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

[Faradj Koliev]

Dear Jim, 

wow! It worked! Thanks a lot. 

I did as you suggested and it worked well with the real data. Although it gave me this error: Error in if (!is.na(x$Y[i])) { : argument is of length zero. For some reason the X1 produced less observations than it is in the data. But it's not a big deal - I identified those cases and simply deleted from the data (it was countries that only appeared twice in the data (e.g. USSR Yugoslavia etc). 

Best, 
Faradj 


> 29 maj 2018 kl. 02:15 skrev Jim Lemon <drjimlemon using gmail.com>:
> 
> Hi Faradj,
> What a problem! I think I have worked it out, but only because the
> result is the one you said you wanted.
> 
> # the sample data frame is named fkdf
> Y2Xby3<-function(x) {
> nrows<-dim(x)[1]
> X<-rep(0,nrows)
> for(i in 1:(nrows-2)) {
>  if(!is.na(x$Y[i])) {
>   if(x$Y[i] == 1 && any(is.na(x$Y[(i+1):(i+2)]))) X[i]<-1
>   if(i > 1) {
>    if(X[i-1] == 1) X[i]<-0
>   }
>  }
>  else {
>   if(!is.na(x$Y[i+1])) {
>    if(x$Y[i+1] == 1 && is.na(x$Y[i+2]) && X[i] == 0)
>     X[i+1]<-1
>   }
>  }
> }
> return(X)
> }
> countries<-as.character(unique(fkdf$country))
> X1<-NULL
> for(country in countries)
> X1<-c(X1,Y2Xby3(fkdf[fkdf$country == country,]))
> X1
>  [1] 1 0 0 1 0 0 1 0 1 0 1 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0
> [38] 1 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 1 0 1 0 1 0
> [75] 1 0 0 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0
>> fkdf$X
>  [1] 1 0 0 1 0 0 1 0 1 0 1 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0
> [38] 1 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 1 0 1 0 1 0
> [75] 1 0 0 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0
> 
> Jim
> 
> On Mon, May 28, 2018 at 8:43 PM, Faradj Koliev <faradj.g using gmail.com> wrote:
>> 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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>> 
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