Question

I have a data.frame in panel format (country-year) and I need to calculate the mean of a variable by country and at each five years. So I just used the ‘cast’ function from ‘reshape’ package and it worked. Now I need to put this information(the mean by quinquennium) in the old data.frame, so I can run some regressions. How can I do that? Below I provide an example to ilustrate what I want:

set.seed(2)
fake= data.frame(y=rnorm(20), x=rnorm(20), country=rep(letters[1:2], each=10), year=rep(1:10,2), quinquenio= rep(rep(1:2, each=5),2))

fake.m = melt.data.frame(fake, id.vars=c("country", "year", "quinquenio"))
cast(fake.m, country ~ quinquenio, mean, subset=variable=="x", na.rm=T)

Now, everything is fine and I get what I wantted: the mean of x and y, by country and by quinquennial years. Now, I would like to put them back in the data.frame fake, like this:

         y            x      country year quinquenio  mean.x
1  -0.89691455  2.090819205       a    1          1    0.8880242
2   0.18484918 -1.199925820       a    2          1    0.8880242
3   1.58784533  1.589638200       a    3          1    0.8880242
4  -1.13037567  1.954651642       a    4          1    0.8880242
5  -0.08025176  0.004937777       a    5          1    0.8880242
6   0.13242028 -2.451706388       a    6          2    -0.2978375
7   0.70795473  0.477237303       a    7          2    -0.2978375
8  -0.23969802 -0.596558169       a    8          2    -0.2978375
9   1.98447394  0.792203270       a    9          2    -0.2978375
10 -0.13878701  0.289636710       a   10          2    -0.2978375
11  0.41765075  0.738938604       b    1          1    0.2146461
12  0.98175278  0.318960401       b    2          1    0.2146461
13 -0.39269536  1.076164354       b    3          1    0.2146461
14 -1.03966898 -0.284157720       b    4          1    0.2146461
15  1.78222896 -0.776675274       b    5          1    0.2146461
16 -2.31106908 -0.595660499       b    6          2    -0.8059598
17  0.87860458 -1.725979779       b    7          2    -0.8059598
18  0.03580672 -0.902584480       b    8          2    -0.8059598
19  1.01282869 -0.559061915       b    9          2    -0.8059598
20  0.43226515 -0.246512567       b   10          2    -0.8059598

I appreciate any tip in the right direction. Thanks in advance.

ps.: the reason I need this is that I’ll run a regression with quinquennial data, and for some variables (like per capita income) I have information for all years, so I decided to average them by 5 years.

Answer 1

I’m sure there’s an easy way to do this with reshape, but my brain defaults to plyr first:

require(plyr)
ddply(fake, c("country", "quinquenio"), transform, mean.x = mean(x))

This is quite hackish, but one way to use reshape building off your earlier work:

zz <- cast(fake.m, country ~ quinquenio, mean, subset=variable=="x", na.rm=T)
merge(fake, melt(zz), by = c("country", "quinquenio"))

though I’m positive there has to be a better solution.