for these dataframe:
d1 <- data.frame(y1=c(1,2,3), y2=c(4,5,6))
d2 <- data.frame(y1=c(3,2,1), y2=c(6,5,4))
d3 <- data.frame(y1=c(6,5,4), y2=c(3,2,1))
d4 <- data.frame(y1=c(9,9,9), y2=c(8,8,8))
dat=sapply(paste('d', seq(2,4,1), sep=''), get, environment(), simplify = FALSE)
For instance i can do this manually
scale(as.numeric(dat$d2$y1))[,1]
but i want to do this to all data.frames d2$y1, d2$y2, d1$y1, d1$y .;;etc and get the output
lapply(
dat,
\(y) {
transform(
y,
y1 = scale(y1)
)
}
)
If you want to change y1 columns only
You can simply run mget (rather than sapply + get)
> (dat <- mget(paste0("d", seq(2, 4, 1))))
$d2
y1 y2
1 3 6
2 2 5
3 1 4
$d3
y1 y2
1 6 3
2 5 2
3 4 1
$d4
y1 y2
1 9 8
2 9 8
3 9 8
If you want to apply a function to a list of dataframes, you can use lapply(dat, f), where f is the function you will proceed with over each dataframe., for example
lst <- lapply(
dat,
\(y) list2DF(lapply(
y,
scale
))
)
which gives
$d2
y1 y2
1 1 1
2 0 0
3 -1 -1
$d3
y1 y2
1 1 1
2 0 0
3 -1 -1
$d4
y1 y2
1 NaN NaN
2 NaN NaN
3 NaN NaN
Furthermore, if you want to overwrite d2, d3 and d4 by the updated values, you can further run
list2env(lst, envir = .GlobalEnv)
