在具有多个观察期的数据框中添加缺失日期值

Question

提前致谢.

我正在尝试添加三个不同个体的观察期内未包含的缺失日期值.

我的数据如下所示:

 IndID       Date Event Number Percent
1   P01 2011-03-04     1      2   0.390
2   P01 2011-03-11     1      2   0.975
3   P01 2011-03-13     0      9   0.795
4   P01 2011-03-14     0     10   0.516
5   P01 2011-03-15     0      1   0.117
6   P01 2011-03-17     0      7   0.093

IndID是个人ID( ,P01,).P03 显然是日期.是一个二进制变量,指示是否发生了事件(= no和= yes). 列并没有直接关系,但需要被保存和这里因此包括在内.P06DateEvent01
NumberPercent

我的样本数据框(PostData)包含在下面dput.

对于每一个IndID,第一个和最后Date一个分别是观察期的开始和结束,其中缺少日期.在这里,我的目标是为每个人添加缺少的日期,并0在Event列中添加一个.其他列(Number和Percent)可以保持空白.

这篇文章很有用,但缺乏关于我的主要问题的信息 - 多个人.

观察期间为每个单独的是从min(PostData$Date)到max(PostData$Date).我一直在尝试为每个人创建一个完整的日期序列,然后merge使用for循环中的现有数据框.肯定有更好的主意.

任何建议表示赞赏.

PostData <-structure(list(IndID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
  5L, 5L), .Label = c("P01", "P02", "P03", "P05", "P06", "P07", 
  "P08", "P09", "P10", "P11", "P12", "P13"), class = "factor"), 
  Date = structure(c(1299196800, 1299801600, 1299974400, 1300060800, 
  1300147200, 1300320000, 1300406400, 1310083200, 1310169600, 
  1310515200, 1310774400, 1310947200, 1311033600, 1311292800, 
  1311552000, 1323129600, 1323388800, 1323648000, 1323993600, 
  1324080000, 1324166400, 1324339200, 1327622400, 1327795200, 
  1327881600), class = c("POSIXct", "POSIXt"), tzone = "GMT"), 
  Event = c(1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 
  0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L), Number = c(2L, 
  2L, 9L, 10L, 1L, 7L, 5L, 9L, 1L, 4L, 5L, 2L, 0L, 1L, 10L, 
  5L, 0L, 6L, 5L, 10L, 9L, 4L, 4L, 8L, 1L), Percent = c(0.39, 
  0.975, 0.795, 0.516, 0.117, 0.093, 0.528, 0.659, 0.308, 0.055, 
  0.185, 0.761, 0.132, 0.676, 0.368, 0.383, 0.272, 0.113, 0.974, 
  0.696, 0.941, 0.751, 0.758, 0.29, 0.15)), .Names = c("IndID", 
  "Date", "Event", "Number", "Percent"), row.names = c(NA, 25L), 
  class = "data.frame")

Answer 1

基础R版本:

do.call(rbind,
  by(
    PostData,
    PostData$IndID,
    function(x) {
      out <- merge(
        data.frame(
          IndID=x$IndID[1],
          Date=seq.POSIXt(min(x$Date),max(x$Date),by="1 day")
        ),
        x,
        all.x=TRUE
      )
      out$Event[is.na(out$Event)] <- 0
      out
    }  
  )
)

结果:

       IndID       Date Event Number Percent
P01.1    P01 2011-03-04     1      2   0.390
P01.2    P01 2011-03-05     0     NA      NA
P01.3    P01 2011-03-06     0     NA      NA
P01.4    P01 2011-03-07     0     NA      NA
P01.5    P01 2011-03-08     0     NA      NA
P01.6    P01 2011-03-09     0     NA      NA
P01.7    P01 2011-03-10     0     NA      NA
P01.8    P01 2011-03-11     1      2   0.975
<<etc>>