Try this:
aggregate(DF[c('data', 'data2')], DF[ 'years'], FUN = sum, na.rm = TRUE)
aggregate(DF[c('data', 'data2')], list(as.character(factor(DF[, 'years'],
labels = c('5-7', '5-7', '5-7', 8, FUN = sum, na.rm = TRUE)
On Sun, Apr 25, 2010 at 3:29 AM, steven mosher wrote:
> I have a 43MB dataf
thx I was struggling with the DF[,3:4] part of it
On Sun, Apr 25, 2010 at 10:47 AM, John Kane wrote:
> Here's one way with aggregate()
>
> library(car) # You probably will need to install it.
>
> aggregate(DF[,3-4], by=list(years), mean,na.rm=TRUE)
>
> recode(x, "c(1,2)='A'; else='B'")
>
> DF$
Here's one way with aggregate()
library(car) # You probably will need to install it.
aggregate(DF[,3-4], by=list(years), mean,na.rm=TRUE)
recode(x, "c(1,2)='A'; else='B'")
DF$years <- recode(DF$years, "c(5,6,7)= '5-7'")
DF
You may also want to have a look at the reshape and plyr packages.
Thanks I'll try that, still need to understand how the other functions
work.. just to satisfy myself..thanks again
On Sun, Apr 25, 2010 at 12:06 AM, Tal Galili wrote:
> Here is one solution for your question:
>
> mean.data <- with(DF, tapply(data, years, mean, na.rm = T))
> mean.data2 <- with(DF
Here is one solution for your question:
mean.data <- with(DF, tapply(data, years, mean, na.rm = T))
mean.data2 <- with(DF, tapply(data2, years, mean, na.rm = T))
cbind(mean.data , mean.data2)
Another one would be for you to read about the package plyr (which is better
for this job, actually)
An
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