3rd   PID1  2020-01-17 uninfected uninfected
#4 1st   PID2  2020-01-01 Asymp      pre-Symp  
#5 2nd   PID2  2020-01-13 Symp       Symp      
#6 3rd   PID2  2020-01-20 uninfected uninfected
#7 1st   PID3  2020-01-01 Asymp      Asymp     
#8 2nd   PID3  2020-01-14 Asymp      Asymp     
#9 3rd   PID3  2020-01-18 uninfected uninfected