Adding column if it does not exist

Question

I have a bunch of data frames with different variables. I want to read them into R and add columns to those that are short of a few variables so that they all have a common set of standard variables, even if some are unobserved.

In other words... Is there a way to add columns of NA in the tidyverse when a column does not exist? My current attempt works for adding new variables where the column doesn't exist (top_speed) but fails when the column already exists (mpg) - it sets all observations to the first value Mazda RX4.

library(tidyverse) mtcars %>%   as_tibble() %>%   rownames_to_column("car") %>%   mutate(top_speed = ifelse("top_speed" %in% names(.), top_speed, NA),          mpg = ifelse("mpg" %in% names(.), mpg, NA)) %>%   select(car, top_speed, mpg, everything())  # # A tibble: 32 x 13 #                  car top_speed   mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb #                <chr>     <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #  1         Mazda RX4        NA    21     6 160.0   110  3.90 2.620 16.46     0     1     4     4 #  2     Mazda RX4 Wag        NA    21     6 160.0   110  3.90 2.875 17.02     0     1     4     4 #  3        Datsun 710        NA    21     4 108.0    93  3.85 2.320 18.61     1     1     4     1 #  4    Hornet 4 Drive        NA    21     6 258.0   110  3.08 3.215 19.44     1     0     3     1 #  5 Hornet Sportabout        NA    21     8 360.0   175  3.15 3.440 17.02     0     0     3     2 #  6           Valiant        NA    21     6 225.0   105  2.76 3.460 20.22     1     0     3     1 #  7        Duster 360        NA    21     8 360.0   245  3.21 3.570 15.84     0     0     3     4 #  8         Merc 240D        NA    21     4 146.7    62  3.69 3.190 20.00     1     0     4     2 #  9          Merc 230        NA    21     4 140.8    95  3.92 3.150 22.90     1     0     4     2 # 10          Merc 280        NA    21     6 167.6   123  3.92 3.440 18.30     1     0     4     4 

Answer 1

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))]) 

Answer 2

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"))