replace_empty_level_in_factor_var.R

# load required libraries
library(tidyverse)
# READ DATA IN MEMORY
df_train<- read.csv("kaggle_fake_job_prediction/data/fake_job_postings.csv",
                    header=T, na.strings=c(" ","NA"), stringsAsFactors = FALSE, strip.white = TRUE)

# create copy
df<- df_train
# coerce character vars to factor for data cleanup
df<- df %>%
  mutate_if(is.character, funs(factor(.)))
find_empty_level<- which(levels(df$employment_type)=="")
levels(df$employment_type)[find_empty_level]<-"NA"