Aliases: eval_rename eval_select
Keywords:
### ** Examples library(rlang)
# Interpret defused code as selection: x <- expr(mpg:cyl) eval_select(x, mtcars)
mpg cyl 1 2
# Interpret defused code as a renaming selection. All inputs must # be named within `c()`: try(eval_rename(expr(mpg), mtcars))
Error in eval(expr, envir) : All renaming inputs must be named.
eval_rename(expr(c(foo = mpg)), mtcars)
foo 1
# Within a function, use `enquo()` to defuse one argument: my_function <- function(x, expr) { eval_select(enquo(expr), x) } # If your function takes dots, evaluate a defused call to `c(...)` # with `expr(c(...))`: my_function <- function(.x, ...) { eval_select(expr(c(...)), .x) } # If your function takes dots and a named argument, use `{{ }}` # inside the defused expression to tunnel it inside the tidyselect DSL: my_function <- function(.x, .expr, ...) { eval_select(expr(c({{ .expr }}, ...)), .x) } # Note that the trick above works because `expr({{ arg }})` is the # same as `enquo(arg)`. # The evaluators return a named vector of locations. Here are # examples of using these location vectors to implement `select()` # and `rename()`: select <- function(.x, ...) { pos <- eval_select(expr(c(...)), .x) set_names(.x[pos], names(pos)) } rename <- function(.x, ...) { pos <- eval_rename(expr(c(...)), .x) names(.x)[pos] <- names(pos) .x } select(mtcars, mpg:cyl)
mpg cyl Mazda RX4 21.0 6 Mazda RX4 Wag 21.0 6 Datsun 710 22.8 4 Hornet 4 Drive 21.4 6 Hornet Sportabout 18.7 8 Valiant 18.1 6 Duster 360 14.3 8 Merc 240D 24.4 4 Merc 230 22.8 4 Merc 280 19.2 6 Merc 280C 17.8 6 Merc 450SE 16.4 8 Merc 450SL 17.3 8 Merc 450SLC 15.2 8 Cadillac Fleetwood 10.4 8 Lincoln Continental 10.4 8 Chrysler Imperial 14.7 8 Fiat 128 32.4 4 Honda Civic 30.4 4 Toyota Corolla 33.9 4 Toyota Corona 21.5 4 Dodge Challenger 15.5 8 AMC Javelin 15.2 8 Camaro Z28 13.3 8 Pontiac Firebird 19.2 8 Fiat X1-9 27.3 4 Porsche 914-2 26.0 4 Lotus Europa 30.4 4 Ford Pantera L 15.8 8 Ferrari Dino 19.7 6 Maserati Bora 15.0 8 Volvo 142E 21.4 4
rename(mtcars, foo = mpg)
foo cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2