eval_relocate() is a variant of eval_select() that moves a selection to
a new location. Either before or after can be provided to specify where
to move the selection to. This powers dplyr::relocate().
Usage
eval_relocate(
expr,
data,
...,
before = NULL,
after = NULL,
strict = TRUE,
name_spec = NULL,
allow_rename = TRUE,
allow_empty = TRUE,
allow_predicates = TRUE,
before_arg = "before",
after_arg = "after",
env = caller_env(),
error_arg = NULL,
error_call = caller_env()
)Arguments
- expr
Defused R code describing a selection according to the tidyselect syntax.
- data
A named list, data frame, or atomic vector. Technically,
datacan be any vector withnames()and"[["implementations.- ...
These dots are for future extensions and must be empty.
- before, after
Defused R code describing a selection according to the tidyselect syntax. The selection represents the destination of the selection provided through
expr. Supplying neither of these will move the selection to the left-hand side. Supplying both of these is an error.- strict
If
TRUE, out-of-bounds errors are thrown ifexprattempts to select or rename a variable that doesn't exist. IfFALSE, failed selections or renamings are ignored.- name_spec
A name specification describing how to combine or propagate names. This is used only in case nested
c()expressions likec(foo = c(bar = starts_with("foo"))). See thename_specargument ofvctrs::vec_c()for a description of valid name specs.- allow_rename
If
TRUE(the default), the renaming syntaxc(foo = bar)is allowed. IfFALSE, it causes an error. This is useful to implement purely selective behaviour.- allow_empty
If
TRUE(the default), it is ok forexprto result in an empty selection. IfFALSE, will error ifexpryields an empty selection.- allow_predicates
If
TRUE(the default), it is ok forexprto use predicates (i.e. inwhere()). IfFALSE, will error ifexpruses a predicate. Will automatically be set toFALSEifdatadoes not support predicates (as determined bytidyselect_data_has_predicates()).- before_arg, after_arg
Argument names for
beforeandafter. These are used in error messages.- env
The environment in which to evaluate
expr. Discarded ifexpris a quosure.- error_arg
Argument names for
expr. These are used in error messages. (You can use"..."ifexpr = c(...)).- error_call
The execution environment of a currently running function, e.g.
caller_env(). The function will be mentioned in error messages as the source of the error. See thecallargument ofabort()for more information.
Value
A named vector of numeric locations with length equal to length(data).
Each position in data will be represented exactly once.
The names are normally the same as in the input data, except when the user
supplied named selections with c(). In the latter case, the names reflect
the new names chosen by the user.
Examples
library(rlang)
# Interpret defused code as a request to relocate
x <- expr(c(mpg, disp))
after <- expr(wt)
eval_relocate(x, mtcars, after = after)
#> cyl hp drat wt mpg disp qsec vs am gear carb
#> 2 4 5 6 1 3 7 8 9 10 11
# Supplying neither `before` nor `after` will move the selection to the
# left-hand side
eval_relocate(x, mtcars)
#> mpg disp cyl hp drat wt qsec vs am gear carb
#> 1 3 2 4 5 6 7 8 9 10 11
# Within a function, use `enquo()` to defuse a single argument.
# Note that `before` and `after` must also be defused with `enquo()`.
my_relocator <- function(x, expr, before = NULL, after = NULL) {
eval_relocate(enquo(expr), x, before = enquo(before), after = enquo(after))
}
my_relocator(mtcars, vs, before = hp)
#> mpg cyl disp vs hp drat wt qsec am gear carb
#> 1 2 3 8 4 5 6 7 9 10 11
# Here is an example of using `eval_relocate()` to implement `relocate()`.
# Note that the dots are passed on as a defused call to `c(...)`.
relocate <- function(.x, ..., .before = NULL, .after = NULL) {
pos <- eval_relocate(
expr(c(...)),
.x,
before = enquo(.before),
after = enquo(.after)
)
set_names(.x[pos], names(pos))
}
relocate(mtcars, vs, .before = hp)
#> mpg cyl disp vs hp drat wt qsec am gear carb
#> Mazda RX4 21.0 6 160.0 0 110 3.90 2.620 16.46 1 4 4
#> Mazda RX4 Wag 21.0 6 160.0 0 110 3.90 2.875 17.02 1 4 4
#> Datsun 710 22.8 4 108.0 1 93 3.85 2.320 18.61 1 4 1
#> Hornet 4 Drive 21.4 6 258.0 1 110 3.08 3.215 19.44 0 3 1
#> Hornet Sportabout 18.7 8 360.0 0 175 3.15 3.440 17.02 0 3 2
#> Valiant 18.1 6 225.0 1 105 2.76 3.460 20.22 0 3 1
#> Duster 360 14.3 8 360.0 0 245 3.21 3.570 15.84 0 3 4
#> Merc 240D 24.4 4 146.7 1 62 3.69 3.190 20.00 0 4 2
#> Merc 230 22.8 4 140.8 1 95 3.92 3.150 22.90 0 4 2
#> Merc 280 19.2 6 167.6 1 123 3.92 3.440 18.30 0 4 4
#> Merc 280C 17.8 6 167.6 1 123 3.92 3.440 18.90 0 4 4
#> Merc 450SE 16.4 8 275.8 0 180 3.07 4.070 17.40 0 3 3
#> Merc 450SL 17.3 8 275.8 0 180 3.07 3.730 17.60 0 3 3
#> Merc 450SLC 15.2 8 275.8 0 180 3.07 3.780 18.00 0 3 3
#> Cadillac Fleetwood 10.4 8 472.0 0 205 2.93 5.250 17.98 0 3 4
#> Lincoln Continental 10.4 8 460.0 0 215 3.00 5.424 17.82 0 3 4
#> Chrysler Imperial 14.7 8 440.0 0 230 3.23 5.345 17.42 0 3 4
#> Fiat 128 32.4 4 78.7 1 66 4.08 2.200 19.47 1 4 1
#> Honda Civic 30.4 4 75.7 1 52 4.93 1.615 18.52 1 4 2
#> Toyota Corolla 33.9 4 71.1 1 65 4.22 1.835 19.90 1 4 1
#> Toyota Corona 21.5 4 120.1 1 97 3.70 2.465 20.01 0 3 1
#> Dodge Challenger 15.5 8 318.0 0 150 2.76 3.520 16.87 0 3 2
#> AMC Javelin 15.2 8 304.0 0 150 3.15 3.435 17.30 0 3 2
#> Camaro Z28 13.3 8 350.0 0 245 3.73 3.840 15.41 0 3 4
#> Pontiac Firebird 19.2 8 400.0 0 175 3.08 3.845 17.05 0 3 2
#> Fiat X1-9 27.3 4 79.0 1 66 4.08 1.935 18.90 1 4 1
#> Porsche 914-2 26.0 4 120.3 0 91 4.43 2.140 16.70 1 5 2
#> Lotus Europa 30.4 4 95.1 1 113 3.77 1.513 16.90 1 5 2
#> Ford Pantera L 15.8 8 351.0 0 264 4.22 3.170 14.50 1 5 4
#> Ferrari Dino 19.7 6 145.0 0 175 3.62 2.770 15.50 1 5 6
#> Maserati Bora 15.0 8 301.0 0 335 3.54 3.570 14.60 1 5 8
#> Volvo 142E 21.4 4 121.0 1 109 4.11 2.780 18.60 1 4 2
relocate(mtcars, starts_with("d"), .after = last_col())
#> mpg cyl hp wt qsec vs am gear carb disp drat
#> Mazda RX4 21.0 6 110 2.620 16.46 0 1 4 4 160.0 3.90
#> Mazda RX4 Wag 21.0 6 110 2.875 17.02 0 1 4 4 160.0 3.90
#> Datsun 710 22.8 4 93 2.320 18.61 1 1 4 1 108.0 3.85
#> Hornet 4 Drive 21.4 6 110 3.215 19.44 1 0 3 1 258.0 3.08
#> Hornet Sportabout 18.7 8 175 3.440 17.02 0 0 3 2 360.0 3.15
#> Valiant 18.1 6 105 3.460 20.22 1 0 3 1 225.0 2.76
#> Duster 360 14.3 8 245 3.570 15.84 0 0 3 4 360.0 3.21
#> Merc 240D 24.4 4 62 3.190 20.00 1 0 4 2 146.7 3.69
#> Merc 230 22.8 4 95 3.150 22.90 1 0 4 2 140.8 3.92
#> Merc 280 19.2 6 123 3.440 18.30 1 0 4 4 167.6 3.92
#> Merc 280C 17.8 6 123 3.440 18.90 1 0 4 4 167.6 3.92
#> Merc 450SE 16.4 8 180 4.070 17.40 0 0 3 3 275.8 3.07
#> Merc 450SL 17.3 8 180 3.730 17.60 0 0 3 3 275.8 3.07
#> Merc 450SLC 15.2 8 180 3.780 18.00 0 0 3 3 275.8 3.07
#> Cadillac Fleetwood 10.4 8 205 5.250 17.98 0 0 3 4 472.0 2.93
#> Lincoln Continental 10.4 8 215 5.424 17.82 0 0 3 4 460.0 3.00
#> Chrysler Imperial 14.7 8 230 5.345 17.42 0 0 3 4 440.0 3.23
#> Fiat 128 32.4 4 66 2.200 19.47 1 1 4 1 78.7 4.08
#> Honda Civic 30.4 4 52 1.615 18.52 1 1 4 2 75.7 4.93
#> Toyota Corolla 33.9 4 65 1.835 19.90 1 1 4 1 71.1 4.22
#> Toyota Corona 21.5 4 97 2.465 20.01 1 0 3 1 120.1 3.70
#> Dodge Challenger 15.5 8 150 3.520 16.87 0 0 3 2 318.0 2.76
#> AMC Javelin 15.2 8 150 3.435 17.30 0 0 3 2 304.0 3.15
#> Camaro Z28 13.3 8 245 3.840 15.41 0 0 3 4 350.0 3.73
#> Pontiac Firebird 19.2 8 175 3.845 17.05 0 0 3 2 400.0 3.08
#> Fiat X1-9 27.3 4 66 1.935 18.90 1 1 4 1 79.0 4.08
#> Porsche 914-2 26.0 4 91 2.140 16.70 0 1 5 2 120.3 4.43
#> Lotus Europa 30.4 4 113 1.513 16.90 1 1 5 2 95.1 3.77
#> Ford Pantera L 15.8 8 264 3.170 14.50 0 1 5 4 351.0 4.22
#> Ferrari Dino 19.7 6 175 2.770 15.50 0 1 5 6 145.0 3.62
#> Maserati Bora 15.0 8 335 3.570 14.60 0 1 5 8 301.0 3.54
#> Volvo 142E 21.4 4 109 2.780 18.60 1 1 4 2 121.0 4.11