Well, a rather simple-minded, brute force approach would be to add a factor
variable to the data frame and use aggregate on it.
I am sure there are better ways but this will work.
EXAMPLE
###
xx <- data.frame(aa =1:24,
b = matrix(sample(c(1,2,3,4,5,6), 72, replace = TRUE),
nrow= 24))
dd <-rep(c("a","b"), each= 12)
xx <- cbind(dd, xx)
aggregate(xx[,3:5], list(xx$dd), mean)
################
By the way, when supplying data samples a good way is to use the dput command.
Try ?dput for information
John Kane
Kingston ON Canada
> -----Original Message-----
> From: simolas2...@gmail.com
> Sent: Sat, 5 Jan 2013 15:33:03 +0200
> To: r-help@r-project.org
> Subject: [R] Need help on dataframe
>
> Dear R users, I came up to a problem by taking means (or other summary
> statistics) of a big dataframe.
>
> Suppose we do have a dataframe:
>
> ID V1 V2 V3 V4 ........................ V71
> 1 6 5 3 2 ........................ 3
> 2 3 2 2 1 ........................ 1
> 3 6 5 3 2 ........................ 3
> 4 12 15 3 2 ........................ 100
> ........................................................
> ........................................................
> 288 10 20 30 30 .......................... 499
>
> I need to find out the way, how to calculate a mean of every 12 lines to
> get:
>
> V1 V2 V3 V4
> ........................... V71
> mean from 1 to 7 same as V1 same as V1
> mean from 8 to 14 same as V1 same as V1
> etc.
>
> I can do it column by column using:
>
> y.ts <- ts(y$V1, frequency=12)
> aggregate(y.ts, FUN=mean)
>
> Bu this is a hardcore... Can anyone suggest a better way to compute all
> the
> dataframe at once and get a result as matrix?
>
> Thank you in advance!
>
> --
> Simonas Kecorius
> **
>
> [[alternative HTML version deleted]]
>
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