Is there an alternative to "revalue" function from plyr when using dplyr?

Question

I'm a fan of the revalue function is plyr for substituting strings. It's simple and easy to remember.

However, I've migrated new code to dplyr which doesn't appear to have a revalue function. What is the accepted idiom in dplyr for doing things previously done with revalue?

Answer 1

There is a recode function available starting with dplyr version dplyr_0.5.0 which looks very similar to revalue from plyr.

Example built from the recode documentation Examples section:

set.seed(16)
x = sample(c("a", "b", "c"), 10, replace = TRUE)
x
 [1] "a" "b" "a" "b" "b" "a" "c" "c" "c" "a"

recode(x, a = "Apple", b = "Bear", c = "Car")

   [1] "Car"   "Apple" "Bear"  "Apple" "Car"   "Apple" "Apple" "Car"   "Car"   "Apple"

If you only define some of the values that you want to recode, by default the rest are filled with NA.

recode(x, a = "Apple", c = "Car")
 [1] "Car"   "Apple" NA      "Apple" "Car"   "Apple" "Apple" "Car"   "Car"   "Apple"

This behavior can be changed using the .default argument.

recode(x, a = "Apple", c = "Car", .default = x)
 [1] "Car"   "Apple" "b"     "Apple" "Car"   "Apple" "Apple" "Car"   "Car"   "Apple"

There is also a .missing argument if you want to replace missing values with something else.