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--------------------------------------
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