I have a data frame containing a factor. When I create a subset of this data frame using
subset() or another indexing function, a new data frame is created. However, the factor variable retains all of its original levels -- even when they do not exist in the new data frame.
This creates headaches when doing faceted plotting or using functions that rely on factor levels.
What is the most succinct way to remove levels from a factor in my new data frame?
Here's my example:
df <- data.frame(letters=letters[1:5], numbers=seq(1:5)) levels(df$letters) ##  "a" "b" "c" "d" "e" subdf <- subset(df, numbers <= 3) ## letters numbers ## 1 a 1 ## 2 b 2 ## 3 c 3 ## but the levels are still there! levels(subdf$letters) ##  "a" "b" "c" "d" "e"
All you should have to do is to apply factor() to your variable again after subsetting:
> subdf$letters  a b c Levels: a b c d e subdf$letters <- factor(subdf$letters) > subdf$letters  a b c Levels: a b c
From the factor page example:
factor(ff) # drops the levels that do not occur
For dropping levels from all factor columns in a dataframe, you can use:
subdf <- subset(df, numbers <= 3) subdf <- lapply(subdf, function(x) if(is.factor(x)) factor(x) else x)
Since R version 2.12, there's a