Hello,
One way to speed it up is to use a matrix instead of a data.frame. Since
data.frames can hold data of all classes, the access to their elements
is slow. And your data is all numeric so it can be hold in a matrix. The
second way below gave me a speed up by a factor of 50.
system.time({
for (i in 2:nrow(df))
{if(df$TreeID[i]==df$TreeID[i-1])
{df$HeightGrowth[i] <- df$Height[i]-df$Height[i-1]
}
}
})
system.time({
df2 <- data.matrix(df)
for(i in seq_len(nrow(df2))[-1]){
if(df2[i, "TreeID"] == df2[i - 1, "TreeID"])
df2[i, "HeightGrowth"] <- df2[i, "Height"] - df2[i - 1,
"Height"]
}
})
all.equal(df, as.data.frame(df2)) # TRUE
Hope this helps,
Rui Barradas
Em 10-06-2013 18:28, Trevor Walker escreveu:
I have a For loop that is quite slow and am wondering if there is a faster
option:
df <- data.frame(TreeID=rep(1:500,each=20), Age=rep(seq(1,20,1),500))
df$Height <- exp(-0.1 + 0.2*df$Age)
df$HeightGrowth <- NA #intialize with NA
for (i in 2:nrow(df))
{if(df$TreeID[i]==df$TreeID[i-1])
{df$HeightGrowth[i] <- df$Height[i]-df$Height[i-1]
}
}
Trevor Walker
Email: trevordaviswal...@gmail.com
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