Assign multiple objects to .GlobalEnv from within a function

Question

A post on here a day back has me wondering how to assign values to multiple objects in the global environment from within a function. This is my attempt using lapply (assign may be safer than <<- but I have never actually used it and am not familiar with it).

#fake data set
df <- data.frame(
  x.2=rnorm(25),
  y.2=rnorm(25),
  g=rep(factor(LETTERS[1:5]), 5)
)

#split it into a list of data frames
LIST <- split(df, df$g)

#pre-allot 5 objects in R with class data.frame()
V <- W <- X <- Y <- Z <- data.frame()

#attempt to assign the data frames in the LIST to the objects just created
lapply(seq_along(LIST), function(x) c(V, W, X, Y, Z)[x] <<- LIST[[x]])

Please feel free to shorten any/all parts of my code to make this work (or work better/faster).

Answer 1

Update of 2018-10-10:

The most succinct way to carry out this specific task is to use list2env() like so:

## Create an example list of five data.frames
df <- data.frame(x = rnorm(25),
                 g = rep(factor(LETTERS[1:5]), 5))
LIST <- split(df, df$g)

## Assign them to the global environment
list2env(LIST, envir = .GlobalEnv)

## Check that it worked
ls()
## [1] "A"    "B"    "C"    "D"    "df"   "E"    "LIST"

---

Original answer, demonstrating use of assign()

You're right that assign() is the right tool for the job. Its envir argument gives you precise control over where assignment takes place -- control that is not available with either <- or <<-.

So, for example, to assign the value of X to an object named NAME in the the global environment, you would do:

assign("NAME", X, envir = .GlobalEnv)

In your case:

df <- data.frame(x = rnorm(25),
                 g = rep(factor(LETTERS[1:5]), 5))
LIST <- split(df, df$g)
NAMES <- c("V", "W", "X", "Y", "Z")

lapply(seq_along(LIST), 
       function(x) {
           assign(NAMES[x], LIST[[x]], envir=.GlobalEnv)
        }
)

ls()
[1] "df"    "LIST"  "NAMES" "V"     "W"     "X"     "Y"     "Z"    

Answer 2

I think this question can have a nice crossover with this one: Can lists be created that name themselves based on input object names?

Say you want to do the same modification to a set of objects on the fly. But list2env() requires a named list, and you don't want to copy and paste them again. Borrowing the namedList function, and combining it with Josh O'Brien anwser:

> namedList <- function(...) {
+   L <- list(...)
+   snm <- sapply(substitute(list(...)), deparse)[-1]
+   if (is.null(nm <- names(L))) nm <- snm
+   if (any(nonames <- nm=="")) nm[nonames] <- snm[nonames]
+   setNames(L ,nm)
+ }
> 
> df_1 <- data.frame(x = 1)
> df_2 <- data.frame(x = 2)
> df_3 <- data.frame(x = 3)
> 
> list2env(lapply(namedList(df_1, df_2, df_3), function(x) {
+   x <- cbind.data.frame(x, y = "B")
+ }), envir = .GlobalEnv)
<environment: R_GlobalEnv>
> 
> df_1
  x y
1 1 B
> df_2
  x y
1 2 B
> df_3
  x y
1 3 B

Answer 3

If you have a list of object names and file paths you can also use mapply:

object_names <- c("df_1", "df_2", "df_3")
file_paths   <- list.files({path}, pattern = ".csv", full.names = T)
    
mapply(function(df_name, file) 
           assign(df_name, read.csv(file), envir=.GlobalEnv),
       object_names,
       file_paths)

• I used list.files() to construct a vector of all the .csv files in a specific directory. But file_paths could be written or constructed in any way.
• If the files you want to read in are in the current working directory, then file_paths could be replaced with a character vector of file names.
• In the code above, you need to replace {path} with a string of the desired directory's path.

Answer 4

This demonstrates how to split out a nested dataframe into objects in the global environment with tidyverse functions:

library(tidyverse)
library(palmerpenguins)

penguins %>% 
  group_nest(species) %>% 
  deframe() %>% 
  list2env(.GlobalEnv)