I need to calculate each component of the time series for each X (50 levels) and Y (80 levels) from my dataset (df).

I wanted to go with something akin to the code below, where I tried to just get the seasonality. If I can get this it should be the same for the trend and random component of the decompose.

```
P <- df$X
for(y in 1:length(P)) {
OneP <- P[y]
AllS <- unique(df$Y[df$X== OneP])
for(i in 1:length(AllS)) {
OneS<- AllS[i]
df$TS[df$Y == OneS & df$X== OneP] <- ts(df$Mean[df$Y == OneS & df$X
== OneP], start = c(1999, 1), end = c(2015, 12), frequency = 12)
df$Dec[df$Y == OneS & df$X== OneP] <- decompose(ts(df$TS[df$Y == OneS &
df$X== OneP], frequency = 12), type = c("additive"))
df$Decomposition_seasonal[df$Y == OneS & df$X== OneP] <- df$Dec([df$Y == OneS & df$X== OneP], Dec$seasonal)
}
```

But this is not working. Error message is:

Error: attempt to apply non-function

I understand that the problem might come from my attempt to put decomposition output in a column. But how else to do it? Make a new dataset for every dev in every X * Y combination?

I know that the first lines of the code work as I used it before for something else. And I know this will run and give me TS and decomposition. It's the individual components bit that I am struggling with. Any advice is deeply appreciated.

Similar data:

```
X Y Mean Date(mY)
Tru A 35.6 02.2015
Fle A 15 05.2010
Srl C 67.1 05.1999
Tru A 13.2 08.2006
Srl B 89 08.2006
Tru B 14.8 12.2001
Fle A 21.5 11.2001
Lub D 34.8 03.2000
```