transform - R: Calculating 5 year averages in panel data

Question

I have a balanced panel by country from 1951 to 2007 in a data frame. I'd like to transform it into a new data frame of five year averages of my other variables. When I sat down to do this I realized the only way I could think to do this involved a for loop and then decided that it was time to come to stackoverflow for help.

So, is there an easy way to turn data that looks like this:

country   country.isocode year      POP           ci      grgdpch
Argentina             ARG 1951 17517.34 18.445022145 3.4602044759
Argentina             ARG 1952 17876.96  17.76066507 -7.887407586
Argentina             ARG 1953 18230.82 18.365255769 2.3118720688
Argentina             ARG 1954 18580.56 16.982113434 1.5693778844
Argentina             ARG 1955 18927.82 17.488907008 5.3690276523
Argentina             ARG 1956 19271.51 15.907756547 0.3125559183
Argentina             ARG 1957 19610.54 17.028450999 2.4896639667
Argentina             ARG 1958 19946.54 17.541597134 5.0025894968
Argentina             ARG 1959 20281.15 16.137310492 -6.763501447
Argentina             ARG 1960 20616.01 20.519539628  8.481742144
...
Venezuela             VEN 1997 22361.80 21.923577413  5.603872759
Venezuela             VEN 1998 22751.36 24.451736863 -0.781844721
Venezuela             VEN 1999 23128.64 21.585034168 -8.728234466
Venezuela             VEN 2000 23492.75 20.224310777 2.6828641218
Venezuela             VEN 2001 23843.87 23.480311721 0.2476965412
Venezuela             VEN 2002 24191.77 16.290691319  -8.02535946
Venezuela             VEN 2003 24545.43 10.972153646 -8.341989049
Venezuela             VEN 2004 24904.62 17.147693312 14.644028806
Venezuela             VEN 2005 25269.18 18.805970212 7.3156977879
Venezuela             VEN 2006 25641.46 22.191098769 5.2737381326
Venezuela             VEN 2007 26023.53 26.518210052 4.1367897561

into something like this:

country   country.isocode period   AvPOP     Avci Avgrgdpch
Argentina             ARG      1   18230 17.38474  1.423454
...
Venezuela             VEN     12   25274 21.45343  5.454334

Do I need to transform this data frame using a specific panel data package? Or is there another easy way to do this that I'm missing?

Answer 1

This is the stuff aggregate is made for. :

Df <- data.frame(
    year=rep(1951:1970,2),
    country=rep(c("Arg","Ven"),each=20),
    var1 = c(1:20,51:70),
    var2 = c(20:1,70:51)
)

Level <-cut(Df$year,seq(1951,1971,by=5),right=F)
id <- c("var1","var2")

> aggregate(Df[id],list(Df$country,Level),mean)
  Group.1     Group.2 var1 var2
1     Arg [1951,1956)    3   18
2     Ven [1951,1956)   53   68
3     Arg [1956,1961)    8   13
4     Ven [1956,1961)   58   63
5     Arg [1961,1966)   13    8
6     Ven [1961,1966)   63   58
7     Arg [1966,1971)   18    3
8     Ven [1966,1971)   68   53

The only thing you might want to do, is to rename the categories and the variable names.