How do I structure data to use R lmer - r

Question

I am trying to do a trending analysis of reliability data. A typical case would be to determine if a 10-year trend exists in the demand rate for a specified system at specified plants.
I am trying to generate a test case but am a bit confused about how to structure the data. The trend years range from 2004 to 2013. In my test case I have, for each year, 10 systems for which demands have been counted. I am using normally distributed demand counts with different means and variances each year. Of course real data will likely not have the same system count each year, and the demand counts are not necessarily normally distributed.
The following R code produces a data frame (df1) that seems reasonable to me:
yr <- 2004:2013
y2004 <- rnorm(10, 10, 3)
y2005 <- rnorm(10, 11, 2)
y2006 <- rnorm(10, 12, 1)
y2007 <- rnorm(10, 13, 5)
y2008 <- rnorm(10, 14, 3)
y2009 <- rnorm(10, 15, 4)
y2010 <- rnorm(10, 16, 1)
y2011 <- rnorm(10, 17, 2)
y2012 <- rnorm(10, 18, 4)
y2013 <- rnorm(10, 19, 1)
df1 <- data.frame(cbind(yr), y2004, y2005, y2006, y2007, y2008, y2009, y2010, y2011, y2012,y2013)
df2 <- data.frame(cbind(rep(0.0, 100), rep(0.0, 100)))
names(df2) <- c("x", "y")
k <-1
for (i in 1:10) {
for (j in 1:10) {
df2$x[k] <- df1$yr[i]
df2$y[k] <- df1[j,i+1]
k <- k + 1
}
}
boxplot(y ~ x, df2)
Anyway, my first problem is the construction of df2 seems unnecessary given I already have the data in df1 - it's just that the call to lmer seems to require the organization of df2. My call to lmer looks like the following:
fit <- lmer(y ~ x + (1|x), data=df2)
So is there a way to use lmer without the construction of df2, using df1 directly? Or is there a better way to structure the data entirely?
My second problem is I am not really sure how to use lmer to do what I want to do. Basically I am looking to pool the count data for each year and fit the mean demand count each year with a straight line. The best fit should consider the variance in the data in each pooled year group. Am I going about it correctly?

Answer 1

Nearly all plotting and modeling functions in R require data in the "long" format (ie df2). So if anything, I would skip the construction of df1. If you want to generate df2 more directly, you could do
df2 <- do.call("rbind.data.frame", Map(cbind,
y=Map(function(n,m,s) rnorm(n,m,s), 10, 10:19, c(3,2,1,5,3,4,1,2,3,1)),
x=2004:2013))