Creating a variable from other two categorical variables R - r

Question

I looked for similar questions/answers on StackOverflow, but I could not find the answer I am looking for.
I have two categorical variables -
Region of education
Educational residence
Both variables (region of education and educational residence) are in one dataset after merging two different datasets.
Region of education has variables such as - Western, Non-western, Unknown
Educational residence has only two variables - In the USA and Out of the USA
Now, I have to make a new categorical variable with recoding options - Western as Education from Western countries, Non-Western as Education from Non-Western countries, Unknown as Unknown, while from the educational residence I have to use only in the USA.
So in end, the new variable will have four options -
Education from western countries,
Education from non-western countries,
Education from the USA,
Unknown
Is there any idea, of how to do this?
I apologise as I cannot post the data output due to ethical and legal issues.
I will be very thankful for any kind of help.

Answer 1

You don't need to share real data to get a pointer to the correct answer, just a simple reproducible example should suffice. According to your description, the relevant columns in your data frame should look something like this reproducible example:
set.seed(1)
df <- data.frame(Region = sample(c("Western", "Non-Western", "Unknown"), 10, T),
Residence = sample(c("USA", "Non-USA"), 10, T))
df
#> Region Residence
#> 1 Western USA
#> 2 Unknown USA
#> 3 Western USA
#> 4 Non-Western USA
#> 5 Western Non-USA
#> 6 Unknown Non-USA
#> 7 Unknown Non-USA
#> 8 Non-Western Non-USA
#> 9 Non-Western USA
#> 10 Unknown USA
We can smoosh these columns together using ifelse. Where the Residence column is "USA", the output will be "USA", and otherwise it will retain the "Western", "Non-Western" and "Unknown" levels from the Region column:
df$Education <- ifelse(df$Residence == "USA", "USA", df$Region)
df
#> Region Residence Education
#> 1 Western USA USA
#> 2 Unknown USA USA
#> 3 Western USA USA
#> 4 Non-Western USA USA
#> 5 Western Non-USA Western
#> 6 Unknown Non-USA Unknown
#> 7 Unknown Non-USA Unknown
#> 8 Non-Western Non-USA Non-Western
#> 9 Non-Western USA USA
#> 10 Unknown USA USA
Created on 2022-08-20 with reprex v2.0.2