Dear all,
If I have the following data frame:
> set.seed(21)
> df1 <- data.frame(col1=c(rep('a',5), rep('b',5), rep('c',5)),
> col4=rnorm(1:15))
col1 col4
1 a 0.793013171
2 a 0.522251264
3 a 1.746222241
4 a -1.271336123
5 a 2.197389533
6 b 0.433130777
7 b -1.570199630
8 b -0.934905667
9 b 0.063493345
10 b -0.002393336
11 c -2.276781240
12 c 0.757412225
13 c -0.548405554
14 c 0.172549478
15 c 0.562853068
How can i make a 2 point moving average within each group? i.e.
col1 col4 SMA
a 0.793013171 NA
a 0.522251264 0.657632218
a 1.746222241 1.134236753
a -1.271336123 0.237443059
a 2.197389533 0.463026705
b 0.433130777 NA
b -1.57019963 -0.568534427
b -0.934905667 -1.252552649
b 0.063493345 -0.435706161
b -0.002393336 0.030550005
c -2.27678124 NA
c 0.757412225 -0.759684508
c -0.548405554 0.104503336
c 0.172549478 -0.187928038
c 0.562853068 0.367701273
>From what i've read, i was thinking it would be something along the
lines of:
> aggregate(df1$col4, by=list(df1$col1), function(x) {filter(x, rep(1/2,2),
> sides=1 )} )
Error in aggregate.data.frame(as.data.frame(x), ...) :
'FUN' must always return a scalar
But this tells me (i think) that aggregate should only return a single
value per group. So what i need, i guess, is something that takes all
the values in a given group, and returns a vector of the same length.
Not sure which function to use for that.
Thanks in advance,
C xx
P.S. on a side note, is it possible to extract the values which
aggregate passes to the function(x) in my example above?
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