Dear Bert,
Thank you very much.This works. I was wondering if the fact that I want to
create new variables (sorry for not stating that fact) makes any
difference? Thank you again.
Sincerely,
Milu
On Sun, Mar 25, 2018 at 10:05 PM, Bert Gunter <bgunter.4...@gmail.com>
wrote:
> I am sure that this sort of thing has been asked and answered before,
> so in case my suggestions don't work for you, just search the archives
> a bit more.
> I am also sure that it can be handled directly by numerous functions
> in numerous packages, e.g. via time series methods or by calculating
> running means of suitably shifted series.
>
> However, as it seems to be a straightforward task, I'll provide what I
> think is a simple solution in base R. Adjust to your situation.
>
> ## First I need a little utility function to offset rows. Lots of ways
> to do this,many nicer than this I'm sure.
>
> > shift <- function(x,k)
> + ## x is a vector of values -- e.g. of a column in your df
> + {
> + sapply(seq_len(k),function(i)c(rep(NA,i),head(x,-i)))
> + }
> >
> >
> > ## Testit
> > x <- c(1,3,5,7,8:11)
> > m <- shift(x,3) ## matrix of prior values up to lag 3
> > m ## note rows have been omitted where lags don't exist
> [,1] [,2] [,3]
> [1,] NA NA NA
> [2,] 1 NA NA
> [3,] 3 1 NA
> [4,] 5 3 1
> [5,] 7 5 3
> [6,] 8 7 5
> [7,] 9 8 7
> [8,] 10 9 8
> > rowMeans(m) ## means of previous 3
> [1] NA NA NA 3.000000 5.000000 6.666667 8.000000 9.000000
> > rowMeans(m[,1:2]) ## means of previous 2
> [1] NA NA 2.0 4.0 6.0 7.5 8.5 9.5
>
>
> Cheers,
> Bert
>
>
>
>
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
> and sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Sun, Mar 25, 2018 at 7:48 AM, Miluji Sb <miluj...@gmail.com> wrote:
> > Dear all,
> >
> > I have weekly data by city (variable citycode). I would like to take the
> > average of the previous two, three, four weeks (without the current week)
> > of the variable called value.
> >
> > This is what I have tried to compute the average of the two previous
> weeks;
> >
> > df = df %>%
> > mutate(value.lag1 = lag(value, n = 1)) %>%
> > mutate(value .2.previous = rollapply(data = value.lag1,
> > width = 2,
> > FUN = mean,
> > align = "right",
> > fill = NA,
> > na.rm = T))
> >
> > I crated the lag of the variable first and then attempted to compute the
> > average but this does not seem to to what I want. What I am doing wrong?
> > Any help will be appreciated. The data is below. Thank you.
> >
> > Sincerely,
> >
> > Milu
> >
> > dput(droplevels(head(df, 10)))
> > structure(list(year = c(1970L, 1970L, 1970L, 1970L, 1970L, 1970L,
> > 1970L, 1970L, 1970L, 1970L), citycode = c(1L, 1L, 1L, 1L, 1L,
> > 1L, 1L, 1L, 1L, 1L), month = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
> > 2L, 3L), week = c(1L, 2L, 3L, 4L, 5L, 5L, 6L, 7L, 8L, 9L), date =
> > structure(c(1L,
> > 2L, 3L, 4L, 5L, 5L, 6L, 7L, 8L, 9L), .Label = c("1970-01-10",
> > "1970-01-17", "1970-01-24", "1970-01-31", "1970-02-07", "1970-02-14",
> > "1970-02-21", "1970-02-28", "1970-03-07"), class = "factor"),
> > value = c(-15.035, -20.478, -22.245, -23.576, -8.84099999999995,
> > -18.497, -13.892, -18.974, -15.919, -13.576)), .Names = c("year",
> > "citycode", "month", "week", "date", "tmin"), row.names = c(NA,
> > 10L), class = "data.frame")
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
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> > PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
[[alternative HTML version deleted]]
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