How to Clear Only a Few Specific Objects from the Workspace

How do I clear only a few specific objects from the workspace?

You'll find the answer by typing ?rm

rm(data_1, data_2, data_3)

How can I remove all objects but one from the workspace in R?

Here is a simple construct that will do it, by using setdiff:

rm(list=setdiff(ls(), "x"))

And a full example. Run this at your own risk - it will remove all variables except x:

x <- 1
y <- 2
z <- 3
ls()
[1] "x" "y" "z"

rm(list=setdiff(ls(), "x"))

ls()
[1] "x"

clear everything but one variable rm(list = ls())

Try: rm(list = setdiff(ls(), x))

Edit based on mickey's comment:

Three objects in environment:

ls()
[1] "data_df" "list_ls" "vector_v"

Remove data_df:

rm(list = setdiff(ls(), "data_df"))
ls()
[1] "data_df"

Vector of things to keep:

toKeep_v <- c("list_ls", "vector_v")
rm(list = setdiff(ls(), toKeep_v)
ls()
[1] "list_ls" "vector_v"

Removing workspace objects whose name start by a pattern using R

The pattern argument uses regular expressions. You can use a caret ^ to match the beginning of the string:

rm(list=ls(pattern="^tp_"))
rm(list=setdiff(ls(pattern = "^tp_"), lsf.str()))

However, there are other patterns for managing temporary items / keeping clean workspaces than name prefixes.

Consider, for example,

temp<-new.env()
temp$x <- 1
temp$y <- 2
with(temp,x+y)
#> 3
rm(temp)

Another possibility is attach(NULL,name="temp") with assign.

R Global Function to Clear Workspace and Dump Storage

Two thoughts about this: Your code does not delete all objects, to also remove the hidden ones use

rm(list = ls(all.names = TRUE))

There is also the command gctorture() which provokes garbage collection on (nearly) every memory allocation (as the man page said). It's intended for R developers to ferret out memory protection bugs:

cleaner <- function(){
    # Turn it on
    gctorture(TRUE)

    # Clear workspace
    rm(list = ls(all.names = TRUE, envir=sys.frame(-1)),
       envir = sys.frame(-1))

    # Turn it off (important or it gets very slow)
    gctorture(FALSE)
}

If this procedure is used within a function, there is the following problem: Since the function has its own stack frame, only the objects within this stack frame are deleted. They still exist outside. Therefore, it must be specified separately with sys.frame(-1) that only the higher-level stack frame should be considered. The variables are then only deleted within the function that calls cleaner() and in cleaner itself when the function is exited.

But this also means that the function may only be called from the top level in order to function correctly (you can use sys.frames() which lists all higher-level stack frames to build something that also avoids this problem if really necessary)

rm(list=ls()) doesn't completely clear the workspace

attach() does not make copies of x and y in your global environment, it attaches a dataframe to the search path.

From ?attach:

The database is not actually attached.  Rather, a new environment
 is created on the search path and the elements of a list
 (including columns of a data frame) or objects in a save file or
 an environment are _copied_ into the new environment.  If you use
 ‘<<-’ or ‘assign’ to assign to an attached database, you only
 alter the attached copy, not the original object.  (Normal
 assignment will place a modified version in the user's workspace:
 see the examples.)  For this reason ‘attach’ can lead to
 confusion.

For example:

> search()
[1] ".GlobalEnv"        "package:stats"     "package:graphics" 
[4] "package:grDevices" "package:utils"     "package:datasets" 
[7] "package:methods"   "Autoloads"         "package:base"     
> a <- data.frame(stuff=rnorm(100))
> search()
[1] ".GlobalEnv"        "package:stats"     "package:graphics" 
[4] "package:grDevices" "package:utils"     "package:datasets" 
[7] "package:methods"   "Autoloads"         "package:base"     
> attach(a)
> search()
 [1] ".GlobalEnv"        "a"                 "package:stats"    
 [4] "package:graphics"  "package:grDevices" "package:utils"    
 [7] "package:datasets"  "package:methods"   "Autoloads"        
[10] "package:base"     
> rm(list=ls())
> search()
 [1] ".GlobalEnv"        "a"                 "package:stats"    
 [4] "package:graphics"  "package:grDevices" "package:utils"    
 [7] "package:datasets"  "package:methods"   "Autoloads"        
[10] "package:base"     
> stuff
  [1] -0.91436377  0.67397624  0.62891651 -0.99669584  2.07692590 -0.62702302
  [...]
> detach(a)
> search()
[1] ".GlobalEnv"        "package:stats"     "package:graphics" 
[4] "package:grDevices" "package:utils"     "package:datasets" 
[7] "package:methods"   "Autoloads"         "package:base"    

rm( ) everything except specific object

The setdiff() function shows the difference between sets, so we can use this to give the difference between all the objects (ls()), and the object you want to keep. For example

## create some objects
df <- data.frame()
v <- as.numeric()

# show everything in environment
objects()
# [1] "df" "v"

## or similarly
ls()
# [1] "df" "v"

## the setdiff() funciton shows the difference between two sets
setdiff(ls(), "df")
# [1] "v"

# so we can use this to remove everything except 'df'
rm(list = setdiff(ls(), "df"))
objects()
# [1] "df"

How to remove all user created variables that start with a specific set of strings

You can probably do this using a regular expression via ls:

rm(list = ls(pattern = "^tmp"))

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