mutate and create multiple dynamic variables all with value NA-CodePudding

I can create ONE variable with all values = NA in a data frame like this:

> library(rlang)
> library(dplyr)
> 
> myvar="x"
> mtcars%>% mutate(!!myvar:=NA) %>% head
                   mpg cyl disp  hp drat    wt  qsec vs am gear carb  x
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4 NA
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4 NA
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 NA
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1 NA
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2 NA
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1 NA
>

My question is : how do I do this for multiple variables?

Here is an attempt:

> f <- function(...){
      mylist =  enexprs(...)
      lapply(mylist,function(x){x<- paste0(x,"=NA")})
  }
> 
> f(x,y,z)
[[1]]
[1] "x=NA"

[[2]]
[1] "y=NA"

[[3]]
[1] "z=NA"

> 
> mtcars %>% mutate(!!!f(x,y,z)) %>% head
                   mpg cyl disp  hp drat    wt  qsec vs am gear carb "x=NA"
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4   x=NA
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4   x=NA
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1   x=NA
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1   x=NA
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2   x=NA
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1   x=NA
                  "y=NA" "z=NA"
Mazda RX4           y=NA   z=NA
Mazda RX4 Wag       y=NA   z=NA
Datsun 710          y=NA   z=NA
Hornet 4 Drive      y=NA   z=NA
Hornet Sportabout   y=NA   z=NA
Valiant             y=NA   z=NA
>

I am able to create 3 columns, but each has values like x=NA when it should be only NA.

Can someone point out my mistake?

CodePudding user response：

You don't need a function for this. We can just use a list and splice it into mutate with !!!:

library(dplyr)
newvars = list(x = NA,
               y = NA,
               z = NA)

mtcars %>% 
  mutate(!!! newvars) %>% 
  glimpse # for printing
#> Rows: 32
#> Columns: 14
#> $ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,~
#> $ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,~
#> $ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16~
#> $ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180~
#> $ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,~
#> $ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.~
#> $ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18~
#> $ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,~
#> $ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,~
#> $ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,~
#> $ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,~
#> $ x    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N~
#> $ y    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N~
#> $ z    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N~

^{Created on 2022-01-13 by the reprex package (v2.0.1)}

We could use the same logic in a function:

library(dplyr)

f <- function(...) {
  dots <- rlang::enexprs(...)
  expr_ls <- purrr::set_names(dots) %>% purrr::map(~ NA)
  tibble(!!! expr_ls)
}

mtcars %>% 
  mutate(f(x, y, z)) %>% 
  glimpse # for printing

#> Rows: 32
#> Columns: 14
#> $ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,~
#> $ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,~
#> $ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16~
#> $ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180~
#> $ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,~
#> $ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.~
#> $ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18~
#> $ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,~
#> $ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,~
#> $ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,~
#> $ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,~
#> $ x    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N~
#> $ y    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N~
#> $ z    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N~

^{Created on 2022-01-13 by the reprex package (v2.0.1)}