The ave solution could be written as: transform(mydf1, yearly_sum = ave(daily_mean, cut(Data, "year"), FUN = cumsum))
On Mon, Aug 10, 2026 at 6:43 AM Eric Berger <[email protected]> wrote: > > I asked ChatGPT (5.5 Medium). Here is its analysis > > The problem is not Feb. 29 itself. The problem is that aggregate() > changes its return structure depending on whether all groups have the > same length. > In your first version, years have different numbers of days: most have > 365, leap years have 366. So aggregate(...) > returns a grouped result where each year’s cumsum() is kept as a list element. > Then this works by accident: > unlist(...[2], use.names = FALSE) > because it flattens the list year by year. > But after you remove Feb. 29, every year has exactly 365 rows. Now > aggregate() sees that every cumsum() result has the same length, so it > “simplifies” the result into a matrix-like structure. When you then > unlist() it, the values are no longer flattened in the chronological > order you expect. > The clean fix is: do not use aggregate() for this. Use ave(). > > mydf1 <- data.frame( > Data = seq( > as.POSIXct("2003-01-01", format = "%Y-%m-%d", tz = "Etc/GMT-1"), > as.POSIXct("2023-12-31", format = "%Y-%m-%d", tz = "Etc/GMT-1"), > by = "1 day" > ), > daily_mean = round(runif(7670, 0, 2), digits = 2) > ) > > mydf1 <- mydf1[format(mydf1$Data, "%m-%d") != "02-29", ] > > mydf1$yearly_sum <- ave( > mydf1$daily_mean, > as.integer(format(mydf1$Data, "%Y")), > FUN = cumsum > ) > > You can also force your original aggregate() approach to behave more > consistently by adding simplify = FALSE: > > tmp <- aggregate( > daily_mean ~ as.integer(format(mydf1$Data, "%Y")), > data = mydf1, > FUN = cumsum, > simplify = FALSE > ) > > mydf1$yearly_sum <- unlist(tmp$daily_mean, use.names = FALSE) > > > > > > > > On Mon, Aug 10, 2026 at 1:07 PM Stefano Sofia via R-help > <[email protected]> wrote: > > > > Dear R-list users, > > > > I've got problems to use the function aggregate. > > > > > > Here there is an example: > > > > > > mydf <- data.frame(Data=seq(as.POSIXct("2003-01-01", format = "%Y-%m-%d", > > tz="Etc/GMT-1"), as.POSIXct("2023-12-31", format = "%Y-%m-%d", > > tz="Etc/GMT-1"), by="1 day"), daily_mean = round(runif(7670, 0, 2), > > digits=2)) > > > > mydf$yearly_sum <- unlist(aggregate(daily_mean~as.integer(format(mydf$Data, > > "%Y")), data=mydf, cumsum)[2], use.names = FALSE) > > > > > > The column "yearly_sum" is the sum of the column "daily_mean" with a reset > > at the beginning of each year. > > > > If for my analysis I want to remove the 29th of February, "yearly_sum" does > > not work anymore: > > > > > > mydf1 <- data.frame(Data=seq(as.POSIXct("2003-01-01", format = "%Y-%m-%d", > > tz="Etc/GMT-1"), as.POSIXct("2023-12-31", format = "%Y-%m-%d", > > tz="Etc/GMT-1"), by="1 day"), daily_mean = round(runif(7670, 0, 2), > > digits=2)) > > > > mydf1 <- mydf1[format(mydf1$Data, "%m-%d") != "02-29", ] > > > > mydf1$yearly_sum <- > > unlist(aggregate(daily_mean~as.integer(format(mydf1$Data, "%Y")), > > data=mydf1, cumsum)[2], use.names = FALSE) > > > > > > In this case the column "yearly_sum" does not sum the values, and honestly > > I do not understand what is happening. Why? > > > > Could somebody help me? I already spent a big amount of hours with no > > success. > > > > > > Thank you for your attention and you help > > > > Stefano > > > > > > > > > > (oo) > > --oOO--( )--OOo-------------------------------------- > > Stefano Sofia MSc, PhD > > Civil Protection Department - Marche Region - Italy > > Meteo Section > > Snow Section > > Via Colle Ameno 5 > > 60126 Torrette di Ancona, Ancona (AN) > > Uff: +39 071 806 7743 > > E-mail: [email protected] > > ---Oo---------oO---------------------------------------- > > > > ________________________________ > > > > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può contenere > > informazioni confidenziali, pertanto è destinato solo a persone autorizzate > > alla ricezione. 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