How to use `assign()` or `get()` on specific named column of a dataframe?

Question

Is there a way to assign a value to a specific column within a data frame? e.g.,

dat2 = data.frame(c1 = 101:149, VAR1 = 151:200)    
j = "dat2[,"VAR1"]"  ## or, j = "dat2[,2]"
assign(j,1:50)

The approach above doesn't work. Neither does this:

j = "dat2"
assign(get(j)[,"VAR1"],1:50)

Answer 1

lets assume that we have a valid data.frame with 50 rows in each

dat2 <- data.frame(c1 = 1:50, VAR1 = 51:100)

1 . Don't use assign and get if you can avoid it.

"dat2[,"VAR1"]" is not valid in R.

You can also note this from the help page for assign

assign does not dispatch assignment methods, so it cannot be used to set elements of vectors, names, attributes, etc.

Note that assignment to an attached list or data frame changes the attached copy and not the original object: see attach and with.

A column of a data.frame is an element of a list

What you are looking for is [[<-

# assign the values from column (named element of the list) `VAR1`
j <- dat2[['VAR1']] 

If you want to assign new values to VAR1 within dat2,

dat2[['VAR1']] <- 1:50

---

The answer to your question....

To manipulate entirely using character strings using get and assign

assign('dat2', `[[<-`(get('dat2'), 'VAR1', value = 2:51))

---

Other approaches

data.table::set

if you want to assign by reference within a data.frame or data.table (replacing an existing column only) then set from the data.table package works (even with data.frames)

library(data.table)
set(dat2, j = 'VAR1', value = 5:54)

---

eval and bquote

dat1 <- data.frame(x=1:5)
dat2 <- data.frame(x=2:6)



for(x in sapply(c('dat1','dat2'),as.name)) {
  eval(bquote(.(x)[['VAR1']] <- 2:6))
}

---

eapply

Or if you use a separate environment

ee <- new.env()
ee$dat1 <- dat1
ee$dat2 <- dat2

# eapply returns a list, so use list2env to assign back to ee
list2env(eapply(ee, `[[<-`, 'y', value =1:5), envir = ee)

---

Answer 2

set2 <- function(x,  val) {
   eval.parent(substitute(x <- val))
 }

> dat2 = data.frame(c1 = 101:150, VAR1 = 151:200)
> set2(dat2[["VAR1"]], 1:50)
> str(dat2)
'data.frame':   50 obs. of  2 variables:
 $ c1  : int  101 102 103 104 105 106 107 108 109 110 ...
 $ VAR1: int  1 2 3 4 5 6 7 8 9 10 ...