Is there a way that I can loop ifelse functions in my list of dataframes?-CodePudding

My dataframe currently looks like this:

employment020406 <- list(emp_02, emp_04, emp_06)

I want to create two new variables called agri_work and TAL in each dataset:

emp_02$agri_work <- ifelse(emp_02$industry == 1 | emp_02$industry == 2 | emp_02$industry == 5, 1, 0)

emp_04$agri_work <- ifelse(emp_04$industry == 1 | emp_04$industry == 2 | emp_04$industry == 5, 1, 0)

emp_06$agri_work <- ifelse(emp_06$industry == 1 | emp_06$industry == 2 | emp_06$industry == 5, 1, 0)

emp_02$tal <- ifelse(emp_02$industry == 17 | emp_02$industry == 18 | emp_02$industry == 19, 1, 0)

emp_04$tal <- ifelse(emp_04$industry == 17 | emp_04$industry == 18 | emp_04$industry == 19, 1, 0)

emp_06$tal <- ifelse(emp_06$industry == 17 | emp_06$industry == 18 | emp_06$industry == 19, 1, 0)

Note that industry exists in all 3 dataframes in the list.

Is there a way I can loop the ifelse function so that I can create the new variables in each dataframe without having to repeat this action many times?

Thank you very much.

CodePudding user response：

You can index into each element of employment020406 using seq_along(). (You can also use df$var %in% c(a, b, c) instead of df$var == a | df$var == b | df$var == c.)

for (i in seq_along(employment020406)) {
  employment020406[[i]]$agri_work <- ifelse(employment020406[[i]]$industry %in% c(1, 2, 5), 1, 0)
  employment020406[[i]]$tal <- ifelse(employment020406[[i]]$industry %in% 17:19, 1, 0)
}

CodePudding user response：

If you only want to change employment020406, you can do this:

employment020406 <- lapply(employment020406, function(x) {
  x %>% 
    mutate(tal = as.numeric(industry %in% c(17,18,19)),
           agri_work = as.numeric(industry %in% c(1,2,5))
    )
})

However, note that this will not change the underlying objects emp_02, emp_04 and emp_06. If you want to change those, you could do this:

employment020406 <- list("emp_02", "emp_04", "emp_06") 
for(f in employment020406) {
  assign(f,get(f) %>%
           mutate(tal = as.numeric(industry %in% c(17,18,19)),
           agri_work = as.numeric(industry %in% c(1,2,5)))
  )
}