R: Replacing NAs in all factors with 'Missing'

factor_NA_levels.R

library(dplyr)   # gives mutate_if
library(forcats) # gives fct_explicit_na

#example dataframe, a and c are factors,
#b is numeric, d is boolean (TRUE/FALSE)
mydata = data.frame(
	a = c( 'Yes', 'No',  NA),
	b = c(  0.5,   NA,   0.6),
	c = c( 'No',   NA,  'Yes'),
	d = c( TRUE,   NA,   FALSE)
)

# Making the missing fields in the columns which are factors explicit
#(by default, fct_explicit_na changes NAs "(Missing)"):
newdata1 = mydata %>% 
	mutate_if(is.factor, fct_explicit_na)

# changing the missing label to "Dunno"
#(note how the syntax is a little bit different 
# than when using fct_explicit_na on a single column)
newdata2 = mydata %>% 
	mutate_if(is.factor, fct_explicit_na, na_level = 'Dunno')


# on a single column it would look like:
mydata$a %>% fct_explicit_na(na_level = 'Dunno')

Thank you so much! This is exactly what I was looking for and made my life so much easier!