I see that @nirgrahamuk has given an elegant general solution. I will offer a much less general but simpler version. It looks from your for loop code that you want to modify all of the columns in each data frame. For that, you can use the mutate_all function from the dplyr package. I put in some extra print statements to make it easy to compare the data frames before and after the processing.
(If you want to modify just some columns, there are functions called mutate_at and mutate_if that may be useful)
library(dplyr)
frame_j <- data.frame(A = c(23, 14, 45), B = c(16, 19, 12), C = c(23, 32, 6))
frame_v <- data.frame(A = c(23, 14, 45), B = c(16, 19, 12), C = c(23, 32, 6))
jFunc <- function(x) ifelse(x <= 16, x, NA)
frame_j
#> A B C
#> 1 23 16 23
#> 2 14 19 32
#> 3 45 12 6
frame_j <- mutate_all(frame_j, jFunc)
frame_j
#> A B C
#> 1 NA 16 NA
#> 2 14 NA NA
#> 3 NA 12 6
vFunc <- function(x) ifelse(x >= 19, x, NA)
frame_v
#> A B C
#> 1 23 16 23
#> 2 14 19 32
#> 3 45 12 6
frame_v <- mutate_all(frame_v, vFunc)
frame_v
#> A B C
#> 1 23 NA 23
#> 2 NA 19 32
#> 3 45 NA NA
Created on 2020-02-20 by the reprex package (v0.3.0)