Whenever I want to lag in a data frame I realize that something that should be simple is not. While the problem has been asked & answered many times (see p.s.), I did not find a simple solution which I can remember until the next time I lag. In general, lagging does not seem to be a simple thing in R as the multiple workarounds testify. I run into this problem often and it would be very helpful to have some basic R solutions which do not need extra packages. Could you provide your simple solution for lagging?
If that is not possible, could you at least provide your workaround here so we can choose amongst second best alternatives? One collection already exists here
Also, in all blog posts on this subject I see people complain about how unexpectedly difficult lagging is so how can we get a simple lag function for data frames into R Core? This must be extremely disappointing for anyone coming from Stata or EViews. Or am I missing something and there is a simple built in solution?
say we want to lag "value" by 3 "year"s for each "country" here:
Data <- data.frame(year=c(rep(2010:2015,2)),country=c(rep("AT",6),rep("DE",6)),value=rnorm(12))
to create L3 like:
year country value L3
2010 AT 0.3407 NA
2011 AT -1.7981 NA
2012 AT -0.8390 NA
2013 AT -0.6888 0.3407
2014 AT -1.1019 -1.7981
2015 AT -0.8953 -0.8390
2010 DE 0.5877 NA
2011 DE -1.0204 NA
2012 DE -0.6576 NA
2013 DE 0.6620 0.5877
2014 DE 0.9579 -1.0204
2015 DE -0.7774 -0.6576
And we neither want to change the nature of our data (to ts or data table) nor do we want to immerse ourselves in three new packages when the deadline is tonight and our supervisor uses Stata and thinks lagging is easy ;-) (its not, I just want to be prepared...)
p.s.:
with data.table: Lag in dataframe or How to create a lag variable within each group?
If the question is how to provide a column with the prior third year's value not using packages then try this:
prior_year3 <- function(x, k = 3) head(c(rep(NA, k), x), length(x))
transform(Data, prior_year_value = ave(value, country, FUN = prior_year3))
giving:
year country value prior_year_value
1 2010 AT -1.66562121 NA
2 2011 AT -0.04950063 NA
3 2012 AT 1.55930293 NA
4 2013 AT -0.40462394 -1.66562121
5 2014 AT 0.78602610 -0.04950063
6 2015 AT 0.73912916 1.55930293
7 2010 DE 1.03710539 NA
8 2011 DE -1.13370942 NA
9 2012 DE -1.20530981 NA
10 2013 DE 1.66870572 1.03710539
11 2014 DE 1.53615793 -1.13370942
12 2015 DE -0.09693335 -1.20530981
That said, to use R effectively you do need to learn how to use the key packages.