indexing through function to gather multiple values - r

Question

I want to extract a sequence of values from this dataframe altogether to form a single output, I can do so individually using:
p <- function(x, i){
r<- rank_data[x][rank_data[,i] %in% 2000:2020,]
}
p(1:2, 2)
#output
jan year
235.2 2008
where the sequence of values in p() continue as:
x=c(1:2, 3:4, 5:6)
i=(2, 4, 6)
I'm looking for a single code, where a variable x or i can be indexed into the dataframe to produce the expected output. Although, using some other iteration function like apply is welcome. I want to better understand indexing through iterative functions.
expected output:
jan year feb year2 mar year3 ...
235.2 2008 287.6 2020 187.8 2019 ...
NA NA 241.9 2002 NA NA
I've asked a similar question here, although, I'm more interested in doing this through indexing with a single iterative function. The technique provided by the author in the previous question, is very specialised, so I'm looking for something simpler to get the hang of this.
Reproducible code:
structure(list(jan = c(268.1, 263.1, 235.2, 223.3, 219.2, 218.3
), year = c(1928, 1948, 2008, 1877, 1995, 1990), feb = c(287.6,
241.9, 213.7, 205.1, 191.9, 191.2), year2 = c(2020, 2002, 1997,
1990, 1958, 1923), mar = c(225.3, 190.7, 187.8, 187.2, 175.9,
173.9), year3 = c(1981, 1903, 2019, 1947, 1994, 1912)), class = "data.frame", row.names = c(NA,
6L))

Answer 1

You should store the values of x in a list because if you store them in a vector there is no way to distinguish between two groups.
x = c(1:2, 3:4, 5:6)
x
#[1] 1 2 3 4 5 6
Storing them in a list.
x= list(1:2, 3:4, 5:6)
x
#[[1]]
#[1] 1 2
#[[2]]
#[1] 3 4
#[[3]]
#[1] 5 6
You can use Map to index rows from your dataframe.
p <- function(x, i){
r<- rank_data[x][rank_data[,i] %in% 2000:2020,]
r
}
x= list(1:2, 3:4, 5:6)
i= c(2, 4, 6)
result <- Map(p, x, i)
result
#[[1]]
# jan year
#3 235.2 2008
#[[2]]
# feb year2
#1 287.6 2020
#2 241.9 2002
#[[3]]
# mar year3
#3 187.8 2019
If you want output same as shown you can add another step to count max number of rows.
nr <- 1:max(sapply(result, nrow))
do.call(cbind, lapply(result, function(x) x[nr, ]))
# jan year feb year2 mar year3
#3 235.2 2008 287.6 2020 187.8 2019
#NA NA NA 241.9 2002 NA NA