I've updated a new different problem. This time I would like to obtain column Oxy2 from Oxy.
ID Oxy Y Oxy2
1 NA 2010 NA
1 0 2011 0
1 NA 2012 NA
1 1 2013 1
1 NA 2014 1
1 NA 2015 1
1 -1 2016 1
2 0 2011 0
2 NA 2012 NA
2 1 2013 1
2 -1 2014 1
3 0 2012 0
3 -1 2013 -1
3 NA 2014 NA
4 -1 2010 -1
4 1 2011 1
4 -1 2012 1
4 -1 2013 1
4 0 2014 1
4 NA 2015 1
Basically, I need to keep NAs, if there any, when previous values of my Oxy variable are 0 or -1, and replace everything coming after the first 1 appears with 1.
Again, thanks for your suggestions.
library(dplyr)
library(zoo)
df %>%
group_by(ID) %>%
mutate(Ins1=na.locf(ifelse(is.na(Ins) & lag(Ins)==0, 999, Ins), na.rm = FALSE), Ins2=na_if(Ins1, 999))
#one step version
#mutate(Ins1 = na_if(na.locf(ifelse(is.na(Ins) & lag(Ins)==0, 999, Ins), na.rm = FALSE), 999))
# A tibble: 8 x 5
# Groups: ID [2]
ID Ins Y Ins1 Ins2
<int> <int> <int> <dbl> <dbl>
1 1 0 2010 0 0
2 1 NA 2011 999 NA
3 1 1 2012 1 1
4 1 NA 2013 1 1
5 1 NA 2014 1 1
6 2 0 2011 0 0
7 2 0 2012 0 0
8 2 NA 2013 999 NA
Update: To solve the -1 issue, I add a small change to what @user12492692 has suggested in the Edit, namely replaced the | with %in%
df %>%
group_by(ID) %>%
mutate(Ins1 = na.locf(ifelse(is.na(Ins) & lag(Ins) %in% c(0,-1), 999, Ins), na.rm = FALSE),
Ins2 = na_if(Ins1, 999))