R has factors, which are very cool (and somewhat analogous to labeled levels in Stata). Unfortunately, the factor list sticks around even if you remove some data such that no examples of a particular level still exist

# Create some fake data

x <- as.factor(sample(head(colors()),100,replace=TRUE))

levels(x)

x <- x[x!="aliceblue"]

levels(x) # still the same levels

table(x) # even though one level has 0 entries!

The solution is simple: run factor() again:

x <- factor(x)

levels(x)

If you need to do this on many factors at once (as is the case with a data.frame containing several columns of factors), use drop.levels() from the gdata package:

x <- x[x!="antiquewhite1"]

df <- data.frame(a=x,b=x,c=x)

df <- drop.levels(df)
Now I’m going to quit monkeying around and get to sleep.

*Related*

To

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

** The Data Monkey**.

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...