Some patterns for `dplyr::rename_with()` that I use frequently for wide datasets

rename-with-patterns.R

# Some handy patterns with dplyr::rename_with()
# Matt Dray

library(dplyr, warn.conflicts = FALSE)


# 1.  Extracting code from question code/label ----------------------------


x <- tibble(
  Placeholder = LETTERS[1:3],              # want to keep the same
  "X01. Placeholder question text" = 1:3,  # want 'X01'
  "X02. Placeholder question text" = 1:3   # want 'X02'
)

x
# # A tibble: 3 × 3
#   Placeholder `X01. Placeholder question text` `X02. Placeholder question text`
#   <chr>                                  <int>                            <int>
# 1 A                                          1                                1
# 2 B                                          2                                2
# 3 C                                          3                                3

x |> 
  rename_with(
    ~str_extract(., "^.*(?=\\.)"),  # get string between start and '.'
    -Placeholder  # ignore name with no question code in it
  )
# # A tibble: 3 × 3
#   Placeholder   X01   X02
#   <chr>       <int> <int>
# 1 A               1     1
# 2 B               2     2
# 3 C               3     3


# 2.  Rename from a lookup ------------------------------------------------


x <- mtcars[1:5, 1:5]

x
#>                    mpg cyl disp  hp drat
#> Mazda RX4         21.0   6  160 110 3.90
#> Mazda RX4 Wag     21.0   6  160 110 3.90
#> Datsun 710        22.8   4  108  93 3.85
#> Hornet 4 Drive    21.4   6  258 110 3.08
#> Hornet Sportabout 18.7   8  360 175 3.15

cols_to_rename <- names(x)[-1]

cols_to_rename
#> [1] "cyl"  "disp" "hp"   "drat"

names_lookup <- data.frame(
  old_names = cols_to_rename,
  new_names = paste0(cols_to_rename, "_", LETTERS[1:4])
)

names_lookup
#>   old_names new_names
#> 1       cyl     cyl_A
#> 2      disp    disp_B
#> 3        hp      hp_C
#> 4      drat    drat_D

x |> 
  rename_with(
    ~ names_lookup |> filter(old_names == .) |> pull(new_names),
    all_of(cols_to_rename)
  )
#>                    mpg cyl_A disp_B hp_C drat_D
#> Mazda RX4         21.0     6    160  110   3.90
#> Mazda RX4 Wag     21.0     6    160  110   3.90
#> Datsun 710        22.8     4    108   93   3.85
#> Hornet 4 Drive    21.4     6    258  110   3.08
#> Hornet Sportabout 18.7     8    360  175   3.15