You can use the following basic syntax to add a new level to a factor variable in R:

levels(df$my_factor) <- c(levels(df$my_factor), 'new_level')

The following example shows how to use this syntax in practice.

Example: Add New Level to Factor in R

Suppose we have the following data frame in R that shows the number of sales made in different regions for some retail store:

#create data frame
df <- data.frame(region=factor(c('A', 'B', NA, 'D', NA, 'F')),
                 sales=c(12, 18, 21, 14, 34, 40))

#view data frame
df

  region sales
1      A    12
2      B    18
3   <NA>    21
4      D    14
5   <NA>    34
6      F    40

Notice that the region variable is a factor.

To view the levels for this factor, we can use the levels() function:

#view factor levels for region
levels(df$region)

[1] "A" "B" "D" "F"

We can use the following syntax to add a new factor level called “no region”:

#add factor level called 'no region'
levels(df$region) <- c(levels(df$region), 'no region')

#convert each NA to 'no region'
df$region[is.na(df$region)] <- 'no region'

#view factor levels for region
levels(df$region)

[1] "A" "B" "D" "F" "no region"

The new level called “no region” has been added as a factor level.

If we’d like, we can use the table() function to count the occurrence of each factor level:

#view occurrences of each factor level
table(df$region)

A         B         D         F no region 
1         1         1         1         2 

From the output we can see that the new factor level called “no region” occurs twice in the region column of the data frame.