I have read several guides on programming with dplyr now and I am still confused about how to solve the problem of evaluating constructed/concatenated strings with non-standard evaluation (NSE). I realize that there are better ways to solve this example than using NSE, but want to learn how to.
t <- tibble( x_01 = c(1, 2, 3), x_02 = c(4, 5, 6))
i <- 1
This is my desired outcome but want the variables in mutate() to be constructed:
t %>% mutate(d_01 = x_01 * 2)
#> A tibble: 3 x 3
#> x_01 x_02 d_01
#> <dbl> <dbl> <dbl>
#> 1 1.00 4.00 2.00
#> 2 2.00 5.00 4.00
#> 3 3.00 6.00 6.00
This is my first attempt, trying to use strings:
new <- sprintf("d_%02d", i)
var <- sprintf("x_%02d", i)
t %>% mutate(new = var * 2)
#> Error in mutate_impl(.data, dots) :
#> Evaluation error: non-numeric argument to binary operator.
This is my second attempt, trying to use quosures:
new <- rlang::quo(sprintf("d_%02d", i))
var <- rlang::quo(sprintf("x_%02d", i))
t %>% mutate(!!new = !!var * 2)
#> Error: unexpected '=' in "t %>% mutate(!!new ="
This is my third attempt, trying to use quosures and the := operator:
new <- rlang::quo(sprintf("d_%02d", i))
var <- rlang::quo(sprintf("x_%02d", i))
t %>% mutate(!!new := !!var * 2)
#> Error in var * 2 : non-numeric argument to binary operator
Use sym and := like this:
library(dplyr)
library(rlang)
t <- tibble( x_01 = c(1, 2, 3), x_02 = c(4, 5, 6))
i <- 1
new <- sym(sprintf("d_%02d", i))
var <- sym(sprintf("x_%02d", i))
t %>% mutate(!!new := (!!var) * 2)
giving:
# A tibble: 3 x 3
x_01 x_02 d_01
<dbl> <dbl> <dbl>
1 1 4 2
2 2 5 4
3 3 6 6
Also note that this is trivial in base R:
tdf <- data.frame( x_01 = c(1, 2, 3), x_02 = c(4, 5, 6))
i <- 1
new <- sprintf("d_%02d", i)
var <- sprintf("x_%02d", i)
tdf[[new]] <- 2 * tdf[[var]]