How to drop unused levels after filtering by factor? [duplicate]

Question

Here is an example that was taken from a fellow SO member.

# define a %not% to be the opposite of %in%
library(dplyr)
# data
f <- c("a","a","a","b","b","c")
s <- c("fall","spring","other", "fall", "other", "other")
v <- c(3,5,1,4,5,2)
(dat0 <- data.frame(f, s, v))
#  f      s v
#1 a   fall 3
#2 a spring 5
#3 a  other 1
#4 b   fall 4
#5 b  other 5
#6 c  other 2
(sp.tmp <- filter(dat0, s == "spring"))
#  f      s v
#1 a spring 5
(str(sp.tmp))
#'data.frame':  1 obs. of  3 variables:
# $ f: Factor w/ 3 levels "a","b","c": 1
# $ s: Factor w/ 3 levels "fall","other",..: 3
# $ v: num 5

The df resulting from filter() has retained all the levels from the original df.

What would be the recommended way to drop the unused level(s), i.e. "fall" and "others", within the dplyr framework?

Answer 1

You could do something like:

dat1 <- dat0 %>%
  filter(s == "spring") %>% 
  droplevels()

Then

str(df)
#'data.frame':  1 obs. of  3 variables:
# $ f: Factor w/ 1 level "a": 1
# $ s: Factor w/ 1 level "spring": 1
# $ v: num 5

Answer 2

You could use droplevels

 sp.tmp <- droplevels(sp.tmp)
 str(sp.tmp)
 #'data.frame': 1 obs. of  3 variables:
 #$ f: Factor w/ 1 level "a": 1
 #$ s: Factor w/ 1 level "spring": 1
# $ v: num 5