如何按组逐行更改基于先前和未来值的值

Question

问题：我正在尝试使用dplyr 或ave 执行以下操作：

按组 ID，如果给定时间段的 x1 为 0，并且之前 (t-1) 和未来 (t+1) 的值等于 1，则用 1 填充 x1。

     ID = c("1","1","1","1","1","2","2","2","2","3","3","3")
     time = c("1","2","3","4","5","1","2","3","4","1","2","3")
     x1 = as.integer(c("0","1","0","1","1","0","0","0","0","1","0","1"))
     df = data.frame(ID,time,x1)

数据：

  ID time x1 
  1    1  0 
  1    2  1 
  1    3  0 
  1    4  1 
  1    5  1 
  2    1  0 
  2    2  0 
  2    3  0 
  2    4  0 
  3    1  1 
  3    2  0 
  3    3  1 

我试图获得的输出：

  ID time x1 
  1    1  0  
  1    2  1  
  1    3  1  
  1    4  1  
  1    5  1  
  2    1  0  
  2    2  0  
  2    3  0  
  2    4  0  
  3    1  1  
  3    2  1  
  3    3  1  

Answer 1

library(dplyr)
df %>%
group_by(id) %>%
mutate(x1 = ifelse(lead(x1) == 1 & lag(x1) == 1 & x1 == 0, 1, x1))

您可以按 id 分组，并使用 dplyr 中的 lead 和 lag 函数的逻辑来填写 1。