[R] How to generate a conditional dummy in R?

[Faradj Koliev]

Hi everyone, 

I am trying to generate a conditional dummy variable ”X" with the following rules

 set X=1 if Y is =1, two years prior to the NA.  [0,0,NA]. 

For example, if  the pattern for Y is 0,0,NA then the X variable is =0 for all  the two years prior to the NA. If the pattern for Y is 0,1,NA or 1,0,NA then the X =1 . To be clear, if 1,1,NA then the X=1 that  first specific year, it should only count once (X=1), not twice. 

The code that I have now is not complete and I would appreciate some advice here. This is the code: 
dat2 <- dat1 %>% 
  group_by(country) %>% 
  group_by(grp = cumsum(is.na(lag(Y))), add = TRUE) %>% 
  mutate(first_year_at_1 = match(1, Y) * any(is.na(Y)) * any(tail(Y, 3) == 1L), 
         X = {x <- integer(length(Y)) ; x[first_year_at_1] <- 1L ; x}) %>% 
  ungroup()

It doesn’t really generate what I described above. Any help here would be much appreciated. 

Below you can see my sample data with the desired outcome ”X” dummy in it.

Thank you! 

> dput(data)
structure(list(year = c(1991L, 1992L, 1993L, 1994L, 1995L, 1996L, 
1997L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 
2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 1990L, 1991L, 1992L, 
1993L, 1994L, 1995L, 1996L, 1997L, 1998L, 1999L, 2000L, 2001L, 
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 
2011L, 1990L, 1991L, 1992L, 1993L, 1994L, 1995L, 1996L, 1997L, 
1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 
2007L, 2008L, 2009L, 2010L, 2011L, 1990L, 1991L, 1992L, 1993L, 
1994L, 1995L, 1996L, 1997L, 1998L, 1999L, 2000L, 2001L, 2002L, 
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 
1990L, 1991L, 1992L, 1993L, 1994L, 1995L, 1996L, 1997L, 1998L, 
1999L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 
2007L, 2008L, 2009L, 2010L, 2011L), country = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("Canada", 
"Cuba", "Dominican Republic", "Haiti", "Jamaica"), class = "factor"), 
    Y = c(1L, NA, 1L, 1L, 1L, NA, 1L, NA, 1L, NA, 1L, NA, 1L, 
    1L, NA, 1L, NA, 1L, NA, 1L, NA, NA, 1L, 1L, NA, NA, 1L, NA, 
    1L, NA, 1L, NA, 1L, 1L, 1L, 1L, NA, 1L, NA, 1L, NA, 1L, NA, 
    NA, 1L, NA, 1L, 0L, 0L, 0L, 1L, NA, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 1L, NA, 0L, 1L, 1L, NA, 0L, 1L, NA, 1L, NA, 1L, NA, 1L, 
    NA, 1L, NA, 1L, 1L, 1L, 1L, NA, 1L, NA, 1L, NA, 1L, NA, 1L, 
    0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, NA, 0L, 1L, 1L, 1L, 
    NA, 1L, NA, 0L, 1L, 1L, NA), X = c(1L, 0L, 0L, 1L, 0L, 0L, 
    1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 
    0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 
    0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 
    1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 
    1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L)), .Names = c("year", 
"country", "Y", "X"), class = "data.frame", row.names = c(NA, 
-110L))



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