Adding column if it does not exist

If you had an empty dataframe that contains all the names to check for, you can use bind_rows to add columns.

I used purrr:map_dfr to make the empty tibble with the appropriate column names.

columns = c("top_speed", "mpg") %>%
     map_dfr( ~tibble(!!.x := logical() ) )

# A tibble: 0 x 2
# ... with 2 variables: top_speed <lgl>, mpg <lgl>

bind_rows(columns, mtcars)

# A tibble: 32 x 12
   top_speed   mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
       <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
 1        NA  21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
 2        NA  21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
 3        NA  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1

You can use the rowwise function like this :

library(tidyverse)
mtcars %>%
  tbl_df() %>%
  rownames_to_column("car") %>%
  rowwise() %>%
  mutate(top_speed = ifelse("top_speed" %in% names(.), top_speed, NA),
         mpg = ifelse("mpg" %in% names(.), mpg, NA)) %>%
  select(car, top_speed, mpg, everything())

Another option that does not require creating a helper function (or an already complete data.frame) using tibble's add_column:

library(tibble)

cols <- c(top_speed = NA_real_, nhj = NA_real_, mpg = NA_real_)

add_column(mtcars, !!!cols[setdiff(names(cols), names(mtcars))])

We could create a helper function to create the column

fncols <- function(data, cname) {
  add <-cname[!cname%in%names(data)]

  if(length(add)!=0) data[add] <- NA
  data
}
fncols(mtcars, "mpg")
fncols(mtcars, c("topspeed","nhj","mpg"))