How to assign values to dynamic names variables

Question

Hi I'm trying to name variables using a for loop so I get dynamic names for my variables.

for (i in 1:nX) {
    paste("X",i, sep="")=datos[,i+1]
    next
}

Hi, I have a data frame with long headers but would like to automatically set my own variables as X1, X2, etc so I can operate with them individually — nopeva
– nopeva, Commented Dec 29, 2012 at 13:27
Why don't you just do colNames(datos) <- paste("X", i, sep="") then? Then you can access them with datos$X1, datos$X2 etc — nico
– nico, Commented Dec 29, 2012 at 13:29
This is faq 7.21, the most important part of that answer is the last part that says not to do this, use a list or environment. — Greg Snow
– Greg Snow, Commented Dec 29, 2012 at 14:34

Jilber Urbina · Accepted Answer · 2012-12-29 13:11:46Z

34

use assign as in:

x <- 1:10

for(i in seq_along(x)){
  assign(paste('X', i, sep=''), x[i])
}

answered Dec 29, 2012 at 13:11

Jilber Urbina

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3 Comments

nopeva Over a year ago

Hi David, why do you think is a bad idea?

joran Over a year ago

@user1228124 Experienced R programmers generally advise against using assign unless you are absolutely forced to. In this case, nico's suggestion of using colnames<- is safer, simpler, and easier to understand.

yanes Over a year ago

plus one, this saved me time

Karsten W. · Accepted Answer · 2012-12-29 14:31:31Z

It can be a good idea to use assign when there are many variables and they are looked up frequently. Lookup in an environment is faster than in vector or list. A separate environment for the data objects is a good idea.

Another idea is to use the hash package. It performs lookup as fast as environments, but is more comfortable to use.

datos <- rnorm(1:10)
library(hash)
h <- hash(paste("x", 1:10, sep=""), datos)
h[["x1"]]

Here is a timing comparision for 10000 vars that are looked up 10^5 times:

datos <- rnorm(1:10000)
lookup <- paste("x", sample.int(length(datos), 100000, replace=TRUE), sep="")

# method 1, takes 16s on my machine
names(datos) <- paste("x", seq_along(datos), sep="")
system.time(for(key in lookup) datos[[key]])

# method 2, takes 1.6s on my machine
library(hash)
h <- hash(paste("x", seq_along(datos), sep=""), datos)
system.time(for(key in lookup) h[[key]])

# method 3, takes 0.2s on my machine
e <- new.env()
for(i in seq_along(datos)){
  assign(paste('x', i, sep=''), datos[i], envir=e)
}
system.time(for(key in lookup) e[[key]])

However, the vectorized version of method 1 is the fastest, but is not always applicable

# method 4, takes 0.02s
names(datos) <- paste("x", seq_along(datos), sep="")
system.time(datos[lookup])

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