R How to Change One of the Level to Na

R how to change one of the level to NA

Set the level to NA:

x <- factor(c("a", "b", "c", "NotPerformed"))
x
## [1] a            b            c            NotPerformed
## Levels: a b c NotPerformed
levels(x)[levels(x)=='NotPerformed'] <- NA
x
## [1] a    b    c    <NA>
## Levels: a b c

Note that the factor level is removed.

fct_recode replace level by NA

You need to use backticks to turn the values to NA :

x1 <- fct %>% forcats::fct_recode(`NA` = "a") 
x1
#[1] NA b 
#Levels: NA b

However, note that although this "looks" like NA it is not real NA. It is string "NA".

is.na(x1)
#[1] FALSE FALSE

x1 == 'NA'
#[1]  TRUE FALSE

To make it real NA replace it to NULL.

x2 <- fct %>% forcats::fct_recode(NULL = "a")
x2
#[1] <NA> b   
#Levels: b

is.na(x2)
#[1]  TRUE FALSE

Replace NA in a series of variables by a factor level

If these are already existing factors, you can use forcats::fct_explicit_na():

library(dplyr)
library(forcats)

# Make sample data vars factors
dat <- dat %>%
  mutate(across(starts_with("s_"), as.factor))

# Add 'No' as factor level
dat %>%
  mutate(across(starts_with("s_"), fct_explicit_na, "No"))

# A tibble: 10 x 6
      id     x s_0   s_1   s_2   s_3  
   <dbl> <dbl> <fct> <fct> <fct> <fct>
 1     1     5 75    A     4     110  
 2     2     9 36    No    No    921  
 3     3    11 13    B     7     769  
 4     4    11 34    C     2     912  
 5     5    11 No    C     No    835  
 6     6    13 39    No    4     No   
 7     7    14 45    B     4     577  
 8     8    19 42    D     6     No   
 9     9    20 4     No    7     577  
10    10    13 28    No    3     573  

Replace unwanted values of factor level with NA

Try this:

df <- data.frame(a=11:18, col=c("C", "", "A", NA, "A", "", "C", NA))
levels(df$col) # ""  "A" "C"
sum(is.na(df$col)) # 2

df$col <- factor(df$col, levels=LETTERS[1:3])
levels(df$col) # "A" "B" "C"
sum(is.na(df$col)) # 4

Since the new levels do not include blank (""), all blanks will become NA.

How to use NA as a factor level and rename it in R?

We can try

lapply(data, function(x) {
     if(anyNA(x)) {
     levels(x) <- c(levels(x), "Missing")
     x[is.na(x)] <- "Missing"
     x}
     else x

  })
#$a
#[1] 1       1       2       2       3       Missing Missing
#Levels: 1 2 3 Missing

#$b
#[1] a b b
#Levels: a b

#$c
#[1] 3       4       Missing 3      
#Levels: 3 4 Missing

Convert NA into a factor level

You can use addNA().

x <- c(1, 1, 2, 2, 3, NA)
addNA(x)
# [1] 1    1    2    2    3    <NA>
# Levels: 1 2 3 <NA>

This is basically a convenience function for factoring with exclude = NULL. From help(factor) -

addNA modifies a factor by turning NA into an extra level (so that NA values are counted in tables, for instance).

So another reason this is nice is because if you already have a factor f, you can use addNA() to quickly add NA as a factor level without changing f. As mentioned in the documentation, this is handy for tables. It also reads nicely.

Replace NA in a factor column

1) addNA If fac is a factor addNA(fac) is the same factor but with NA added as a level. See ?addNA

To force the NA level to be 88:

facna <- addNA(fac)
levels(facna) <- c(levels(fac), 88)

giving:

> facna
 [1] 1  2  3  3  4  88 2  4  88 3 
Levels: 1 2 3 4 88

1a) This can be written in a single line as follows:

`levels<-`(addNA(fac), c(levels(fac), 88))

2) factor It can also be done in one line using the various arguments of factor like this:

factor(fac, levels = levels(addNA(fac)), labels = c(levels(fac), 88), exclude = NULL)

2a) or equivalently:

factor(fac, levels = c(levels(fac), NA), labels = c(levels(fac), 88), exclude = NULL)

3) ifelse Another approach is:

factor(ifelse(is.na(fac), 88, paste(fac)), levels = c(levels(fac), 88))

4) forcats The forcats package has a function for this:

library(forcats)

fct_explicit_na(fac, "88")
## [1] 1  2  3  3  4  88 2  4  88 3 
## Levels: 1 2 3 4 88

Note: We used the following for input fac

fac <- structure(c(1L, 2L, 3L, 3L, 4L, NA, 2L, 4L, NA, 3L), .Label = c("1", 
"2", "3", "4"), class = "factor")

Update: Have improved (1) and added (1a). Later added (4).

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