Yes, you have access to the .SD
variable which represents all columns other than the ones involved in grouping, so
Dtable[,lapply(.SD, paste, collapse=", "), by=station.id]
should do the trick
Question
I have this line of code that i am using in order to create the table below.
DtTemp <- Dtable[,list("temperature"=paste(temperature,collapse=", ")),by=station.id]
table:
station.id temperature
1: S1 18, 20.5, 18, 18.6, 21.5
2: S2 20.1, 18.3, 16.8, 17.5, 16.4
3: S3 11, 19.1, 18.9, 17.8, 17.6
4: S4 18, 15.5, 15, 14.9, 15.8
In the table above, temperature
values are grouped according to station.id
.
I am looking for to create other similar tables, automatically, for every other column in my Dtable
dataset. That being said it is obvious that i have more than one station.id
values in my original dataset Dtable
.
Assuming that a for
loop might do it, or something like foreach
or iter
how should i use them to implement it.?
Is there a way to achieve this, giving at each temperature
column, as the example above, the relevant Dtable
column name, for which the table is created.?
Appreciate any help.
Solution
Yes, you have access to the .SD
variable which represents all columns other than the ones involved in grouping, so
Dtable[,lapply(.SD, paste, collapse=", "), by=station.id]
should do the trick