Augment a data set with resampling identifiers

Source: R/lables.R

For a data set, add_resample_id() will add at least one new column that identifies which resample that the data came from. In most cases, a single column is added but for some resampling methods, two or more are added.

add_resample_id(.data, split, dots = FALSE)

Arguments

.data

A data frame
split

A single rset object.
dots

A single logical: should the id columns be prefixed with a "." to avoid name conflicts with .data?

Value

An updated data frame.

See also

labels.rsplit

Examples

library(dplyr)

#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

set.seed(363)
car_folds <- vfold_cv(mtcars, repeats = 3)

analysis(car_folds$splits[[1]]) %>%
  add_resample_id(car_folds$splits[[1]]) %>%
  head()

#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb      id
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4 Repeat1
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4 Repeat1
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 Repeat1
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1 Repeat1
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2 Repeat1
#> Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1 Repeat1
#>                      id2
#> Mazda RX4         Fold01
#> Mazda RX4 Wag     Fold01
#> Datsun 710        Fold01
#> Hornet 4 Drive    Fold01
#> Hornet Sportabout Fold01
#> Valiant           Fold01

car_bt <- bootstraps(mtcars)

analysis(car_bt$splits[[1]]) %>%
  add_resample_id(car_bt$splits[[1]]) %>%
  head()

#>                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
#> Chrysler Imperial.1 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> Volvo 142E.1        21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
#>                              id
#> Toyota Corona       Bootstrap01
#> Mazda RX4           Bootstrap01
#> Chrysler Imperial   Bootstrap01
#> Volvo 142E          Bootstrap01
#> Chrysler Imperial.1 Bootstrap01
#> Volvo 142E.1        Bootstrap01