比较R中不同列的不同列

Question

我想检查一下个人在资格状态中是否没有任何差距。我将缺口定义为在最后一个elig_end_date之后30天发生的date_of_claim。因此，我想要做的是检查每个date_of_claim不超过紧接前一行的elig_end_date + 30天。理想情况下，我希望有一个指标说0表示没有差距，1表示如果每个人存在差距，差距出现在哪里。下面是一个示例df，其中内置解决方案为'间隙'。

names date_of_claim elig_end_date obs gaps 
1 tom 2010-01-01 2010-07-01 1 NA 
2 tom 2010-05-04 2010-07-01 1 0 
3 tom 2010-06-01 2014-01-01 2 0 
4 tom 2010-10-10 2014-01-01 2 0 
5 mary 2010-03-01 2014-06-14 1 NA 
6 mary 2010-05-01 2014-06-14 1 0 
7 mary 2010-08-01 2014-06-14 1 0 
8 mary 2010-11-01 2014-06-14 1 0 
9 mary 2011-01-01 2014-06-14 1 0 
10 john 2010-03-27 2011-03-01 1 NA 
11 john 2010-07-01 2011-03-01 1 0 
12 john 2010-11-01 2011-03-01 1 0 
13 john 2011-02-01 2011-03-01 1 0 
14 sue 2010-02-01 2010-04-30 1 NA 
15 sue 2010-02-27 2010-04-30 1 0 
16 sue 2010-03-13 2010-05-31 2 0 
17 sue 2010-04-27 2010-06-30 3 0 
18 sue 2010-04-27 2010-06-30 3 0 
19 sue 2010-05-06 2010-08-31 4 0 
20 sue 2010-06-08 2010-09-30 5 0 
21 mike 2010-05-01 2010-07-30 1 NA 
22 mike 2010-06-01 2010-07-30 1 0 
23 mike 2010-11-12 2011-07-30 2 1 

我发现这个职位是非常有用How can I compare a value in a column to the previous one using R?，但觉得我不能使用循环作为我的DF拥有400万行，而我也有很多困难的尝试在它已经运行一个循环。

为此，我想我需要的代码是这样的：

df$gaps<-ifelse(df$date_of_claim>=df$elig_end_date+30,1,0) ##this doesn't use the preceeding row. 

我用这个做了一个笨拙的尝试：

df$gaps<-df$date_of_claim>=df$elig_end_date[-1,] 

，但我得到一个错误说我有不正确的尺寸数量。

非常感谢！谢谢。

Answer 1

备有四点万余意见，我会用data.table：

DF <- read.table(text="names date_of_claim elig_end_date obs gaps 
1 tom 2010-01-01 2010-07-01 1 NA 
2 tom 2010-05-04 2010-07-01 1 0 
3 tom 2010-06-01 2014-01-01 2 0 
4 tom 2010-10-10 2014-01-01 2 0 
5 mary 2010-03-01 2014-06-14 1 NA 
6 mary 2010-05-01 2014-06-14 1 0 
7 mary 2010-08-01 2014-06-14 1 0 
8 mary 2010-11-01 2014-06-14 1 0 
9 mary 2011-01-01 2014-06-14 1 0 
10 john 2010-03-27 2011-03-01 1 NA 
11 john 2010-07-01 2011-03-01 1 0 
12 john 2010-11-01 2011-03-01 1 0 
13 john 2011-02-01 2011-03-01 1 0 
14 sue 2010-02-01 2010-04-30 1 NA 
15 sue 2010-02-27 2010-04-30 1 0 
16 sue 2010-03-13 2010-05-31 2 0 
17 sue 2010-04-27 2010-06-30 3 0 
18 sue 2010-04-27 2010-06-30 3 0 
19 sue 2010-05-06 2010-08-31 4 0 
20 sue 2010-06-08 2010-09-30 5 0 
21 mike 2010-05-01 2010-07-30 1 NA 
22 mike 2010-06-01 2010-07-30 1 0 
23 mike 2010-11-12 2011-07-30 2 1", header=TRUE) 

library(data.table) 
DT <- data.table(DF) 

DT[, c("date_of_claim", "elig_end_date") := list(as.Date(date_of_claim), as.Date(elig_end_date))] 

DT[, gaps2:= c(NA, date_of_claim[-1] > head(elig_end_date, -1)+30), by=names] 

# names date_of_claim elig_end_date obs gaps gaps2 
# 1: tom 2010-01-01 2010-07-01 1 NA NA 
# 2: tom 2010-05-04 2010-07-01 1 0 FALSE 
# 3: tom 2010-06-01 2014-01-01 2 0 FALSE 
# 4: tom 2010-10-10 2014-01-01 2 0 FALSE 
# 5: mary 2010-03-01 2014-06-14 1 NA NA 
# 6: mary 2010-05-01 2014-06-14 1 0 FALSE 
# 7: mary 2010-08-01 2014-06-14 1 0 FALSE 
# 8: mary 2010-11-01 2014-06-14 1 0 FALSE 
# 9: mary 2011-01-01 2014-06-14 1 0 FALSE 
# 10: john 2010-03-27 2011-03-01 1 NA NA 
# 11: john 2010-07-01 2011-03-01 1 0 FALSE 
# 12: john 2010-11-01 2011-03-01 1 0 FALSE 
# 13: john 2011-02-01 2011-03-01 1 0 FALSE 
# 14: sue 2010-02-01 2010-04-30 1 NA NA 
# 15: sue 2010-02-27 2010-04-30 1 0 FALSE 
# 16: sue 2010-03-13 2010-05-31 2 0 FALSE 
# 17: sue 2010-04-27 2010-06-30 3 0 FALSE 
# 18: sue 2010-04-27 2010-06-30 3 0 FALSE 
# 19: sue 2010-05-06 2010-08-31 4 0 FALSE 
# 20: sue 2010-06-08 2010-09-30 5 0 FALSE 
# 21: mike 2010-05-01 2010-07-30 1 NA NA 
# 22: mike 2010-06-01 2010-07-30 1 0 FALSE 
# 23: mike 2010-11-12 2011-07-30 2 1 TRUE 
#  names date_of_claim elig_end_date obs gaps gaps2