How to reduce memory usage in R while looping through dataframes

Question

I have two data frames and i am doing a grouping operation based on weighted scores. I used PROFVIS to profile the code and figured that looping through the dataframes to check and add group labels is a costly operation. I understand we can use lapply, but not sure how to parse two dataframes and a new variable for this. Please help. I just need to reduce the time and space complexity of this code using apply functions.

rank1<-c()
occup_cats<-c()
for(i in 1:length(data_set$primary_occupation)){
  for(j in 1:length(occup_cat_prop$Category)){
    **if((as.character(data_set$primary_occupation[i])) == (as.character(occup_cat_prop$income_source[j])))**{

      rank1[i]<-occup_cat_prop$prop[j]
      occup_cats[i]<-as.character(occup_cat_prop$Category[j])

    }
  }
}