Question

我试图根据上一行的值来估算时间。

Concat               ID     Date           Time1    Time2
1615 - 2019-05-14   1615   5/14/2019    20:57:56    21:26:45
161 - 2019-05-14    161    5/14/2019    21:52:19    NA
161 - 2019-05-15    161    5/15/2019    NA          1:10:49
161 - 2019-05-14    161    5/17/2019    21:52:19    NA
161 - 2019-05-15    161    5/20/2019    NA          1:10:49

对于每个ID列，如果日期差小于2，并且如果Time1为NA，而先前的相邻Time2为NA，那么我想替换Time1中的“ 00:00:01”和“ 23:59:59” ”，如下所示。

 Concat              ID     Date           Time1    Time2
1615 - 2019-05-14   1615   5/14/2019    20:57:56    21:26:45
161 - 2019-05-14    161    5/14/2019    21:52:19    23:59:59
161 - 2019-05-15    161    5/15/2019    00:00:01    1:10:49
161 - 2019-05-14    161    5/17/2019    21:52:19    NA
161 - 2019-05-15    161    5/20/2019    NA          1:10:49

我尝试使用dplyr的超前和滞后值，但无法正确获取

Answer 1

缺少可重复的数据示例，我只能猜测这将对您有所帮助：

library(dplyr)
library(lubridate)

df %>%
  group_by(ID) %>%
  mutate(
    Time1_fixed = ifelse(
      (lag(Date,1)+1 == Date) & # the previous Date was one day before this one
       is.na(Time1) & # AND this Time1 is NA
       is.na(lag(Time2,1)), # AND the previous Time1 was NA
      '00:00:01',
      Time1
    ),
    Time2_fixed = ifelse(
      (lead(Date,1) == Date+1) & # the next Date is one day after this one
       is.na(Time2) & # AND this Time2 is NA
       is.na(lead(Time1,1)), # AND the next Time1 is NA
      '23:59:59',
      Time2
    )
)

根据条件估算时间

1 个答案: