(This article was first published on

** jottR**, and kindly contributed to

R-bloggers)
Sometimes a minor change to your R code can make a big difference in processing time. Here is an example showing that if you’re don’t care about the names attribute when unlist():ing a list, specifying argument use.names=FALSE can speed up the processing lots!

> x <- split(sample(1000, size=1e6, rep=TRUE), rep(1:1e5, times=10))

> t1 <- system.time(y1 <- unlist(x))

> t2 <- system.time(y2 <- unlist(x, use.names=FALSE))

> stopifnot(identical(y2, unname(y1)))

> t1/t2

user system elapsed

103 NaN 104

That’s more than a 100 times speedup.

So, check your code to see to which unlist() statements you can add an use.names=FALSE.

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** jottR**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...