[R] reshape/aggregate

[jim holtman]

You can use data.table:

> group <- c(rep('A', 8), rep('B', 15), rep('C', 6))
> time <- c(rep(seq(1:4), 2), rep(seq(1:5), 3), rep(seq(1:3), 2))
> value <- runif (29, 1, 10)
> dfx <- data.frame (group, time, value)
> require(data.table)
> dfx <- data.table(dfx)
> dfx[,
+     list(mean = mean(value), sd = sd(value))
+     , by = list(group, time)
+     ]
      group time     mean        sd
 [1,]     A    1 7.902432 0.8484807
 [2,]     A    2 5.583566 1.1996167
 [3,]     A    3 3.412691 1.1138794
 [4,]     A    4 7.786522 2.2367483
 [5,]     B    1 6.669257 2.1476769
 [6,]     B    2 2.902291 1.6630821
 [7,]     B    3 6.913593 0.9110182
 [8,]     B    4 4.713124 0.9521689
 [9,]     B    5 7.285824 1.5884689
[10,]     C    1 3.799665 3.7728015
[11,]     C    2 9.218785 0.9415034
[12,]     C    3 5.098077 3.5256497


On Wed, Aug 31, 2011 at 4:19 AM, Kai Megerle <govokai at gmail.com> wrote:
> Hi all,
> I apologize for this probably stupid question, but I really can't figure it
> out.
> I have a dataframe like this:
>
> group <- c(rep('A', 8), rep('B', 15), rep('C', 6))
> time <- c(rep(seq(1:4), 2), rep(seq(1:5), 3), rep(seq(1:3), 2))
> value <- runif (29, 1, 10)
> dfx <- data.frame (group, time, value)
>
> I want to calculate mean and standard deviation for all values that belong
> to the same group and the same time and end up with a dataframe with the
> columns time, group, mean and sd that contains the calculated values for
> every group at every time point only once (12).
> What is the most elegant way to do this? Oh, and I would like to avoid
> renaming columns (like the _X1/_X2 created by casting with multiple
> functions), if possible.
> I am sure that this is pretty basic, but I have already wasted a ridiculous
> amount of time on this.
>
> Thanks,
>
> Kai
>
>        [[alternative HTML version deleted]]
>
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>



-- 
Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?