See: https://stackoverflow.com/questions/64989435/r-transform-dummies-into-factor-variable/64993518#64993518

dummies_to_factor.R

library(plm)
library(tidyverse)
library(fastDummies)
data(EmplUK)

EmplUK %>%
  select(-sector) %>% 
  dummy_cols(.data = .,select_columns = c("firm","year"),remove_selected_columns = TRUE,remove_first_dummy = TRUE) -> paneldata
head(paneldata)




# This just defines a function that allows you to recreate the original dataset
# By this, I mean that it gives you back the "country" and "id" columns from the dummy variables of the isat object
getfactorback <- function(data,
                          groupdummyprefix,
                          timedummyprefix,
                          grouplabel,
                          timelabel,
                          firstgroup,
                          firsttime) {
  
  data %>% 
    mutate(newgroup = ifelse(rowSums(cur_data() %>% select(starts_with(groupdummyprefix)))==1,0,1),
           newtime = ifelse(rowSums(cur_data() %>% select(starts_with(timedummyprefix)))==1,0,1)) %>%
    
    rename(!!paste0(groupdummyprefix,firstgroup):=newgroup,
           !!paste0(timedummyprefix,firsttime):=newtime) %>%
    
    
    pivot_longer(cols = starts_with(groupdummyprefix),names_to = grouplabel,names_prefix = groupdummyprefix) %>%
    filter(value == 1) %>%
    select(-value) %>%
    
    pivot_longer(cols = starts_with(timedummyprefix),names_to = timelabel,names_prefix = timedummyprefix) %>%
    filter(value == 1) %>%
    select(-value)  %>%
    
    mutate(across(.cols = c(all_of(grouplabel),all_of(timelabel)),factor)) %>%
    relocate(all_of(c(grouplabel,timelabel))) -> output
  
  return(output)
  
}

getfactorback(data = paneldata,
              groupdummyprefix = "firm_",
              grouplabel = "firm",
              timedummyprefix = "year_",
              timelabel = "year",
              firstgroup = "1",
              firsttime = 1976)